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bioc
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
monocle:Clustering, differential expression, and trajectory analysis for single- cell RNA-Seq
Monocle performs differential expression and time-series analysis for single-cell expression experiments. It orders individual cells according to progress through a biological process, without knowing ahead of time which genes define progress through that process. Monocle also performs differential expression analysis, clustering, visualization, and other useful tasks on single cell expression data. It is designed to work with RNA-Seq and qPCR data, but could be used with other types as well.
Maintained by Cole Trapnell. Last updated 5 months ago.
immunooncologysequencingrnaseqgeneexpressiondifferentialexpressioninfrastructuredataimportdatarepresentationvisualizationclusteringmultiplecomparisonqualitycontrolcpp
8.71 score 1.6k scripts 2 dependents