To analyze RNA-seq count data, there are several ways/methods for each steps like
transforming/scaling of the count data,
QC by clustering and
most importantly Differential expression of genes.
Additionally for each of these steps, there are different packages or tools whose input and output structure is very different. Therefore it is very difficult to include useful features from different packages in a study.
Input and output data structures of different methods to idetify differentially expressed genes.
Flowchart
The silent features of broadSeq are
data.frame
ggplot2
and ggpubr
packages for publication ready figures