Scalable Open Science Approach for Mutation Calling of Tumor Exomes Using Multiple Genomic Pipelines.
Scalable Open Science Approach for Mutation Calling of Tumor Exomes Using Multiple Genomic Pipelines.
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DOI:
10.1016/j.cels.2018.03.002
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发表时间:
2018-03-28
期刊:
影响因子:
9.3
通讯作者:
Cancer Genome Atlas Research Network
中科院分区:
文献类型:
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作者:
Ellrott K;Bailey MH;Saksena G;Covington KR;Kandoth C;Stewart C;Hess J;Ma S;Chiotti KE;McLellan M;Sofia HJ;Hutter C;Getz G;Wheeler D;Ding L;MC3 Working Group;Cancer Genome Atlas Research Network
The Cancer Genome Atlas (TCGA) cancer genomics dataset includes over ten-thousand tumor-normal exome pairs across 33 different cancer types, in total >400 TB of raw data files requiring analysis. Here we describe the Multi-Center Mutation Calling in Multiple Cancers (MC3) project, our effort to generate a comprehensive encyclopedia of somatic mutation calls for the TCGA data to enable robust cross-tumor-type analyses. Our approach accounts for variance and batch effects introduced by the rapid advancement of DNA extraction, hybridization-capture, sequencing, and analysis methods over time. We present best practices for applying an ensemble of seven mutation-calling algorithms with scoring and artifact filtering. The dataset created by this analysis includes 3.5 million somatic variants and forms the basis for PanCan Atlas papers. The results have been made available to the research community along with the methods used to generate them. This project is the result of collaboration from a number of institutes and demonstrates how team science drives extremely large genomics projects. The MC3 project is a variant calling of over 10,000 cancer exome samples from 33 cancer types. Over 3 million somatic variants were detected using 7 different methods developed from institutions across the United States. These variants formed the basis for the PanCan Atlas papers.
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影响因子:
12.3
作者:
McLaren W;Gil L;Hunt SE;Riat HS;Ritchie GR;Thormann A;Flicek P;Cunningham F
通讯作者:
Cunningham F
影响因子:
14.9
作者:
Costello M;Pugh TJ;Fennell TJ;Stewart C;Lichtenstein L;Meldrim JC;Fostel JL;Friedrich DC;Perrin D;Dionne D;Kim S;Gabriel SB;Lander ES;Fisher S;Getz G
通讯作者:
Getz G
影响因子:
7
作者:
Dees ND;Zhang Q;Kandoth C;Wendl MC;Schierding W;Koboldt DC;Mooney TB;Callaway MB;Dooling D;Mardis ER;Wilson RK;Ding L
通讯作者:
Ding L
影响因子:
3
作者:
Kim, Su Yeon;Speed, Terence P.
通讯作者:
Speed, Terence P.
影响因子:
46.9
作者:
通讯作者:
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