Assembly

Alignment

Quantification

QualityControl

Normalisation

Imputation

Integration

GeneFiltering

Clustering

Classification

DifferentialExpression

MarkerGenes

ExpressionPatterns

VariableGenes

GeneSets

GeneNetworks

DimensionalityReduction

Transformation

AlternativeSplicing

Haplotypes

AlleleSpecific

Visualisation

Interactive

Simulation

10.1101/532093;10.1093/bioinformatics/btz592

PREPRINT;2019-07-29

https://github.com/mafeiyang/ACTINN

ACTINN (Automated Cell Type Identification using Neural Networks) is a bioinformatic tool to quickly and accurately identify cell types in scRNA-Seq.

C++/R/MATLAB

10.1038/s41467-018-03933-2

https://github.com/shmohammadi86/ACTION

ACTION infers the functional identity of cells from their transcriptional profile, classifies them based on their dominant function, and reconstructs regulatory networks that are responsible for mediating their identity.

https://github.com/csoneson/alevinQC

Generate QC reports summarizing the output from an alevin run

10.1101/397588

https://github.com/KlugerLab/ALRA

ALRA is a method for imputation of missing values in single cell RNA-sequencing data

10.1038/nature19348;10.1101/412080

2016-08-31;PREPRINT

https://github.com/nsalomonis/altanalyze

AltAnalyze is a multi-functional and easy-to-use software package for automated single-cell and bulk gene and splicing analyses.

10.1016/j.molcel.2017.06.003

https://github.com/yeolab/anchor

Find bimodal, unimodal, and multimodal features in your data

10.1101/096222;10.1093/bioinformatics/btx337

PREPRINT;2017-10-01

https://github.com/DeplanckeLab/ASAP

ASAP : Automated Single-cell Analysis Pipeline

10.1101/207704;10.1093/gigascience/giz087

PREPRINT;2019-08-24

https://github.com/powellgenomicslab/ascend

Analysis of Single Cell Expresssion Normalisation and Differential Expression

10.1101/144501;10.1038/nmeth.4463

PREPRINT;2017-10-09

https://github.com/aertslab/AUCell

AUCell is an R-package to analyze the state of gene-sets in single-cell RNA-seq data (i.e. identify cells with active gene signatures).

10.1038/s41598-018-34688-x

https://github.com/divyanshu-talwar/AutoImpute

AutoImpute: Autoencoder based imputation of single cell RNA-seq data

10.1126/science.aaa1934

https://github.com/linnarsson-lab/BackSPIN

Biclustering algorithm developed taking into account intrinsic features of single-cell RNA-seq experiments.

https://github.com/JEFworks/badger

Bayesian approach for detecting copy number alterations from single cell RNA-seq data

10.1186/s13073-018-0528-3

https://github.com/BosingerLab/BALDR

BALDR is a pipeline for reconstructing human or rhesus macaque immunoglobulin(Ig)/B cell receptor(BCR) sequences from single cell RNA-Seq data generated by Illumina sequencing.

10.1101/392662;10.1038/s41467-019-09639-3

PREPRINT;2019-04-09

https://github.com/CHPGenetics/BAMMSC

A Bayesian mixture model for clustering droplet-based single cell transcriptomic data from population studies

10.1093/bioinformatics/btw631

http://ttic.uchicago.edu/~aakhan/BASIC/

BASIC is a semi-de novo assembly method to determine the full-length sequence of the BCR in single B cells from scRNA-seq data.

10.1371/journal.pcbi.1004333;10.1186/s13059-016-0930-3;10.1101/237214;10.1016/j.cels.2018.06.011

2015-06-01;2016-04-15;PREPRINT;2018-08-29

https://github.com/catavallejos/BASiCS

Bayesian Analysis of single-cell RNA-seq data. Estimates cell-specific normalization constants. Technical variability is quantified based on spike-in genes. The total variability of the expression counts is decomposed into technical and biological components.

10.1038/nbt.4091

https://github.com/LTLA/batchelor

Implements a variety of methods for batch correction of single-cell (RNA sequencing) data.

