CNVfilteR

CNVfilteR filters false-positive germline copy-number variant (CNV) calls by leveraging single-nucleotide variant (SNV) calls from germline NGS pipelines, implemented as an R/Bioconductor package to improve CNV detection accuracy.


Key Features:

  • Implementation: Implemented as an R package within the Bioconductor framework.
  • SNV integration: Uses single-nucleotide variant (SNV) calls obtained during germline NGS pipelines to assess CNV calls.
  • False deletion and duplication detection: Identifies false deletions and false duplications within CNV callsets.
  • Compatibility with multiple callers: Applies to CNV callsets generated by a variety of CNV calling tools.
  • Performance gains: Demonstrated reductions in false positives up to 44.8% and consistent improvements in F1-score.
  • Evaluation scope: Tested on callsets from 13 CNV calling tools across three whole-genome sequencing projects and 541 panel samples.
  • Pipeline integration: Designed to be applied within existing CNV calling pipelines to refine results.

Scientific Applications:

  • Hereditary disease studies: Refines germline CNV calls used in studies of hereditary diseases.
  • Variant interpretation: Reduces false positives to improve interpretation of CNVs in genetic analyses.
  • CNV-caller benchmarking: Supports evaluation and comparison of CNV calling tool performance.

Methodology:

Integrates SNV calls from germline NGS pipelines with CNV callsets to identify and flag false deletions and duplications; implemented as an R/Bioconductor package.

Topics

Details

License:
Artistic-2.0
Tool Type:
library
Programming Languages:
R
Added:
6/14/2021
Last Updated:
11/24/2024

Operations

Publications

Moreno-Cabrera JM, del Valle J, Castellanos E, Feliubadaló L, Pineda M, Serra E, Capellá G, Lázaro C, Gel B. CNVfilteR: an R/Bioconductor package to identify false positives produced by germline NGS CNV detection tools. Bioinformatics. 2021;37(22):4227-4229. doi:10.1093/bioinformatics/btab356. PMID:33983414. PMCID:PMC9502136.

PMID: 33983414
PMCID: PMC9502136
Funding: - CERCA: PI16/00563, PI19/00553 - CIBERONC: 2017SGR1282, 2017SGR496

Links