CNVannotator: a comprehensive annotation server for copy number variation in the human genome

Unravelling the Genetic Landscape of Hemiplegic Migraine: Exploring Innovative Strategies and Emerging Approaches

Migraine is a severe, debilitating neurovascular disorder. Hemiplegic migraine (HM) is a rare and debilitating neurological condition with a strong genetic basis. Sequencing technologies have improved the diagnosis and our understanding of the molecular pathophysiology of HM. Linkage analysis and sequencing studies in HM families have identified pathogenic variants in ion channels and related genes, including CACNA1A, ATP1A2, and SCN1A, that cause HM. However, approximately 75% of HM patients are negative for these mutations, indicating there are other genes involved in disease causation. In this review, we explored our current understanding of the genetics of HM. The evidence presented herein summarises the current knowledge of the genetics of HM, which can be expanded further to explain the remaining heritability of this debilitating condition. Innovative bioinformatics and computational strategies to cover the entire genetic spectrum of HM are also discussed in this review.

ENLIGHTENMENT: A Scalable Annotated Database of Genomics and NGS-Based Nucleotide Level Profiles

The revolution in sequencing technologies has enabled human genomes to be sequenced at a very low cost and time leading to exponential growth in the availability of whole-genome sequences. However, the complete understanding of our genome and its association with cancer is a far way to go. Researchers are striving hard to detect new variants and find their association with diseases, which further gives rise to the need for aggregation of this Big Data into a common standard scalable platform. In this work, a database named Enlightenment has been implemented which makes the availability of genomic data integrated from eight public databases, and DNA sequencing profiles of H. sapiens in a single platform. Annotated results with respect to cancer specific biomarkers, pharmacogenetic biomarkers and its association with variability in drug response, and DNA profiles along with novel copy number variants are computed and stored, which are accessible through a web interface. In order to overcome the challenge of storage and processing of NGS technology-based whole-genome DNA sequences, Enlightenment has been extended and deployed to a flexible and horizontally scalable database HBase, which is distributed over a hadoop cluster, which would enable the integration of other omics data into the database for enlightening the path towards eradication of cancer.

Identifying the Common Cell-Free DNA Biomarkers across Seven Major Cancer Types

Blood-based detection of circulating cell-free DNA (cfDNA) is a non-invasive and easily accessible method for early cancer detection. Despite the extensive utility of cfDNA, there are still many challenges to developing clinical biomarkers. For example, cfDNA with genetic alterations often composes a small portion of the DNA circulating in plasma, which can be confounded by cfDNA contributed by normal cells. Therefore, filtering out the potential false-positive cfDNA mutations from healthy populations will be important for cancer-based biomarkers. Additionally, many low-frequency genetic alterations are easily overlooked in a small number of cfDNA-based cancer tests. We hypothesize that the combination of diverse types of cancer studies on cfDNA will provide us with a new perspective on the identification of low-frequency genetic variants across cancer types for promoting early diagnosis. By building a standardized computational pipeline for 1358 cfDNA samples across seven cancer types, we prioritized 129 shard genetic variants in the major cancer types. Further functional analysis of the 129 variants found that they are mainly enriched in ribosome pathways such as cotranslational protein targeting the membrane, some of which are tumour suppressors, oncogenes, and genes related to cancer initiation. In summary, our integrative analysis revealed the important roles of ribosome proteins as common biomarkers in early cancer diagnosis.

circExp database: an online transcriptome platform for human circRNA expressions in cancers

