R toolkit for single cell genomics
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Updated
Oct 25, 2024 - R
R toolkit for single cell genomics
Deep probabilistic analysis of single-cell and spatial omics data
🐟 🍣 🍱 Highly-accurate & wicked fast transcript-level quantification from RNA-seq reads using selective alignment
NicheNet: predict active ligand-target links between interacting cells
Spatial Single Cell Analysis in Python
An end-to-end Single-Cell Pipeline designed to facilitate comprehensive analysis and exploration of single-cell data.
DANCE: a deep learning library and benchmark platform for single-cell analysis
CellRank: dynamics from multi-view single-cell data
Table of software for the analysis of single-cell RNA-seq data.
Multi-subject Single Cell Deconvolution
R package with collection of functions created and/or curated to aid in the visualization and analysis of single-cell data using R.
R package for analyzing and interactively exploring large-scale single-cell RNA-seq datasets
R package for the joint analysis of multiple single-cell RNA-seq datasets
Differential expression analysis for single-cell RNA-seq data.
Color blindness friendly visualization of single-cell and bulk RNA-sequencing data
🐟 🔬🦀 alevin-fry is an efficient and flexible tool for processing single-cell sequencing data, currently focused on single-cell transcriptomics and feature barcoding.
LIANA+: an all-in-one framework for cell-cell communication
Haplotype-aware CNV analysis from single-cell RNA-seq
Generate high quality, publication ready visualizations for single cell transcriptomics data.
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