Article

Unique K-mer sequences for validating cancer-related substitution, insertion and deletion mutations

2020-06-20

Abstract excerpt

<h4>ABSTRACT</h4> The cancer genome sequencing has led to important discoveries such as identifying cancer gene. However, challenges remain in the analysis of cancer genome sequencing. One significant issue is that mutations identified by multiple variant callers are frequently discordant even when using the same genome sequencing data. For insertion and deletion mutations, oftentimes there is no agreement among...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 500f5fd5-589a-5f0a-8566-f31453712e5f
DOI: 10.1101/2020.06.20.163113

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Unique K-mer sequences for validating cancer-related substitution, insertion and deletion mutationsDOI 10.1101/2020.06.20.163113Read

A pan-cancer landscape of somatic substitutions in non-unique regions of the human genomeSemantic proximity Read

A pan-cancer landscape of somatic mutations in non-unique regions of the human genome.Semantic proximity Read

Ultra-fast Prediction of Somatic Structural Variations by Reduced Read Mapping via Pan-Genome <i>k</i> -mer SetsSemantic proximity Read

Identifying cancer mutation targets across thousands of samples: MuteProc, a high throughput mutation analysis pipeline.Semantic proximity Read

CANCERSIGN: a user-friendly and robust tool for identification and classification of mutational signatures and patterns in cancer genomesSemantic proximity Read

BreaKmer: detection of structural variation in targeted massively parallel sequencing data using kmers.Semantic proximity Read

Systematic comparison of somatic variant calling performance among different sequencing depth and mutation frequency.Semantic proximity Read

SomaticSniper: identification of somatic point mutations in whole genome sequencing data.Semantic proximity Read

CANCERSIGN: a user-friendly and robust tool for identification and classification of mutational signatures and patterns in cancer genomes.Semantic proximity Read

Combining calls from multiple somatic mutation-callers.Semantic proximity Read

Characterization of cancer-driving nucleotides (CDNs) across genes, cancer types, and patients.Semantic proximity Read

Mis-annotated multi nucleotide variants in public cancer genomics datasets can lead to inaccurate mutation calls with significant implicationsSemantic proximity Read