Systematic identification of significantly mutated regions reveals a rich landscape of functional molecular alterations across cancer genomes

Abstract excerpt

Cancer genome sequencing studies have identified cancer-driver genes from the increased accumulation of protein-altering mutations. However, the positional distributions of coding mutations, and the 79% of somatic variants in exome data that do not alter protein sequence or RNA splicing, remain largely unstudied. We employed density-based clustering methods on ~4,700 exomes from 21 tumor types to detect variably-s...

Topics

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• Databases, Nucleic Acid
• Exome
• Genes, Neoplasm
• Genome, Human
• Genomics
• High-Throughput Nucleotide Sequencing
• Mutation
• Neoplasms

Identifiers and source

Literature Corpus work

5178d614-7bb3-52c9-9c26-bc7323f4ad93

DOI

10.1101/020875