anchor.diff:  GRM,R,10.1093/bioinformatics/btv122,2015-07-01,,Normalization and noise reduction for singlecell RNA-seq experiments,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,2016-09-09
   HocusPocus,R,,,https://github.com/joeburns06/hocuspocus,Basic PCA-based workflow for analysis and plotting of single cell RNA-seq data.,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,2016-09-08
   ISOP,R,10.1101/036988,PREPRINT,https://github.com/nghiavtr/ISOP,ISOform-level expression Patterns in single-cell RNA-sequencing data.,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,2016-09-09
  -LEAP,R,,,,Constructing Gene Co-Expression Networks for Single-Cell RNA-Sequencing Data Using Pseudotime Ordering.,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,2016-09-13
  +LEAP,R,,,,Constructing Gene Co-Expression Networks for Single-Cell RNA-Sequencing Data Using Pseudotime Ordering.,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,2016-09-12
   MAST,R,10.1186/s13059-015-0844-5,2015-12-10,https://github.com/RGLab/MAST,"Model-based Analysis of Single-cell Transcriptomics (MAST) fits a two-part, generalized linear models that are specially adapted for bimodal and/or zero-inflated single cell gene expression data.",FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,2016-09-08
   Monocle,R,10.1038/nbt.2859,2014-04-01,https://github.com/cole-trapnell-lab/monocle-release,Differential expression and time-series analysis for single-cell RNA-Seq.,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,2016-09-08
   Mpath,R,10.1038/ncomms11988,2016-06-30,https://github.com/JinmiaoChenLab/Mpath,Mpath: an algorithm for constructing multi-branching cell lineages from single-cell data,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,2016-09-09
   OEFinder,R,10.1093/bioinformatics/btw004,2016-01-06,https://github.com/lengning/OEFinder,"Identify ordering effect genes in single cell RNA-seq data. OEFinder shiny impelemention depends on packages shiny, shinyFiles, gdata, and EBSeq.",FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,2016-09-08
   Oscope,R,10.1038/nmeth.3549,2015-08-24,https://github.com/Bioconductor-mirror/Oscope,Oscope: a statistical pipeline for identifying oscillatory genes in unsynchronized single cell RNA-seq experiments.,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,2016-09-09
  -Ouija,R,10.1101/060442,PREPRINT,https://github.com/kieranrcampbell/ouija,Incorporate prior information into single-cell trajectory (pseudotime) analyses using Bayesian nonlinear factor analysis.,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,2016-09-08
  +Ouija,R,10.1101/060442,PREPRINT,https://github.com/kieranrcampbell/ouija,Incorporate prior information into single-cell trajectory (pseudotime) analyses using Bayesian nonlinear factor analysis.,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,2016-09-13
   Outrigger,Python,,,https://github.com/YeoLab/outrigger,"Outrigger is a program to calculate alternative splicing scores of RNA-Seq data based on junction reads and a de novo, custom annotation created with a graph database, especially made for single-cell analyses.",FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,2016-09-08
   pcaReduce,R,10.1186/s12859-016-0984-y,2016-03-22,https://github.com/JustinaZ/pcaReduce,Hierarchical clustering of single cell transcriptional profiles,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,2016-09-09
   pseudogp,R,10.1101/047365,PREPRINT,https://github.com/kieranrcampbell/pseudogp,pseudogp is an R package for Bayesian inference of Gaussian Process Latent Variable models learning pseudotimes from single-cell RNA-seq.,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,2016-09-09
   RaceID2,R,10.1016/j.stem.2016.05.010,2016-06-21,https://github.com/dgrun/StemID,"RaceID2 is an advanced version of RaceID, an algorithm for the identification of rare and abundant cell types from single cell transcriptome data.",FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,2016-09-09
   SAMstrt,R,10.1093/bioinformatics/btt511,2013-11-15,https://github.com/shka/R-SAMstrt,Statistical test for differential expression in single-celltranscriptome with spike-in normalization,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,2016-09-09
   SC3,R,10.1101/036558,PREPRINT,https://github.com/hemberg-lab/sc3,SC3 is an interactive tool for the unsupervised clustering of cells from single cell RNA-Seq experiments.,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,2016-09-08