10.1101/384586

https://github.com/WT215/bayNorm

bayNorm provides an efficient, integrated solution for global scaling normalisation, imputation and true count recovery of gene expression measurements from scRNA-seq data

10.1101/397042;10.1093/bioinformatics/btz625

PREPRINT;2019-08-10

https://github.com/Teichlab/bbknn

BBKNN is a fast and intuitive batch effect removal tool for direct use in the scanpy workflow.

10.1093/nar/gky308

http://www-rcf.usc.edu/~liangche/software.html

BCseq: accurate single cell RNA-seq quantification with bias correction

10.1101/118919

https://bitbucket.org/bsblabludwig/bearscc

BEARscc is a noise estimation and injection tool that is designed to assess putative single-cell RNA-seq clusters in the context of experimental noise estimated by ERCC spike-in controls.

Python/Docker

10.1101/642926

https://github.com/murali-group/Beeline

BEELINE: Benchmarking gEnE reguLatory network Inference from siNgle-cEll transcriptomic data

10.1038/s41421-019-0114-x

https://github.com/jumphone/BEER

BEER: Batch EffEct Remover for single-cell data

10.1101/197244

https://github.com/iaconogi/bigSCale

bigSCale is an analytical framework scalable to analyze millions of cells

10.1101/gr.230771.117;10.1186/s13059-019-1713-4

2018-05-03;2019-06-04

https://github.com/iaconogi/bigSCale2

bigSCale is a complete framework for the analysis and visualization of single cell data. It allows cluster, phenotype, perform pseudotime analysis, infer gene regulatory networks and reduce large datasets in smaller datasets with higher quality.

10.1038/s41467-017-01188-x;10.1093/nar/gkz716

2017-08-24;2019-08-20

https://github.com/WeiqiangZhou/BIRD

BIRD: Big data Regression for predicting DNase I hypersensitivity

10.18547/gcb.2017.vol3.iss1.e46

https://github.com/sandhya212/BISCUIT_SingleCell_IMM_ICML_2016

Bayesian Inference for Single-cell Clustering and ImpuTing

10.1101/669911

https://github.com/cozygene/bisque

An R toolkit for accurate and efficient estimation of cell composition ('decomposition') from bulk expression data with single-cell information.

10.1016/j.molcel.2017.06.003

https://github.com/yeolab/bonvoyage

Transform percentage-based units into a 2d space to evaluate changes in distribution with both magnitude and direction.

10.1093/bioinformatics/btw202

https://github.com/nghiavtr/BPSC

Beta-Poisson model for single-cell RNA-seq data analyses

10.1101/185504;10.1038/s41592-018-0082-3

PREPRINT;2018-07-31

https://github.com/teichlab/bracer

BraCeR - reconstruction of B cell receptor sequences from single-cell RNA-seq data.

10.1101/166868;10.1186/s13059-018-1440-2

PREPRINT;2018-05-29

https://github.com/ManchesterBioinference/BranchedGP

BranchedGP is a package for building Branching Gaussian process models in python, using TensorFlow and GPFlow.

10.1101/389999

https://github.com/YosefLab/BRAPeS

BRAPeS (BCR Reconstruction Algorithm for Paired-End Single-cell), software for reconstruction of B cell receptors (BCR) using short, paired-end single-cell RNA-sequencing.

10.1101/098517;10.1186/s13059-017-1248-5

PREPRINT;2017-06-27

https://github.com/huangyh09/brie

BRIE (Bayesian regression for isoform estimate) is a Bayesian method to estimate isoform proportions from RNA-seq data.

10.1016/j.cels.2016.08.011

https://github.com/shenorrLab/bseqsc

BSeq-sc is a bioinformatics analysis pipeline that leverages single-cell sequencing data to estimate cell type proportion and cell type-specific gene expression differences from RNA-seq data from bulk tissue samples.

10.1186/s12859-016-1235-y

https://github.com/cheeyeelim/btr

BTR is a model learning algorithm for reconstructing and training asynchronous Boolean models using single-cell expression data.

