DANCE: a deep learning library and benchmark platform for single-cell analysis
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Updated
May 9, 2024 - Python
DANCE: a deep learning library and benchmark platform for single-cell analysis
Expectation-Maximization-based clustering algorithm to identify groups defined by biological variates as clusters in single-cell transcriptomic data.
R toolkit for single cell genomics
Deep probabilistic analysis of single-cell and spatial omics data
A Package for Cas9-Enabled Single Cell Lineage Tracing Tree Reconstruction
Bayesian MCMC matrix factorization algorithm
This GitHub repository contains all the analysis code used in, "Single cell transcriptomic analysis of the canine duodenum in chronic inflammatory enteropathy and health."
Various utility functions for Seurat single-cell analysis
Table of software for the analysis of single-cell RNA-seq data.
This repository contains the source code of the python shiny app which is recommended to be used for the downstream analysis of the output of the SIMBA🦁 pipeline.
User-friendly tool to infer cell-cell interactions and communication from gene expression of interacting proteins
Spatial Single Cell Analysis in Python
scBoolSeq: scRNA-Seq data binarisation and synthetic generation from Boolean dynamics
Access and Format Single-cell RNA-seq Datasets from Public Resources
Brings SingleCellExperiment objects to the tidyverse
RankCompV3: a differential expression analysis algorithm based on the relative expression orderings (REOs) of gene pairs
simplified cellranger for long-read data
R package for pathway analysis in scRNA-seq data
Haplotype-aware CNV analysis from single-cell RNA-seq
One single-cell pipeline to rule them all, one pipeline to find them, one pipeline to unify them all, and with the data bind them.
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