  -Scater,R,10.1101/069633,PREPRINT,https://github.com/davismcc/scater,"Scater places an emphasis on tools for quality control, visualisation and pre-processing of data before further downstream analysis, filling a useful niche between raw RNA-sequencing count or transcripts-per-million data and more focused downstream modelling tools such as monocle, scLVM, SCDE, edgeR, limma and so on.",TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,2016-09-08
  +Scater,R,10.1101/069633,PREPRINT,https://github.com/davismcc/scater,"Scater places an emphasis on tools for quality control, visualisation and pre-processing of data before further downstream analysis, filling a useful niche between raw RNA-sequencing count or transcripts-per-million data and more focused downstream modelling tools such as monocle, scLVM, SCDE, edgeR, limma and so on.",TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,2016-09-13
   scDD,R,10.1101/035501,PREPRINT,https://github.com/kdkorthauer/scDD,"scDD (Single-Cell Differential Distributions) is a framework to identify genes with different expression patterns between biological groups of interest. In addition to traditional differential expression, it can detect differences that are more complex and subtle than a mean shift.",FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,2016-09-08
   SCDE,R,10.1038/nmeth.2967,2014-07-01,https://github.com/hms-dbmi/scde,Differential expression using error models and overdispersion-based identification of important gene sets.,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,2016-09-08
   SCell,Matlab,10.1093/bioinformatics/btw201,2016-04-19,https://github.com/diazlab/SCell,"SCell is an integrated software tool for quality filtering, normalization, feature selection, iterative dimensionality reduction, clustering and the estimation of gene-expression gradients from large ensembles of single-cell RNA-seq datasets. SCell is open source, and implemented with an intuitive graphical interface.",FALSE,TRUE,TRUE,FALSE,TRUE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,2016-09-08
  -SCIMITAR,Python,10.1101/070151,PREPRINT,https://github.com/dimenwarper/scimitar,SCIMITAR provides a variety of tools to analyze trajectory maps of single-cell measurements.,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,2016-09-13
  +SCIMITAR,Python,10.1101/070151,PREPRINT,https://github.com/dimenwarper/scimitar,SCIMITAR provides a variety of tools to analyze trajectory maps of single-cell measurements.,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,2016-09-12
   scLVM,R/Python,10.1038/nbt.3102,2015-02-01,https://github.com/PMBio/scLVM,"scLVM is a modelling framework for single-cell RNA-seq data that can be used to dissect the observed heterogeneity into different sources, thereby allowing for the correction of confounding sources of variation. scLVM was primarily designed to account for cell-cycle induced variations in single-cell RNA-seq data where cell cycle is the primary soure of variability.",FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,2016-09-08
   SCONE,R,,,https://github.com/YosefLab/scone,"SCONE (Single-Cell Overview of Normalized Expression), a package for single-cell RNA-seq data quality control (QC) and normalization. This data-driven framework uses summaries of expression data to assess the efficacy of normalization workflows.",FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,2016-09-08
   SCOUP,C++,,,https://github.com/hmatsu1226/SCOUP,Uses probabilistic model based on the Ornstein-Uhlenbeck process to analyze single-cell expression data during differentiation.,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,2016-09-08
   SCPattern,R,10.1101/046110,PREPRINT,https://github.com/lengning/SCPattern,A statistical approach to identify and classify expression changes in single cell RNA-seq experiments with ordered conditions.,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,2016-09-09
   scphaser,R,10.1093/bioinformatics/btw484,2016-08-06,https://github.com/edsgard/scphaser,scphaser is an R package for haplotype phasing using single-cell RNA-seq data.,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,2016-09-09
   scran,R,10.1186/s13059-016-0947-7,2016-04-27,https://github.com/MarioniLab/scran,"This package implements a variety of low-level analyses of single-cell RNA-seq data. Methods are provided for normalization of cell-specific biases, pool-based norms to estimate size factors, assignment of cell cycle phase, and detection of highly variable and significantly correlated genes.",FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,2016-09-08
  -SCUBA,Matlab,10.1073/pnas.1408993111,2014-12-30,https://github.com/gcyuan/SCUBA,"SCUBA stands for ""Single-cell Clustering Using Bifurcation Analysis."" SCUBA is a novel computational method for extracting lineage relationships from single-cell gene expression data, and modeling the dynamic changes associated with cell differentiation.",FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,2016-09-13
