gcell

gcell is a comprehensive toolkit for genomic data analysis, focusing on cell type-specific regulatory analysis, DNA sequence manipulation, protein structure prediction, and pathway analysis. It integrates various modules to facilitate the study of different aspects of gene expression regulation.

News

• I dropped graphviz and pygraphviz dependency due to complexity of maintain installing across different platform. It only affects the network layout for drawing causal graph. nx.spring_layout(G) is used instead of nx.nx_agraph.graphviz_layout(G) now, which is uglier unforturnately.
• Feature: Now you can load pre-infered cell types on getdemo website easily:

from gcell.cell.celltype import GETDemoLoader
g = GETDemoLoader()
print(g.available_celltypes) # this gives you a list of cell type names
g.load_celltype('Plasma Cell')

• Fix: zarr has been limited to <3.0.0 to avoid s3 problem

Goal

The long term goal of this package is to create a open-source, community-involved python-centric playground/tool-set for future AI Agent to discover new biology through predictive model.

Key Modules

• Celltype: Tools for cell type analysis, including gene expression and motif analysis. Basis for get_model interpretation analysis.
• DNA: Functions for DNA sequence manipulation, motif scanning, and track visualization.
• RNA: Classes for handling GENCODE gene annotations and GTF files.
• Protein: Functionality for protein domain analysis (Uniprot, InterPro) and AlphaFold2 predictions parsing as well as retrieve protein-protein interaction networks from the STRING database..
• Pathway: Tools for pathway (GO, KEGG, Reactome, etc.) analysis using gprofiler.

Installation

pip install git+https://github.com/GET-Foundation/gcell.git@main

License

gcell is open-source software licensed under the MIT License. See the LICENSE file for more details.