Circular RNA (circRNA) is a highly stable, single-stranded, closed-loop RNA that works as RNA or as a protein decoy to regulate gene expression. In humans, thousands of circRNA transcriptional products precisely express in specific developmental stages, tissues and cell types. Due to their stability and specificity, circRNAs are ideal biomarkers for cancer diagnosis and prognosis. To provide an integrated and standardized circRNA expression profile for human cancers, we performed extensive data curation across 11 technical platforms, collecting 48 expression profile data sets for 18 cancer types and amassing 860 751 expression records. We also identified 189 193 differential expression signatures that are significantly different between normal and cancer samples. All the pre-calculated expression analysis results are organized into 132 plain text files for bulk download. Our online interface, circExp, provides data browsing and search functions. For each data set, a dynamic expression heatmap provides a profile overview. Based on the processed data, we found that 52 circRNAs were consistently and differentially expressed in 20 or more processed analyses. By mapping those circRNAs to their parent protein-coding genes, we found that they may have profoundly affected the survival of 10 797 patients in the The Cancer Genome Atlas pan-cancer data set. In sum, we developed circExp and demonstrated that it is useful to identify circRNAs that have potential diagnostic and prognostic significance for a variety of cancer types. In this online and reusable database, found at http://soft.bioinfo-minzhao.org/circexp, we have provided pre-calculated expression data about circRNAs and their parental genes, as well as data browsing and searching functions. Database URL: http://soft.bioinfominzhao.org/circexp/.

Copy Number Variation: Methods and Clinical Applications

Gains and losses of large segments of genomic DNA, known as copy number variants (CNVs) gained considerable interest in clinical diagnostics lately, as particular forms may lead to inherited genetic diseases. In recent decades, researchers developed a wide variety of cytogenetic and molecular methods with different detection capabilities to detect clinically relevant CNVs. In this review, we summarize methodological progress from conventional approaches to current state of the art techniques capable of detecting CNVs from a few bases up to several megabases. Although the recent rapid progress of sequencing methods has enabled precise detection of CNVs, determining their functional effect on cellular and whole-body physiology remains a challenge. Here, we provide a comprehensive list of databases and bioinformatics tools that may serve as useful assets for researchers, laboratory diagnosticians, and clinical geneticists facing the challenge of CNV detection and interpretation.

Monoallelic Mutations in CC2D1A Suggest a Novel Role in Human Heterotaxy and Ciliary Dysfunction

BACKGROUND

Human heterotaxy is a group of congenital disorders characterized by misplacement of one or more organs according to the left-right axis. The genetic causes of human heterotaxy are highly heterogeneous.

METHODS

We performed exome sequencing in a cohort of 26 probands with heterotaxy followed by gene burden analysis for the enrichment of novel rare damaging mutations. Transcription activator-like effector nuclease was used to generate somatic loss-of-function mutants in a zebrafish model. Ciliary defects were examined by whole-mount immunostaining of acetylated α-tubulin.

RESULTS

We identified a significant enrichment of novel rare damaging mutations in the CC2D1A gene. Seven occurrences of CC2D1A mutations were found to affect 4 highly conserved amino acid residues of the protein. Functional analyses in the transcription activator-like effector nuclease-mediated zebrafish knockout models were performed, and heterotaxy phenotypes of the cardiovascular and gastrointestinal systems in both somatic and germline mutants were observed. Defective cilia were demonstrated by whole-mount immunostaining of acetylated α-tubulin. These abnormalities were rescued by wild-type cc2d1a mRNA but not cc2d1a mutant mRNA, strongly suggesting a loss-of-function mechanism. On the other hand, overexpression of cc2d1a orthologous mutations cc2d1a P559L and cc2d1a G808V (orthologous to human CC2D1A P532L and CC2D1A G781V) did not affect embryonic development.

CONCLUSIONS

Using a zebrafish model, we were able to establish a novel association of CC2D1A with heterotaxy and ciliary dysfunction in the F2 generation via a loss-of-function mechanism. Future mechanistic studies are needed for a better understanding of the role of CC2D1A in left-right patterning and ciliary dysfunction.

REDBot: Natural language process methods for clinical copy number variation reporting in prenatal and products of conception diagnosis

Background

Current copy number variation (CNV) identification methods have rapidly become mature. However, the postdetection processes such as variant interpretation or reporting are inefficient. To overcome this situation, we developed REDBot as an automated software package for accurate and direct generation of clinical diagnostic reports for prenatal and products of conception (POC) samples.

