anchor.diff:  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,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,2016-09-12,2016-09-12
   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,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,2016-09-09,2016-09-09
   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,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,2016-09-09,2016-09-09
  +demuxlet,C++,10.1101/118778,PREPRINT,https://github.com/hyunminkang/apigenome,Sample demultiplexing of droplet sc-RNAseq reads.,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,2017-03-29,2017-03-29
   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,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,2016-09-09,2016-09-09
   DPT,R/Matlab,10.1038/nmeth.3971,2019-08-29,http://www.helmholtz-muenchen.de/icb/research/groups/machine-learning/projects/dpt/index.html,"Our DPT software implementations make it possible to reconstruct the developmental progression of cells and identify transient or metastable states, branching decisions and differentiation endpoints.",FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,2016-09-22,2016-09-22
   dropbead,R,10.1101/099473,PREPRINT,https://github.com/rajewsky-lab/dropbead,"It offers a quick and straightfoward way to explore and perform basic analysis of single cell sequencing data coming from droplet sequencing, such as Drop-seq.",FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,2017-01-16,2017-01-16
  
positive.code: SSrGE,Python,10.1101/095810,PREPRINT,https://github.com/lanagarmire/SSrGE,This procedure aims to fit sparse linear models using a binary matrix (n_samples x n_SNV) as features matrix and a gene expression matrix (n_genes x n_samples) as response.,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,2017-01-10,2017-01-10
  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,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,2016-09-09,2016-09-09
  switchde,R,10.1093/bioinformatics/btw798,2016-12-23,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,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,2016-09-09,2017-01-10
  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,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,2016-09-12,2016-09-12
  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,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,2016-09-09,2016-09-09
  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). ,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,2016-09-12,2016-09-12
  
negative.code: powsim,R,10.1101/117150,PREPRINT,https://github.com/bvieth/powsim,Power analysis for bulk and single cell RNA-seq experiments,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,2017-03-20,2017-03-20
  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,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,2016-09-09,2016-09-09
  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,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,2016-09-09,2016-09-09
  RCA,R,10.1038/ng.3818,2017-03-20,https://github.com/GIS-SP-Group/RCA,"RCA, short for Reference Component Analysis, is an R package for robust clustering analysis of single cell RNA sequencing data (scRNAseq).",FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,2017-03-27,2017-03-27
  sake,R,,,https://github.com/naikai/sake,Single-cell RNA-Seq Analysis and Klustering Evaluation. The aim of sake is to provide a user-friendly tool for easy analysis of NGS Single-Cell transcriptomic data.,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,2016-10-10,2016-10-10
  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,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,2016-09-09,2016-09-09
  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,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,2016-09-08,2016-09-08
  