{"library":"pydeseq2","type":"library","category":null,"description":"PyDESeq2 is a Python implementation of the DESeq2 method for differential expression analysis (DEA) with bulk RNA-seq data. It enables researchers to perform single-factor and multi-factor designs, Wald tests with multiple testing correction, and optional LFC shrinkage. The library is actively maintained, with version 0.5.4 being the latest stable release, and it is part of the scverse ecosystem, integrating with AnnData for data handling.","language":"python","status":"active","version":"0.5.4","tags":["bioinformatics","rna-seq","differential-expression","deseq2","anndata","data-science"],"install":[{"cmd":"pip install pydeseq2","imports":["from pydeseq2.dds import DeseqDataSet","from pydeseq2.ds import DeseqStats","from pydeseq2.utils import load_example_data"]},{"cmd":"conda install -c bioconda pydeseq2","imports":[]}],"homepage":null,"github":"https://github.com/owkin/PyDESeq2","docs":"https://pydeseq2.readthedocs.io/","changelog":null,"pypi":"https://pypi.org/project/pydeseq2/","npm":null,"openapi_spec":null,"status_page":null,"smithery":null,"compatibility":{"summary":{"python_range":"3.10–3.9","success_rate":50,"avg_install_s":19.9,"avg_import_s":6.54,"wheel_type":"wheel"},"url":"https://checklist.day/v1/registry/pydeseq2/compatibility"},"provenance":{"verified_status":"passing","verified_at":"Sun Jun 28","last_verified":"Sun Jun 28","next_check":"Tue Jul 28","install_tag":null}}