Methods

We applied natural language process (NLP) methods for analyzing 30,235 in‐house historical clinical reports through active learning, and then, developed clinical knowledge bases, evidence‐based interpretation methods and reporting criteria to support the whole postdetection pipeline.

Results

Of the 30,235 reports, we obtained 37,175 CNV‐paragraph pairs. For these pairs, the active learning approaches achieved a 0.9466 average F1‐score in sentence classification. The overall accuracy for variant classification was 95.7%, 95.2%, and 100.0% in retrospective, prospective, and clinical utility experiments, respectively.

Conclusion

By integrating NLP methods in CNVs postdetection pipeline, REDBot is a robust and rapid tool with clinical utility for prenatal and POC diagnosis.

AnnotSV: an integrated tool for structural variations annotation

Summary

Structural Variations (SV) are a major source of variability in the human genome that shaped its actual structure during evolution. Moreover, many human diseases are caused by SV, highlighting the need to accurately detect those genomic events but also to annotate them and assist their biological interpretation. Therefore, we developed AnnotSV that compiles functionally, regulatory and clinically relevant information and aims at providing annotations useful to (i) interpret SV potential pathogenicity and (ii) filter out SV potential false positive. In particular, AnnotSV reports heterozygous and homozygous counts of single nucleotide variations (SNVs) and small insertions/deletions called within each SV for the analyzed patients, this genomic information being extremely useful to support or question the existence of an SV. We also report the computed allelic frequency relative to overlapping variants from DGV (MacDonald et al., 2014), that is especially powerful to filter out common SV. To delineate the strength of AnnotSV, we annotated the 4751 SV from one sample of the 1000 Genomes Project, integrating the sample information of four million of SNV/indel, in less than 60 s.

Availability and implementation

AnnotSV is implemented in Tcl and runs in command line on all platforms. The source code is available under the GNU GPL license. Source code, README and Supplementary data are available at http://lbgi.fr/AnnotSV/.

Supplementary information

Supplementary data are available at Bioinformatics online.

iCopyDAV: Integrated platform for copy number variations-Detection, annotation and visualization

Discovery of copy number variations (CNVs), a major category of structural variations, have dramatically changed our understanding of differences between individuals and provide an alternate paradigm for the genetic basis of human diseases. CNVs include both copy gain and copy loss events and their detection genome-wide is now possible using high-throughput, low-cost next generation sequencing (NGS) methods. However, accurate detection of CNVs from NGS data is not straightforward due to non-uniform coverage of reads resulting from various systemic biases. We have developed an integrated platform, iCopyDAV, to handle some of these issues in CNV detection in whole genome NGS data. It has a modular framework comprising five major modules: data pre-treatment, segmentation, variant calling, annotation and visualization. An important feature of iCopyDAV is the functional annotation module that enables the user to identify and prioritize CNVs encompassing various functional elements, genomic features and disease-associations. Parallelization of the segmentation algorithms makes the iCopyDAV platform even accessible on a desktop. Here we show the effect of sequencing coverage, read length, bin size, data pre-treatment and segmentation approaches on accurate detection of the complete spectrum of CNVs. Performance of iCopyDAV is evaluated on both simulated data and real data for different sequencing depths. It is an open-source integrated pipeline available at https://github.com/vogetihrsh/icopydav and as Docker’s image at http://bioinf.iiit.ac.in/icopydav/.

