Community-curated list of software packages and data resources for single-cell, including RNA-seq, ATAC-seq, etc.

AltAnalyze is a multi-functional and easy-to-use software package for automated single-cell and bulk gene and splicing analyses. Easy-to-use precompiled graphical user-interface versions available from our website.

Cell2Sentence turns scRNA-seq data into text for LLM training.

Coarse-graining of large single-cell RNA-seq data into metacells

🦠 Regularly updated list of publicly available datasets with single-cell (scRNAseq) and T-cell/antibody immune repertoire (AIRR / RepSeq / immunosequencing) data of COVID-19 patients with SARS-CoV-2.

Using Bulk Gene Expression to Estimate Cell-Type-Specific Gene Expression via Deconvolution

metadata and data from the database

The Cornell Single-Cell Muscle Project (scMuscle) aims to collect, analyze and provide to the research community skeletal muscle transcriptomic data

Single cell transcriptomic data from Tasic, et al. (2016)

V-SVA: An R Shiny application for detecting and annotating hidden sources of variation in single cell RNA-seq data

Extracellular vesicle-derived miRNA-mediated cell-cell communication inference for single-cell transcriptomic data

PicturedRocks Single Cell Analysis Tool

A package that performs cell type annotations on single cell resolution of spatial transcriptomics data, find the niche interactions and covariation patterns between interacted cell types.

ScRNA-seq Analysis Copilot serves as an interactive agent to learn single cell sequencing, answering questions and helping new learners to practice analysis.

Gene expression on C. elegans single cells

Repo linked to our recent publication in Science Advances

Large-scale Benchmarking of Single-cell Differential Expression Analysis Methods

V-SVA: An R Shiny application for detecting and annotating hidden sources of variation in single cell RNA-seq data

Benchmarking records for scRNA-seq CNV detection.

scRNA-seq datasets to support Jung et al, Sci Adv, 7(6): eabe5735, 2021. DOI: 10.1126/sciadv.abe5735