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Emani PS, Liu JJ, Clarke D, Jensen M, Warrell J, Gupta C, Meng R, Lee CY, Xu S, Dursun C, Lou S, Chen Y, Chu Z, Galeev T, Hwang A, Li Y, Ni P, Zhou X, Bakken TE, Bendl J, Bicks L, Chatterjee T, Cheng L, Cheng Y, Dai Y, Duan Z, Flaherty M, Fullard JF, Gancz M, Garrido-Martín D, Gaynor-Gillett S, Grundman J, Hawken N, Henry E, Hoffman GE, Huang A, Jiang Y, Jin T, Jorstad NL, Kawaguchi R, Khullar S, Liu J, Liu J, Liu S, Ma S, Margolis M, Mazariegos S, Moore J, Moran JR, Nguyen E, Phalke N, Pjanic M, Pratt H, Quintero D, Rajagopalan AS, Riesenmy TR, Shedd N, Shi M, Spector M, Terwilliger R, Travaglini KJ, Wamsley B, Wang G, Xia Y, Xiao S, Yang AC, Zheng S, Gandal MJ, Lee D, Lein ES, Roussos P, Sestan N, Weng Z, White KP, Won H, Girgenti MJ, Zhang J, Wang D, Geschwind D, Gerstein M. Single-cell genomics and regulatory networks for 388 human brains. bioRxiv 2024:2024.03.18.585576. [PMID: 38562822 PMCID: PMC10983939 DOI: 10.1101/2024.03.18.585576] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
Single-cell genomics is a powerful tool for studying heterogeneous tissues such as the brain. Yet, little is understood about how genetic variants influence cell-level gene expression. Addressing this, we uniformly processed single-nuclei, multi-omics datasets into a resource comprising >2.8M nuclei from the prefrontal cortex across 388 individuals. For 28 cell types, we assessed population-level variation in expression and chromatin across gene families and drug targets. We identified >550K cell-type-specific regulatory elements and >1.4M single-cell expression-quantitative-trait loci, which we used to build cell-type regulatory and cell-to-cell communication networks. These networks manifest cellular changes in aging and neuropsychiatric disorders. We further constructed an integrative model accurately imputing single-cell expression and simulating perturbations; the model prioritized ~250 disease-risk genes and drug targets with associated cell types.
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Affiliation(s)
- Prashant S Emani
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Jason J Liu
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Declan Clarke
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Matthew Jensen
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Jonathan Warrell
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Chirag Gupta
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI, 53706, USA
- Waisman Center, University of Wisconsin-Madison, Madison, WI, 53705, USA
| | - Ran Meng
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Che Yu Lee
- Department of Computer Science, University of California, Irvine, CA, 92697, USA
| | - Siwei Xu
- Department of Computer Science, University of California, Irvine, CA, 92697, USA
| | - Cagatay Dursun
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Shaoke Lou
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Yuhang Chen
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Zhiyuan Chu
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
| | - Timur Galeev
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Ahyeon Hwang
- Department of Computer Science, University of California, Irvine, CA, 92697, USA
- Mathematical, Computational and Systems Biology, University of California, Irvine, CA, 92697, USA
| | - Yunyang Li
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
- Department of Computer Science, Yale University, New Haven, CT, 06520, USA
| | - Pengyu Ni
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Xiao Zhou
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | | | - Jaroslav Bendl
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Lucy Bicks
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA
| | - Tanima Chatterjee
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | | | - Yuyan Cheng
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA
- Department of Opthalmology, Perlman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Yi Dai
- Department of Computer Science, University of California, Irvine, CA, 92697, USA
| | - Ziheng Duan
- Department of Computer Science, University of California, Irvine, CA, 92697, USA
| | | | - John F Fullard
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Michael Gancz
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Diego Garrido-Martín
- Department of Genetics, Microbiology and Statistics, Universitat de Barcelona, Barcelona, 08028, Spain
| | - Sophia Gaynor-Gillett
- Tempus Labs, Inc., Chicago, IL, 60654, USA
- Department of Biology, Cornell College, Mount Vernon, IA, 52314, USA
| | - Jennifer Grundman
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA
| | - Natalie Hawken
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA
| | - Ella Henry
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Gabriel E Hoffman
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Mental Illness Research Education and Clinical Center, James J. Peters VA Medical Center, Bronx, NY, 10468, USA
- Center for Precision Medicine and Translational Therapeutics, James J. Peters VA Medical Center, Bronx, NY, 10468, USA
| | - Ao Huang
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
| | - Yunzhe Jiang
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Ting Jin
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI, 53706, USA
- Waisman Center, University of Wisconsin-Madison, Madison, WI, 53705, USA
| | | | - Riki Kawaguchi
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA
- Center for Autism Research and Treatment, Semel Institute, University of California, Los Angeles, CA, 90095, USA
| | - Saniya Khullar
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI, 53706, USA
- Waisman Center, University of Wisconsin-Madison, Madison, WI, 53705, USA
| | - Jianyin Liu
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA
| | - Junhao Liu
- Department of Computer Science, University of California, Irvine, CA, 92697, USA
| | - Shuang Liu
- Waisman Center, University of Wisconsin-Madison, Madison, WI, 53705, USA
| | - Shaojie Ma
- Department of Neuroscience, Yale University, New Haven, CT, 06510, USA
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Michael Margolis
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA
| | - Samantha Mazariegos
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA
| | - Jill Moore
- Department of Genomics and Computational Biology, UMass Chan Medical School, Worcester, MA, 01605, USA
| | | | - Eric Nguyen
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Nishigandha Phalke
- Department of Genomics and Computational Biology, UMass Chan Medical School, Worcester, MA, 01605, USA
| | - Milos Pjanic
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Henry Pratt
- Department of Genomics and Computational Biology, UMass Chan Medical School, Worcester, MA, 01605, USA
| | - Diana Quintero
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA
| | | | - Tiernon R Riesenmy
- Department of Statistics & Data Science, Yale University, New Haven, CT, 06520, USA
| | - Nicole Shedd
- Department of Genomics and Computational Biology, UMass Chan Medical School, Worcester, MA, 01605, USA
| | - Manman Shi
- Tempus Labs, Inc., Chicago, IL, 60654, USA
| | | | - Rosemarie Terwilliger
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, 06520, USA
| | | | - Brie Wamsley
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA
| | - Gaoyuan Wang
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Yan Xia
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Shaohua Xiao
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA
| | - Andrew C Yang
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Suchen Zheng
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Michael J Gandal
- Interdepartmental Program in Bioinformatics, University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Department of Psychiatry, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Lifespan Brain Institute, The Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Donghoon Lee
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Ed S Lein
- Allen Institute for Brain Science, Seattle, WA, 98109, USA
- Department of Neurological Surgery, University of Washington, Seattle, WA, 98195, USA
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, 98195, USA
| | - Panos Roussos
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Mental Illness Research Education and Clinical Center, James J. Peters VA Medical Center, Bronx, NY, 10468, USA
- Center for Precision Medicine and Translational Therapeutics, James J. Peters VA Medical Center, Bronx, NY, 10468, USA
| | - Nenad Sestan
- Department of Neuroscience, Yale University, New Haven, CT, 06510, USA
| | - Zhiping Weng
- Department of Genomics and Computational Biology, UMass Chan Medical School, Worcester, MA, 01605, USA
| | - Kevin P White
- Yong Loo Lin School of Medicine, National University of Singapore, 117597, Singapore
| | - Hyejung Won
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Matthew J Girgenti
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, 06520, USA
- Wu Tsai Institute, Yale University, New Haven, CT, 06520, USA
- Clinical Neuroscience Division, National Center for Posttraumatic Stress Disorder, Veterans Affairs Connecticut Healthcare System, West Haven, CT, 06516, USA
| | - Jing Zhang
- Department of Computer Science, University of California, Irvine, CA, 92697, USA
| | - Daifeng Wang
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI, 53706, USA
- Waisman Center, University of Wisconsin-Madison, Madison, WI, 53705, USA
- Department of Computer Sciences, University of Wisconsin-Madison, Madison, WI, 53706, USA
| | - Daniel Geschwind
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA
- Center for Autism Research and Treatment, Semel Institute, University of California, Los Angeles, CA, 90095, USA
- Department of Psychiatry, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Institute for Precision Health, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA
| | - Mark Gerstein
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
- Department of Computer Science, Yale University, New Haven, CT, 06520, USA
- Department of Statistics & Data Science, Yale University, New Haven, CT, 06520, USA
- Department of Biomedical Informatics & Data Science, Yale University, New Haven, CT, 06520, USA
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Warrell J, Salichos L, Gancz M, Gerstein MB. Latent evolutionary signatures: a general framework for analysing music and cultural evolution. J R Soc Interface 2024; 21:20230647. [PMID: 38503341 PMCID: PMC10950459 DOI: 10.1098/rsif.2023.0647] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2023] [Accepted: 02/14/2024] [Indexed: 03/21/2024] Open
Abstract
Cultural processes of change bear many resemblances to biological evolution. The underlying units of non-biological evolution have, however, remained elusive, especially in the domain of music. Here, we introduce a general framework to jointly identify underlying units and their associated evolutionary processes. We model musical styles and principles of organization in dimensions such as harmony and form as following an evolutionary process. Furthermore, we propose that such processes can be identified by extracting latent evolutionary signatures from musical corpora, analogously to identifying mutational signatures in genomics. These signatures provide a latent embedding for each song or musical piece. We develop a deep generative architecture for our model, which can be viewed as a type of variational autoencoder with an evolutionary prior constraining the latent space; specifically, the embeddings for each song are tied together via an energy-based prior, which encourages songs close in evolutionary space to share similar representations. As illustration, we analyse songs from the McGill Billboard dataset. We find frequent chord transitions and formal repetition schemes and identify latent evolutionary signatures related to these features. Finally, we show that the latent evolutionary representations learned by our model outperform non-evolutionary representations in such tasks as period and genre prediction.
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Affiliation(s)
- Jonathan Warrell
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Leonidas Salichos
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
- Department of Biological and Chemical Sciences, New York Institute of Technology, New York, NY 10023, USA
- Biomedical Data Science Center, New York Institute of Technology, New York, NY 10023, USA
| | - Michael Gancz
- Department of Music, Yale University, New Haven, CT 06520, USA
| | - Mark B. Gerstein
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
- Department of Computer Science, Yale University, New Haven, CT 06520, USA
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Salichos L, Warrell J, Cevasco H, Chung A, Gerstein M. Genetic determination of regional connectivity in modelling the spread of COVID-19 outbreak for more efficient mitigation strategies. Sci Rep 2023; 13:8470. [PMID: 37231011 DOI: 10.1038/s41598-023-34959-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2022] [Accepted: 05/10/2023] [Indexed: 05/27/2023] Open
Abstract
For the COVID-19 pandemic, viral transmission has been documented in many historical and geographical contexts. Nevertheless, few studies have explicitly modeled the spatiotemporal flow based on genetic sequences, to develop mitigation strategies. Additionally, thousands of SARS-CoV-2 genomes have been sequenced with associated records, potentially providing a rich source for such spatiotemporal analysis, an unprecedented amount during a single outbreak. Here, in a case study of seven states, we model the first wave of the outbreak by determining regional connectivity from phylogenetic sequence information (i.e. "genetic connectivity"), in addition to traditional epidemiologic and demographic parameters. Our study shows nearly all of the initial outbreak can be traced to a few lineages, rather than disconnected outbreaks, indicative of a mostly continuous initial viral flow. While the geographic distance from hotspots is initially important in the modeling, genetic connectivity becomes increasingly significant later in the first wave. Moreover, our model predicts that isolated local strategies (e.g. relying on herd immunity) can negatively impact neighboring regions, suggesting more efficient mitigation is possible with unified, cross-border interventions. Finally, our results suggest that a few targeted interventions based on connectivity can have an effect similar to that of an overall lockdown. They also suggest that while successful lockdowns are very effective in mitigating an outbreak, less disciplined lockdowns quickly decrease in effectiveness. Our study provides a framework for combining phylodynamic and computational methods to identify targeted interventions.
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Affiliation(s)
- Leonidas Salichos
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA.
- Biological and Chemical Sciences, New York Institute of Technology, Manhattan, NY, 10023, USA.
| | - Jonathan Warrell
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
| | - Hannah Cevasco
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
| | - Alvin Chung
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
| | - Mark Gerstein
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA.
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA.
- Department of Computer Science, Yale University, New Haven, CT, 06520, USA.
- Center for Biomedical Data Science, Yale University, New Haven, CT, 06520, USA.
- Department of Statistics & Data Science, Yale University, New Haven, CT, 06520, USA.
