ARACRA: Automated RNA-seq Analysis for Chemical Risk Assessment

Transcriptomics data captures genome-wide gene expression changes through in vitro or in vivo studies and can be used in chemical risk assessment for characterizing and identifying the effects of chemicals. While several bioinformatics tools and pipelines address discrete steps of the RNA sequencing (RNA-seq) workflow, a complete end-to-end framework from raw FASTQ files to transcriptomic point of departure in a streamlined way is unavailable and limits its accessibility to researchers without computational expertise. To address this gap, we present ARACRA, a fully automated RNA-seq analysis pipeline including entire transcriptomics workflow from raw FASTQ files to the transcriptomic point of departure with human-in-the-loop review process. Overall, the analysis is performed in 2 phases: Phase 1 carries out the acquisition of raw reads, prealignment quality control, alignment to reference genome, and quantification of gene expression, whereas Phase 2 performs statistical analysis including differential gene expression analysis and dose-response modeling. ARACRA was validated against a publicly available dataset (GSE271332) comprising 286 samples from MCF-7 cells exposed to bisphenol A (BPA) and 11 data-poor alternatives. The potency ranking of the chemicals were consistent with original results in which 2,4'BPA and BPA were found to be most transcriptionally active chemicals. Overall, ARACRA facilitates end-to-end analysis of RNA-seq data through an interactive web-based application developed on Nextflow (workflow management system) and Streamlit (an open-source python framework for graphical user interface) that minimizes computational complexities and ensures correct downstream processing.