scikit-allel - Explore and analyse genetic variation¶
- Source: https://github.com/cggh/scikit-allel
- Documentation: http://scikit-allel.readthedocs.org/
- Download: https://pypi.python.org/pypi/scikit-allel
- Gitter: https://gitter.im/cggh/pygenomics
Please feel free to ask questions via cggh/pygenomics on Gitter. Release announcements are posted to the cggh/pygenomics Gitter channel and the biovalidation mailing list. If you find a bug or would like to suggest a feature, please raise an issue on GitHub.
This site provides reference documentation for scikit-allel. For worked examples with real data, see the following articles:
If you would like to cite scikit-allel please use the DOI below.
“SciKits” (short for SciPy Toolkits) are add-on packages for SciPy, hosted and developed separately and independently from the main SciPy distribution.
“Allel” (Greek ἀλλήλ) is the root of the word “allele” short for “allelomorph”, a word coined by William Bateson to mean variant forms of a gene. Today we use “allele” to mean any of the variant forms found at a site of genetic variation, such as the different nucleotides observed at a single nucleotide polymorphism (SNP).
Install pre-built binaries via conda:
$ conda install -c conda-forge scikit-allel
Install and compile source code via pip:
$ pip install scikit-allel
N.B., this package requires numpy, scipy, matplotlib, seaborn, pandas, scikit-learn, h5py, numexpr, bcolz, zarr and dask. If installing via conda, these should be installed automatically. If installing via pip, please install these dependencies first, then use pip to install scikit-allel.
- Data structures
- Statistics and plotting
- Input/output utilities
- Chunked storage utilities
- Miscellaneous utilities
- Release notes
Development of this package is supported by the MRC Centre for Genomics and Global Health.