Expression of epithelial-mesenchymal transition-related genes increases with copy number in multiple cancer types

Epithelial-mesenchymal transition (EMT) is a cellular process through which epithelial cells transform into mesenchymal cells. EMT-implicated genes initiate and promote cancer metastasis because mesenchymal cells have greater invasive and migration capacities than epithelial cells. In this pan-cancer analysis, we explored the relationship between gene expression changes and copy number variations (CNVs) for EMT-implicated genes. Based on curated 377 EMT-implicated genes from the literature, we identified 212 EMT-implicated genes associated with more frequent copy number gains (CNGs) than copy number losses (CNLs) using data from The Cancer Genome Atlas (TCGA). Then by correlating these CNV data with TCGA gene expression data, we identified 71 EMT-implicated genes with concordant CNGs and gene up-regulation in 20 or more tumor samples. Of those, 14 exhibited such concordance in over 110 tumor samples. These 14 genes were predominantly apoptosis regulators, which may implies that apoptosis is critical during EMT. Moreover, the 71 genes with concordant CNG and up-regulation were largely involved in cellular functions such as phosphorylation cascade signaling. This is the first observation of concordance between CNG and up-regulation of specific genes in hundreds of samples, which may indicate that somatic CNGs activate gene expression by increasing the gene dosage.

An interspecies heart-to-heart: Using Xenopus to uncover the genetic basis of congenital heart disease

PURPOSE OF REVIEW

Given the enormous impact congenital heart disease has on child health, it is imperative that we improve our understanding of the disease mechanisms that underlie patient phenotypes and clinical outcomes. This review will outline the merits of using the frog model, Xenopus, as a tool to study human cardiac development and left-right patterning mechanisms associated with congenital heart disease.

RECENT FINDINGS

Patient-driven gene discovery continues to provide new insight into the mechanisms of congenital heart disease, and by extension, patient phenotypes and outcomes. By identifying gene variants in CHD patients, studies in Xenopus have elucidated the molecular mechanisms of how these candidate genes affect cardiac development, both cardiogenesis as well as left-right patterning, which can have a major impact on cardiac morphogenesis. Xenopus has also proved to be a useful screening tool for the biological relevance of identified patient-mutations, and ongoing investigations continue to illuminate disease mechanisms.

SUMMARY

Analyses in model organisms can help to elucidate the disease mechanisms underlying CHD patient phenotypes. Using Xenopus to disentangle the genotype-phenotype relationships of well-known and novel disease genes could enhance the ability of physicians to efficaciously treat patients and predict clinical outcomes, ultimately improving quality of life and survival rates of patients born with congenital heart disease.

Concordance of copy number loss and down-regulation of tumor suppressor genes: a pan-cancer study

Background

Tumor suppressor genes (TSGs) encode the guardian molecules to control cell growth. The genomic alteration of TSGs may cause tumorigenesis and promote cancer progression. So far, investigators have mainly studied the functional effects of somatic single nucleotide variants in TSGs. Copy number variation (CNV) is another important form of genetic variation, and is often involved in cancer biology and drug treatment, but studies of CNV in TSGs are less represented in literature. In addition, there is a lack of a combinatory analysis of gene expression and CNV in this important gene set. Such a study may provide more insights into the relationship between gene dosage and tumorigenesis. To meet this demand, we performed a systematic analysis of CNVs and gene expression in TSGs to provide a systematic view of CNV and gene expression change in TSGs in pan-cancer.

Results

We identified 1170 TSGs with copy number gain or loss in 5846 tumor samples. Among them, 207 TSGs tended to have copy number loss (CNL), from which fifteen CNL hotspot regions were identified. The functional enrichment analysis revealed that the 207 TSGs were enriched in cancer-related pathways such as P53 signaling pathway and the P53 interactome. We further performed integrative analyses of CNV with gene expression using the data from the matched tumor samples. We found 81 TSGs with concordant CNL events and decreased gene expression in the tumor samples we examined. Remarkably, seven TSGs displayed concordant CNL and gene down-regulation in at least 50 tumor samples: MTAP (212 samples), PTEN (139), MCPH1 (85), FBXO25 (67), SMAD4 (64), TRIM35 (57), and RB1 (54). Specifically to MTAP, this concordance was found in 14 cancer types, an observation that is not much reported in literature yet. Further network-based analysis revealed that these TSGs with concordant CNL and gene down-regulation were highly connected.

