An R package to test for batch effects in high-dimensional single-cell RNA sequencing data.
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Updated
Jan 26, 2024 - HTML
An R package to test for batch effects in high-dimensional single-cell RNA sequencing data.
Clustering scRNAseq by genotypes
This repository contains R code, with which you can create 3D UMAP and tSNE plots of Seurat analyzed scRNAseq data
Cell type pipes for R
Explore and share your scRNAseq clustering results
a scalable python suite for tree inference and advanced pseudotime analysis from scRNAseq data.
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.
R package - Analysis of Single Cell Expression, Normalisation and Differential expression (ascend)
Reliable, scalable, efficient demultiplexing for single-cell RNA sequencing
Robust single cell clustering and comparison of population compositions across tissues and experimental models via similarity analysis.
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.
A tool to quantify transposable elements expression in scRNA-seq
R Package for Single Cell RNAseq Synthetic Data Simulation
Hello there! Some code on how to merge >2 Seurat objects and maintain object identity :)
Nextflow pipeline for extracting and counting clonal barcodes
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