Clustering scRNAseq by genotypes

An R package to test for batch effects in high-dimensional single-cell RNA sequencing data.

This repository contains R code, with which you can create 3D UMAP and tSNE plots of Seurat analyzed scRNAseq data

Single Cell Cluster Evaluation

Cell type pipes for R

scGSVA: Perform GSVA for single cell RNA seq

a scalable python suite for tree inference and advanced pseudotime analysis from scRNAseq data.

Explore and share your scRNAseq clustering results

Differential expression and allelic analysis, nonparametric statistics

R package developed for single-cell RNA-seq analysis. It was designed using the Seurat framework, and offers existing and novel single-cell analytic work flows.

Reliable, scalable, efficient demultiplexing for single-cell RNA sequencing

R package - Analysis of Single Cell Expression, Normalisation and Differential expression (ascend)

Uncertainty-aware quantification of Transposable Elements expression in scRNA-seq

Visualize clonal expansion via circle-packing. 'APackOfTheClones' extends 'scRepertoire' to produce a publication-ready visualization of clonal expansion at a single cell resolution, by representing expanded clones as differently sized circles.

Robust single cell clustering and comparison of population compositions across tissues and experimental models via similarity analysis.

Normalization for single cell RNA-seq data

A data structure for single cell sequencing data analysis in Julia.

R Package for Single Cell RNAseq Synthetic Data Simulation

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.

Hello there! Some code on how to merge >2 Seurat objects and maintain object identity :)