EMOGEA (Error Modeled Gene Expression Analysis ) is a computational method for the analysis of RNA-Seq gene expression data. It is suitable for the analysis of data deriving from three of the most common experimental design strategies in -omics research: Binary comparisons(case/control), Temporal (ordinal) measurements, and single-cell RNA-seq (scRNAseq) for trajectory inference.
Technical description of the method and extended usage examples will soon be available upon completion of the academic peer-review process.
The current implementation of EMOGEA is in R (this repository). The output from any of the implementations can be explored either in R or Python.
To use R for the whole analysis, there is the main tutorial:
The tutorials in R include a more detailed explanation of the workflow and source code.
To install the package, type the following in the R console:
devtools::install_github("itikadi/emogeav1", build_vignettes = TRUE)Check the vignette to see how to use the package:
browseVignettes("EMOGEA")It is highly recommended to use the Microsoft R Open distribution to use the package (R >= 4.0.0).