The RNA sequencing technique known as ‘RNA-seq’ captures the expressed genes by sequencing the RNA molecules. In other words, the RNA-seq analysis allows for identifying the genes that are expressed in a given condition. Then, the functional annotation of these identified genes provides with the biological insights on how an organism operates in that particular condition. This RNA-seq along with many other genomic approaches are being increasingly applied as the sequencing cost is becoming affordable. However, analysing these sequencing data and extracting reliable biological insights from them remain a challenge due to the technical complexity of the sequencing data analysis.
Researchers from the University of Western Australia present a bioinformatics workflow from RNA-seq raw data processing to generating a gene expression matrix required for differential gene expression analysis. To help understand the computation steps in an RNA-seq workflow, the researchers first illustrate on how the samples are prepared for RNA-seq purpose. The modifications made to the transcriptome during sample preparation for sequencing need to be reversed to reconstruct the original transcriptome. Furthermore, they provide with an example script for each step in the RNA-seq workflow and explain the codes concisely. This intuitive guide will be a valuable resource for a wide range of audience especially the graduate students and molecular biologists aiming to carry out RNA-seq analysis on their own for the first time.
RNA-seq data analysis workflow