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4
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Lau B, Emani PS, Chapman J, Yao L, Lam T, Merrill P, Warrell J, Gerstein MB, Lam HYK. Insights from incorporating quantum computing into drug design workflows. Bioinformatics 2023; 39:6881079. [PMID: 36477833 PMCID: PMC9825754 DOI: 10.1093/bioinformatics/btac789] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Revised: 10/14/2022] [Accepted: 12/06/2022] [Indexed: 12/12/2022] Open
Abstract
MOTIVATION While many quantum computing (QC) methods promise theoretical advantages over classical counterparts, quantum hardware remains limited. Exploiting near-term QC in computer-aided drug design (CADD) thus requires judicious partitioning between classical and quantum calculations. RESULTS We present HypaCADD, a hybrid classical-quantum workflow for finding ligands binding to proteins, while accounting for genetic mutations. We explicitly identify modules of our drug-design workflow currently amenable to replacement by QC: non-intuitively, we identify the mutation-impact predictor as the best candidate. HypaCADD thus combines classical docking and molecular dynamics with quantum machine learning (QML) to infer the impact of mutations. We present a case study with the coronavirus (SARS-CoV-2) protease and associated mutants. We map a classical machine-learning module onto QC, using a neural network constructed from qubit-rotation gates. We have implemented this in simulation and on two commercial quantum computers. We find that the QML models can perform on par with, if not better than, classical baselines. In summary, HypaCADD offers a successful strategy for leveraging QC for CADD. AVAILABILITY AND IMPLEMENTATION Jupyter Notebooks with Python code are freely available for academic use on GitHub: https://www.github.com/hypahub/hypacadd_notebook. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
| | | | | | - Lijing Yao
- HypaHealth, HypaHub Inc., San Jose, CA 95128, USA
| | - Tarsus Lam
- HypaHealth, HypaHub Inc., San Jose, CA 95128, USA
| | - Paul Merrill
- HypaHealth, HypaHub Inc., San Jose, CA 95128, USA
| | - Jonathan Warrell
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
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5
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Gerstung M, Jolly C, Leshchiner I, Dentro SC, Gonzalez S, Rosebrock D, Mitchell TJ, Rubanova Y, Anur P, Yu K, Tarabichi M, Deshwar A, Wintersinger J, Kleinheinz K, Vázquez-García I, Haase K, Jerman L, Sengupta S, Macintyre G, Malikic S, Donmez N, Livitz DG, Cmero M, Demeulemeester J, Schumacher S, Fan Y, Yao X, Lee J, Schlesner M, Boutros PC, Bowtell DD, Zhu H, Getz G, Imielinski M, Beroukhim R, Sahinalp SC, Ji Y, Peifer M, Markowetz F, Mustonen V, Yuan K, Wang W, Morris QD, Spellman PT, Wedge DC, Van Loo P, Tarabichi M, Wintersinger J, Deshwar AG, Yu K, Gonzalez S, Rubanova Y, Macintyre G, Adams DJ, Anur P, Beroukhim R, Boutros PC, Bowtell DD, Campbell PJ, Cao S, Christie EL, Cmero M, Cun Y, Dawson KJ, Demeulemeester J, Donmez N, Drews RM, Eils R, Fan Y, Fittall M, Garsed DW, Getz G, Ha G, Imielinski M, Jerman L, Ji Y, Kleinheinz K, Lee J, Lee-Six H, Livitz DG, Malikic S, Markowetz F, Martincorena I, Mitchell TJ, Mustonen V, Oesper L, Peifer M, Peto M, Raphael BJ, Rosebrock D, Sahinalp SC, Salcedo A, Schlesner M, Schumacher S, Sengupta S, Shi R, Shin SJ, Spiro O, Pitkänen E, Pivot X, Piñeiro-Yáñez E, Planko L, Plass C, Polak P, Pons T, Popescu I, Potapova O, Prasad A, Stein LD, Preston SR, Prinz M, Pritchard AL, Prokopec SD, Provenzano E, Puente XS, Puig S, Puiggròs M, Pulido-Tamayo S, Pupo GM, Vázquez-García I, Purdie CA, Quinn MC, Rabionet R, Rader JS, Radlwimmer B, Radovic P, Raeder B, Raine KM, Ramakrishna M, Ramakrishnan K, Vembu S, Ramalingam S, Raphael BJ, Rathmell WK, Rausch T, Reifenberger G, Reimand J, Reis-Filho J, Reuter V, Reyes-Salazar I, Reyna MA, Wheeler DA, Reynolds SM, Rheinbay E, Riazalhosseini Y, Richardson AL, Richter J, Ringel M, Ringnér M, Rino Y, Rippe K, Roach J, Yang TP, Roberts LR, Roberts ND, Roberts SA, Robertson AG, Robertson AJ, Rodriguez JB, Rodriguez-Martin B, Rodríguez-González FG, Roehrl MHA, Rohde M, Yao X, Rokutan H, Romieu G, Rooman I, Roques T, Rosebrock D, Rosenberg M, Rosenstiel PC, Rosenwald A, Rowe EW, Royo R, Yuan 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Author Correction: The evolutionary history of 2,658 cancers. Nature 2023; 614:E42. [PMID: 36697833 PMCID: PMC9931577 DOI: 10.1038/s41586-022-05601-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Affiliation(s)
- Moritz Gerstung
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Cambridge, UK. .,European Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany. .,Wellcome Sanger Institute, Cambridge, UK.
| | - Clemency Jolly
- grid.451388.30000 0004 1795 1830The Francis Crick Institute, London, UK
| | - Ignaty Leshchiner
- grid.66859.340000 0004 0546 1623Broad Institute of MIT and Harvard, Cambridge, MA USA
| | - Stefan C. Dentro
- grid.10306.340000 0004 0606 5382Wellcome Sanger Institute, Cambridge, UK ,grid.451388.30000 0004 1795 1830The Francis Crick Institute, London, UK ,grid.4991.50000 0004 1936 8948Big Data Institute, University of Oxford, Oxford, UK
| | - Santiago Gonzalez
- grid.225360.00000 0000 9709 7726European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Cambridge, UK
| | - Daniel Rosebrock
- grid.66859.340000 0004 0546 1623Broad Institute of MIT and Harvard, Cambridge, MA USA
| | - Thomas J. Mitchell
- grid.10306.340000 0004 0606 5382Wellcome Sanger Institute, Cambridge, UK ,grid.5335.00000000121885934University of Cambridge, Cambridge, UK
| | - Yulia Rubanova
- grid.17063.330000 0001 2157 2938University of Toronto, Toronto, Ontario Canada ,grid.494618.6Vector Institute, Toronto, Ontario Canada
| | - Pavana Anur
- grid.5288.70000 0000 9758 5690Molecular and Medical Genetics, Oregon Health & Science University, Portland, OR USA
| | - Kaixian Yu
- grid.240145.60000 0001 2291 4776The University of Texas MD Anderson Cancer Center, Houston, TX USA
| | - Maxime Tarabichi
- grid.10306.340000 0004 0606 5382Wellcome Sanger Institute, Cambridge, UK ,grid.451388.30000 0004 1795 1830The Francis Crick Institute, London, UK
| | - Amit Deshwar
- grid.17063.330000 0001 2157 2938University of Toronto, Toronto, Ontario Canada ,grid.494618.6Vector Institute, Toronto, Ontario Canada
| | - Jeff Wintersinger
- grid.17063.330000 0001 2157 2938University of Toronto, Toronto, Ontario Canada ,grid.494618.6Vector Institute, Toronto, Ontario Canada
| | - Kortine Kleinheinz
- grid.7497.d0000 0004 0492 0584German Cancer Research Center (DKFZ), Heidelberg, Germany ,grid.7700.00000 0001 2190 4373Heidelberg University, Heidelberg, Germany
| | - Ignacio Vázquez-García
- grid.10306.340000 0004 0606 5382Wellcome Sanger Institute, Cambridge, UK ,grid.5335.00000000121885934University of Cambridge, Cambridge, UK
| | - Kerstin Haase
- grid.451388.30000 0004 1795 1830The Francis Crick Institute, London, UK
| | - Lara Jerman
- grid.225360.00000 0000 9709 7726European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Cambridge, UK ,grid.8954.00000 0001 0721 6013University of Ljubljana, Ljubljana, Slovenia
| | - Subhajit Sengupta
- grid.240372.00000 0004 0400 4439NorthShore University HealthSystem, Evanston, IL USA
| | - Geoff Macintyre
- grid.5335.00000000121885934Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK
| | - Salem Malikic
- grid.61971.380000 0004 1936 7494Simon Fraser University, Burnaby, British Columbia Canada ,grid.412541.70000 0001 0684 7796Vancouver Prostate Centre, Vancouver, British Columbia Canada
| | - Nilgun Donmez
- grid.61971.380000 0004 1936 7494Simon Fraser University, Burnaby, British Columbia Canada ,grid.412541.70000 0001 0684 7796Vancouver Prostate Centre, Vancouver, British Columbia Canada
| | - Dimitri G. Livitz
- grid.66859.340000 0004 0546 1623Broad Institute of MIT and Harvard, Cambridge, MA USA
| | - Marek Cmero
- grid.1008.90000 0001 2179 088XUniversity of Melbourne, Melbourne, Victoria Australia ,grid.1042.70000 0004 0432 4889Walter and Eliza Hall Institute, Melbourne, Victoria Australia
| | - Jonas Demeulemeester
- grid.451388.30000 0004 1795 1830The Francis Crick Institute, London, UK ,grid.5596.f0000 0001 0668 7884University of Leuven, Leuven, Belgium
| | - Steven Schumacher
- grid.66859.340000 0004 0546 1623Broad Institute of MIT and Harvard, Cambridge, MA USA
| | - Yu Fan
- grid.240145.60000 0001 2291 4776The University of Texas MD Anderson Cancer Center, Houston, TX USA
| | - Xiaotong Yao
- grid.5386.8000000041936877XWeill Cornell Medicine, New York, NY USA ,grid.429884.b0000 0004 1791 0895New York Genome Center, New York, NY USA
| | - Juhee Lee
- grid.205975.c0000 0001 0740 6917University of California Santa Cruz, Santa Cruz, CA USA
| | - Matthias Schlesner
- grid.7497.d0000 0004 0492 0584German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Paul C. Boutros
- grid.17063.330000 0001 2157 2938University of Toronto, Toronto, Ontario Canada ,grid.419890.d0000 0004 0626 690XOntario Institute for Cancer Research, Toronto, Ontario Canada ,grid.19006.3e0000 0000 9632 6718University of California, Los Angeles, CA USA
| | - David D. Bowtell
- grid.1055.10000000403978434Peter MacCallum Cancer Centre, Melbourne, Victoria Australia
| | - Hongtu Zhu
- grid.240145.60000 0001 2291 4776The University of Texas MD Anderson Cancer Center, Houston, TX USA
| | - Gad Getz
- grid.66859.340000 0004 0546 1623Broad Institute of MIT and Harvard, Cambridge, MA USA ,grid.32224.350000 0004 0386 9924Center for Cancer Research, Massachusetts General Hospital, Charlestown, MA USA ,grid.32224.350000 0004 0386 9924Department of Pathology, Massachusetts General Hospital, Boston, MA USA ,grid.38142.3c000000041936754XHarvard Medical School, Boston, MA USA
| | - Marcin Imielinski
- grid.5386.8000000041936877XWeill Cornell Medicine, New York, NY USA ,grid.429884.b0000 0004 1791 0895New York Genome Center, New York, NY USA
| | - Rameen Beroukhim
- grid.66859.340000 0004 0546 1623Broad Institute of MIT and Harvard, Cambridge, MA USA ,grid.65499.370000 0001 2106 9910Dana-Farber Cancer Institute, Boston, MA USA
| | - S. Cenk Sahinalp
- grid.412541.70000 0001 0684 7796Vancouver Prostate Centre, Vancouver, British Columbia Canada ,grid.411377.70000 0001 0790 959XIndiana University, Bloomington, IN USA
| | - Yuan Ji
- grid.240372.00000 0004 0400 4439NorthShore University HealthSystem, Evanston, IL USA ,grid.170205.10000 0004 1936 7822The University of Chicago, Chicago, IL USA
| | - Martin Peifer
- grid.6190.e0000 0000 8580 3777University of Cologne, Cologne, Germany
| | - Florian Markowetz
- grid.5335.00000000121885934Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK
| | - Ville Mustonen
- grid.7737.40000 0004 0410 2071University of Helsinki, Helsinki, Finland
| | - Ke Yuan
- grid.5335.00000000121885934Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK ,grid.8756.c0000 0001 2193 314XUniversity of Glasgow, Glasgow, UK
| | - Wenyi Wang
- grid.240145.60000 0001 2291 4776The University of Texas MD Anderson Cancer Center, Houston, TX USA
| | - Quaid D. Morris
- grid.17063.330000 0001 2157 2938University of Toronto, Toronto, Ontario Canada ,grid.494618.6Vector Institute, Toronto, Ontario Canada
| | | | - Paul T. Spellman
- grid.5288.70000 0000 9758 5690Molecular and Medical Genetics, Oregon Health & Science University, Portland, OR USA
| | - David C. Wedge
- grid.4991.50000 0004 1936 8948Big Data Institute, University of Oxford, Oxford, UK ,grid.454382.c0000 0004 7871 7212Oxford NIHR Biomedical Research Centre, Oxford, UK
| | - Peter Van Loo
- The Francis Crick Institute, London, UK. .,University of Leuven, Leuven, Belgium.
