anchor.diff:  demuxlet,C++,10.1101/118778,PREPRINT,https://github.com/hyunminkang/apigenome,Sample demultiplexing of droplet sc-RNAseq reads.,GPL-3,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,FALSE,2017-03-29,2017-03-29
   destiny,R,10.1093/bioinformatics/btv715,2016-04-15,https://www.helmholtz-muenchen.de/icb/research/groups/quantitative-single-cell-dynamics/software/destiny/index.html,Diffusion maps for single-cell RNA-seq.,GPL,FALSE,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,2016-09-09,2017-04-18
   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.",GPL-3,FALSE,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
  +Dr.seq2,Python,10.1101/143271,PrePRINT,https://github.com/ChengchenZhao/DrSeq2,Quality control and analysis pipeline for parallel single cell transcriptome and epigenome data,GPL-3,FALSE,TRUE,TRUE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,2017-06-26,2017-06-26
   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.",GPL-3,FALSE,FALSE,TRUE,FALSE,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
   dropSeqPipe,Snakemake,,,https://github.com/Hoohm/dropSeqPipe,This pipeline is based on snakemake and the dropseq tools provided by the McCarroll Lab. It allows to go from raw data of your dropSeq/scrbSeq experiment until the final count matrix with QC plots along the way.,,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,2017-05-21,2017-05-21
   DTWScore,R,10.1186/s12859-017-1647-3,2017-05-23,https://github.com/xiaoxiaoxier/DTWscore,Transcriptional heterogeneity analysis for time-series single-cell RNA-seq data,,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,2017-05-30,2017-05-30
  
positive.code: 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.,GPL (>=2),FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,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).,MIT,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,FALSE,2016-09-12,2016-09-12
  umis,Python,10.1038/nmeth.4220,2017-03-06,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.",MIT,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,FALSE,2016-09-12,2017-03-10
  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.,Apache-2.0,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,2016-09-12,2016-09-12
  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.,GPL-2,FALSE,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,TRUE,FALSE,2016-09-09,2016-11-29
  ZIFA,Python,10.1186/s13059-015-0805-z,2015-11-02,https://github.com/epierson9/ZIFA,Zero-inflated dimensionality reduction algorithm for single-cell data.,MIT,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,2016-12-22,2016-12-22
  
negative.code: scDD,R,10.1186/s13059-016-1077-y,2016-10-25,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.",GPL-2,FALSE,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,TRUE,2016-09-08,2016-11-07
  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,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,2016-09-08,2016-09-08
  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.",GNU,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,2016-09-08,2016-09-08
  SCENIC,R,10.1101/144501,PREPRINT,https://github.com/aertslab/SCENIC,SCENIC is a tool to infer Gene Regulatory Networks and cell types from single-cell RNA-seq data.,Custom,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,2017-06-26,2017-06-26
  SCENT,R,10.1038/ncomms15599,2017-06-01,https://github.com/aet21/SCENT,scent_1.0 is an R-package for analysis of single-cell RNA-Seq data. It uses single-cell entropy to help analyse and interpret such data.,GPL-3,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,FALSE,2016-11-09,2017-06-08
  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,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,2016-09-12,2016-09-12
  scImpute,R,10.1101/141598,PREPRINT,https://github.com/Vivianstats/scImpute,scImpute is developed to accurately and robustly impute the dropout values in scRNA-seq data,,FALSE,FALSE,FALSE,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,2017-05-30,2017-05-30
  