Deep probabilistic analysis of single-cell and spatial omics data
A python library for multi omics included bulk, single cell and spatial RNA-seq analysis.
🧬 gget enables efficient querying of genomic reference databases
Tools to process and analyze deep sequencing data.
A Python implementation of the DESeq2 pipeline for bulk RNA-seq DEA.
Cell type annotation for single-cell RNA-seq using multi-LLM consensus
Spatial Single Cell Analysis in Python
Inclusive model of expression dynamics with conventional or metabolic labeling based scRNA-seq / multiomics, vector field reconstruction and differential geometry analyses
State-of-the-art bio cell models for inference and training. Minimal, readable, and produciton-ready.