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README.md

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 # Overview of SCDE
 
 The `scde` package implements a set of statistical methods for analyzing single-cell RNA-seq data. `scde` fits individual error models for single-cell RNA-seq measurements. These models can then be used for assessment of differential expression between groups of cells, as well as other types of analysis. The `scde` package also contains the `pagoda` framework which applies pathway and gene set overdispersion analysis to identify aspects of transcriptional heterogeneity among single cells. 
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       <code>scde</code> fits individual error models for single cells using counts derived from single-cell RNA-seq data to estimate drop-out and amplification biases on gene expression magnitude.
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       <code>scde</code> contains <code>pagoda</code> routines that characterize aspects of transcriptional heterogeneity in populations of single cells using pre-defined gene sets as well as 'de novo' gene sets derived from the data. Significant aspects are used to cluster cells into subpopulations. A graphical user interface can be deployed to interactively explore results. See examples from the PAGODA publication <a href="http://pklab.med.harvard.edu/scde/pagoda.links.html">here</a>. See analysis of the PBMC data from 10x Genomics <a href="http://pklab.med.harvard.edu/cgi-bin/R/rook/10x.pbmc/index.html">here</a>.