anchor.diff:  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).,MIT,FALSE,FALSE,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,2016-09-09,2016-09-09
   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.",GPL (>=2),FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,2016-09-08,2016-09-08
   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.",GPL-3,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,2016-09-08,2016-10-07
  -SIMLR,R,10.1038/nmeth.4207,2017-03-06,https://github.com/BatzoglouLabSU/SIMLR,"Single-cell Interpretation via Multi-kernel LeaRning which learns an appropriate distance metric from the data for dimension reduction, clustering and visualization. ",GPL-3,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,2016-09-09,2017-03-10
  +SIMLR,R,10.1038/nmeth.4207,2017-03-06,https://github.com/BatzoglouLabSU/SIMLR,"Single-cell Interpretation via Multi-kernel LeaRning which learns an appropriate distance metric from the data for dimension reduction, clustering and visualization.",GPL-3,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,2016-09-09,2017-03-10
   sincell,R,10.1101/014472,PREPRINT,https://github.com/Bioconductor-mirror/sincell,"Existing computational approaches for the assessment of cell-state hierarchies from single-cell data might be formalized under a general workflow composed of i) a metric to assess cell-to-cell similarities (combined or not with a dimensionality reduction step), and ii) a graph-building algorithm (optionally making use of a cells-clustering step). Sincell R package implements a methodological toolbox allowing flexible workflows under such framework.",GPL (>= 2),FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,2016-09-08,2016-09-08
  -Sincera,R,10.1371/journal.pcbi.1004575,2015-11-04,https://research.cchmc.org/pbge/sincera.html,R-based pipeline for single-cell analysis including clustering and visualization.,GPL-3,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,2016-09-08,2016-09-08
  +Sincera,R,10.1371/journal.pcbi.1004575,2015-11-04,https://research.cchmc.org/pbge/sincera.html,R-based pipeline for single-cell analysis including clustering and visualization.,GPL-3,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,2016-09-08,2017-04-18
   SingleSplice,R/Perl/C++,10.1093/nar/gkv1525,2016-01-05,https://github.com/jw156605/SingleSplice,Algorithm for detecting alternative splicing in a population of single cells.,GPL-2,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,FALSE,2017-01-24,2017-01-24
  -SinQC,R/Python,10.1093/bioinformatics/btw176,2016-04-10,http://www.morgridge.net/SinQC.html,A Method and Tool to Control Single-cell RNA-seq Data Quality.,,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,FALSE,2016-09-08,2016-09-08
  +SinQC,R/Python,10.1093/bioinformatics/btw176,2016-04-10,http://www.morgridge.net/SinQC.html,A Method and Tool to Control Single-cell RNA-seq Data Quality.,,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,FALSE,2016-09-08,2017-04-18
   SLICE,R,10.1093/nar/gkw1278,2016-12-19,https://research.cchmc.org/pbge/slice.html,The SLICE (Single Cell Lineage Inference Using Cell Expression Similarity and Entropy) algorithm consists of two major steps: (1) measuring cell differentiation states based on the calculation of single cell entropy (scEntropy) and (2) predicting cell differentiation trajectories by ordering single cells according to their scEntropy-derived differentiation states.,GPL-3,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,2017-01-10,2017-01-10
   SLICER,R,10.1186/s13059-016-0975-3,2016-05-23,https://github.com/jw156605/SLICER,Selective Locally linear Inference of Cellular Expression Relationships (SLICER) algorithm for inferring cell trajectories.,GPL-2,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,2016-09-08,2016-09-08
   slingshot,R,,,https://github.com/kstreet13/slingshot,Functions for identifying and characterizing continuous developmental trajectories in single-cell sequencing data.,Artistic-2.0,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,2016-09-09,2016-09-09
  -SPADE,R,10.1038/nprot.2016.066,2016-06-16,https://github.com/nolanlab/spade,Visualization and cellular hierarchy inference of single-cell data using SPADE.,GPL (>=2),FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,2016-09-09,2016-09-09
  +SPADE,R,10.1038/nprot.2016.066,2016-06-16,https://github.com/nolanlab/spade,Visualization and cellular hierarchy inference of single-cell data using SPADE.,GPL (>=2),FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,2016-09-09,2017-04-18
