PyPI 官网下载 | regulon-enrichment-0.3.1a0.tar.gz

 [](https://www.python.org/downloads/release/python-367)   # Enrich **regulon-enrichment** is a Python module used to predict the activity of regulatory proteins from RNAseq data. *regulon-enrichment* submodules: ### `enricher.features` ### Load -omic datasets ### `enricher.regulon` ### Regulon utilities # Dependencies **regulon-enrichment** requires: ~~~~~~~~~~~~ - Python (>= 3.6) - scikit-learn (>= 0.21.3) - NumPy (>= 1.17.3) - SciPy (>= 1.3.1) - pandas (>= 0.25.3) - tqdm (>= 4.38.0) - dill (>= 0.3.1.1) ~~~~~~~~~~~~ # User installation ~~~~~~~~~~~~~~~~~ If you already have a working installation of numpy and scipy, the easiest way to install regulon-enrichment is using ``pip`` :: pip install regulon-enrichment==0.0.2b0 or ``conda``:: conda install -c estabroj89 regulon-enrichment # Overview This method leverages pathway information and gene expression data to produce regulon-based protein activity scores. Our method tests for positional shifts in experimental-evidence supported networks consisting of transcription factors and their downstream signaling pathways when projected onto a rank-sorted gene-expression signature. A regulatory gene’s expression is generally a poor proxy for its protein’s behavior. We shift our focus to the collective enrichment of a regulatory protein’s target genes (its “regulon”). We extract protein-protein edges from Pathway Commons to build regulatory networks.