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Calabrese C, Davidson NR, Demircioğlu D, Fonseca NA, He Y, Kahles A, Lehmann KV, Liu F, Shiraishi Y, Soulette CM, Urban L, Greger L, Li S, Liu D, Perry MD, Xiang Q, Zhang F, Zhang J, Bailey P, Erkek S, Hoadley KA, Hou Y, Huska MR, Kilpinen H, Korbel JO, Marin MG, Markowski J, Nandi T, Pan-Hammarström Q, Pedamallu CS, Siebert R, Stark SG, Su H, Tan P, Waszak SM, Yung C, Zhu S, Awadalla P, Creighton CJ, Meyerson M, Ouellette BFF, Wu K, Yang H, Brazma A, Brooks AN, Göke J, Rätsch G, Schwarz RF, Stegle O, Zhang Z, Wu K, Yang H, Fonseca NA, Kahles A, Lehmann KV, Urban L, Soulette CM, Shiraishi Y, Liu F, He Y, Demircioğlu D, Davidson NR, Calabrese C, Zhang J, Perry MD, Xiang Q, Greger L, Li S, Liu D, Stark SG, Zhang F, Amin SB, Bailey P, Chateigner A, Cortés-Ciriano I, Craft B, Erkek S, Frenkel-Morgenstern M, Goldman M, Hoadley KA, Hou Y, Huska MR, Khurana E, Kilpinen H, Korbel JO, Lamaze FC, Li C, Li X, Li X, Liu X, Marin MG, Markowski J, Nandi T, Nielsen MM, Ojesina AI, Pan-Hammarström Q, Park PJ, Pedamallu CS, Pedersen JS, Pederzoli P, Peifer M, Pennell NA, Perou CM, Perry MD, Petersen GM, Peto M, Petrelli N, Pedamallu CS, Petryszak R, Pfister SM, Phillips M, Pich O, Pickett HA, Pihl TD, Pillay N, Pinder S, Pinese M, Pinho AV, Pedersen JS, Pitkänen E, Pivot X, Piñeiro-Yáñez E, Planko L, Plass C, Polak P, Pons T, Popescu I, Potapova O, Prasad A, Siebert R, Preston SR, Prinz M, Pritchard AL, Prokopec SD, Provenzano E, Puente XS, Puig S, Puiggròs M, Pulido-Tamayo S, Pupo GM, Su H, Purdie CA, Quinn MC, Rabionet R, Rader JS, Radlwimmer B, Radovic P, Raeder B, Raine KM, Ramakrishna M, Ramakrishnan K, Tan P, Ramalingam S, Raphael BJ, Rathmell WK, Rausch T, Reifenberger G, Reimand J, Reis-Filho J, Reuter V, Reyes-Salazar I, Reyna MA, Teh BT, Reynolds SM, Rheinbay E, Riazalhosseini Y, Richardson AL, Richter J, Ringel M, Ringnér M, Rino Y, Rippe K, Roach J, Wang J, Roberts LR, Roberts ND, Roberts SA, Robertson AG, Robertson AJ, Rodriguez JB, Rodriguez-Martin B, Rodríguez-González FG, Roehrl MHA, Rohde M, Waszak SM, Rokutan H, Romieu G, Rooman I, Roques T, Rosebrock D, Rosenberg M, Rosenstiel PC, Rosenwald A, Rowe EW, Royo R, Xiong H, Rozen SG, Rubanova Y, Rubin MA, Rubio-Perez C, Rudneva VA, Rusev BC, Ruzzenente A, Rätsch G, Sabarinathan R, Sabelnykova VY, Yakneen S, Sadeghi S, Sahinalp SC, Saini N, Saito-Adachi M, Saksena G, Salcedo A, Salgado R, Salichos L, Sallari R, Saller C, Ye C, Salvia R, Sam M, Samra JS, Sanchez-Vega F, Sander C, Sanders G, Sarin R, Sarrafi I, Sasaki-Oku A, Sauer T, Yung C, Sauter G, Saw RPM, Scardoni M, Scarlett CJ, Scarpa A, Scelo G, Schadendorf D, Schein JE, Schilhabel MB, Schlesner M, Zhang X, Schlomm T, Schmidt HK, Schramm SJ, Schreiber S, Schultz N, Schumacher SE, Schwarz RF, Scolyer RA, Scott D, Scully R, Zheng L, Seethala R, Segre AV, Selander I, Semple CA, Senbabaoglu Y, Sengupta S, Sereni E, Serra S, Sgroi DC, Shackleton M, Zhu J, Shah NC, Shahabi S, Shang CA, Shang P, Shapira O, Shelton T, Shen C, Shen H, Shepherd R, Shi R, Zhu S, Shi Y, Shiah YJ, Shibata T, Shih J, Shimizu E, Shimizu K, Shin SJ, Shiraishi Y, Shmaya T, Shmulevich I, Awadalla P, Shorser SI, Short C, Shrestha R, Shringarpure SS, Shriver C, Shuai S, Sidiropoulos N, Siebert R, Sieuwerts AM, Sieverling L, Creighton CJ, Signoretti S, Sikora KO, Simbolo M, Simon R, Simons JV, Simpson JT, Simpson PT, Singer S, Sinnott-Armstrong N, Sipahimalani P, Meyerson M, Skelly TJ, Smid M, Smith J, Smith-McCune K, Socci ND, Sofia HJ, Soloway MG, Song L, Sood AK, Sothi S, Ouellette BFF, Sotiriou C, Soulette CM, Span PN, Spellman PT, Sperandio N, Spillane AJ, Spiro O, Spring J, Staaf J, Stadler PF, Wu K, Staib P, Stark SG, Stebbings L, Stefánsson ÓA, Stegle O, Stein LD, Stenhouse A, Stewart C, Stilgenbauer S, Stobbe MD, Yang H, Stratton MR, Stretch JR, Struck AJ, Stuart JM, Stunnenberg HG, Su H, Su X, Sun RX, Sungalee S, Susak H, Göke J, Suzuki A, Sweep F, Szczepanowski M, Sültmann H, Yugawa T, Tam A, Tamborero D, Tan BKT, Tan D, Tan P, Schwarz RF, Tanaka H, Taniguchi H, Tanskanen TJ, Tarabichi M, Tarnuzzer R, Tarpey P, Taschuk ML, Tatsuno K, Tavaré S, Taylor DF, Stegle O, Taylor-Weiner A, Teague JW, Teh BT, Tembe V, Temes J, Thai K, Thayer SP, Thiessen N, Thomas G, Thomas S, Zhang Z, Thompson A, Thompson AM, Thompson JFF, Thompson RH, Thorne H, Thorne LB, Thorogood A, Tiao G, Tijanic N, Timms LE, Brazma A, Tirabosco R, Tojo M, Tommasi S, Toon CW, Toprak UH, Torrents D, Tortora G, Tost J, Totoki Y, Townend D, Rätsch G, Traficante N, Treilleux I, Trotta JR, Trümper LHP, Tsao M, Tsunoda T, Tubio JMC, Tucker O, Turkington R, Turner DJ, Brooks AN, Tutt A, Ueno M, Ueno NT, Umbricht C, Umer HM, Underwood TJ, Urban L, Urushidate T, Ushiku T, Uusküla-Reimand L, Brazma A, Valencia A, Van Den Berg DJ, Van Laere S, Van Loo P, Van Meir EG, Van den Eynden GG, Van der Kwast T, Vasudev N, Vazquez M, Vedururu R, Brooks AN, Veluvolu U, Vembu S, Verbeke LPC, Vermeulen P, Verrill C, Viari A, Vicente D, Vicentini C, VijayRaghavan K, Viksna J, Göke J, Vilain RE, Villasante I, Vincent-Salomon A, Visakorpi T, Voet D, Vyas P, Vázquez-García I, Waddell NM, Waddell N, Wadelius C, Rätsch G, Wadi L, Wagener R, Wala JA, Wang J, Wang J, Wang L, Wang Q, Wang W, Wang Y, Wang Z, Schwarz RF, Waring PM, Warnatz HJ, Warrell J, Warren AY, Waszak SM, Wedge DC, Weichenhan D, Weinberger P, Weinstein JN, Weischenfeldt J, Stegle O, Weisenberger DJ, Welch I, Wendl MC, Werner J, Whalley JP, Wheeler DA, Whitaker HC, Wigle D, Wilkerson MD, Williams A, Zhang Z, Wilmott JS, Wilson GW, Wilson JM, Wilson RK, Winterhoff B, Wintersinger JA, Wiznerowicz M, Wolf S, Wong BH, Wong T, Aaltonen LA, Wong W, Woo Y, Wood S, Wouters BG, Wright AJ, Wright DW, Wright MH, Wu CL, Wu DY, Wu G, Abascal F, Wu J, Wu K, Wu Y, Wu Z, Xi L, Xia T, Xiang Q, Xiao X, Xing R, Xiong H, Abeshouse A, Xu Q, Xu Y, Xue H, Yachida S, Yakneen S, Yamaguchi R, Yamaguchi TN, Yamamoto M, Yamamoto S, Yamaue H, Aburatani H, Yang F, Yang H, Yang JY, Yang L, Yang L, Yang S, Yang TP, Yang Y, Yao X, Yaspo ML, Adams DJ, Yates L, Yau C, Ye C, Ye K, Yellapantula VD, Yoon CJ, Yoon SS, Yousif F, Yu J, Yu K, Agrawal N, Yu W, Yu Y, Yuan K, Yuan Y, Yuen D, Yung CK, Zaikova O, Zamora J, Zapatka M, Zenklusen JC, Ahn KS, Zenz T, Zeps N, Zhang CZ, Zhang F, Zhang H, Zhang H, Zhang H, Zhang J, Zhang J, Zhang J, Ahn SM, Zhang X, Zhang X, Zhang Y, Zhang Z, Zhao Z, Zheng L, Zheng X, Zhou W, Zhou Y, Zhu B, Aikata H, Zhu H, Zhu J, Zhu S, Zou L, Zou X, deFazio A, van As N, van Deurzen CHM, van de Vijver MJ, van’t Veer L, Akbani R, von Mering C, Akdemir KC, Al-Ahmadie H, Al-Sedairy ST, Al-Shahrour F, Alawi M, Albert M, Aldape K, Alexandrov LB, Ally A, Alsop K, Alvarez EG, Amary F, Amin SB, Aminou B, Ammerpohl O, Anderson MJ, Ang Y, Antonello D, Anur P, Aparicio S, Appelbaum EL, Arai Y, Aretz A, Arihiro K, Ariizumi SI, Armenia J, Arnould L, Asa S, Assenov Y, Atwal G, Aukema S, Auman JT, Aure MRR, Awadalla P, Aymerich M, Bader GD, Baez-Ortega A, Bailey MH, Bailey PJ, Balasundaram M, Balu S, Bandopadhayay P, Banks RE, Barbi S, Barbour AP, Barenboim J, Barnholtz-Sloan J, Barr H, Barrera E, Bartlett J, Bartolome J, Bassi C, Bathe OF, Baumhoer D, Bavi P, Baylin SB, Bazant W, Beardsmore D, Beck TA, Behjati S, Behren A, Niu B, Bell C, Beltran S, Benz C, Berchuck A, Bergmann AK, Bergstrom EN, Berman BP, Berney DM, Bernhart SH, Beroukhim R, Berrios M, Bersani S, Bertl J, Betancourt M, Bhandari V, Bhosle SG, Biankin AV, Bieg M, Bigner D, Binder H, Birney E, Birrer M, Biswas NK, Bjerkehagen B, Bodenheimer T, Boice L, Bonizzato G, De Bono JS, Boot A, Bootwalla MS, Borg A, Borkhardt A, Boroevich KA, Borozan I, Borst C, Bosenberg M, Bosio M, Boultwood J, Bourque G, Boutros PC, Bova GS, Bowen DT, Bowlby R, Bowtell DDL, Boyault S, Boyce R, Boyd J, Brazma A, Brennan P, Brewer DS, Brinkman AB, Bristow RG, Broaddus RR, Brock JE, Brock M, Broeks A, Brooks AN, Brooks D, Brors B, Brunak S, Bruxner TJC, Bruzos AL, Buchanan A, Buchhalter I, Buchholz C, Bullman S, Burke H, Burkhardt B, Burns KH, Busanovich J, Bustamante CD, Butler AP, Butte AJ, Byrne NJ, Børresen-Dale AL, Caesar-Johnson SJ, Cafferkey A, Cahill D, Calabrese C, Caldas C, Calvo F, Camacho N, Campbell PJ, Campo E, Cantù C, Cao S, Carey TE, Carlevaro-Fita J, Carlsen R, Cataldo I, Cazzola M, Cebon J, Cerfolio R, Chadwick DE, Chakravarty D, Chalmers D, Chan CWY, Chan K, Chan-Seng-Yue M, Chandan VS, Chang DK, Chanock SJ, Chantrill LA, Chateigner A, Chatterjee N, Chayama K, Chen HW, Chen J, Chen K, Chen Y, Chen Z, Cherniack AD, Chien J, Chiew YE, Chin SF, Cho J, Cho S, Choi JK, Choi W, Chomienne C, Chong Z, Choo SP, Chou A, Christ AN, Christie EL, Chuah E, Cibulskis C, Cibulskis K, Cingarlini S, Clapham P, Claviez A, Cleary S, Cloonan N, Cmero M, Collins CC, Connor AA, Cooke SL, Cooper CS, Cope L, Corbo V, Cordes MG, Cordner SM, Cortés-Ciriano I, Covington K, Cowin PA, Craft B, Craft D, Creighton CJ, Cun Y, Curley E, Cutcutache I, Czajka K, Czerniak B, Dagg RA, Danilova L, Davi MV, Davidson NR, Davies H, Davis IJ, 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Author Correction: Genomic basis for RNA alterations in cancer. Nature 2023; 614:E37. [PMID: 36697831 PMCID: PMC9931574 DOI: 10.1038/s41586-022-05596-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Affiliation(s)
| | - Claudia Calabrese
- grid.225360.00000 0000 9709 7726European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK
| | - Natalie R. Davidson
- grid.5801.c0000 0001 2156 2780ETH Zurich, Zurich, Switzerland ,grid.51462.340000 0001 2171 9952Memorial Sloan Kettering Cancer Center, New York, NY USA ,grid.5386.8000000041936877XWeill Cornell Medical College, New York, NY USA ,grid.419765.80000 0001 2223 3006SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland ,grid.412004.30000 0004 0478 9977University Hospital Zurich, Zurich, Switzerland
| | - Deniz Demircioğlu
- grid.4280.e0000 0001 2180 6431National University of Singapore, Singapore, Singapore ,grid.418377.e0000 0004 0620 715XGenome Institute of Singapore, Singapore, Singapore
| | - Nuno A. Fonseca
- grid.225360.00000 0000 9709 7726European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK
| | - Yao He
- grid.11135.370000 0001 2256 9319Peking University, Beijing, China
| | - André Kahles
- grid.5801.c0000 0001 2156 2780ETH Zurich, Zurich, Switzerland ,grid.51462.340000 0001 2171 9952Memorial Sloan Kettering Cancer Center, New York, NY USA ,grid.419765.80000 0001 2223 3006SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland ,grid.412004.30000 0004 0478 9977University Hospital Zurich, Zurich, Switzerland
| | - Kjong-Van Lehmann
- grid.5801.c0000 0001 2156 2780ETH Zurich, Zurich, Switzerland ,grid.51462.340000 0001 2171 9952Memorial Sloan Kettering Cancer Center, New York, NY USA ,grid.419765.80000 0001 2223 3006SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland ,grid.412004.30000 0004 0478 9977University Hospital Zurich, Zurich, Switzerland
| | - Fenglin Liu
- grid.11135.370000 0001 2256 9319Peking University, Beijing, China
| | - Yuichi Shiraishi
- grid.26999.3d0000 0001 2151 536XThe University of Tokyo, Minato-ku, Japan
| | - Cameron M. Soulette
- grid.205975.c0000 0001 0740 6917University of California, Santa Cruz, Santa Cruz, CA USA
| | - Lara Urban
- grid.225360.00000 0000 9709 7726European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK
| | - Liliana Greger
- grid.225360.00000 0000 9709 7726European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK
| | - Siliang Li
- grid.21155.320000 0001 2034 1839BGI-Shenzhen, Shenzhen, China ,grid.507779.b0000 0004 4910 5858China National GeneBank-Shenzhen, Shenzhen, China
| | - Dongbing Liu
- grid.21155.320000 0001 2034 1839BGI-Shenzhen, Shenzhen, China ,grid.507779.b0000 0004 4910 5858China National GeneBank-Shenzhen, Shenzhen, China
| | - Marc D. Perry
- grid.17063.330000 0001 2157 2938Ontario Institute for Cancer Research, Toronto, Ontario, Canada ,grid.266102.10000 0001 2297 6811University of California, San Francisco, San Francisco, CA USA
