monet

scRNA-Seq analyzer

An open-source Python package for analyzing scRNA-Seq data using PCA-based latent spaces

Monet: An open-source Python package for analyzing scRNA-Seq data using PCA-based latent spaces

GitHub

39 stars
5 watching
10 forks
Language: Python
last commit: almost 5 years ago
Linked from 1 awesome list


Backlinks from these awesome lists:

Related projects:

RepositoryDescriptionStars
scverse/muonA Python framework for multimodal omics analysis of high-throughput biological data222
catavallejos/basicsAn integrated Bayesian hierarchical model to analyze single-cell sequencing data84
lingfeiwang/normalisrA software framework for analyzing single-cell RNA sequencing data18
iosonofabio/singletAnalyzes single cell RNA sequence data with quantitative phenotypes13
rabadanlab/sctdaAn object-oriented Python library for analyzing single-cell RNA-seq data using topological representations7
bcbio/bcbio-nextgenA high-level configuration file drives parallel variant calling and analysis on sequencing data.995
scverse/scvi-toolsProbabilistic analysis tools for single-cell omics data1,270
helenalc/muscatAnalyzes multi-sample scRNA-seq data to identify differential states between cell subpopulations and experimental conditions.171
jhu99/scbeanAnalyzes single-cell multi-omics data from various modalities like RNA-seq and ATAC-seq16
comprna/suppaAn analysis tool for studying splicing at different levels across multiple conditions264
kirstlab/asc_seuratAn R-based web application for scRNA-seq analysis that provides a user-friendly interface for data preprocessing, visualization, and annotation.23
zji90/scratA software tool for analyzing single-cell regulome data from ATAC-seq experiments.13
cellgeni/scrna.seq.courseAn educational resource teaching computational analysis of single-cell RNA-seq data using R and Bioconductor tools125
scverse/scirpyAnalyzes single-cell TCR and BCR data from scRNA-seq using Python222
hemberg-lab/scrna.seq.courseAn open-source teaching package for the computational analysis of single-cell RNA-seq data using R.673