10.1101/533372

https://github.com/songfd2018/BUSseq

The BUSseq R package implements the BUSseq model to adjust single-cell RNA-sequencing data for batch effects when there are unknown cell types.

10.1101/472571;10.1101/673285

PREPRINT;PREPRINT

https://github.com/BUStools/bustools

bustools is a program for manipulating BUS files for single cell RNA-Seq datasets

10.1101/257550

https://github.com/CABSEL/CALISTA

CALISTA provides a user-friendly toolbox for the analysis of single cell expression data.

10.1101/328807

https://github.com/FertigLab/CancerInSilico

The CancerInSilico package provides an R interface for running mathematical models of tumor progresson.

10.1101/413047

https://github.com/PMBio/cardelino

Methods to infer clonal structure for a population of cells using single-cell RNA-seq data

10.1371/journal.pone.0205499

https://github.com/yuvallb/CaSTLe

Classification of Single cells by Transfer Learning

10.1101/434746;10.1038/s41467-019-11591-1

PREPRINT;2019-07-23

https://github.com/sridnona/cb_sniffer

Mutation barcode caller, calls mutant and ref barcodes from 10x single cell data

10.26508/lsa.201900443

https://github.com/hjunwoo/ccfindR

single-cell RNA-seq data analysis using Bayesian non-negative matrix factorization

arxiv/1605.04492;10.1038/srep33892

PREPRINT;2016-05-12

https://github.com/cran/ccRemover

Implements a method for identifying and removing the cell-cycle effect from scRNA-Seq data.

https://github.com/MonashBioinformaticsPlatform/celaref

The celaref (cell labelling by reference) package aims to streamline the cell-type identification step, by suggesting cluster labels on the basis of similarity to an already-characterised reference dataset.

https://github.com/campbio/celda

"celda" stands for "CEllular Latent Dirichlet Allocation", which is a suite of Bayesian hierarchical models and supporting functions to perform gene and cell clustering for count data generated by single cell RNA-seq platforms.

10.1101/587360

https://github.com/gao-lab/Cell_BLAST

Cell BLAST is a cell querying tool for single-cell transcriptomics data.

10.1038/nmeth.4628

https://github.com/shenorrLab/cellAlign

CellAlign is a tool for quantitative comparison of expression dynamics within or between single-cell trajectories.

10.1101/521914;10.1038/s41592-019-0529-1

PREPRINT;2019-09-09

https://github.com/irrationone/cellassign

cellassign automatically assigns single-cell RNA-seq data to known cell types across thousands of cells accounting for patient and batch specific effects.

10.1101/433102;10.1038/s41592-019-0425-8

PREPRINT;2019-05-27

https://github.com/shians/cellbench

R package for benchmarking single cell analysis methods, primarily inspired by the modelling structure used in DSC

10.1093/nar/gky698

https://github.com/neocaleb/CellBIC

CellBIC is bimodality-based top-down clustering of single-cell RNA sequencing data.

https://github.com/maximilianh/cellBrowser

Python pipeline and Javascript scatter plot library for single-cell datasets

10.1101/374462

https://github.com/bicycle1885/CellFishing.jl

CellFishing.jl (cell finder via hashing) is a tool to find similar cells of query cells based on their transcriptome expression profiles.

10.1186/s13059-016-0888-1

https://github.com/teichlab/cellity

Classification of low quality cells in scRNA-seq data using R

10.1101/634097

https://github.com/deweylab/CellO

CellO (Cell Ontology-based classification) is a Python package for performing cell type classification of RNA-seq data.

10.1038/s41586-018-0698-6;10.1101/680926

2018-11-14;PREPRINT

https://github.com/Teichlab/cellphonedb

CellPhoneDB is a publicly available repository of curated receptors, ligands and interactions.

10.1038/ncomms14049

https://github.com/10XGenomics/cellranger

Cell Ranger is a set of analysis pipelines that process Chromium single cell 3’ RNA-seq output to align reads, generate gene-cell matrices and perform clustering and gene expression analysis.

