Community-curated list of software packages and data resources for single-cell, including RNA-seq, ATAC-seq, etc.
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Updated
Feb 11, 2022
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Community-curated list of software packages and data resources for single-cell, including RNA-seq, ATAC-seq, etc.
PHATE (Potential of Heat-diffusion for Affinity-based Transition Embedding) is a tool for visualizing high dimensional data.
An overview of algorithms for estimating pseudotime in single-cell RNA-seq data
Bayesian haplotype-based mutation calling
R package for integrating and analyzing multiple single-cell datasets
Table of software for the analysis of single-cell RNA-seq data.
zUMIs: A fast and flexible pipeline to process RNA sequencing data with UMIs
pySCENIC is a lightning-fast python implementation of the SCENIC pipeline (Single-Cell rEgulatory Network Inference and Clustering) which enables biologists to infer transcription factors, gene regulatory networks and cell types from single-cell RNA-seq data.
R/shiny interface for interactive visualization of data in SummarizedExperiment objects
Reference mapping for single-cell genomics
Single cell perturbation prediction
R package for analyzing single-cell RNA-seq data
R toolkit for the analysis of single-cell chromatin data
A collection of awesome things regarding all omics.
Collection of public scRNA-Seq datasets used by our group
R package for analyzing and interactively exploring large-scale single-cell RNA-seq datasets
Deep neural networks for predicting CpG methylation
Automatic Annotation on Cell Types of Clusters from Single-Cell RNA Sequencing Data
RNA velocity estimation in Python
A software package for analyzing snapshots of developmental processes
A fast and unsupervised algorithm for spike detection and sorting using wavelets and super-paramagnetic clustering
Power analysis is essential to optimize the design of RNA-seq experiments and to assess and compare the power to detect differentially expressed genes. PowsimR is a flexible tool to simulate and evaluate differential expression from bulk and especially single-cell RNA-seq data making it suitable for a priori and posterior power analyses.
Color blindness friendly visualization of single-cell and bulk RNA-sequencing data
BASiCS: Bayesian Analysis of Single-Cell Sequencing Data. This is an unstable experimental version. Please see http://bioconductor.org/packages/BASiCS/ for the official release version
Seurat meets tidyverse. The best of both worlds.
Vitessce is a visual integration tool for exploration of spatial single-cell experiments.
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