Conclusions

This study provides a draft landscape of CNV in pan-cancer. Our findings of systematic concordance between CNL and down-regulation of gene expression may help better understand the TSG biology in tumorigenesis and cancer progression.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-2904-y) contains supplementary material, which is available to authorized users.

REGene: a literature-based knowledgebase of animal regeneration that bridge tissue regeneration and cancer

Regeneration is a common phenomenon across multiple animal phyla. Regeneration-related genes (REGs) are critical for fundamental cellular processes such as proliferation and differentiation. Identification of REGs and elucidating their functions may help to further develop effective treatment strategies in regenerative medicine. So far, REGs have been largely identified by small-scale experimental studies and a comprehensive characterization of the diverse biological processes regulated by REGs is lacking. Therefore, there is an ever-growing need to integrate REGs at the genomics, epigenetics, and transcriptome level to provide a reference list of REGs for regeneration and regenerative medicine research. Towards achieving this, we developed the first literature-based database called REGene (REgeneration Gene database). In the current release, REGene contains 948 human (929 protein-coding and 19 non-coding genes) and 8445 homologous genes curated from gene ontology and extensive literature examination. Additionally, the REGene database provides detailed annotations for each REG, including: gene expression, methylation sites, upstream transcription factors, and protein-protein interactions. An analysis of the collected REGs reveals strong links to a variety of cancers in terms of genetic mutation, protein domains, and cellular pathways. We have prepared a web interface to share these regeneration genes, supported by refined browsing and searching functions at http://REGene.bioinfo-minzhao.org/.

cnvScan: a CNV screening and annotation tool to improve the clinical utility of computational CNV prediction from exome sequencing data

Background

With advances in next generation sequencing technology and analysis methods, single nucleotide variants (SNVs) and indels can be detected with high sensitivity and specificity in exome sequencing data. Recent studies have demonstrated the ability to detect disease-causing copy number variants (CNVs) in exome sequencing data. However, exonic CNV prediction programs have shown high false positive CNV counts, which is the major limiting factor for the applicability of these programs in clinical studies.

Results

We have developed a tool (cnvScan) to improve the clinical utility of computational CNV prediction in exome data. cnvScan can accept input from any CNV prediction program. cnvScan consists of two steps: CNV screening and CNV annotation. CNV screening evaluates CNV prediction using quality scores and refines this using an in-house CNV database, which greatly reduces the false positive rate. The annotation step provides functionally and clinically relevant information using multiple source datasets.

We assessed the performance of cnvScan on CNV predictions from five different prediction programs using 64 exomes from Primary Immunodeficiency (PIDD) patients, and identified PIDD-causing CNVs in three individuals from two different families.

Conclusions

In summary, cnvScan reduces the time and effort required to detect disease-causing CNVs by reducing the false positive count and providing annotation. This improves the clinical utility of CNV detection in exome data.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-2374-2) contains supplementary material, which is available to authorized users.

TSGene 2.0: an updated literature-based knowledgebase for tumor suppressor genes

Tumor suppressor genes (TSGs) are a major type of gatekeeper genes in the cell growth. A knowledgebase with the systematic collection and curation of TSGs in multiple cancer types is critically important for further studying their biological functions as well as for developing therapeutic strategies. Since its development in 2012, the Tumor Suppressor Gene database (TSGene), has become a popular resource in the cancer research community. Here, we reported the TSGene version 2.0, which has substantial updates of contents (e.g. up-to-date literature and pan-cancer genomic data collection and curation), data types (noncoding RNAs and protein-coding genes) and content accessibility. Specifically, the current TSGene 2.0 contains 1217 human TSGs (1018 protein-coding and 199 non-coding genes) curated from over 9000 articles. Additionally, TSGene 2.0 provides thousands of expression and mutation patterns derived from pan-cancer data of The Cancer Genome Atlas. A new web interface is available at http://bioinfo.mc.vanderbilt.edu/TSGene/. Systematic analyses of 199 non-coding TSGs provide numerous cancer-specific non-coding mutational events for further screening and clinical use. Intriguingly, we identified 49 protein-coding TSGs that were consistently down-regulated in 11 cancer types. In summary, TSGene 2.0, which is the only available database for TSGs, provides the most updated TSGs and their features in pan-cancer.