10.1038/s41467-018-03214-y

https://github.com/edroaldo/cellrouter

CellRouter is a multifaceted single-cell analysis platform that identifies complex cell-state transition trajectories by using flow networks to explore the subpopulation structure of multi-dimensional, single-cell omics data.

10.1016/j.celrep.2018.05.002

https://github.com/dcellwanger/CellTrails

CellTrails: Inference of Temporal Gene Expression Dynamics of Branching Biological Processes from Single-cell Expression Data

10.1186/s12859-016-1175-6

Cell population analysis and visualization from single cell RNA-seq data using a Latent Dirichlet Allocation model.

10.1101/123810

https://github.com/mohanbolisetty/CellView

A ShinyApp to visualize and explore single cell datasets

Python/Javascript

https://github.com/chanzuckerberg/cellxgene

cellxgene is an interactive data explorer for single-cell transcriptomics datasets, such as those coming from the Human Cell Atlas

10.1101/558908

https://github.com/jdekanter/CHETAH

CHETAH (CHaracterization of cEll Types Aided by Hierarchical clustering): a selective, hierarchical cell type identification method for single-cell RNA sequencing

10.1101/068775;10.1186/s13059-017-1188-0

PREPRINT;2017-03-28

https://github.com/VCCRI/CIDR

Ultrafast and accurate clustering through imputation and dimensionality reduction for single-cell RNA-seq data.

https://github.com/Hoohm/CITE-seq-Count

A python package that allows to count antibody TAGS from a CITE-seq and/or cell hashing experiment.

10.1101/045070;10.1038/s41598-017-13665-w

PREPRINT;2017-10-19

https://github.com/ChenMengjie/Citrus

A normalization method to remove unwanted variation using both control and target genes.

10.1101/344309;10.1186/s13059-019-1645-z

PREPRINT;2019-03-12

https://github.com/kieranrcampbell/clonealign

clonealign assigns single-cell RNA-seq expression to cancer clones by mapping RNA-seq to clone-specific copy number profiles

clusterExperiment

10.1101/280545

https://github.com/epurdom/clusterExperiment

Functions for running and comparing many different clusterings of single-cell sequencing data. Meant to work with SCONE and slingshot.

10.1101/331330;10.1093/bioinformatics/btz024

PREPRINT;2019-01-14

https://github.com/xgaoo/ClusterMap

ClusterMap is an R package to analyze and compare two or more single cell expression datasets

10.1101/255711

http://www.genemine.org/clustermine.php

ClusterMine is a knowledge-integrated clustering approach to cluster samples based on gene expression profile.

10.7554/eLife.43803

https://github.com/dylkot/cNMF

Consensus Non-negative Matrix Factorization on single-cell RNA-Seq data

10.1101/365007

https://github.com/xiaoyeye/CNNC

Convolutional neural network co-expression analysis (CNNC)

10.1371/journal.pcbi.1006772

https://github.com/ChengF-Lab/COAC

Component Overlapping Attribute Clustering (COAC) algorithm to perform the localized (subpopulation) gene co-expression network analysis from large-scale scRNA-seq profiles

10.1101/655753

https://github.com/MSingerLab/COMETSC

COMET: Identifying candidate marker panels from single-cell transcriptomic data

10.1093/bioinformatics/bty316

https://github.com/diazlab/CONICS

CONICS: COpy-Number analysis In single-Cell RNA-Sequencing

10.1101/460246;10.1038/s41592-019-0466-z

PREPRINT;2019-07-15

https://github.com/hms-dbmi/conos

Clustering on Network of Samples

https://github.com/ivirshup/constclust

Consistent Clusters for scRNA-seq

https://github.com/kkdey/CountClust

Clustering and Visualizing RNA-Seq Expression Data using Grade of Membership Models. Fits grade of membership models (GoM, also known as admixture models) to cluster RNA-seq gene expression count data, identifies characteristic genes driving cluster memberships, and provides a visual summary of the cluster memberships.

