This pipeline is implemented in the drake Make-like toolkit (https://github.com/ropensci/drake) and provides the following steps of scRNA-seq secondary analysis: input quality control, filtering of cells/genes, normalization, clustering, cell type annotation, cluster markers, differential expression analysis (constrasts -> cluster vs. cluster), integration of multiple samples. All main parts are accompanied by rich graphical outputs and HTML reports (RMarkdown). Thanks to the drake package, the pipeline is highly reproducible, scalable and efficient, provides easy access to all intermediate results, and can be arbitrarily extended as pipeline definitions are abstracted as R objects. A command line interface is available to perform the most important actions directly in shell terminal.
Package details |
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Bioconductor views | Clustering DifferentialExpression Normalization QualityControl SingleCell Transcription |
Maintainer | |
License | MIT + file LICENSE |
Version | 1.6.0 |
URL | https://github.com/bioinfocz/scdrake https://bioinfocz.github.io/scdrake |
Package repository | View on GitHub |
Installation |
Install the latest version of this package by entering the following in R:
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