RNAflow: An Effective and Simple RNA-Seq Differential Gene Expression Pipeline Using Nextflow

Area of Science:

• Bioinformatics
• Genomics
• Computational Biology

Background:

• RNA sequencing (RNA-Seq) is crucial for gene expression analysis but lacks standardized computational methods.
• Previous RNA-Seq studies have faced reproducibility challenges, hindering reliable results.

Purpose of the Study:

• To develop a portable, scalable, and reproducible Nextflow pipeline for detecting differentially expressed genes (DEGs) using RNA-Seq data.
• To address common RNA-Seq analysis pitfalls and incorporate downstream pathway analysis for key species.

Main Methods:

• Implementation of a Nextflow-based RNA-Seq pipeline designed for portability, scalability, and parallel processing.
• Automated handling of ribosomal RNA removal and low-abundance gene filtering.
• Integration of visualization tools and pathway analysis for species including Homo sapiens and Mus musculus.

Main Results:

• The pipeline demonstrated high reproducibility in DEG detection.
• Evaluation using qRT-PCR data showed a strong correlation with the pipeline's calculated gene expression fold changes.
• Successful implementation of automated quality control and downstream analysis features.

Conclusions:

• The developed Nextflow pipeline offers a robust and reproducible solution for RNA-Seq DEG analysis.
• This tool enhances the reliability of gene expression studies and facilitates downstream biological interpretation.
• The pipeline's validation confirms its accuracy and utility in genomic research.