96 Open Source Single Cell Rna Seq Software Projects
Free and open source single cell rna seq code projects including engines, APIs, generators, and tools.
Combine Lab Salmon 518 ⭐
🐟 🍣 🍱 Highly-accurate & wicked fast transcript-level quantification from RNA-seq reads using selective alignment
Swne 91 ⭐
Similarity Weighted Nonnegative Embedding (SWNE), a method for visualizing high dimensional datasets
Honeybadger 76 ⭐
HMM-integrated Bayesian approach for detecting CNV and LOH events from single-cell RNA-seq data
Dynverse 61 ⭐
A set of tools supporting the development, execution, and benchmarking of trajectory inference methods. 🌍
Too Many Cells 66 ⭐
Cluster single cells and analyze cell clade relationships with colorful visualizations.
Singlecellexperiment 49 ⭐
Clone of the Bioconductor repository for the SingleCellExperiment package, see https://bioconductor.org/packages/devel/bioc/html/SingleCellExperiment.html for the official development version.
Sctda 43 ⭐
An object oriented python library for topological data analysis of high-throughput single-cell RNA-seq data
Kb_python 67 ⭐
A wrapper for the kallisto | bustools workflow for single-cell RNA-seq pre-processing
Scrnaseq_cell_cluster_labeling 36 ⭐
Scripts to run and benchmark scRNA-seq cell cluster labeling methods
Orchestratingsinglecellanalysis Release 35 ⭐
An online companion to the OSCA manuscript demonstrating Bioconductor resources and workflows for single-cell RNA-seq analysis.
Seuratv3wizard 28 ⭐
A web-based interactive (wizard style) application to perform a guided single-cell RNA-seq data analysis and clustering based on Seurat v3
Popscle 26 ⭐
A suite of population scale analysis tools for single-cell genomics data including implementation of Demuxlet / Freemuxlet methods and auxilary tools
Ewce 29 ⭐
Expression Weighted Celltype Enrichment. See the package website for up-to-date instructions on usage.
Tgplvm 16 ⭐
tGPLVM: A Nonparametric, Generative Model for Manifold Learning with scRNA-seq experimental data
Cyclum 15 ⭐
Identify circular trajectories in scRNA-seq data using an autoencoder with sinusoidal activations
Soptsc 18 ⭐
SoptSC for single cell data analysis: unsupervised inference of clustering, cell lineage, pseudotime and cell-cell communication network from scRNA-seq data.
Seuratwizard 12 ⭐
This is a web-based interactive (wizard style) application to perform a guided single-cell RNA-seq data analysis and clustering based on Seurat.
Robustsinglecell 11 ⭐
Robust single cell clustering and comparison of population compositions across tissues and experimental models via similarity analysis.
Deweylab Cello 34 ⭐
CellO: Gene expression-based hierarchical cell type classification using the Cell Ontology
Pagoda2 118 ⭐
R package for analyzing and interactively exploring large-scale single-cell RNA-seq datasets
Alevin Fry 43 ⭐
🐟 🔬🦀 alevin-fry is an efficient and flexible tool for processing single-cell sequencing data, currently focused on single-cell transcriptomics and feature barcoding.
Ccbr Pipeliner 36 ⭐
An open-source and scalable solution to NGS analysis powered by the NIH's Biowulf cluster.
Parashardhapola Scarf 31 ⭐
Toolkit for highly memory efficient analysis of single-cell RNA-Seq, scATAC-Seq and CITE-Seq data. Analyze atlas scale datasets with millions of cells on laptop.
Nebulosa 35 ⭐
R package to visualize gene expression data based on weighted kernel density estimation
Umi Normalization 20 ⭐
Companion repository to Lause, Berens & Kobak (2021): "Analytic Pearson residuals for normalization of single-cell RNA-seq UMI data", Genome Biology
Kmer Homology Paper 12 ⭐
Manuscript for functional prediction of transcriptomic “dark matter” across species
Rpanglaodb 14 ⭐
An R package to download and merge labeled single-cell RNA-seq data from the PanglaoDB database into a Seurat object.
Elefhant 15 ⭐
Ensemble Learning for Harmonization and Annotation of Single Cells (ELeFHAnt) provides an easy to use R package for users to annotate clusters of single cells, harmonize labels across single cell datasets to generate a unified atlas and infer relationship among celltypes between two datasets. It provides users with a flexibility of choosing a machine learning based classifiers or let ELeFHAnt automatically use the power of robust classifiers like randomForest and SVM (Support Vector Machines) to make predictions. It has three functions 1) CelltypeAnnotation 2) LabelHarmonization 3) DeduceRelationship.
Gficf 11 ⭐
An R implementation of the Gene Frequency - Inverse Cell Frequency method for single cell data normalization
Csbb Shiny 10 ⭐
Computational Suite for Bioinformaticians and Biologists (CSBB) is a RShiny application developed with an intention to empower researchers from wet and dry lab to perform downstream Bioinformatics analysis
Sctreeviz 10 ⭐
R/Bioconductor package to interactively explore single cell clusters at multiple resolutions