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Article

ENVE: a novel computational framework characterizes copy-number mutational landscapes in colorectal cancers from African American patients.

Genome medicine - 1 Jan 2015

Varadan Vinay, Singh Salendra, Nosrati Arman, Ravi Lakshmeswari, Lutterbaugh James, Barnholtz-Sloan Jill S, Markowitz Sanford D, Willis Joseph E, Guda Kishore

Abstract excerpt

Reliable detection of somatic copy-number alterations (sCNAs) in tumors using whole-exome sequencing (WES) remains challenging owing to technical (inherent noise) and sample-associated variability in WES data. We present a novel computational framework, ENVE, which models inherent noise in any WES dataset, enabling robust detection of sCNAs across WES platforms. ENVE achieved high concordance with orthogonal sCNA...

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Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

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Identifiers

PMID: 26269717
DOI: 10.1186/s13073-015-0192-9
PMCID: PMC4534088

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-07.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

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