gReLU is a python library to train, interpret, and apply deep learning models to DNA sequences.

Pandas utilities for tab-delimited and other genomic data files

Implementation of Enformer, Deepmind's attention network for predicting gene expression, in Pytorch

polygenic scores using variational inference on GWAS summary statistics from multiple cohorts

Annotated data.

Benchmarking analysis of data integration tools

TraCeR - reconstruction of T cell receptor sequences from single-cell RNAseq data

Dorothea package in Python

Scanpy Tutorials.

Hyper-parameter optimization for Keras

supervenn: precise and easy-to-read multiple sets visualization in Python

A minimal PyTorch re-implementation of the OpenAI GPT (Generative Pretrained Transformer) training

RNA Velocity generalized through dynamical modeling

Conditional out-of-distribution prediction

Two-sample Higher Criticism test for frequency tables

R package to visualize gene expression data based on weighted kernel density estimation

Scipy library main repository

Python implementation of Bayesian hierarchical clustering and Bayesian rose trees algorithms.

Genie++ Fast and Robust Hierarchical Clustering with Noise Point Detection - for Python and R

A Python framework for integrating biological databases and structured data sources in Biological Expression Language (BEL)

Experiments for understanding disentanglement in VAE latent representations

Using stochastic block models for topic modeling