  +SCUBA,Matlab,10.1073/pnas.1408993111,2014-12-30,https://github.com/gcyuan/SCUBA,"SCUBA stands for ""Single-cell Clustering Using Bifurcation Analysis."" SCUBA is a novel computational method for extracting lineage relationships from single-cell gene expression data, and modeling the dynamic changes associated with cell differentiation.",FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,2016-09-12
   scVEGs,R,10.1186/s12864-016-2897-6,2016-08-22,https://github.com/hillas/scVEGs,scVEGs is a novel algorithm for single-cell RNA-seq (scRNA-seq) data to determine significant variably expressed genes (VEGs) using a gene expression variation model (GEVM).,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,2016-09-09
   SEPA,R,,,https://github.com/zji90/SEPA,"SEPA provides convenient functions for users to assign genes into different gene expression patterns such as constant, monotone increasing and increasing then decreasing. SEPA then performs GO enrichment analysis to analysis the functional roles of genes with same or similar patterns.",FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,2016-09-08
   Seurat,R,10.1038/nbt.3192,2015-04-13,https://github.com/satijalab/seurat,"It contains easy-to-use implementations of commonly used analytical techniques, including the identification of highly variable genes, dimensionality reduction (PCA, ICA, t-SNE), standard unsupervised clustering algorithms (density clustering, hierarchical clustering, k-means), and the discovery of differentially expressed genes and markers.",FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,2016-09-08
  
positive.code: SPADE,R,10.1038/nprot.2016.066,2016-06-16,,Visualization and cellular hierarchy inference of single-cell data using SPADE.,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,2016-09-09
  StemID,R,10.1016/j.stem.2016.05.010,2016-06-21,https://github.com/dgrun/StemID,StemID is an algorithm for the derivation of cell lineage trees based on RaceID2 results and predicts multipotent cell identites.,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,2016-09-09
  switchde,R,,,https://github.com/kieranrcampbell/switchde,Differential expression analysis across pseudotime. Identify genes that exhibit switch-like up or down regulation along single-cell trajectories along with where in the trajectory the regulation occurs.,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,2016-09-09
  topslam,Python,10.1101/057778,PREPRINT,https://github.com/mzwiessele/topslam,Extracting and using probabilistic Waddington's landscape recreation from single cell gene expression measurements.,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,2016-09-13
  TSCAN,R,10.1093/nar/gkw430,2016-05-13,https://github.com/zji90/TSCAN,Pseudo-time reconstruction and evaluation in single-cell RNA-seq analysis.,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,2016-09-09
  UMI-tools,Python,10.1101/051755,PREPRINT,https://github.com/CGATOxford/UMI-tools,This repository contains tools for dealing with Unique Molecular Identifiers (UMIs)/Random Molecular Tags (RMTs). ,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,2016-09-13
  umis,Python,10.1101/073692,PREPRINT,https://github.com/vals/umis,"umis provides tools for estimating expression in RNA-Seq data which performs sequencing of end tags of trancsript, and incorporate molecular tags to correct for amplification bias.",TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,2016-09-13
  WaveCrest,R,10.1186/s13059-016-1033-x,2016-08-17,https://github.com/lengning/WaveCrest,WaveCrest is a statistical approach to reconstruct gene expression trajectory in single cell RNA-seq experiments with ordered conditions.,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,2016-09-13
  Wishbone,Python,10.1038/nbt.3569,2016-05-02,https://github.com/ManuSetty/wishbone,Wishbone is an algorithm to align single cells from differentiation systems with bifurcating branches. ,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,2016-09-09
negative.code: Name,Platform,DOI,Pub Date,Code,Description,Quantification,QC,Normalisation,Imputation,Gene Filtering,Clustering,Pseudotime,DE,Marker Genes,Expression Patterns,Variable Genes,Gene Sets,Gene Networks,Cell Cycle,Dimensionality Reduction,Transformation,Modality,Alternative Splicing,Rare Cells,Stem Cells,Haplotypes,Visualisation,Interactive,Simulation,Updated
  anchor,Python,,,https://github.com/yeolab/anchor,"Find bimodal, unimodal, and multimodal features in your data",FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,2016-09-08