| | - Qian Xiang
- grid.17063.330000 0001 2157 2938Ontario Institute for Cancer Research, Toronto, Ontario, Canada
| | - Fan Zhang
- grid.11135.370000 0001 2256 9319Peking University, Beijing, China
| | - Junjun Zhang
- grid.17063.330000 0001 2157 2938Ontario Institute for Cancer Research, Toronto, Ontario, Canada
| | - Peter Bailey
- grid.8756.c0000 0001 2193 314XUniversity of Glasgow, Glasgow, UK
| | - Serap Erkek
- grid.4709.a0000 0004 0495 846XEuropean Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany
| | - Katherine A. Hoadley
- grid.10698.360000000122483208The University of North Carolina at Chapel Hill, Chapel Hill, NC USA
| | - Yong Hou
- grid.21155.320000 0001 2034 1839BGI-Shenzhen, Shenzhen, China ,grid.507779.b0000 0004 4910 5858China National GeneBank-Shenzhen, Shenzhen, China
| | - Matthew R. Huska
- grid.419491.00000 0001 1014 0849Berlin Institute for Medical Systems Biology, Max Delbruck Center for Molecular Medicine, Berlin, Germany
| | - Helena Kilpinen
- grid.83440.3b0000000121901201University College London, London, UK
| | - Jan O. Korbel
- grid.4709.a0000 0004 0495 846XEuropean Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany
| | - Maximillian G. Marin
- grid.205975.c0000 0001 0740 6917University of California, Santa Cruz, Santa Cruz, CA USA
| | - Julia Markowski
- grid.419491.00000 0001 1014 0849Berlin Institute for Medical Systems Biology, Max Delbruck Center for Molecular Medicine, Berlin, Germany
| | - Tannistha Nandi
- grid.418377.e0000 0004 0620 715XGenome Institute of Singapore, Singapore, Singapore
| | - Qiang Pan-Hammarström
- grid.21155.320000 0001 2034 1839BGI-Shenzhen, Shenzhen, China ,grid.4714.60000 0004 1937 0626Karolinska Institutet, Stockholm, Sweden
| | - Chandra Sekhar Pedamallu
- grid.66859.340000 0004 0546 1623Broad Institute, Cambridge, MA USA ,grid.65499.370000 0001 2106 9910Dana-Farber Cancer Institute, Boston, MA USA ,grid.38142.3c000000041936754XHarvard Medical School, Boston, MA USA
| | - Reiner Siebert
- grid.410712.10000 0004 0473 882XUlm University and Ulm University Medical Center, Ulm, Germany
| | - Stefan G. Stark
- grid.5801.c0000 0001 2156 2780ETH Zurich, Zurich, Switzerland ,grid.51462.340000 0001 2171 9952Memorial Sloan Kettering Cancer Center, New York, NY USA ,grid.419765.80000 0001 2223 3006SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland ,grid.412004.30000 0004 0478 9977University Hospital Zurich, Zurich, Switzerland
| | - Hong Su
- grid.21155.320000 0001 2034 1839BGI-Shenzhen, Shenzhen, China ,grid.507779.b0000 0004 4910 5858China National GeneBank-Shenzhen, Shenzhen, China
| | - Patrick Tan
- grid.418377.e0000 0004 0620 715XGenome Institute of Singapore, Singapore, Singapore ,grid.428397.30000 0004 0385 0924Duke-NUS Medical School, Singapore, Singapore
| | - Sebastian M. Waszak
- grid.4709.a0000 0004 0495 846XEuropean Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany
| | - Christina Yung
- grid.17063.330000 0001 2157 2938Ontario Institute for Cancer Research, Toronto, Ontario, Canada
| | - Shida Zhu
- grid.21155.320000 0001 2034 1839BGI-Shenzhen, Shenzhen, China ,grid.507779.b0000 0004 4910 5858China National GeneBank-Shenzhen, Shenzhen, China
| | - Philip Awadalla
- grid.17063.330000 0001 2157 2938Ontario Institute for Cancer Research, Toronto, Ontario, Canada ,grid.17063.330000 0001 2157 2938University of Toronto, Toronto, Ontario Canada
| | - Chad J. Creighton
- grid.39382.330000 0001 2160 926XBaylor College of Medicine, Houston, TX USA
| | - Matthew Meyerson
- grid.66859.340000 0004 0546 1623Broad Institute, Cambridge, MA USA ,grid.65499.370000 0001 2106 9910Dana-Farber Cancer Institute, Boston, MA USA ,grid.38142.3c000000041936754XHarvard Medical School, Boston, MA USA
| | | | - Kui Wu
- grid.21155.320000 0001 2034 1839BGI-Shenzhen, Shenzhen, China ,grid.507779.b0000 0004 4910 5858China National GeneBank-Shenzhen, Shenzhen, China
| | - Huanming Yang
- grid.21155.320000 0001 2034 1839BGI-Shenzhen, Shenzhen, China
| | | | - Alvis Brazma
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK.
| | - Angela N. Brooks
- grid.205975.c0000 0001 0740 6917University of California, Santa Cruz, Santa Cruz, CA USA ,grid.66859.340000 0004 0546 1623Broad Institute, Cambridge, MA USA ,grid.65499.370000 0001 2106 9910Dana-Farber Cancer Institute, Boston, MA USA
| | - Jonathan Göke
- grid.418377.e0000 0004 0620 715XGenome Institute of Singapore, Singapore, Singapore ,grid.410724.40000 0004 0620 9745National Cancer Centre Singapore, Singapore, Singapore
| | - Gunnar Rätsch
- ETH Zurich, Zurich, Switzerland. .,Memorial Sloan Kettering Cancer Center, New York, NY, USA. .,Weill Cornell Medical College, New York, NY, USA. .,SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland. .,University Hospital Zurich, Zurich, Switzerland.
| | - Roland F. Schwarz
- grid.225360.00000 0000 9709 7726European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK ,grid.419491.00000 0001 1014 0849Berlin Institute for Medical Systems Biology, Max Delbruck Center for Molecular Medicine, Berlin, Germany ,grid.7497.d0000 0004 0492 0584German Cancer Consortium (DKTK), partner site Berlin, Germany ,grid.7497.d0000 0004 0492 0584German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Oliver Stegle
- grid.225360.00000 0000 9709 7726European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK ,grid.4709.a0000 0004 0495 846XEuropean Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany ,grid.7497.d0000 0004 0492 0584German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Zemin Zhang
- grid.11135.370000 0001 2256 9319Peking University, Beijing, China
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7
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Emani PS, Warrell J, Anticevic A, Bekiranov S, Gandal M, McConnell MJ, Sapiro G, Aspuru-Guzik A, Baker JT, Bastiani M, Murray JD, Sotiropoulos SN, Taylor J, Senthil G, Lehner T, Gerstein MB, Harrow AW. Quantum computing at the frontiers of biological sciences. Nat Methods 2021; 18:701-709. [PMID: 33398186 PMCID: PMC8254820 DOI: 10.1038/s41592-020-01004-3] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
Computing plays a critical role in the biological sciences but faces increasing challenges of scale and complexity. Quantum computing, a computational paradigm exploiting the unique properties of quantum mechanical analogs of classical bits, seeks to address many of these challenges. We discuss the potential for quantum computing to aid in the merging of insights across different areas of biological sciences.
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Affiliation(s)
- Prashant S Emani
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA
| | - Jonathan Warrell
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA
| | - Alan Anticevic
- Yale School of Medicine, Department of Psychiatry, New Haven, CT, USA
| | - Stefan Bekiranov
- Department of Biochemistry and Molecular Genetics, University of Virginia School of Medicine, Charlottesville, VA, USA
| | - Michael Gandal
- Department of Psychiatry, Semel Institute, David Geffen School of Medicine, University of California-Los Angeles, Los Angeles, CA, USA
| | | | - Guillermo Sapiro
- Department of Electrical and Computer Engineering, Duke University, Durham, NC, USA
| | - Alán Aspuru-Guzik
- Department of Chemistry, University of Toronto, Toronto, Ontario, Canada
- Canadian Institute for Advanced Research (CIFAR) Artificial Intelligence Research Chair, Toronto, Ontario, Canada
- Vector Institute, Toronto, Ontario, Canada
- Department of Computer Science, University of Toronto, Toronto, Ontario, Canada
| | - Justin T Baker
- Institute for Technology in Psychiatry, McLean Hospital, Belmont, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Matteo Bastiani
- Sir Peter Mansfield Imaging Centre, School of Medicine, University of Nottingham, Nottingham, UK
- Wellcome Centre for Integrative Neuroimaging, FMRIB Centre, Nuffield Department of Clinical Neurosciences, University of Oxford, John Radcliffe Hospital, Oxford, UK
| | - John D Murray
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Department of Physics, Yale University, New Haven, CT, USA
| | - Stamatios N Sotiropoulos
- Sir Peter Mansfield Imaging Centre, School of Medicine, University of Nottingham, Nottingham, UK
- NIHR Nottingham Biomedical Research Centre, Queen's Medical Centre, Nottingham University Hospitals NHS Trust, Nottingham, UK
| | - Jacob Taylor
- Joint Center for Quantum Information and Computer Science, University of Maryland, College Park, MD, USA
- National Institute of Standards and Technology, Gaithersburg, MD, USA
| | | | - Thomas Lehner
- New York Genome Center, New York, NY, USA.
- National Institute of Mental Health, Bethesda, MD, USA.
- Neuropsychiatric Disease Genomics, New York Genome Center, New York, NY, USA.
| | - Mark B Gerstein
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA.
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA.
- Department of Computer Science, Yale University, New Haven, CT, USA.
- Department of Statistics and Data Science, Yale University, New Haven, CT, USA.
| | - Aram W Harrow
- Center for Theoretical Physics, Department of Physics, Massachusetts Institute of Technology, Cambridge, MA, USA.
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8
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Zhang J, Lee D, Dhiman V, Jiang P, Xu J, McGillivray P, Yang H, Liu J, Meyerson W, Clarke D, Gu M, Li S, Lou S, Xu J, Lochovsky L, Ung M, Ma L, Yu S, Cao Q, Harmanci A, Yan KK, Sethi A, Gürsoy G, Schoenberg MR, Rozowsky J, Warrell J, Emani P, Yang YT, Galeev T, Kong X, Liu S, Li X, Krishnan J, Feng Y, Rivera-Mulia JC, Adrian J, Broach JR, Bolt M, Moran J, Fitzgerald D, Dileep V, Liu T, Mei S, Sasaki T, Trevilla-Garcia C, Wang S, Wang Y, Zang C, Wang D, Klein RJ, Snyder M, Gilbert DM, Yip K, Cheng C, Yue F, Liu XS, White KP, Gerstein M. An integrative ENCODE resource for cancer genomics. Nat Commun 2020; 11:3696. [PMID: 32728046 PMCID: PMC7391744 DOI: 10.1038/s41467-020-14743-w] [Citation(s) in RCA: 67] [Impact Index Per Article: 16.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2019] [Accepted: 01/20/2020] [Indexed: 12/13/2022] Open
Abstract
ENCODE comprises thousands of functional genomics datasets, and the encyclopedia covers hundreds of cell types, providing a universal annotation for genome interpretation. However, for particular applications, it may be advantageous to use a customized annotation. Here, we develop such a custom annotation by leveraging advanced assays, such as eCLIP, Hi-C, and whole-genome STARR-seq on a number of data-rich ENCODE cell types. A key aspect of this annotation is comprehensive and experimentally derived networks of both transcription factors and RNA-binding proteins (TFs and RBPs). Cancer, a disease of system-wide dysregulation, is an ideal application for such a network-based annotation. Specifically, for cancer-associated cell types, we put regulators into hierarchies and measure their network change (rewiring) during oncogenesis. We also extensively survey TF-RBP crosstalk, highlighting how SUB1, a previously uncharacterized RBP, drives aberrant tumor expression and amplifies the effect of MYC, a well-known oncogenic TF. Furthermore, we show how our annotation allows us to place oncogenic transformations in the context of a broad cell space; here, many normal-to-tumor transitions move towards a stem-like state, while oncogene knockdowns show an opposing trend. Finally, we organize the resource into a coherent workflow to prioritize key elements and variants, in addition to regulators. We showcase the application of this prioritization to somatic burdening, cancer differential expression and GWAS. Targeted validations of the prioritized regulators, elements and variants using siRNA knockdowns, CRISPR-based editing, and luciferase assays demonstrate the value of the ENCODE resource.
