Introduction to broadSeq

To analyze RNA-seq count data, there are several ways/methods for each steps like

  1. transforming/scaling of the count data,

  2. QC by clustering and

  3. 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.

Input and output data structures of different methods to idetify differentially expressed genes.

The broadSeq package simplifies the process of including many RNAseq packages and evaluating their performance.

Flowchart

Flowchart

The silent features of broadSeq are