Community-curated list of software packages and data resources for single-cell, including RNA-seq, ATAC-seq, etc.
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Updated
Nov 14, 2024
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
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
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
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.
Repo linked to our recent publication in Science Advances
Large-scale Benchmarking of Single-cell Differential Expression Analysis Methods
Benchmarking records for scRNA-seq CNV detection.
V-SVA: An R Shiny application for detecting and annotating hidden sources of variation in single cell RNA-seq data
scRNA-seq datasets to support Jung et al, Sci Adv, 7(6): eabe5735, 2021. DOI: 10.1126/sciadv.abe5735
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