Scalable Open Science Approach for Mutation Calling of Tumor Exomes Using Multiple Genomic Pipelines

By K. Ellrott, Matthew H. Bailey, G. Saksena, K. Covington, Cyriac Kandoth, Chip Stewart, Julian M. Hess, Singer Ma, M. McLellan, H. Sofia and 4 more. Cell Systems, 2018

746 citations recorded by the source corpus.

Summary 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.

Subfields: Cancer Research, Genetics, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/ac74cf1c41701486cd42fd3c00fc8e945f75ef14

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Citations in the corpus

SeSAMe: reducing artifactual detection of DNA methylation by Infinium BeadChips in genomic deletions (2018, methodology): “Somatic mutation MAF files for 10,290 TCGA tumor samples were downloaded from a previous study (19).”
Comprehensive Characterization of Cancer Driver Genes and Mutations (2018, methodology): “Mutation calls were produced by theMulti-Center Mutation Calling inMultiple Cancers (MC3) working group that harmonized the results of seven algorithms (Ellrott et al. 2018) (STAR Methods).”
Co-occurring genomic alterations in non-small cell lung cancer biology and therapy (2019, neutral): “The pervasive diversity of this oncogenotype was aptly demonstrated in a study that applied affinity propagation clustering analysis36 to mRNA expression a Early stage b Metastatic Data from TCGA (Sanchez-Vega et al.178, Ellrott et al.179 and Hoadley et al.180), Imielinski et al.62 and Kadara et al.”
Comprehensive Analysis of Alternative Splicing Across Tumors from 8,705 Patients (2018, background): “REAGENT or RESOURCE SOURCE IDENTIFIER Deposited Data TCGA Unified MC3 Variant Calls Ellrott et al., 2018 https://www.synapse.org/#!Synapse: syn7214402 Comprehensive set of alternative splicing events This Paper https://gdc.cancer.gov/about-data/ publications/PanCanAtlas-Splicing-2018 HLA types Shukl”
Maftools: efficient and comprehensive analysis of somatic variants in cancer (2018, methodology): “…addition, we also provide an R data package containing ready-to-use, precompiled somatic variants fromBroadFirehose,andMulti-CenterMutationCallinginMultipleCancersprojectforall34TCGAcohortsalongwiththerelevantclin-icalinformation(https://github.com/PoisonAlien/TCGAmutations) (Ellrott et al. 2018).”
Oncogenic Signaling Pathways in The Cancer Genome Atlas (2018, background): “This topic is further addressed in Bailey et al. (Bailey et al., 2018).”
Calling Somatic SNVs and Indels with Mutect2 (2019, methodology): “…Genomes Project, replicated this three times for each mixture, and sequenced the mixtures to obtain simulated subclonal tumor samples with a range [4] Mutect2 performs at or near the top of each leaderboard, although note that teams were allowed an unlimited number of submission after which they…”
The Immune Landscape of Cancer (2018, methodology): “First, source datasets from all 33 TCGA cancer types and six molecular platforms (mRNA, microRNA, and exome sequencing; DNA methylation-, copy number-, and reversephase protein arrays) were harmonized by the PanCanAtlas consortium for uniform quality control, batch effect correction, normalization, ”