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scran:Methods for Single-Cell RNA-Seq Data Analysis
Implements miscellaneous functions for interpretation of single-cell RNA-seq data. Methods are provided for assignment of cell cycle phase, detection of highly variable and significantly correlated genes, identification of marker genes, and other common tasks in routine single-cell analysis workflows.
Maintained by Aaron Lun. Last updated 5 months ago.
immunooncologynormalizationsequencingrnaseqsoftwaregeneexpressiontranscriptomicssinglecellclusteringbioconductor-packagehuman-cell-atlassingle-cell-rna-seqopenblascpp
41 stars 13.05 score 7.6k scripts 37 dependentsbioc
scrapper:Bindings to C++ Libraries for Single-Cell Analysis
Implements R bindings to C++ code for analyzing single-cell (expression) data, mostly from various libscran libraries. Each function performs an individual step in the single-cell analysis workflow, ranging from quality control to clustering and marker detection. It is mostly intended for other Bioconductor package developers to build more user-friendly end-to-end workflows.
Maintained by Aaron Lun. Last updated 13 days ago.
normalizationrnaseqsoftwaregeneexpressiontranscriptomicssinglecellbatcheffectqualitycontroldifferentialexpressionfeatureextractionprincipalcomponentclusteringopenblascpp
5.57 score 32 scripts