10.1093/bioinformatics/btz296

https://github.com/jessica1338/CSHMM-for-time-series-scRNA-Seq

CSHMM accurately infers branching topology in time series data and correctly and continuously assign cells to paths

10.1101/272443

http://page.amss.ac.cn/shihua.zhang/software.html

CSMF (Common and Specific Matrix Factorization) is a MATLAB package to simultaneously extract common and specific patterns from the data of two or multiple biological interrelated conditions via matrix factorization.

10.1093/nar/gkz172

https://github.com/wys8c764/CSN

Cell-specific Network Constructed from Single-cell RNA Sequencing Data

10.1101/671180

https://github.com/zhouzilu/cTPnet

Single cell Transcriptome to Protein prediction with deep neural networks

10.1101/625566

https://github.com/KChen-lab/cyclum

Cyclum is a package to recover cell cycle information and remove cell cycle factors from scRNA-seq data

10.1186/s12859-016-0944-6

https://github.com/hemberg-lab/D3E

D3E is a tool for identifying differentially-expressed genes, based on single-cell RNA-seq data. D3E consists of two modules: one for identifying differentially expressed (DE) genes, and one for fitting the parameters of a Poisson-Beta distribution.

10.1101/300681;10.1038/s41467-018-07931-2

PREPRINT;2019-01-23

https://github.com/theislab/dca

A deep count autoencoder network to denoise scRNA-seq data and remove the dropout effect by taking the count structure, overdispersed nature and sparsity of the data into account using a deep autoencoder with zero-inflated negative binomial (ZINB) loss function.

10.1371/journal.pcbi.1006391

https://github.com/cran/DCA

Finding dominant latent signals that regulate dynamic correlation between many pairs of variables.

10.1186/s12864-018-5249-x

https://github.com/cgplab/ddSeeker

A tool for processing Bio-Rad ddSEQ single cell RNA-seq data

10.1101/225177;10.1093/bioinformatics/btz453

PREPRINT;2019-06-14

https://github.com/cz-ye/DECENT

Differential Expression with Capture Efficiency AdjustmeNT for Single-Cell RNA-seq Data

C++/R/MATLAB

10.1101/241646

https://github.com/shmohammadi86/DECODE

DECODE-ing sparsity patterns in single-cell RNA-seq

10.1101/353607

https://github.com/lanagarmire/DeepImpute

DeepImpute: an accurate and efficient deep learning method for single-cell RNA-seq data imputation

10.1093/bioinformatics/btw372

https://github.com/JohnReid/DeLorean

R package to model time series accounting for noise in the temporal dimension. Specifically designed for single cell transcriptome experiments.

10.1101/118778;10.1038/nbt.4042

PREPRINT;2017-12-11

https://github.com/statgen/demuxlet

Genetic multiplexing of barcoded single cell RNA-seq

10.1101/457622

https://github.com/zhouzilu/DENDRO

DENDRO, stands for Dna based EvolutioNary tree preDiction by scRna-seq technOlogy, is an R package, which takes scRNA-seq data for a tumor (or related somatic tissues) and accurately reconstructs its phylogeny, assigning each single cell from the single cell RNA sequencing (scRNA-seq) data to a subclone.

10.1101/191254

https://github.com/jessemzhang/dendrosplit

DendroSplit, an interpretable framework for analyzing single-cell RNA-Seq datasets.

10.1093/bioinformatics/btw227

https://bitbucket.org/jerry00/densitycut_dev

densityCut is an efficient density-based clustering algorithm to analyze large-scale biological data

10.1101/276311;10.1093/bioinformatics/bty1009

PREPRINT;2018-12-07

https://github.com/ucasdp/DensityPath

DensityPath can accurately and efficiently reconstruct the underlying cell developmental trajectories for large-scale scRNAseq data.

10.1101/396135

https://github.com/Theorell/DepecheR

DepecheR is an R package for clustering cytometry and single-cell RNA sequencing data according to a minimal set of biological markers

10.1101/530378

https://github.com/eleozzr/desc

DESC is an unsupervised deep learning algorithm for clustering scRNA-seq data.