AutoRNAseq: Automated Bulk RNA-seq Analysis Pipeline

Area of Science:

• Bioinformatics
• Computational Biology
• Genomics

Background:

• High-throughput RNA sequencing (RNA-seq) generates vast amounts of data annually.
• The increasing volume of RNA-seq data necessitates reproducible and consistent analysis pipelines.
• Existing workflows often require complex user coordination and pre-configuration of reference data.

Purpose of the Study:

• To develop an automated, end-to-end workflow for bulk RNA sequencing data analysis.
• To address the need for reproducible RNA-seq data processing across diverse experiments.
• To simplify the analysis pipeline, reducing user intervention and pre-configuration requirements.

Main Methods:

• Implementation of a Snakemake-based workflow named AutoRNAseq.
• Automation of data retrieval, quality control, alignment, and gene quantification.
• Integration of automated reference data preparation.

Main Results:

• AutoRNAseq offers a single, unified workflow for comprehensive RNA-seq analysis.
• The workflow automates critical steps from data acquisition to gene quantification.
• Minimal user intervention is required, enhancing reproducibility and efficiency.

Conclusions:

• AutoRNAseq provides a robust solution for consistent bulk RNA-seq data processing.
• The workflow is applicable to various research domains, including bioinformatics and drug-response studies.
• This tool enhances the accessibility and reliability of RNA-seq data analysis.