  BackSPIN,Python,10.1126/science.aaa1934,2015-03-06,https://github.com/linnarsson-lab/BackSPIN, Biclustering algorithm developed taking into account intrinsic features of single-cell RNA-seq experiments.,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,2016-09-08
  BASiCs,R,10.1371/journal.pcbi.1004333,2015-06-01,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.,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,2016-09-13
  bonvoyage,Python,,,https://github.com/yeolab/bonvoyage,Transform percentage-based units into a 2d space to evaluate changes in distribution with both magnitude and direction.,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,2016-09-08
  BPSC,R,10.1093/bioinformatics/btw202,2016-04-19,https://github.com/nghiavtr/BPSC,Beta-Poisson model for single-cell RNA-seq data analyses,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,2016-09-08
  BTR,R,10.1186/s12859-016-1235-y,2016-09-06,https://github.com/cheeyeelim/btr,BTR is a model learning algorithm for reconstructing and training asynchronous Boolean models using single-cell expression data.,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,2016-09-12
  Cellity,R,10.1186/s13059-016-0888-1,2016-02-17,https://github.com/teichlab/cellity,Classification of low quality cells in scRNA-seq data using R,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,2016-09-08
  cellTree,R,,,,Cell population analysis and visualization from single cell RNA-seq data using a Latent Dirichlet Allocation model.,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,2016-09-08
  CIDR,R,10.1101/068775,PREPRINT,https://github.com/VCCRI/CIDR,Ultrafast and accurate clustering through imputation and dimensionality reduction for single-cell RNA-seq data.,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,2016-09-09
  Citrus (scPLS),R,10.1101/045070,PREPRINT,https://github.com/ChenMengjie/Citrus,A normalization method to remove unwanted variation using both control and target genes.,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,2016-09-09
  clusterExperiment,R,,,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.,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,2016-09-08
  countClust,R,,,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.",FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,2016-09-12
  D3E,Python,10.1186/s12859-016-0944-6,2016-02-29,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.",FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,2016-09-09
  DeLorean,R,10.1093/bioinformatics/btw372,2016-06-17,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.,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,2016-09-09
  destiny,R,10.1093/bioinformatics/btv715,2016-04-15,,Diffusion maps for single-cell RNA-seq.,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,2016-09-09
  ECLAIR,Python,10.1101/036533,PREPRINT,https://github.com/GGiecold/ECLAIR,"ECLAIR stands for Ensemble Clustering for Lineage Analysis, Inference and Robustness. Robust and scalable inference of cell lineages from gene expression data.",FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,2016-09-08
  embeddr,R,10.1101/027219,PREPRINT,https://github.com/kieranrcampbell/embeddr,Embeddr creates a reduced dimensional representation of the gene space using a high-variance gene correlation graph and laplacian eigenmaps. It then fits a smooth pseudotime trajectory using principal curves.,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,2016-09-12
  ESAT,Java,10.1101/gr.207902.116,2016-07-28,https://github.com/garber-lab/ESAT,"The ESAT toolkit is designed for expression analysis of Digital expression (DGE) libraries that target transcript ""ends"". ESAT takes a set of alignment files (SAM or BAM) with genome alignment coordinates, a file containing transcript coordinates (BED or text file) and outputs read counts for each transcript provided.",TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,2016-09-09
  Falco,AWS,10.1101/064006,PREPRINT,https://github.com/VCCRI/Falco/,A Cloud-based Genetic Feature Quantification Analysis Tool,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,2016-09-08
  FastProject,Python,10.1186/s12859-016-1176-5,2016-08-23,https://github.com/YosefLab/FastProject,"Here we present FastProject, a software package for two-dimensional visualization of single cell data, which utilizes a plethora of projection methods and provides a way to systematically investigate the biological relevance of these low dimensional representations by incorporating domain knowledge.",FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,2016-09-09
  