   Splatter,R,,,https://github.com/Oshlack/splatter,Splatter is a package for the simple simulation of single-cell RNA-seq count data.,GPL-3,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,2016-10-27,2016-10-27
   SPRING,Python/Matlab/Javascript,10.1101/090332,PREPRINT,https://github.com/AllonKleinLab/SPRING/,SPRING is a collection of pre-processing scripts and a web browser-based tool for visualizing and interacting with high dimensional data.,,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,TRUE,FALSE,2016-12-05,2016-12-05
   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.,MIT,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
  
positive.code: TASC,C++,10.1101/116939,PREPRINT,https://github.com/scrna-seq/TASC,"TASC (Toolkit for Analysis of Single Cell RNA-seq), an empirical Bayes approach to reliably model the cell-specific dropout rates and amplification bias by use of external RNA spike-ins.",MIT,FALSE,TRUE,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,2017-03-29,2017-03-29
  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.,BSD-3-clause,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.,GPL (>=2),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). ,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,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,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,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,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,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,2016-12-22,2016-12-22
negative.code: GiniClust,R/Python,10.1186/s13059-016-1010-4,2016-07-01,https://github.com/lanjiangboston/GiniClust,GiniClust is a clustering method implemented in Python and R for detecting rare cell-types from large-scale single-cell gene expression data.,MIT,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,2016-09-09,2016-09-09
  GPfates,Python,10.1126/sciimmunol.aal2192,2017-03-03,https://github.com/Teichlab/GPfates,Model transcriptional cell fates as mixtures of Gaussian Processes,MIT,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,2016-09-19,2017-03-10
  Granatum,Virtualbox,10.1101/110759,PREPRINT,https://gitlab.com/uhcclxgg/granatum,This is a graphical single-cell RNA-seq (scRNA-seq) analysis pipeline for genomics scientists.,,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,2017-03-01,2017-03-01
  GRM,R,10.1093/bioinformatics/btv122,2015-07-01,http://wanglab.ucsd.edu/star/GRM/,Normalization and noise reduction for singlecell RNA-seq experiments,,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,2016-09-09,2017-04-18
  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,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,2016-09-08,2016-09-08
  ISOP,R,10.1101/036988,PREPRINT,https://github.com/nghiavtr/ISOP,ISOform-level expression Patterns in single-cell RNA-sequencing data.,GPL-3,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,2016-09-09,2016-09-09
  k-branches,R,10.1101/094532,PREPRINT,https://github.com/theislab/kbranches,The main idea behind the K-Branches method is to identify regions of interest (branching regions and tips) in differentiation trajectories of single cells.,GPL-3,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,2016-12-22,2016-12-22
  LEAP,R,10.1093/bioinformatics/btw729,2016-12-19,https://cran.r-project.org/web/packages/LEAP/index.html,Constructing Gene Co-Expression Networks for Single-Cell RNA-Sequencing Data Using Pseudotime Ordering.,GPL-2,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,2016-09-12,2017-04-18
  Linnorm,R,,,https://github.com/Bioconductor-mirror/Linnorm,"Linnorm is an R package for the analysis of RNA-seq, scRNA-seq, ChIP-seq count data or any large scale count data.",MIT,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE,TRUE,FALSE,TRUE,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,TRUE,2017-02-01,2017-02-01
  M3Drop,R,10.1101/065094,PREPRINT,https://github.com/tallulandrews/M3Drop,R package providing functions for fitting a modified Michaelis-Menten (MM) equation to the pattern of dropouts observed in a single-cell sequencing experiment.,GPL (>=2),FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,2016-10-10,2016-10-10
  MAGIC,Python,10.1101/111591,PREPRINT,https://github.com/pkathail/magic/,Markov Affinity-based Graph Imputation of Cells (MAGIC),GPL-2,FALSE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,FALSE,2017-02-27,2017-02-17
  