CNVkit
A command-line toolkit and Python library for detecting copy number variations and alterations from targeted DNA sequencing.
Read the full documentation at: http://cnvkit.readthedocs.org
Installation
The script cnvkit.py requires no installation and can be used in-place. Just install the dependencies.
To install the script and Python library (and some associated scripts), use setup.py as usual:
python setup.py build python setup.py install
Python dependencies
Install these via pip or conda:
On Ubuntu or Debian Linux:
sudo apt-get install python-numpy python-matplotlib python-reportlab python-pip sudo pip install biopython pysam pyvcf --upgrade
On Mac OS X you may instead find it much easier to install the Anaconda distribution (https://store.continuum.io/cshop/anaconda/ or http://repo.continuum.io/miniconda/), which includes most of the dependencies already:
conda install numpy matplotlib reportlab biopython pysam pyvcf
Otherwise, we recommend using Homebrew (http://brew.sh/) or MacPorts to install an up-to-date Python (e.g. brew install python) and as many of the Python packages as possible (primarily numpy, scipy and matplotlib). Then, proceed with pip:
sudo pip install numpy matplotlib reportlab biopython pysam pyvcf
R dependencies
Copy number segmentation currently depends on R packages.
In CRAN:
PSCBS
matrixStats (for pruneByHClust in PSCBS)
PSCBS depends on the package DNAcopy which part of Bioconductor, and cannot be installed through CRAN directly. To use it, you must first install Bioconductor, then DNAcopy, then the PSCBS package as shown below.
Within R:
> source("http://bioconductor.org/biocLite.R")
> biocLite("DNAcopy")
> install.packages(c("PSCBS", "matrixStats", "cghFLasso"))
Testing
You can test your installation by running the CNVkit pipeline on the example files in the test/ directory. The pipeline is implemented as a Makefile and can be run with the make command (standard on Unix/Linux/Mac OS X systems):
cd test/ make
If this pipeline completes successfully (it should take less than a minute), you’ve installed CNVkit correctly.
To run the pipeline on additional, larger example file sets (named TR and EX), do this:
make all
The Python library cnvlib included with CNVkit has unit tests in this directory, too. To run the test suite:
python test_cnvlib.py
Citation
We are in the process of publishing a manuscript describing CNVkit. A preprint is available here: http://dx.doi.org/10.1101/010876
If you use this software in a publication, for now, please cite it by this DOI like so:
Eric Talevich, A. Hunter Shain, Boris C. Bastian (2014) CNVkit: Copy number detection and visualization for targeted sequencing using off-target reads. bioRxiv doi: 10.1101/010876
A recent poster presentation is also available on F1000 Posters: http://f1000.com/posters/browse/summary/1096236
1 maintainer
Metadata
1 maintainer
Release files for CNVkit 0.2.4
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
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| CNVkit-0.2.4.tar.gz | 67.9 kB | Details |
Release files / CNVkit-0.2.4.tar.gz
| Download URL | CNVkit-0.2.4.tar.gz |
|---|---|
| Size | 67.9 kB |
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