Integrated analysis of oral tongue squamous cell carcinoma identifies key variants and pathways linked to risk habits, HPV, clinical parameters and tumor recurrence

Oral tongue squamous cell carcinomas (OTSCC) are a homogeneous group of tumors characterized by aggressive behavior, early spread to lymph nodes and a higher rate of regional failure. Additionally, the incidence of OTSCC among younger population (<50yrs) is on the rise; many of whom lack the typical associated risk factors of alcohol and/or tobacco exposure. We present data on single nucleotide variations (SNVs), indels, regions with loss of heterozygosity (LOH), and copy number variations (CNVs) from fifty-paired oral tongue primary tumors and link the significant somatic variants with clinical parameters, epidemiological factors including human papilloma virus (HPV) infection and tumor recurrence. Apart from the frequent somatic variants harbored in TP53, CASP8, RASA1, NOTCH and CDKN2A genes, significant amplifications and/or deletions were detected in chromosomes 6-9, and 11 in the tumors. Variants in CASP8 and CDKN2A were mutually exclusive. CDKN2A, PIK3CA, RASA1 and DMD variants were exclusively linked to smoking, chewing, HPV infection and tumor stage. We also performed a whole-genome gene expression study that identified matrix metalloproteases to be highly expressed in tumors and linked pathways involving arachidonic acid and NF-k-B to habits and distant metastasis, respectively. Functional knockdown studies in cell lines demonstrated the role of CASP8 in a HPV-negative OTSCC cell line. Finally, we identified a 38-gene minimal signature that predicts tumor recurrence using an ensemble machine-learning method. Taken together, this study links molecular signatures to various clinical and epidemiological factors in a homogeneous tumor population with a relatively high HPV prevalence.

The Role of Constitutional Copy Number Variants in Breast Cancer

Constitutional copy number variants (CNVs) include inherited and de novo deviations from a diploid state at a defined genomic region. These variants contribute significantly to genetic variation and disease in humans, including breast cancer susceptibility. Identification of genetic risk factors for breast cancer in recent years has been dominated by the use of genome-wide technologies, such as single nucleotide polymorphism (SNP)-arrays, with a significant focus on single nucleotide variants. To date, these large datasets have been underutilised for generating genome-wide CNV profiles despite offering a massive resource for assessing the contribution of these structural variants to breast cancer risk. Technical challenges remain in determining the location and distribution of CNVs across the human genome due to the accuracy of computational prediction algorithms and resolution of the array data. Moreover, better methods are required for interpreting the functional effect of newly discovered CNVs. In this review, we explore current and future application of SNP array technology to assess rare and common CNVs in association with breast cancer risk in humans.

The promise of omics-based approaches to cancer prevention

Cancer is a complex category of diseases caused in large part by genetic or genomic, transcriptomic, and epigenetic or epigenomic alterations in affected cells and the surrounding microenvironment. Carcinogenesis reflects the clonal expansion of cells that progressively acquire these genetic and epigenetic alterations-changes that, in turn, lead to modifications at the RNA level. Gradually advancing technology and most recently, the advent of next-generation sequencing (NGS), combined with bioinformatics analytic tools, have revolutionized our ability to interrogate cancer cells. The ultimate goal is to apply these high-throughput technologies to the various aspects of clinical cancer care: cancer-risk assessment, diagnosis, as well as target identification for treatment and prevention. In this article, we emphasize how the knowledge gained through large-scale omics-oriented approaches, with a focus on variations at the level of nucleic acids, can inform the field of chemoprevention.

