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Corbett RD, Eveleigh R, Whitney J, Barai N, Bourgey M, Chuah E, Johnson J, Moore RA, Moradin N, Mungall KL, Pereira S, Reuter MS, Thiruvahindrapuram B, Wintle RF, Ragoussis J, Strug LJ, Herbrick JA, Aziz N, Jones SJM, Lathrop M, Scherer SW, Staffa A, Mungall AJ. A Distributed Whole Genome Sequencing Benchmark Study. Front Genet 2020; 11:612515. [PMID: 33335541 PMCID: PMC7736078 DOI: 10.3389/fgene.2020.612515] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2020] [Accepted: 11/10/2020] [Indexed: 12/30/2022] Open
Abstract
Population sequencing often requires collaboration across a distributed network of sequencing centers for the timely processing of thousands of samples. In such massive efforts, it is important that participating scientists can be confident that the accuracy of the sequence data produced is not affected by which center generates the data. A study was conducted across three established sequencing centers, located in Montreal, Toronto, and Vancouver, constituting Canada's Genomics Enterprise (www.cgen.ca). Whole genome sequencing was performed at each center, on three genomic DNA replicates from three well-characterized cell lines. Secondary analysis pipelines employed by each site were applied to sequence data from each of the sites, resulting in three datasets for each of four variables (cell line, replicate, sequencing center, and analysis pipeline), for a total of 81 datasets. These datasets were each assessed according to multiple quality metrics including concordance with benchmark variant truth sets to assess consistent quality across all three conditions for each variable. Three-way concordance analysis of variants across conditions for each variable was performed. Our results showed that the variant concordance between datasets differing only by sequencing center was similar to the concordance for datasets differing only by replicate, using the same analysis pipeline. We also showed that the statistically significant differences between datasets result from the analysis pipeline used, which can be unified and updated as new approaches become available. We conclude that genome sequencing projects can rely on the quality and reproducibility of aggregate data generated across a network of distributed sites.
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Affiliation(s)
- Richard D. Corbett
- Canada’s Michael Smith Genome Sciences Centre, BC Cancer Research Institute, Provincial Health Services Authority, Vancouver, BC, Canada
| | - Robert Eveleigh
- McGill Genome Centre, McGill University, Montreal, QC, Canada
| | - Joe Whitney
- The Centre for Applied Genomics, The Hospital for Sick Children and University of Toronto, Toronto, ON, Canada
| | - Namrata Barai
- The Centre for Applied Genomics, The Hospital for Sick Children and University of Toronto, Toronto, ON, Canada
| | - Mathieu Bourgey
- McGill Genome Centre, McGill University, Montreal, QC, Canada
| | - Eric Chuah
- Canada’s Michael Smith Genome Sciences Centre, BC Cancer Research Institute, Provincial Health Services Authority, Vancouver, BC, Canada
| | - Joanne Johnson
- Canada’s Michael Smith Genome Sciences Centre, BC Cancer Research Institute, Provincial Health Services Authority, Vancouver, BC, Canada
| | - Richard A. Moore
- Canada’s Michael Smith Genome Sciences Centre, BC Cancer Research Institute, Provincial Health Services Authority, Vancouver, BC, Canada
| | - Neda Moradin
- The Centre for Applied Genomics, The Hospital for Sick Children and University of Toronto, Toronto, ON, Canada
| | - Karen L. Mungall
- Canada’s Michael Smith Genome Sciences Centre, BC Cancer Research Institute, Provincial Health Services Authority, Vancouver, BC, Canada
| | - Sergio Pereira
- The Centre for Applied Genomics, The Hospital for Sick Children and University of Toronto, Toronto, ON, Canada
| | - Miriam S. Reuter
- Canada’s Genomics Enterprise (CGEn), The Hospital for Sick Children, Toronto, ON, Canada
| | - Bhooma Thiruvahindrapuram