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Affiliation(s)
- Jing Zhang
- Program in Computational Biology & Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics & Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Donghoon Lee
- Program in Computational Biology & Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics & Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Vineet Dhiman
- Department of Human Genetics, University of Chicago, Chicago, IL, 60637, USA
- Institute for Genomics and Systems Biology, University of Chicago, Chicago, IL, 60637, USA
| | - Peng Jiang
- Department of Data Science, Dana-Farber Cancer Institute and Harvard T.H. Chan School of Public Health, Boston, MA, 02215, USA
- Cancer Data Science Lab, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Jie Xu
- Department of Biochemistry and Molecular Genetics, Feinberg School of Medicine, Northwestern University, Chicago, IL, 60611, USA
- Robert H. Lurie Comprehensive Cancer Center of Northwestern University, Chicago, IL, 60611, USA
- Department of Biochemistry and Molecular Biology, College of Medicine, The Pennsylvania State University, Hershey, PA, 17033, USA
| | - Patrick McGillivray
- Program in Computational Biology & Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics & Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Hongbo Yang
- Department of Biochemistry and Molecular Genetics, Feinberg School of Medicine, Northwestern University, Chicago, IL, 60611, USA
- Robert H. Lurie Comprehensive Cancer Center of Northwestern University, Chicago, IL, 60611, USA
| | - Jason Liu
- Program in Computational Biology & Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics & Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - William Meyerson
- Program in Computational Biology & Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics & Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Declan Clarke
- Program in Computational Biology & Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics & Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Mengting Gu
- Program in Computational Biology & Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics & Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Shantao Li
- Program in Computational Biology & Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics & Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Shaoke Lou
- Program in Computational Biology & Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics & Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Jinrui Xu
- Program in Computational Biology & Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics & Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Lucas Lochovsky
- Program in Computational Biology & Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics & Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Matthew Ung
- Department of Biomedical Data Science, Department of Molecular and Systems Biology, Geisel School of Medicine at Dartmouth, Lebanon, NH, 03765, USA
| | - Lijia Ma
- Department of Human Genetics, University of Chicago, Chicago, IL, 60637, USA
- Institute for Genomics and Systems Biology, University of Chicago, Chicago, IL, 60637, USA
- School of Life Sciences, Westlake University, Hangzhou, Zhejiang, 310024, China
| | - Shan Yu
- Department of Human Genetics, University of Chicago, Chicago, IL, 60637, USA
- Institute for Genomics and Systems Biology, University of Chicago, Chicago, IL, 60637, USA
| | - Qin Cao
- Department of Computer Science and Engineering, The Chinese University of Hong Kong, Shatin, Hong Kong SAR
| | - Arif Harmanci
- Center for Precision Health, School of Biomedical Informatics, University of Texas Health Science Center at Houston, Houston, TX, 77030, USA
| | - Koon-Kiu Yan
- Program in Computational Biology & Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics & Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Anurag Sethi
- Program in Computational Biology & Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics & Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Gamze Gürsoy
- Program in Computational Biology & Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics & Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Michael Rutenberg Schoenberg
- Program in Computational Biology & Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics & Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Joel Rozowsky
- Program in Computational Biology & Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics & Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Jonathan Warrell
- Program in Computational Biology & Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics & Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Prashant Emani
- Program in Computational Biology & Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics & Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Yucheng T Yang
- Program in Computational Biology & Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics & Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Timur Galeev
- Program in Computational Biology & Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics & Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Xiangmeng Kong
- Program in Computational Biology & Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics & Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Shuang Liu
- Program in Computational Biology & Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics & Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Xiaotong Li
- Program in Computational Biology & Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics & Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Jayanth Krishnan
- Program in Computational Biology & Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics & Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Yanlin Feng
- Program in Computational Biology & Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics & Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Juan Carlos Rivera-Mulia
- Department of Biological Science, Florida State University, Tallahassee, FL, 32306, USA
- Department of Biochemistry, Molecular Biology and Biophysics, University of Minnesota Medical School, Minneapolis, MN, 55455, USA
| | - Jessica Adrian
- Department of Genetics, School of Medicine, Stanford University, Stanford, CA, 94305, USA
| | - James R Broach
- Department of Biochemistry and Molecular Biology, College of Medicine, The Pennsylvania State University, Hershey, PA, 17033, USA
| | - Michael Bolt
- Department of Human Genetics, University of Chicago, Chicago, IL, 60637, USA
- Institute for Genomics and Systems Biology, University of Chicago, Chicago, IL, 60637, USA
| | - Jennifer Moran
- Department of Human Genetics, University of Chicago, Chicago, IL, 60637, USA
- Institute for Genomics and Systems Biology, University of Chicago, Chicago, IL, 60637, USA
| | - Dominic Fitzgerald
- Department of Human Genetics, University of Chicago, Chicago, IL, 60637, USA
- Institute for Genomics and Systems Biology, University of Chicago, Chicago, IL, 60637, USA
| | - Vishnu Dileep
- Department of Biological Science, Florida State University, Tallahassee, FL, 32306, USA
| | - Tingting Liu
- Department of Biochemistry and Molecular Genetics, Feinberg School of Medicine, Northwestern University, Chicago, IL, 60611, USA
- Robert H. Lurie Comprehensive Cancer Center of Northwestern University, Chicago, IL, 60611, USA
| | - Shenglin Mei
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, 02115, USA
| | - Takayo Sasaki
- Department of Biological Science, Florida State University, Tallahassee, FL, 32306, USA
| | - Claudia Trevilla-Garcia
- Department of Biological Science, Florida State University, Tallahassee, FL, 32306, USA
- Department of Biochemistry, Molecular Biology and Biophysics, University of Minnesota Medical School, Minneapolis, MN, 55455, USA
| | - Su Wang
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, 02115, USA
| | - Yanli Wang
- Department of Biochemistry and Molecular Biology, College of Medicine, The Pennsylvania State University, Hershey, PA, 17033, USA
| | - Chongzhi Zang
- Center for Public Health Genomics, Department of Public Health Sciences, University of Virginia, Charlottesville, VA, 22908, USA
| | - Daifeng Wang
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI, 53726, USA
- Waisman Center, University of Wisconsin-Madison, Madison, WI, 53705, USA
| | - Robert J Klein
- Department of Genetics and Genomic Sciences, Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Michael Snyder
- Department of Genetics, School of Medicine, Stanford University, Stanford, CA, 94305, USA
| | - David M Gilbert
- Department of Biological Science, Florida State University, Tallahassee, FL, 32306, USA
| | - Kevin Yip
- Department of Computer Science and Engineering, The Chinese University of Hong Kong, Shatin, Hong Kong SAR
| | - Chao Cheng
- Department of Biomedical Data Science, Department of Molecular and Systems Biology, Geisel School of Medicine at Dartmouth, Lebanon, NH, 03765, USA
- Department of Medicine, Institute for Clinical and Translational Research, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Feng Yue
- Department of Biochemistry and Molecular Genetics, Feinberg School of Medicine, Northwestern University, Chicago, IL, 60611, USA.
- Robert H. Lurie Comprehensive Cancer Center of Northwestern University, Chicago, IL, 60611, USA.
- Department of Biochemistry and Molecular Biology, College of Medicine, The Pennsylvania State University, Hershey, PA, 17033, USA.
| | - X Shirley Liu
- Department of Data Science, Dana-Farber Cancer Institute and Harvard T.H. Chan School of Public Health, Boston, MA, 02215, USA.
| | - Kevin P White
- Department of Human Genetics, University of Chicago, Chicago, IL, 60637, USA.
- Institute for Genomics and Systems Biology, University of Chicago, Chicago, IL, 60637, USA.
- Tempus Labs, Chicago, IL, 60654, USA.
| | - Mark Gerstein
- Program in Computational Biology & Bioinformatics, Yale University, New Haven, CT, 06520, USA.
- Department of Molecular Biophysics & Biochemistry, Yale University, New Haven, CT, 06520, USA.
- Department of Computer Science, Yale University, New Haven, CT, 06520, USA.
- Department of Statistics & Data Science, Yale University, New Haven, CT, 06520, USA.
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9
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Kumar S, Warrell J, Li S, McGillivray PD, Meyerson W, Salichos L, Harmanci A, Martinez-Fundichely A, Chan CWY, Nielsen MM, Lochovsky L, Zhang Y, Li X, Lou S, Pedersen JS, Herrmann C, Getz G, Khurana E, Gerstein MB. Passenger Mutations in More Than 2,500 Cancer Genomes: Overall Molecular Functional Impact and Consequences. Cell 2020; 180:915-927.e16. [PMID: 32084333 PMCID: PMC7210002 DOI: 10.1016/j.cell.2020.01.032] [Citation(s) in RCA: 66] [Impact Index Per Article: 16.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2018] [Revised: 08/23/2019] [Accepted: 01/29/2020] [Indexed: 01/23/2023]
Abstract
The dichotomous model of "drivers" and "passengers" in cancer posits that only a few mutations in a tumor strongly affect its progression, with the remaining ones being inconsequential. Here, we leveraged the comprehensive variant dataset from the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) project to demonstrate that-in addition to the dichotomy of high- and low-impact variants-there is a third group of medium-impact putative passengers. Moreover, we also found that molecular impact correlates with subclonal architecture (i.e., early versus late mutations), and different signatures encode for mutations with divergent impact. Furthermore, we adapted an additive-effects model from complex-trait studies to show that the aggregated effect of putative passengers, including undetected weak drivers, provides significant additional power (∼12% additive variance) for predicting cancerous phenotypes, beyond PCAWG-identified driver mutations. Finally, this framework allowed us to estimate the frequency of potential weak-driver mutations in PCAWG samples lacking any well-characterized driver alterations.
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Affiliation(s)
- Sushant Kumar
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Jonathan Warrell
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Shantao Li
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Patrick D McGillivray
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA; Yale School of Medicine, Yale University, New Haven, CT 06510, USA
| | - William Meyerson
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA; Yale School of Medicine, Yale University, New Haven, CT 06510, USA
| | - Leonidas Salichos
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Arif Harmanci
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA; Center for Precision Health, School of Biomedical Informatics, University of Texas Health Sciences Center, Houston, TX 77030, USA
| | - Alexander Martinez-Fundichely
- Institute for Computational Biomedicine, Weill Cornell Medical College, New York, NY 10021, USA; Department of Physiology and Biophysics, Weill Cornell Medicine, 1300 York Avenue, New York, NY 10065, USA; Caryl and Israel Englander Institute for Precision Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Calvin W Y Chan
- Division of Theoretical Bioinformatics, German Cancer Research Center (DKFZ), Heidelberg 69120, Germany; Faculty of Biosciences, Heidelberg University, Heidelberg 69120, Germany
| | - Morten Muhlig Nielsen
- Department of Molecular Medicine (MOMA), Aarhus University Hospital, Aarhus, Denmark
| | - Lucas Lochovsky
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Yan Zhang
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA; Department of Biomedical Informatics, College of Medicine, Ohio State University, Columbus, OH 43210, USA; The Ohio State University Comprehensive Cancer Center (OSUCCC-James), Columbus, OH 43210, USA
| | - Xiaotong Li
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
| | - Shaoke Lou
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Jakob Skou Pedersen
- Department of Molecular Medicine (MOMA), Aarhus University Hospital, Aarhus, Denmark; Bioinformatics Research Centre (BiRC), Aarhus University, Aarhus, Denmark
| | - Carl Herrmann
- Division of Theoretical Bioinformatics, German Cancer Research Center (DKFZ), Heidelberg 69120, Germany; Health Data Science Unit, Medical Faculty Heidelberg and BioQuant, Heidelberg 69120, Germany
| | - Gad Getz
- The Broad Institute of MIT and Harvard, Cambridge, MA 02124, USA; Massachusetts General Hospital Center for Cancer Research, Charlestown, MA 02129, USA; Harvard Medical School, 250 Longwood Avenue, Boston, MA 02115, USA
| | - Ekta Khurana
- Institute for Computational Biomedicine, Weill Cornell Medical College, New York, NY 10021, USA; Department of Physiology and Biophysics, Weill Cornell Medicine, 1300 York Avenue, New York, NY 10065, USA; Caryl and Israel Englander Institute for Precision Medicine, Weill Cornell Medicine, New York, NY, USA; Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA
| | - Mark B Gerstein
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA; Department of Computer Science, Yale University, New Haven, CT 06511, USA.
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Salichos L, Meyerson W, Warrell J, Gerstein M. Estimating growth patterns and driver effects in tumor evolution from individual samples. Nat Commun 2020; 11:732. [PMID: 32024824 PMCID: PMC7002450 DOI: 10.1038/s41467-020-14407-9] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2018] [Accepted: 11/26/2019] [Indexed: 01/01/2023] Open
Abstract
Tumors accumulate thousands of mutations, and sequencing them has given rise to methods for finding cancer drivers via mutational recurrence. However, these methods require large cohorts and underperform for low recurrence. Recently, ultra-deep sequencing has enabled accurate measurement of VAFs (variant-allele frequencies) for mutations, allowing the determination of evolutionary trajectories. Here, based solely on the VAF spectrum for an individual sample, we report on a method that identifies drivers and quantifies tumor growth. Drivers introduce perturbations into the spectrum, and our method uses the frequency of hitchhiking mutations preceding a driver to measure this. As validation, we use simulation models and 993 tumors from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium with previously identified drivers. Then we apply our method to an ultra-deep sequenced acute myeloid leukemia (AML) tumor and identify known cancer genes and additional driver candidates. In summary, our framework presents opportunities for personalized driver diagnosis using sequencing data from a single individual.
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Affiliation(s)
- Leonidas Salichos
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - William Meyerson
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Jonathan Warrell
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Mark Gerstein
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA.
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA.
- Department of Computer Science, Yale University, New Haven, CT, 06520, USA.
- Center for Biomedical Data Science, Yale University, New Haven, CT, 06520, USA.
