DeTiN: overcoming tumor-in-normal contamination

NATURE METHODS(2018)

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摘要
Comparison of sequencing data from a tumor sample with data from a matched germline control is a key step for accurate detection of somatic mutations. Detection sensitivity for somatic variants is greatly reduced when the matched normal sample is contaminated with tumor cells. To overcome this limitation, we developed deTiN, a method that estimates the tumor-in-normal (TiN) contamination level and, in cases affected by contamination, improves sensitivity by reclassifying initially discarded variants as somatic.
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关键词
Cancer genomics,Computational models,Mutation,Statistical methods,Life Sciences,general,Biological Techniques,Biological Microscopy,Biomedical Engineering/Biotechnology,Bioinformatics,Proteomics
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