ArticleBMC genomics2017
Pan-cancer analysis reveals technical artifacts in TCGA germline variant calls.
Article in BMC genomics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.
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Who cites it
32 citing papers in PubMed.
- A Practical Workflow for Correcting Kit-Specific Effects in Whole-Exome Sequencing Data.Methods and protocols · 2026Article
- Formal verification of bioinformatics software using model checking and theorem proving.Briefings in bioinformatics · 2025Article
- A model workflow for microfluidic enrichment and genetic analysis of circulating melanoma cells.Scientific reports · 2025Article
- Assessment of candidate high-grade serous ovarian carcinoma predisposition genes through integrated germline and tumour sequencing.NPJ genomic medicine · 2025Article
- A benchmarking study of individual somatic variant callers and voting-based ensembles for whole-exome sequencing.Briefings in bioinformatics · 2024Article
- MHC Hammer reveals genetic and non-genetic HLA disruption in cancer evolution.Nature genetics · 2024Article
- A comprehensive analysis of clinical and polygenic germline influences on somatic mutational burden.American journal of human genetics · 2024Article
- Associating somatic mutation with clinical outcomes through kernel regression and optimal transport.Biometrics · 2023Article
- Discordant calls across genotype discovery approaches elucidate variants with systematic errors.Genome research · 2023Article
- Validation of genetic variants from NGS data using deep convolutional neural networks.BMC bioinformatics · 2023Article
- Persistent mutation burden drives sustained anti-tumor immune responses.Nature medicine · 2023Article
- Interrogating the Human Diplome: Computational Methods, Emerging Applications, and Challenges.Methods in molecular biology (Clifton, N.J.) · 2023Article
- Dual Domestication, Diversity, and Differential Introgression in Old World Cotton Diploids.Genome biology and evolution · 2022Article
- Computational analysis of cancer genome sequencing data.Nature reviews. Genetics · 2022Review
- Prevalence of cancer susceptibility variants in patients with multiple Lynch syndrome related cancers.Scientific reports · 2021Article
- Exome-Wide Pan-Cancer Analysis of Germline Variants in 8,719 Individuals Finds Little Evidence of Rare Variant Associations.Human heredity · 2021Article
- Impact of variant-level batch effects on identification of genetic risk factors in large sequencing studies.PloS one · 2021Article
- Germline genomic patterns are associated with cancer risk, oncogenic pathways, and clinical outcomes.Science advances · 2020Article
- Epithelial ovarian cancer risk: A review of the current genetic landscape.Clinical genetics · 2020Review
- Oncogenic effects of germline variants in lysosomal storage disease genes.Genetics in medicine : official journal of the American College of Medical Genetics · 2019Article
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Authors and funding
8 authors.
Funding
Abstract
backgroundCancer research to date has largely focused on somatically acquired genetic aberrations. In contrast, the degree to which germline, or inherited, variation contributes to tumorigenesis remains unclear, possibly due to a lack of accessible germline variant data. Here we called germline variants on 9618 cases from The Cancer Genome Atlas (TCGA) database representing 31 cancer types.
resultsWe identified batch effects affecting loss of function (LOF) variant calls that can be traced back to differences in the way the sequence data were generated both within and across cancer types. Overall, LOF indel calls were more sensitive to technical artifacts than LOF Single Nucleotide Variant (SNV) calls. In particular, whole genome amplification of DNA prior to sequencing led to an artificially increased burden of LOF indel calls, which confounded association analyses relating germline variants to tumor type despite stringent indel filtering strategies. The samples affected by these technical artifacts include all acute myeloid leukemia and practically all ovarian cancer samples.
conclusionsWe demonstrate how technical artifacts induced by whole genome amplification of DNA can lead to false positive germline-tumor type associations and suggest TCGA whole genome amplified samples be used with caution. This study draws attention to the need to be sensitive to problems associated with a lack of uniformity in data generation in TCGA data.
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