DeAnnCNV: a tool for online detection and annotation of copy number variations from whole-exome sequencing data

With the decrease in costs, whole-exome sequencing (WES) has become a very popular and powerful tool for the identification of genetic variants underlying human diseases. However, integrated tools to precisely detect and systematically annotate copy number variations (CNVs) from WES data are still in great demand. Here, we present an online tool, DeAnnCNV (Detection and Annotation of Copy Number Variations from WES data), to meet the current demands of WES users. Upon submitting the file generated from WES data by an in-house tool that can be downloaded from our server, DeAnnCNV can detect CNVs in each sample and extract the shared CNVs among multiple samples. DeAnnCNV also provides additional useful supporting information for the detected CNVs and associated genes to help users to find the potential candidates for further experimental study. The web server is implemented in PHP + Perl + MATLAB and is online available to all users for free at http://mcg.ustc.edu.cn/db/cnv/.

The variation game: Cracking complex genetic disorders with NGS and omics data

Tremendous advances in Next Generation Sequencing (NGS) and high-throughput omics methods have brought us one step closer towards mechanistic understanding of the complex disease at the molecular level. In this review, we discuss four basic regulatory mechanisms implicated in complex genetic diseases, such as cancer, neurological disorders, heart disease, diabetes, and many others. The mechanisms, including genetic variations, copy-number variations, posttranscriptional variations, and epigenetic variations, can be detected using a variety of NGS methods. We propose that malfunctions detected in these mechanisms are not necessarily independent, since these malfunctions are often found associated with the same disease and targeting the same gene, group of genes, or functional pathway. As an example, we discuss possible rewiring effects of the cancer-associated genetic, structural, and posttranscriptional variations on the protein-protein interaction (PPI) network centered around P53 protein. The review highlights multi-layered complexity of common genetic disorders and suggests that integration of NGS and omics data is a critical step in developing new computational methods capable of deciphering this complexity.

Using network clustering to predict copy number variations associated with health disparities

Substantial health disparities exist between African Americans and Caucasians in the United States. Copy number variations (CNVs) are one form of human genetic variations that have been linked with complex diseases and often occur at different frequencies among African Americans and Caucasian populations. Here, we aimed to investigate whether CNVs with differential frequencies can contribute to health disparities from the perspective of gene networks. We inferred network clusters from human gene/protein networks based on two different data sources. We then evaluated each network cluster for the occurrences of known pathogenic genes and genes located in CNVs with different population frequencies, and used false discovery rates to rank network clusters. This approach let us identify five clusters enriched with known pathogenic genes and with genes located in CNVs with different frequencies between African Americans and Caucasians. These clustering patterns predict two candidate causal genes located in four population-specific CNVs that play potential roles in health disparities

SG-ADVISER CNV: copy-number variant annotation and interpretation

PURPOSE

Copy-number variants have been associated with a variety of diseases, especially cancer, autism, schizophrenia, and developmental delay. The majority of clinically relevant events occur de novo, necessitating the interpretation of novel events. In this light, we present the Scripps Genome ADVISER CNV annotation pipeline and Web server, which aims to fill the gap between copy number variant detection and interpretation by performing in-depth annotations and functional predictions for copy number variants.

METHODS

The Scripps Genome ADVISER CNV suite includes a Web server interface to a high-performance computing environment for calculations of annotations and a table-based user interface that allows for the execution of numerous annotation-based variant filtration strategies and statistics.

RESULTS

The annotation results include details regarding location, impact on the coding portion of genes, allele frequency information (including allele frequencies from the Scripps Wellderly cohort), and overlap information with other reference data sets (including ClinVar, DGV, DECIPHER). A summary variant classification is produced (ADVISER score) based on the American College of Medical Genetics and Genomics scoring guidelines. We demonstrate >90% sensitivity/specificity for detection of pathogenic events.

CONCLUSION

Scripps Genome ADVISER CNV is designed to allow users with no prior bioinformatics expertise to manipulate large volumes of copy-number variant data. Scripps Genome ADVISER CNV is available at http://genomics.scripps.edu/ADVISER/.