anchor.diff:  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,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,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,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,FALSE,2016-09-13
   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,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,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,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,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,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,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,FALSE,2016-09-13
   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,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,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,FALSE,2016-09-08
  
positive.code: 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,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,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,FALSE,2016-09-09
  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,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,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,FALSE,2016-09-09
  
negative.code: 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,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,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,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,FALSE,2016-09-13
  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,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,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,FALSE,TRUE,TRUE,FALSE,2016-09-09
  