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Driven by high throughput next generation sequencing technologies and the pressing need to decipher cancer genomes, computational approaches for detecting somatic single nucleotide variants (sSNVs) have undergone dramatic improvements during the past 2 years. The recently developed tools typically compare a tumor sample directly with a matched normal sample at each variant locus in order to increase the accuracy of sSNV calling. These programs also address the detection of sSNVs at low allele frequencies, allowing for the study of tumor heterogeneity, cancer subclones, and mutation evolution in cancer development.
Pubmed ID: 24112718 RIS Download
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THIS RESOURCE IS NO LONGER IN SERVICE. Documented on March 17, 2022. Genome databases housed at the Genome Institute at Washington University. Included are genome databases from Humans/Primates, other vertebrates, microorganisms, plants and invertebrates.
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