Apr 10, 2020

Deep learning discerns cancer mutation exclusivity

BioRxiv : the Preprint Server for Biology
Debarka Sen GuptaDebarka Sengupta

Abstract

The exclusivity of a vast majority of cancer mutations remains poorly understood, despite the availability of large amounts of whole genome and exome sequencing data. In clinical settings, this markedly hinders the identification of the previously uncharacterized deleterious mutations due to the unavailability of matched normal samples. We employed state of the art deep learning algorithms for cross-exome learning of mutational embeddings and demonstrated their utility in sequence based detection of cancer-specific Single Nucleotide Variants (SNVs).

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Mentioned in this Paper

Vertebrates
Sequence Determinations, RNA
Basic Local Alignment Search Tool
Ncbi Taxonomy
Genome Assembly Sequence
Bos taurus
Taurine
Babesia bigemina (antigen)
Infection by Babesia Bigemina
Massively-Parallel Sequencing

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