Comprehensive Python Cheatsheet

Automatic detection of consensus gene clusters across multiple single-cell datasets

SMGR: a joint statistical method for integrative analysis of single-cell multi-omics data

scAMACE R implementation

Discover differential transcript usage from polyA-captured single cell RNA-seq data

A collection of implementations of adversarial domain adaptation algorithms

pytorch implementation of Domain-Adversarial Training of Neural Networks

ENCODE ATAC-seq pipeline

This is the repository that contains the analysis of the lung adenocarcinoma single cell dataset

benchmark dataset and Deep learning method (Hierarchical Interaction Network, HINT) for clinical trial approval probability prediction, published in Cell Patterns 2022.

A tool for visualising and interacting with pathways data

scGCN is a graph convolutional networks algorithm for knowledge transfer in single cell omics

R Package for Producing and Visualizing Hillshaded Maps from Elevation Matrices, in 2D and 3D

create alluvial plots with a single line of code

[NeurIPS 2020] "Graph Contrastive Learning with Augmentations" by Yuning You, Tianlong Chen, Yongduo Sui, Ting Chen, Zhangyang Wang, Yang Shen

Code for paper "A deep learning framework for drug repurposing via emulating clinical trials on real world patient data" (Accepted to Nature Machine Intelligence).

Fit Gamma-Poisson Generalized Linear Models Reliably

Inclusive model of expression dynamics with conventional or metabolic labeling based scRNA-seq / multiomics, vector field reconstruction and differential geometry analyses

An R package for performing patient level prediction in an observational database in the OMOP Common Data Model.

The fastai book, published as Jupyter Notebooks

A collection of sequencing protocols and bioinformatic resources for SARS-CoV-2 sequencing.

Mapping out the coarse-grained connectivity structures of complex manifolds.

a simple vae and cvae from keras

SemI-SUpervised generative Autoencoder models for single cell data

Supplement to the report in https://greenelab.github.io/czi-hca-report/

Here I cover linear and non-linear dimension reduction techniques for single cell genomics

An actionable database of publicly available single-cell RNA-seq data

An interactive web portal for exploring immuno-oncology data. This repo now superseded by iatlas-app