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Aaltonen LA, Abascal F, Abeshouse A, Aburatani H, Adams DJ, Agrawal N, Ahn KS, Ahn SM, Aikata H, Akbani R, Akdemir KC, Al-Ahmadie H, Al-Sedairy ST, Al-Shahrour F, Alawi M, Albert M, Aldape K, Alexandrov LB, Ally A, Alsop K, Alvarez EG, Amary F, Amin SB, Aminou B, Ammerpohl O, Anderson MJ, Ang Y, Antonello D, Anur P, Aparicio S, Appelbaum EL, Arai Y, Aretz A, Arihiro K, Ariizumi SI, Armenia J, Arnould L, Asa S, Assenov Y, Atwal G, Aukema S, Auman JT, Aure MRR, Awadalla P, Aymerich M, Bader GD, Baez-Ortega A, Bailey MH, Bailey PJ, Balasundaram M, Balu S, Bandopadhayay P, Banks RE, Barbi S, Barbour AP, Barenboim J, Barnholtz-Sloan J, Barr H, Barrera E, Bartlett J, Bartolome J, Bassi C, Bathe OF, Baumhoer D, Bavi P, Baylin SB, Bazant W, Beardsmore D, Beck TA, Behjati S, Behren A, Niu B, Bell C, Beltran S, Benz C, Berchuck A, Bergmann AK, Bergstrom EN, Berman BP, Berney DM, Bernhart SH, Beroukhim R, Berrios M, Bersani S, Bertl J, Betancourt M, Bhandari V, Bhosle SG, Biankin AV, Bieg M, Bigner D, Binder H, Birney E, Birrer M, Biswas NK, Bjerkehagen B, Bodenheimer T, Boice L, Bonizzato G, De Bono JS, Boot A, Bootwalla MS, Borg A, Borkhardt A, Boroevich KA, Borozan I, Borst C, Bosenberg M, Bosio M, Boultwood J, Bourque G, Boutros PC, Bova GS, Bowen DT, Bowlby R, Bowtell DDL, Boyault S, Boyce R, Boyd J, Brazma A, Brennan P, Brewer DS, Brinkman AB, Bristow RG, Broaddus RR, Brock JE, Brock M, Broeks A, Brooks AN, Brooks D, Brors B, Brunak S, Bruxner TJC, Bruzos AL, Buchanan A, Buchhalter I, Buchholz C, Bullman S, Burke H, Burkhardt B, Burns KH, Busanovich J, Bustamante CD, Butler AP, Butte AJ, Byrne NJ, Børresen-Dale AL, Caesar-Johnson SJ, Cafferkey A, Cahill D, Calabrese C, Caldas C, Calvo F, Camacho N, Campbell PJ, Campo E, Cantù C, Cao S, Carey TE, Carlevaro-Fita J, Carlsen R, Cataldo I, Cazzola M, Cebon J, Cerfolio R, Chadwick DE, Chakravarty D, Chalmers D, Chan CWY, Chan K, Chan-Seng-Yue M, Chandan VS, Chang DK, Chanock SJ, Chantrill LA, Chateigner A, Chatterjee N, Chayama K, Chen HW, Chen J, Chen K, Chen Y, Chen Z, Cherniack AD, Chien J, Chiew YE, Chin SF, Cho J, Cho S, Choi JK, Choi W, Chomienne C, Chong Z, Choo SP, Chou A, Christ AN, Christie EL, Chuah E, Cibulskis C, Cibulskis K, Cingarlini S, Clapham P, Claviez A, Cleary S, Cloonan N, Cmero M, Collins CC, Connor AA, Cooke SL, Cooper CS, Cope L, Corbo V, Cordes MG, Cordner SM, Cortés-Ciriano I, Covington K, Cowin PA, Craft B, Craft D, Creighton CJ, Cun Y, Curley E, Cutcutache I, Czajka K, Czerniak B, Dagg RA, Danilova L, Davi MV, Davidson NR, Davies H, Davis IJ, Davis-Dusenbery BN, Dawson KJ, De La Vega FM, De Paoli-Iseppi R, Defreitas T, Tos APD, Delaneau O, Demchok JA, Demeulemeester J, Demidov GM, Demircioğlu D, Dennis NM, Denroche RE, Dentro SC, Desai N, Deshpande V, Deshwar AG, Desmedt C, Deu-Pons J, Dhalla N, Dhani NC, Dhingra P, Dhir R, DiBiase A, Diamanti K, Ding L, Ding S, Dinh HQ, Dirix L, Doddapaneni H, Donmez N, Dow MT, Drapkin R, Drechsel O, Drews RM, Serge S, Dudderidge T, Dueso-Barroso A, Dunford AJ, Dunn M, Dursi LJ, Duthie FR, Dutton-Regester K, Eagles J, Easton DF, Edmonds S, Edwards PA, Edwards SE, Eeles RA, Ehinger A, Eils J, Eils R, El-Naggar A, Eldridge M, Ellrott K, Erkek S, Escaramis G, Espiritu SMG, Estivill X, Etemadmoghadam D, Eyfjord JE, Faltas BM, Fan D, Fan Y, Faquin WC, Farcas C, Fassan M, Fatima A, Favero F, Fayzullaev N, Felau I, Fereday S, Ferguson ML, Ferretti V, Feuerbach L, Field MA, Fink JL, Finocchiaro G, Fisher C, Fittall MW, Fitzgerald A, Fitzgerald RC, Flanagan AM, Fleshner NE, Flicek P, Foekens JA, Fong KM, Fonseca NA, Foster CS, Fox NS, Fraser M, Frazer S, Frenkel-Morgenstern M, Friedman W, Frigola J, Fronick CC, Fujimoto A, Fujita M, Fukayama M, Fulton LA, Fulton RS, Furuta M, Futreal PA, Füllgrabe A, Gabriel SB, Gallinger S, Gambacorti-Passerini C, Gao J, Gao S, Garraway L, Garred Ø, Garrison E, Garsed DW, Gehlenborg N, Gelpi JLL, George J, Gerhard DS, Gerhauser C, Gershenwald JE, Gerstein M, Gerstung M, Getz G, Ghori M, Ghossein R, Giama NH, Gibbs RA, Gibson B, Gill AJ, Gill P, Giri DD, Glodzik D, Gnanapragasam VJ, Goebler ME, Goldman MJ, Gomez C, Gonzalez S, Gonzalez-Perez A, Gordenin DA, Gossage J, Gotoh K, Govindan R, Grabau D, Graham JS, Grant RC, Green AR, Green E, Greger L, Grehan N, Grimaldi S, Grimmond SM, Grossman RL, Grundhoff A, Gundem G, Guo Q, Gupta M, Gupta S, Gut IG, Gut M, Göke J, Ha G, Haake A, Haan D, Haas S, Haase K, Haber JE, Habermann N, Hach F, Haider S, Hama N, Hamdy FC, Hamilton A, Hamilton MP, Han L, Hanna GB, Hansmann M, Haradhvala NJ, Harismendy O, Harliwong I, Harmanci AO, Harrington E, Hasegawa T, Haussler D, Hawkins S, Hayami S, Hayashi S, Hayes DN, Hayes SJ, Hayward NK, Hazell S, He Y, Heath AP, Heath SC, Hedley D, Hegde AM, Heiman DI, Heinold MC, Heins Z, Heisler LE, Hellstrom-Lindberg E, Helmy M, Heo SG, Hepperla AJ, Heredia-Genestar JM, Herrmann C, Hersey P, Hess JM, Hilmarsdottir H, Hinton J, Hirano S, Hiraoka N, Hoadley KA, Hobolth A, Hodzic E, Hoell JI, Hoffmann S, Hofmann O, Holbrook A, Holik AZ, Hollingsworth MA, Holmes O, Holt RA, Hong C, Hong EP, Hong JH, Hooijer GK, Hornshøj H, Hosoda F, Hou Y, Hovestadt V, Howat W, Hoyle AP, Hruban RH, Hu J, Hu T, Hua X, Huang KL, Huang M, Huang MN, Huang V, Huang Y, Huber W, Hudson TJ, Hummel M, Hung JA, Huntsman D, Hupp TR, Huse J, Huska MR, Hutter B, Hutter CM, Hübschmann D, Iacobuzio-Donahue CA, Imbusch CD, Imielinski M, Imoto S, Isaacs WB, Isaev K, Ishikawa S, Iskar M, Islam SMA, Ittmann M, Ivkovic S, Izarzugaza JMG, Jacquemier J, Jakrot V, Jamieson NB, Jang GH, Jang SJ, Jayaseelan JC, Jayasinghe R, Jefferys SR, Jegalian K, Jennings JL, Jeon SH, Jerman L, Ji Y, Jiao W, Johansson PA, Johns AL, Johns J, Johnson R, Johnson TA, Jolly C, Joly Y, Jonasson JG, Jones CD, Jones DR, Jones DTW, Jones N, Jones SJM, Jonkers J, Ju YS, Juhl H, Jung J, Juul M, Juul RI, Juul S, Jäger N, Kabbe R, Kahles A, Kahraman A, Kaiser VB, Kakavand H, Kalimuthu S, von Kalle C, Kang KJ, Karaszi K, Karlan B, Karlić R, Karsch D, Kasaian K, Kassahn KS, Katai H, Kato M, Katoh H, Kawakami Y, Kay JD, Kazakoff SH, Kazanov MD, Keays M, Kebebew E, Kefford RF, Kellis M, Kench JG, Kennedy CJ, Kerssemakers JNA, Khoo D, Khoo V, Khuntikeo N, Khurana E, Kilpinen H, Kim HK, Kim HL, Kim HY, Kim H, Kim J, Kim J, Kim JK, Kim Y, King TA, Klapper W, Kleinheinz K, Klimczak LJ, Knappskog S, Kneba M, Knoppers BM, Koh Y, Komorowski J, Komura D, Komura M, Kong G, Kool M, Korbel JO, Korchina V, Korshunov A, Koscher M, Koster R, Kote-Jarai Z, Koures A, Kovacevic M, Kremeyer B, Kretzmer H, Kreuz M, Krishnamurthy S, Kube D, Kumar K, Kumar P, Kumar S, Kumar Y, Kundra R, Kübler K, Küppers R, Lagergren J, Lai PH, Laird PW, Lakhani SR, Lalansingh CM, Lalonde E, Lamaze FC, Lambert A, Lander E, Landgraf P, Landoni L, Langerød A, Lanzós A, Larsimont D, Larsson E, Lathrop M, Lau LMS, Lawerenz C, Lawlor RT, Lawrence MS, Lazar AJ, Lazic AM, Le X, Lee D, Lee D, Lee EA, Lee HJ, Lee JJK, Lee JY, Lee J, Lee MTM, Lee-Six H, Lehmann KV, Lehrach H, Lenze D, Leonard CR, Leongamornlert DA, Leshchiner I, Letourneau L, Letunic I, Levine DA, Lewis L, Ley T, Li C, Li CH, Li HI, Li J, Li L, Li S, Li S, Li X, Li X, Li X, Li Y, Liang H, Liang SB, Lichter P, Lin P, Lin Z, Linehan WM, Lingjærde OC, Liu D, Liu EM, Liu FFF, Liu F, Liu J, Liu X, Livingstone J, Livitz D, Livni N, Lochovsky L, Loeffler M, Long GV, Lopez-Guillermo A, Lou S, Louis DN, Lovat LB, Lu Y, Lu YJ, Lu Y, Luchini C, Lungu I, Luo X, Luxton HJ, Lynch AG, Lype L, López C, López-Otín C, Ma EZ, Ma Y, MacGrogan G, MacRae S, Macintyre G, Madsen T, Maejima K, Mafficini A, Maglinte DT, Maitra A, Majumder PP, Malcovati L, Malikic S, Malleo G, Mann GJ, Mantovani-Löffler L, Marchal K, Marchegiani G, Mardis ER, Margolin AA, Marin MG, Markowetz F, Markowski J, Marks J, Marques-Bonet T, Marra MA, Marsden L, Martens JWM, Martin S, Martin-Subero JI, Martincorena I, Martinez-Fundichely A, Maruvka YE, Mashl RJ, Massie CE, Matthew TJ, Matthews L, Mayer E, Mayes S, Mayo M, Mbabaali F, McCune K, McDermott U, McGillivray PD, McLellan MD, McPherson JD, McPherson JR, McPherson TA, Meier SR, Meng A, Meng S, Menzies A, Merrett ND, Merson S, Meyerson M, Meyerson W, Mieczkowski PA, Mihaiescu GL, Mijalkovic S, Mikkelsen T, Milella M, Mileshkin L, Miller CA, Miller DK, Miller JK, Mills GB, Milovanovic A, Minner S, Miotto M, Arnau GM, Mirabello L, Mitchell C, Mitchell TJ, Miyano S, Miyoshi N, Mizuno S, Molnár-Gábor F, Moore MJ, Moore RA, Morganella S, Morris QD, Morrison C, Mose LE, Moser CD, Muiños F, Mularoni L, Mungall AJ, Mungall K, Musgrove EA, Mustonen V, Mutch D, Muyas F, Muzny DM, Muñoz A, Myers J, Myklebost O, Möller P, Nagae G, Nagrial AM, Nahal-Bose HK, Nakagama H, Nakagawa H, Nakamura H, Nakamura T, Nakano K, Nandi T, Nangalia J, Nastic M, Navarro A, Navarro FCP, Neal DE, Nettekoven G, Newell F, Newhouse SJ, Newton Y, Ng AWT, Ng A, Nicholson J, Nicol D, Nie Y, Nielsen GP, Nielsen MM, Nik-Zainal S, Noble MS, Nones K, Northcott PA, Notta F, O’Connor BD, O’Donnell P, O’Donovan M, O’Meara S, O’Neill BP, O’Neill JR, Ocana D, Ochoa A, Oesper L, Ogden C, Ohdan H, Ohi K, Ohno-Machado L, Oien KA, Ojesina AI, Ojima H, Okusaka T, Omberg L, Ong CK, Ossowski S, Ott G, Ouellette BFF, P’ng C, Paczkowska M, Paiella S, Pairojkul C, Pajic M, Pan-Hammarström Q, Papaemmanuil E, Papatheodorou I, Paramasivam N, Park JW, Park JW, Park K, Park K, Park PJ, Parker JS, Parsons SL, Pass H, Pasternack D, Pastore A, Patch AM, Pauporté I, Pea A, Pearson JV, Pedamallu CS, Pedersen JS, Pederzoli P, Peifer M, Pennell NA, Perou CM, Perry MD, Petersen GM, Peto M, Petrelli N, Petryszak R, Pfister SM, Phillips M, Pich O, Pickett HA, Pihl TD, Pillay N, Pinder S, Pinese M, Pinho AV, Pitkänen E, Pivot X, Piñeiro-Yáñez E, Planko L, Plass C, Polak P, Pons T, Popescu I, Potapova O, Prasad A, Preston SR, Prinz M, Pritchard AL, Prokopec SD, Provenzano E, Puente XS, Puig S, Puiggròs M, Pulido-Tamayo S, Pupo GM, Purdie CA, Quinn MC, Rabionet R, Rader JS, Radlwimmer B, Radovic P, Raeder B, Raine KM, Ramakrishna M, Ramakrishnan K, Ramalingam S, Raphael BJ, Rathmell WK, Rausch T, Reifenberger G, Reimand J, Reis-Filho J, Reuter V, Reyes-Salazar I, Reyna MA, Reynolds SM, Rheinbay E, Riazalhosseini Y, Richardson AL, Richter J, Ringel M, Ringnér M, Rino Y, Rippe K, Roach J, Roberts LR, Roberts ND, Roberts SA, Robertson AG, Robertson AJ, Rodriguez JB, Rodriguez-Martin B, Rodríguez-González FG, Roehrl MHA, Rohde M, Rokutan H, Romieu G, Rooman I, Roques T, Rosebrock D, Rosenberg M, Rosenstiel PC, Rosenwald A, Rowe EW, Royo R, Rozen SG, Rubanova Y, Rubin MA, Rubio-Perez C, Rudneva VA, Rusev BC, Ruzzenente A, Rätsch G, Sabarinathan R, Sabelnykova VY, Sadeghi S, Sahinalp SC, Saini N, Saito-Adachi M, Saksena G, Salcedo A, Salgado R, Salichos L, Sallari R, Saller C, Salvia R, Sam M, Samra JS, Sanchez-Vega F, Sander C, Sanders G, Sarin R, Sarrafi I, Sasaki-Oku A, Sauer T, Sauter G, Saw RPM, Scardoni M, Scarlett CJ, Scarpa A, Scelo G, Schadendorf D, Schein JE, Schilhabel MB, Schlesner M, Schlomm T, Schmidt HK, Schramm SJ, Schreiber S, Schultz N, Schumacher SE, Schwarz RF, Scolyer RA, Scott D, Scully R, Seethala R, Segre AV, Selander I, Semple CA, Senbabaoglu Y, Sengupta S, Sereni E, Serra S, Sgroi DC, Shackleton M, Shah NC, Shahabi S, Shang CA, Shang P, Shapira O, Shelton T, Shen C, Shen H, Shepherd R, Shi R, Shi Y, Shiah YJ, Shibata T, Shih J, Shimizu E, Shimizu K, Shin SJ, Shiraishi Y, Shmaya T, Shmulevich I, Shorser SI, Short C, Shrestha R, Shringarpure SS, Shriver C, Shuai S, Sidiropoulos N, Siebert R, Sieuwerts AM, Sieverling L, Signoretti S, Sikora KO, Simbolo M, Simon R, Simons JV, Simpson JT, Simpson PT, Singer S, Sinnott-Armstrong N, Sipahimalani P, Skelly TJ, Smid M, Smith J, Smith-McCune K, Socci ND, Sofia HJ, Soloway MG, Song L, Sood AK, Sothi S, Sotiriou C, Soulette CM, Span PN, Spellman PT, Sperandio N, Spillane AJ, Spiro O, Spring J, Staaf J, Stadler PF, Staib P, Stark SG, Stebbings L, Stefánsson ÓA, Stegle O, Stein LD, Stenhouse A, Stewart C, Stilgenbauer S, Stobbe MD, Stratton MR, Stretch JR, Struck AJ, Stuart JM, Stunnenberg HG, Su H, Su X, Sun RX, Sungalee S, Susak H, Suzuki A, Sweep F, Szczepanowski M, Sültmann H, Yugawa T, Tam A, Tamborero D, Tan BKT, Tan D, Tan P, Tanaka H, Taniguchi H, Tanskanen TJ, Tarabichi M, Tarnuzzer R, Tarpey P, Taschuk ML, Tatsuno K, Tavaré S, Taylor DF, Taylor-Weiner A, Teague JW, Teh BT, Tembe V, Temes J, Thai K, Thayer SP, Thiessen N, Thomas G, Thomas S, Thompson A, Thompson AM, Thompson JFF, Thompson RH, Thorne H, Thorne LB, Thorogood A, Tiao G, Tijanic N, Timms LE, Tirabosco R, Tojo M, Tommasi S, Toon CW, Toprak UH, Torrents D, Tortora G, Tost J, Totoki