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Seurat meets tidyverse. The best of both worlds.
Differential abundance (DA) and correlation analyses for microbial absolute abundance data
iCellR is an interactive R package designed to facilitate the analysis and visualization of high-throughput single-cell sequencing data. It supports a variety of single-cell technologies, including scRNA-seq, scVDJ-seq, scATAC-seq, CITE-Seq, and Spatial Transcriptomics (ST).
Convert Counts to Fragments per Kilobase of Transcript per Million (FPKM)
A Snakemake workflow and MrBiomics module to split, filter, normalize, integrate and select highly variable features of count matrices resulting from next-generation sequencing (NGS) experiments (e.g., RNA-seq, ATAC-seq, ChIP-seq, Methyl-seq, miRNA-seq,...) including confounding factor analysis and diagnostic visualizations.
R package for pre-processing of mass and flow cytometry data
Tools for normalization, evaluation of outliers, technical biases and batch effects and differential expression analysis.
Joint normalization of two Hi-C matrices, visualization and detection of differential chromatin interactions. See multiHiCcompare for the analysis of multiple Hi-C matrices
PlotTwist - a web app for plotting and annotating time-series data
Tools for Batch Effects Diagnostics and Correction
This package has migrated to https://github.com/rezakj/iCellR please use iCellR instead of scSeqR for more functionalities and updates.
Cytofin-an R package for CyTOF data integration
LambertW R package: Lambert W x F distributions and Gaussianization for skewed & heavy-tailed data
'geoquimica' is an open-source package built-in ≥ R 3.6.0 that gathers functions for assist on the exploration data analysis of geochemistry data. This package was built by researchers of the Geological Survey of Brazil.
Archived version of RUVSeq
R Package for preprocessing, normalizing, and analyzing proteomics data
Methylation array preprocessing.
An archived version of the scran repository, see https://github.com/MarioniLab/scran for the active version.
MUREN: a Robust and Multi-reference Approach of RNA-seq Transcript Normalization