CNVkit statistics

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CNVkit specifications

Information


Unique identifier OMICS_11538
Name CNVkit
Software type Toolkit/Suite
Interface Command line interface
Restrictions to use None
Input data One or more DNA sequencing read alignments and the capture bait locations or a pre-built “reference” file.
Input format BAM
Operating system Unix/Linux, Mac OS, Windows
License Apache License version 2.0
Computer skills Advanced
Version 0.9.5
Stability Stable
Requirements
DNAcopy, biopython, python, scipy, numpy, conda, pysam, matplotlib, bioconda, pandas, pyvcf, miniconda, anaconda, cnvkit, conda-forge
Maintained Yes

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Versioning


No version available

Documentation


Maintainer


  • person_outline Eric Talevich

Publications for CNVkit

CNVkit citations

 (24)
library_books

Genomic features of renal cell carcinoma with venous tumor thrombus

2018
Sci Rep
PMCID: 5945671
PMID: 29748622
DOI: 10.1038/s41598-018-25544-z

[…] CNAs were inferred from whole exome sequencing data with cnvKit version 0.8.6 (git repository hash: 85774ac) with default parameter settings.Heterozygous SNPs were determined as those positions with alternative allele fraction between 0.3 and 0.7 in the res […]

library_books

Genomic characterization of chronic lymphocytic leukemia (CLL) in radiation exposed Chornobyl cleanup workers

2018
PMCID: 5930419
PMID: 29720177
DOI: 10.1186/s12940-018-0387-9

[…] CNAs were analyzed using CNVkit [] and off-target reads from the target area with capture probes. CNVkit was run with default parameters and female genome as reference. A threshold of 0.3 was applied to identify the signals f […]

library_books

Deterministic Evolutionary Trajectories Influence Primary Tumor Growth: TRACERx Renal

2018
Cell
PMCID: 5938372
PMID: 29656894
DOI: 10.1016/j.cell.2018.03.043

[…] To estimate SCNAs, CNVkit v0.7.3 was performed with default parameter on paired tumour-normal sequencing data (). Outliers of the derived log2-ratio (logR) calls from CNVkit were detected and modified using Median Absol […]

library_books

Tracking Cancer Evolution Reveals Constrained Routes to Metastases: TRACERx Renal

2018
Cell
PMCID: 5938365
PMID: 29656895
DOI: 10.1016/j.cell.2018.03.057

[…] To estimate somatic copy number alterations, CNVkit v0.7.3 was performed with default parameter on paired tumour-normal sequencing data (). Outliers of the derived log2-ratio (logR) calls from CNVkit were detected and modified using Median Absol […]

library_books

Mutation hotspots at CTCF binding sites coupled to chromosomal instability in gastrointestinal cancers

2018
Nat Commun
PMCID: 5906695
PMID: 29670109
DOI: 10.1038/s41467-018-03828-2

[…] Copy number segmentations were generated by CNVkit using default settings (bcbio-nextgen v0.9.3). SCNA breakpoints were defined as the ends of non-diploid segments. Assuming tumor purity of 50%, the estimated mean purity of these tumors, non-di […]

library_books

Validation of CZECANCA (CZEch CAncer paNel for Clinical Application) for targeted NGS based analysis of hereditary cancer syndromes

2018
PLoS One
PMCID: 5896995
PMID: 29649263
DOI: 10.1371/journal.pone.0195761

[…] 35 samples tested positively using the MLPA analysis (). All CNVs including 18 samples with large BRCA1 deletions or duplications, 12 CNVs in CHEK2, four in PALB2 and one in TP53 were detected using CNVkit software in routine settings targeting 100X coverage (; ). This analysis also enabled to setup CNVkit thresholds indicating the presence of a deletion or a duplication. To estimate the number o […]

Citations

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CNVkit institution(s)
Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, CA, USA; Department of Dermatology, University of California, San Francisco, CA, USA
CNVkit funding source(s)
Supported by the National Institutes of Health [R01 CA131524, P01 CA025874].

CNVkit review

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Anonymous user #12651

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Desktop
I have been using this tool since 2017 for the detection of CNV in genes predisposed to breast and ovarian cancer.
This software is very precise (specificity, sensitivity). I'm now using it in diagnostics, on small and large panels of genes.
the documentation is rich and well done. Recommended for immediate use!!