SEPA: SEPA: Single-Cell Gene Expression Pattern Analysis
In SEPA: SEPA
Description
SEPA provides useful functions to analysis gene expression patterns and perform GO analysis for single-cell RNA-seq data.
Details
Given single-cell RNA-seq data and true experiment time of cells or pseudo-time cell ordering, 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.
SEPA comes with a user-friendly Graphical User Interface written in shiny.
SEPA documentation built on May 6, 2019, 2:42 a.m.
R Package Documentation
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Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Description
SEPA provides useful functions to analysis gene expression patterns and perform GO analysis for single-cell RNA-seq data.
Details
Given single-cell RNA-seq data and true experiment time of cells or pseudo-time cell ordering, 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. SEPA comes with a user-friendly Graphical User Interface written in shiny.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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