Research output: Contribution to journal › Article › peer-review
Pygenomics: manipulating genomic intervals and data files in Python. / Tamazian, Gaik ; Cherkasov, Nikolay ; Kanapin, Alexander ; Samsonova, Anastasia .
In: Bioinformatics, Vol. 39, No. 6, btad34, 01.06.2023, p. 1-3.Research output: Contribution to journal › Article › peer-review
}
TY - JOUR
T1 - Pygenomics: manipulating genomic intervals and data files in Python
AU - Tamazian, Gaik
AU - Cherkasov, Nikolay
AU - Kanapin, Alexander
AU - Samsonova, Anastasia
PY - 2023/6/1
Y1 - 2023/6/1
N2 - SUMMARY: We present pygenomics, a Python package for working with genomic intervals and bioinformatic data files. The package implements interval operations, provides both API and CLI, and supports reading and writing data in widely used bioinformatic formats, including BAM, BED, GFF3, and VCF. The source code of pygenomics is provided with in-source documentation and type annotations and adheres to the functional programming paradigm. These features facilitate seamless integration of pygenomics routines into scripts and pipelines. The package is implemented in pure Python using its standard library only and contains the property-based testing framework. Comparison of pygenomics with other Python bioinformatic packages with relation to features and performance is presented. The performance comparison covers operations with genomic intervals, read alignments, and genomic variants and demonstrates that pygenomics is suitable for computationally effective analysis.AVAILABILITY AND IMPLEMENTATION: The source code is available at https://gitlab.com/gtamazian/pygenomics.
AB - SUMMARY: We present pygenomics, a Python package for working with genomic intervals and bioinformatic data files. The package implements interval operations, provides both API and CLI, and supports reading and writing data in widely used bioinformatic formats, including BAM, BED, GFF3, and VCF. The source code of pygenomics is provided with in-source documentation and type annotations and adheres to the functional programming paradigm. These features facilitate seamless integration of pygenomics routines into scripts and pipelines. The package is implemented in pure Python using its standard library only and contains the property-based testing framework. Comparison of pygenomics with other Python bioinformatic packages with relation to features and performance is presented. The performance comparison covers operations with genomic intervals, read alignments, and genomic variants and demonstrates that pygenomics is suitable for computationally effective analysis.AVAILABILITY AND IMPLEMENTATION: The source code is available at https://gitlab.com/gtamazian/pygenomics.
KW - Computational Biology
KW - Gene Library
KW - Genome
KW - Genomics
KW - Software
UR - https://www.mendeley.com/catalogue/6c67d65c-bb1d-3e2c-aeda-1c4dfa49dd00/
U2 - 10.1093/bioinformatics/btad346
DO - 10.1093/bioinformatics/btad346
M3 - Article
C2 - 37228014
VL - 39
SP - 1
EP - 3
JO - Bioinformatics
JF - Bioinformatics
SN - 1367-4803
IS - 6
M1 - btad34
ER -
ID: 106363578