- The Centre for Applied Genomics, The Hospital for Sick Children and University of Toronto, Toronto, ON, Canada
| | - Richard F. Wintle
- The Centre for Applied Genomics, The Hospital for Sick Children and University of Toronto, Toronto, ON, Canada
| | | | - Lisa J. Strug
- The Centre for Applied Genomics, The Hospital for Sick Children and University of Toronto, Toronto, ON, Canada
| | - Jo-Anne Herbrick
- The Centre for Applied Genomics, The Hospital for Sick Children and University of Toronto, Toronto, ON, Canada
| | - Naveed Aziz
- Canada’s Genomics Enterprise (CGEn), The Hospital for Sick Children, Toronto, ON, Canada
| | - Steven J. M. Jones
- Canada’s Michael Smith Genome Sciences Centre, BC Cancer Research Institute, Provincial Health Services Authority, Vancouver, BC, Canada
| | - Mark Lathrop
- McGill Genome Centre, McGill University, Montreal, QC, Canada
| | - Stephen W. Scherer
- The Centre for Applied Genomics, The Hospital for Sick Children and University of Toronto, Toronto, ON, Canada
| | - Alfredo Staffa
- McGill Genome Centre, McGill University, Montreal, QC, Canada
| | - Andrew J. Mungall
- Canada’s Michael Smith Genome Sciences Centre, BC Cancer Research Institute, Provincial Health Services Authority, Vancouver, BC, Canada
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Chilcott RP, Barai N, Beezer AE, Brain SI, Brown MB, Bunge AL, Burgess SE, Cross S, Dalton CH, Dias M, Farinha A, Finnin BC, Gallagher SJ, Green DM, Gunt H, Gwyther RL, Heard CM, Jarvis CA, Kamiyama F, Kasting GB, Ley EE, Lim ST, McNaughton GS, Morris A, Nazemi MH, Pellett MA, Du Plessis J, Quan YS, Raghavan SL, Roberts M, Romonchuk W, Roper CS, Schenk D, Simonsen L, Simpson A, Traversa BD, Trottet L, Watkinson A, Wilkinson SC, Williams FM, Yamamoto A, Hadgraft J. Inter‐ and intralaboratory variation of in vitro diffusion cell measurements: An international multicenter study using quasi‐standardized methods and materials. J Pharm Sci 2005; 94:632-8. [PMID: 15666298 DOI: 10.1002/jps.20229] [Citation(s) in RCA: 47] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
In vitro measurements of skin absorption are an increasingly important aspect of regulatory studies, product support claims, and formulation screening. However, such measurements are significantly affected by skin variability. The purpose of this study was to determine inter- and intralaboratory variation in diffusion cell measurements caused by factors other than skin. This was attained through the use of an artificial (silicone rubber) rate-limiting membrane and the provision of materials including a standard penetrant, methyl paraben (MP), and a minimally prescriptive protocol to each of the 18 participating laboratories. "Standardized" calculations of MP flux were determined from the data submitted by each laboratory by applying a predefined mathematical model. This was deemed necessary to eliminate any interlaboratory variation caused by different methods of flux calculations. Average fluxes of MP calculated and reported by each laboratory (60 +/- 27 microg cm(-2) h(-1), n = 25, range 27-101) were in agreement with the standardized calculations of MP flux (60 +/- 21 microg cm(-2) h(-1), range 19-120). The coefficient of variation between laboratories was approximately 35% and was manifest as a fourfold difference between the lowest and highest average flux values and a sixfold difference between the lowest and highest individual flux values. Intralaboratory variation was lower, averaging 10% for five individuals using the same equipment within a single laboratory. Further studies should be performed to clarify the exact components responsible for nonskin-related variability in diffusion cell measurements. It is clear that further developments of in vitro methodologies for measuring skin absorption are required.
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Affiliation(s)
- R P Chilcott
- Dstl Biomedical Sciences, Porton Down, Salisbury, Wiltshire, SP4 0JQ, United Kingdom.
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