Y, Townend D, Traficante N, Treilleux I, Trotta JR, Trümper LHP, Tsao M, Tsunoda T, Tubio JMC, Tucker O, Turkington R, Turner DJ, Tutt A, Ueno M, Ueno NT, Umbricht C, Umer HM, Underwood TJ, Urban L, Urushidate T, Ushiku T, Uusküla-Reimand L, Valencia A, Van Den Berg DJ, Van Laere S, Van Loo P, Van Meir EG, Van den Eynden GG, Van der Kwast T, Vasudev N, Vazquez M, Vedururu R, Veluvolu U, Vembu S, Verbeke LPC, Vermeulen P, Verrill C, Viari A, Vicente D, Vicentini C, VijayRaghavan K, Viksna J, Vilain RE, Villasante I, Vincent-Salomon A, Visakorpi T, Voet D, Vyas P, Vázquez-García I, Waddell NM, Waddell N, Wadelius C, Wadi L, Wagener R, Wala JA, Wang J, Wang J, Wang L, Wang Q, Wang W, Wang Y, Wang Z, Waring PM, Warnatz HJ, Warrell J, Warren AY, Waszak SM, Wedge DC, Weichenhan D, Weinberger P, Weinstein JN, Weischenfeldt J, Weisenberger DJ, Welch I, Wendl MC, Werner J, Whalley JP, Wheeler DA, Whitaker HC, Wigle D, Wilkerson MD, Williams A, Wilmott JS, Wilson GW, Wilson JM, Wilson RK, Winterhoff B, Wintersinger JA, Wiznerowicz M, Wolf S, Wong BH, Wong T, Wong W, Woo Y, Wood S, Wouters BG, Wright AJ, Wright DW, Wright MH, Wu CL, Wu DY, Wu G, Wu J, Wu K, Wu Y, Wu Z, Xi L, Xia T, Xiang Q, Xiao X, Xing R, Xiong H, Xu Q, Xu Y, Xue H, Yachida S, Yakneen S, Yamaguchi R, Yamaguchi TN, Yamamoto M, Yamamoto S, Yamaue H, Yang F, Yang H, Yang JY, Yang L, Yang L, Yang S, Yang TP, Yang Y, Yao X, Yaspo ML, Yates L, Yau C, Ye C, Ye K, Yellapantula VD, Yoon CJ, Yoon SS, Yousif F, Yu J, Yu K, Yu W, Yu Y, Yuan K, Yuan Y, Yuen D, Yung CK, Zaikova O, Zamora J, Zapatka M, Zenklusen JC, Zenz T, Zeps N, Zhang CZ, Zhang F, Zhang H, Zhang H, Zhang H, Zhang J, Zhang J, Zhang J, Zhang X, Zhang X, Zhang Y, Zhang Z, Zhao Z, Zheng L, Zheng X, Zhou W, Zhou Y, Zhu B, Zhu H, Zhu J, Zhu S, Zou L, Zou X, deFazio A, van As N, van Deurzen CHM, van de Vijver MJ, van’t Veer L, von Mering C. Pan-cancer analysis of whole genomes. Nature 2020; 578:82-93. [PMID: 32025007 PMCID: PMC7025898 DOI: 10.1038/s41586-020-1969-6] [Citation(s) in RCA: 1435] [Impact Index Per Article: 358.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2018] [Accepted: 12/11/2019] [Indexed: 02/07/2023]
Abstract
Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale1-3. Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter4; identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation5,6; analyses timings and patterns of tumour evolution7; describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity8,9; and evaluates a range of more-specialized features of cancer genomes8,10-18.
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Murillo OD, Thistlethwaite W, Rozowsky J, Subramanian SL, Lucero R, Shah N, Jackson AR, Srinivasan S, Chung A, Laurent CD, Kitchen RR, Galeev T, Warrell J, Diao JA, Welsh JA, Hanspers K, Riutta A, Burgstaller-Muehlbacher S, Shah RV, Yeri A, Jenkins LM, Ahsen ME, Cordon-Cardo C, Dogra N, Gifford SM, Smith JT, Stolovitzky G, Tewari AK, Wunsch BH, Yadav KK, Danielson KM, Filant J, Moeller C, Nejad P, Paul A, Simonson B, Wong DK, Zhang X, Balaj L, Gandhi R, Sood AK, Alexander RP, Wang L, Wu C, Wong DTW, Galas DJ, Van Keuren-Jensen K, Patel T, Jones JC, Das S, Cheung KH, Pico AR, Su AI, Raffai RL, Laurent LC, Roth ME, Gerstein MB, Milosavljevic A. exRNA Atlas Analysis Reveals Distinct Extracellular RNA Cargo Types and Their Carriers Present across Human Biofluids. Cell 2019; 177:463-477.e15. [PMID: 30951672 PMCID: PMC6616370 DOI: 10.1016/j.cell.2019.02.018] [Citation(s) in RCA: 183] [Impact Index Per Article: 36.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2018] [Revised: 11/06/2018] [Accepted: 02/11/2019] [Indexed: 12/11/2022]
Abstract
To develop a map of cell-cell communication mediated by extracellular RNA (exRNA), the NIH Extracellular RNA Communication Consortium created the exRNA Atlas resource (https://exrna-atlas.org). The Atlas version 4P1 hosts 5,309 exRNA-seq and exRNA qPCR profiles from 19 studies and a suite of analysis and visualization tools. To analyze variation between profiles, we apply computational deconvolution. The analysis leads to a model with six exRNA cargo types (CT1, CT2, CT3A, CT3B, CT3C, CT4), each detectable in multiple biofluids (serum, plasma, CSF, saliva, urine). Five of the cargo types associate with known vesicular and non-vesicular (lipoprotein and ribonucleoprotein) exRNA carriers. To validate utility of this model, we re-analyze an exercise response study by deconvolution to identify physiologically relevant response pathways that were not detected previously. To enable wide application of this model, as part of the exRNA Atlas resource, we provide tools for deconvolution and analysis of user-provided case-control studies.
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Affiliation(s)
- Oscar D Murillo
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
| | - William Thistlethwaite
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
| | - Joel Rozowsky
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Sai Lakshmi Subramanian
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
| | - Rocco Lucero
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
| | - Neethu Shah
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
| | - Andrew R Jackson
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
| | - Srimeenakshi Srinivasan
- Department of Obstetrics, Gynecology, and Reproductive Sciences and Sanford Consortium for Regenerative Medicine, University of California, San Diego, La Jolla, CA 92037, USA
| | - Allen Chung
- Department of Surgery, University of California, San Francisco, San Francisco, CA 94143, USA; Surgical Service, San Francisco Veterans Affairs Medical Center, San Francisco, CA 94121, USA
| | - Clara D Laurent
- Department of Obstetrics, Gynecology, and Reproductive Sciences and Sanford Consortium for Regenerative Medicine, University of California, San Diego, La Jolla, CA 92037, USA
| | | | - Timur Galeev
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Jonathan Warrell
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - James A Diao
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA; Harvard-MIT Division of Health Sciences and Technology, Harvard Medical School, Boston, MA 02115, USA
| | - Joshua A Welsh
- Translational Nanobiology Section, Laboratory of Pathology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | | | | | | | - Ravi V Shah
- Cardiovascular Research Center, Cardiology Division, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
| | - Ashish Yeri
- Cardiovascular Research Center, Cardiology Division, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
| | - Lisa M Jenkins
- Laboratory of Cell Biology, Center for Cancer Research, NIH, Bethesda, MD 20892, USA
| | - Mehmet E Ahsen
- Department of Genetics and Genomics Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Carlos Cordon-Cardo
- Department of Pathology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Navneet Dogra
- Department of Genetics and Genomics Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; IBM T.J. Watson Research Center, IBM Research, Yorktown Heights, NY 10598, USA
| | - Stacey M Gifford
- IBM T.J. Watson Research Center, IBM Research, Yorktown Heights, NY 10598, USA
| | - Joshua T Smith
- IBM T.J. Watson Research Center, IBM Research, Yorktown Heights, NY 10598, USA
| | - Gustavo Stolovitzky
- Department of Genetics and Genomics Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; IBM T.J. Watson Research Center, IBM Research, Yorktown Heights, NY 10598, USA
| | - Ashutosh K Tewari
- Department of Urology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Benjamin H Wunsch
- IBM T.J. Watson Research Center, IBM Research, Yorktown Heights, NY 10598, USA
| | - Kamlesh K Yadav
- Department of Urology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Sema4, Stamford, CT 06902, USA
| | - Kirsty M Danielson
- Cardiovascular Research Center, Cardiology Division, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
| | - Justyna Filant
- Department of Gynecologic Oncology and Reproductive Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Courtney Moeller
- Department of Obstetrics, Gynecology, and Reproductive Sciences and Sanford Consortium for Regenerative Medicine, University of California, San Diego, La Jolla, CA 92037, USA
| | - Parham Nejad
- Department of Neurology, Center for Neurologic Diseases, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Anu Paul
- Department of Neurology, Center for Neurologic Diseases, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Bridget Simonson
- Cardiovascular Research Center, Cardiology Division, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
| | - David K Wong
- Department of Surgery, University of California, San Francisco, San Francisco, CA 94143, USA; Surgical Service, San Francisco Veterans Affairs Medical Center, San Francisco, CA 94121, USA
| | - Xuan Zhang
- Exosome Diagnostics, Inc., Waltham, MA 02451, USA
| | - Leonora Balaj
- Department of Neurosurgery, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Roopali Gandhi
- Department of Neurology, Center for Neurologic Diseases, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Anil K Sood
- Department of Gynecologic Oncology and Reproductive Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA; Center for RNA Interference and Non-Coding RNAs, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA; Department of Cancer Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | | | - Liang Wang
- Department of Pathology and MCW Cancer Center, Medical College of Wisconsin, Milwaukee, WI 53226, USA
| | - Chunlei Wu
- Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA 92037, USA
| | - David T W Wong
- School of Dentistry, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - David J Galas
- Pacific Northwest Research Institute, Seattle, WA 98122, USA
| | | | - Tushar Patel
- Department of Transplantation, Mayo Clinic, Jacksonville, FL 32224, USA
| | - Jennifer C Jones
- Translational Nanobiology Section, Laboratory of Pathology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Saumya Das
- Cardiovascular Research Center, Cardiology Division, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
| | - Kei-Hoi Cheung
- Department of Emergency Medicine, Yale University School of Medicine, New Haven, CT 06520, USA
| | | | - Andrew I Su
- Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA 92037, USA
| | - Robert L Raffai
- Department of Surgery, University of California, San Francisco, San Francisco, CA 94143, USA; Surgical Service, San Francisco Veterans Affairs Medical Center, San Francisco, CA 94121, USA
| | - Louise C Laurent
- Department of Obstetrics, Gynecology, and Reproductive Sciences and Sanford Consortium for Regenerative Medicine, University of California, San Diego, La Jolla, CA 92037, USA
| | - Matthew E Roth
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
| | - Mark B Gerstein
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA; Program in Computational Biology & Bioinformatics, Yale University, New Haven, CT 06520, USA; Department of Computer Science, Yale University, New Haven, CT 06520, USA
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Rozowsky J, Kitchen RR, Park JJ, Galeev TR, Diao J, Warrell J, Thistlethwaite W, Subramanian SL, Milosavljevic A, Gerstein M. exceRpt: A Comprehensive Analytic Platform for Extracellular RNA Profiling. Cell Syst 2019; 8:352-357.e3. [PMID: 30956140 DOI: 10.1016/j.cels.2019.03.004] [Citation(s) in RCA: 85] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2017] [Revised: 01/31/2019] [Accepted: 03/06/2019] [Indexed: 01/09/2023]
Abstract
Small RNA sequencing has been widely adopted to study the diversity of extracellular RNAs (exRNAs) in biofluids; however, the analysis of exRNA samples can be challenging: they are vulnerable to contamination and artifacts from different isolation techniques, present in lower concentrations than cellular RNA, and occasionally of exogenous origin. To address these challenges, we present exceRpt, the exRNA-processing toolkit of the NIH Extracellular RNA Communication Consortium (ERCC). exceRpt is structured as a cascade of filters and quantifications prioritized based on one's confidence in a given set of annotated RNAs. It generates quality control reports and abundance estimates for RNA biotypes. It is also capable of characterizing mappings to exogenous genomes, which, in turn, can be used to generate phylogenetic trees. exceRpt has been used to uniformly process all ∼3,500 exRNA-seq datasets in the public exRNA Atlas and is available from genboree.org and github.gersteinlab.org/exceRpt.
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Affiliation(s)
- Joel Rozowsky
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA
| | - Robert R Kitchen
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA
| | - Jonathan J Park
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA
| | - Timur R Galeev
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA
| | - James Diao
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA
| | - Jonathan Warrell
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA
| | - William Thistlethwaite
- Bioinformatics Research Laboratory, Molecular and Human Genetics Department, Baylor College of Medicine, Houston, TX, USA
| | - Sai L Subramanian
- Bioinformatics Research Laboratory, Molecular and Human Genetics Department, Baylor College of Medicine, Houston, TX, USA
| | - Aleksandar Milosavljevic
- Bioinformatics Research Laboratory, Molecular and Human Genetics Department, Baylor College of Medicine, Houston, TX, USA
| | - Mark Gerstein
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA; Department of Computer Science, Yale University, New Haven, CT, USA.
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14
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Wang D, Liu S, Warrell J, Won H, Shi X, Navarro FCP, Clarke D, Gu M, Emani P, Yang YT, Xu M, Gandal MJ, Lou S, Zhang J, Park JJ, Yan C, Rhie SK, Manakongtreecheep K, Zhou H, Nathan A, Peters M, Mattei E, Fitzgerald D, Brunetti T, Moore J, Jiang Y, Girdhar K, Hoffman GE, Kalayci S, Gümüş ZH, Crawford GE, Roussos P, Akbarian S, Jaffe AE, White KP, Weng Z, Sestan N, Geschwind DH, Knowles JA, Gerstein MB. Comprehensive functional genomic resource and integrative model for the human brain. Science 2019; 362:362/6420/eaat8464. [PMID: 30545857 DOI: 10.1126/science.aat8464] [Citation(s) in RCA: 462] [Impact Index Per Article: 92.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2018] [Accepted: 11/15/2018] [Indexed: 12/12/2022]
Abstract
Despite progress in defining genetic risk for psychiatric disorders, their molecular mechanisms remain elusive. Addressing this, the PsychENCODE Consortium has generated a comprehensive online resource for the adult brain across 1866 individuals. The PsychENCODE resource contains ~79,000 brain-active enhancers, sets of Hi-C linkages, and topologically associating domains; single-cell expression profiles for many cell types; expression quantitative-trait loci (QTLs); and further QTLs associated with chromatin, splicing, and cell-type proportions. Integration shows that varying cell-type proportions largely account for the cross-population variation in expression (with >88% reconstruction accuracy). It also allows building of a gene regulatory network, linking genome-wide association study variants to genes (e.g., 321 for schizophrenia). We embed this network into an interpretable deep-learning model, which improves disease prediction by ~6-fold versus polygenic risk scores and identifies key genes and pathways in psychiatric disorders.
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Gandal MJ, Zhang P, Hadjimichael E, Walker RL, Chen C, Liu S, Won H, van Bakel H, Varghese M, Wang Y, Shieh AW, Haney J, Parhami S, Belmont J, Kim M, Moran Losada P, Khan Z, Mleczko J, Xia Y, Dai R, Wang D, Yang YT, Xu M, Fish K, Hof PR, Warrell J, Fitzgerald D, White K, Jaffe AE, Peters MA, Gerstein M, Liu C, Iakoucheva LM, Pinto D, Geschwind DH. Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder. Science 2019; 362:362/6420/eaat8127. [PMID: 30545856 DOI: 10.1126/science.aat8127] [Citation(s) in RCA: 635] [Impact Index Per Article: 127.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2018] [Accepted: 11/13/2018] [Indexed: 12/12/2022]
Abstract
Most genetic risk for psychiatric disease lies in regulatory regions, implicating pathogenic dysregulation of gene expression and splicing. However, comprehensive assessments of transcriptomic organization in diseased brains are limited. In this work, we integrated genotypes and RNA sequencing in brain samples from 1695 individuals with autism spectrum disorder (ASD), schizophrenia, and bipolar disorder, as well as controls. More than 25% of the transcriptome exhibits differential splicing or expression, with isoform-level changes capturing the largest disease effects and genetic enrichments. Coexpression networks isolate disease-specific neuronal alterations, as well as microglial, astrocyte, and interferon-response modules defining previously unidentified neural-immune mechanisms. We integrated genetic and genomic data to perform a transcriptome-wide association study, prioritizing disease loci likely mediated by cis effects on brain expression. This transcriptome-wide characterization of the molecular pathology across three major psychiatric disorders provides a comprehensive resource for mechanistic insight and therapeutic development.
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Vineet V, Warrell J, Torr PHS. Filter-Based Mean-Field Inference for Random Fields with Higher-Order Terms and Product Label-Spaces. Int J Comput Vis 2014. [DOI: 10.1007/s11263-014-0708-6] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
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17
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Manning L, Laman M, Rosanas-Urgell A, Turlach B, Aipit S, Bona C, Warrell J, Siba P, Mueller I, Davis TME. Rapid antigen detection tests for malaria diagnosis in severely ill Papua New Guinean children: a comparative study using Bayesian latent class models. PLoS One 2012; 7:e48701. [PMID: 23144935 PMCID: PMC3489828 DOI: 10.1371/journal.pone.0048701] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2012] [Accepted: 09/28/2012] [Indexed: 11/18/2022] Open
Abstract
Background Although rapid diagnostic tests (RDTs) have practical advantages over light microscopy (LM) and good sensitivity in severe falciparum malaria in Africa, their utility where severe non-falciparum malaria occurs is unknown. LM, RDTs and polymerase chain reaction (PCR)-based methods have limitations, and thus conventional comparative malaria diagnostic studies employ imperfect gold standards. We assessed whether, using Bayesian latent class models (LCMs) which do not require a reference method, RDTs could safely direct initial anti-infective therapy in severe ill children from an area of hyperendemic transmission of both Plasmodium falciparum and P. vivax. Methods and Findings We studied 797 Papua New Guinean children hospitalized with well-characterized severe illness for whom LM, RDT and nested PCR (nPCR) results were available. For any severe malaria, the estimated prevalence was 47.5% with RDTs exhibiting similar sensitivity and negative predictive value (NPV) to nPCR (≥96.0%). LM was the least sensitive test (87.4%) and had the lowest NPV (89.7%), but had the highest specificity (99.1%) and positive predictive value (98.9%). For severe falciparum malaria (prevalence 42.9%), the findings were similar. For non-falciparum severe malaria (prevalence 6.9%), no test had the WHO-recommended sensitivity and specificity of >95% and >90%, respectively. RDTs were the least sensitive (69.6%) and had the lowest NPV (96.7%). Conclusions RDTs appear a valuable point-of-care test that is at least equivalent to LM in diagnosing severe falciparum malaria in this epidemiologic situation. None of the tests had the required sensitivity/specificity for severe non-falciparum malaria but the number of false-negative RDTs in this group was small.
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Affiliation(s)
- Laurens Manning
- School of Medicine and Pharmacology, University of Western Australia, Fremantle Hospital, Fremantle, Western Australia, Australia
| | - Moses Laman
- School of Medicine and Pharmacology, University of Western Australia, Fremantle Hospital, Fremantle, Western Australia, Australia
- Papua New Guinea Institute of Medical Research, Madang, Papua New Guinea
| | | | - Berwin Turlach
- Centre for Applied Statistics, University of Western Australia, Crawley, Western Australia, Australia
| | - Susan Aipit
- Papua New Guinea Institute of Medical Research, Madang, Papua New Guinea
| | - Cathy Bona
- Papua New Guinea Institute of Medical Research, Madang, Papua New Guinea
| | - Jonathan Warrell
- Papua New Guinea Institute of Medical Research, Madang, Papua New Guinea
| | - Peter Siba
- Papua New Guinea Institute of Medical Research, Madang, Papua New Guinea
| | - Ivo Mueller
- Papua New Guinea Institute of Medical Research, Madang, Papua New Guinea
- Barcelona Centre for International Health Research (CRESIB), Barcelona, Spain
- Walter and Eliza Hall Institute, Parkville, Melbourne, Australia
| | - Timothy M. E. Davis
- School of Medicine and Pharmacology, University of Western Australia, Fremantle Hospital, Fremantle, Western Australia, Australia
- * E-mail:
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Manning L, Laman M, Law I, Bona C, Aipit S, Teine D, Warrell J, Rosanas-Urgell A, Lin E, Kiniboro B, Vince J, Hwaiwhanje I, Karunajeewa H, Michon P, Siba P, Mueller I, Davis TME. Features and prognosis of severe malaria caused by Plasmodium falciparum, Plasmodium vivax and mixed Plasmodium species in Papua New Guinean children. PLoS One 2011; 6:e29203. [PMID: 22216212 PMCID: PMC3245265 DOI: 10.1371/journal.pone.0029203] [Citation(s) in RCA: 62] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2011] [Accepted: 11/22/2011] [Indexed: 11/28/2022] Open
Abstract
Background Mortality from severe pediatric falciparum malaria appears low in Oceania but Plasmodium vivax is increasingly recognized as a cause of complications and death. The features and prognosis of mixed Plasmodium species infections are poorly characterized. Detailed prospective studies that include accurate malaria diagnosis and detection of co-morbidities are lacking. Methods and Findings We followed 340 Papua New Guinean (PNG) children with PCR-confirmed severe malaria (77.1% P. falciparum, 7.9% P. vivax, 14.7% P. falciparum/vivax) hospitalized over a 3-year period. Bacterial cultures were performed to identify co-incident sepsis. Clinical management was under national guidelines. Of 262 children with severe falciparum malaria, 30.9%, 24.8% and 23.2% had impaired consciousness, severe anemia, and metabolic acidosis/hyperlactatemia, respectively. Two (0.8%) presented with hypoglycemia, seven (2.7%) were discharged with neurologic impairment, and one child died (0.4%). The 27 severe vivax malaria cases presented with similar phenotypic features to the falciparum malaria cases but respiratory distress was five times more common (P = 0.001); one child died (3.7%). The 50 children with P. falciparum/vivax infections shared phenotypic features of mono-species infections, but were more likely to present in deep coma and had the highest mortality (8.0%; P = 0.003 vs falciparum malaria). Overall, bacterial cultures were positive in only two non-fatal cases. 83.6% of the children had alpha-thalassemia trait and seven with coma/impaired consciousness had South Asian ovalocytosis (SAO). Conclusions The low mortality from severe falciparum malaria in PNG children may reflect protective genetic factors other than alpha-thalassemia trait/SAO, good nutrition, and/or infrequent co-incident sepsis. Severe vivax malaria had similar features but severe P. falciparum/vivax infections were associated with the most severe phenotype and worst prognosis.
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Affiliation(s)
- Laurens Manning
- School of Medicine and Pharmacology, University of Western Australia, Fremantle Hospital, Fremantle, Western Australia, Australia
| | - Moses Laman
- School of Medicine and Pharmacology, University of Western Australia, Fremantle Hospital, Fremantle, Western Australia, Australia
- Papua New Guinea Institute of Medical Research, Madang, Madang Province, Papua New Guinea
| | - Irwin Law
- Papua New Guinea Institute of Medical Research, Madang, Madang Province, Papua New Guinea
| | - Cathy Bona
- Papua New Guinea Institute of Medical Research, Madang, Madang Province, Papua New Guinea
| | - Susan Aipit
- Papua New Guinea Institute of Medical Research, Madang, Madang Province, Papua New Guinea
| | - David Teine
- Papua New Guinea Institute of Medical Research, Madang, Madang Province, Papua New Guinea
| | - Jonathan Warrell
- Papua New Guinea Institute of Medical Research, Madang, Madang Province, Papua New Guinea
| | - Anna Rosanas-Urgell
- Papua New Guinea Institute of Medical Research, Madang, Madang Province, Papua New Guinea
| | - Enmoore Lin
- Papua New Guinea Institute of Medical Research, Madang, Madang Province, Papua New Guinea
| | - Benson Kiniboro
- Papua New Guinea Institute of Medical Research, Madang, Madang Province, Papua New Guinea
| | - John Vince
- School of Medicine and Health Sciences, University of Papua New Guinea, Boroko, Port Moresby, Papua New Guinea
| | - Ilomo Hwaiwhanje
- Department of Pediatrics, Goroka Base Hospital, Goroka, Eastern Highlands Province, Papua New Guinea
| | - Harin Karunajeewa
- School of Medicine and Pharmacology, University of Western Australia, Fremantle Hospital, Fremantle, Western Australia, Australia
| | - Pascal Michon
- Papua New Guinea Institute of Medical Research, Madang, Madang Province, Papua New Guinea
| | - Peter Siba
- Papua New Guinea Institute of Medical Research, Madang, Madang Province, Papua New Guinea
| | - Ivo Mueller
- Papua New Guinea Institute of Medical Research, Madang, Madang Province, Papua New Guinea
| | - Timothy M. E. Davis
- School of Medicine and Pharmacology, University of Western Australia, Fremantle Hospital, Fremantle, Western Australia, Australia
- * E-mail:
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Prince SJD, Elder JH, Warrell J, Felisberti FM. Tied factor analysis for face recognition across large pose differences. IEEE Trans Pattern Anal Mach Intell 2008; 30:970-984. [PMID: 18421104 DOI: 10.1109/tpami.2008.48] [Citation(s) in RCA: 29] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/26/2023]
Abstract
Face recognition algorithms perform very unreliably when the pose of the probe face is different from the gallery face: typical feature vectors vary more with pose than with identity. We propose a generative model that creates a one-to-many mapping from an idealized "identity" space to the observed data space. In identity space, the representation for each individual does not vary with pose. We model the measured feature vector as being generated by a pose-contingent linear transformation of the identity variable in the presence of Gaussian noise. We term this model "tied" factor analysis. The choice of linear transformation (factors) depends on the pose, but the loadings are constant (tied) for a given individual. We use the EM algorithm to estimate the linear transformations and the noise parameters from training data. We propose a probabilistic distance metric which allows a full posterior over possible matches to be established. We introduce a novel feature extraction process and investigate recognition performance using the FERET, XM2VTS and PIE databases. Recognition performance compares favourably to contemporary approaches.
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Affiliation(s)
- Simon J D Prince
- Department of Computer Sciences, University College London, London, UK.
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