RNA-Seq is increasingly being used to measure human RNA expression on a genome-wide scale.Expression profiles can be interrogated to identify and functionally characterize treatment-responsive genes.Ultimately, such controlled studies promise to reveal insights into molecular mechanisms of treatment effects, identify biomarkers, and realize personalized medicine.RNA-Seq Reports (RSEQREP) is a new open-source cloud-enabled framework that allows users to execute start-to-end gene-level RNA-Seq analysis on a preconfigured RSEQREP Amazon Virtual Machine Image (AMI) hosted by AWS or on their own Ubuntu Linux click here machine via a Docker container or installation script.
The framework works with unstranded, stranded, and paired-end sequence FASTQ files stored locally, on Amazon Simple Storage Service (S3), or at the Sequence Read Archive (SRA).RSEQREP automatically executes a series of customizable steps including reference alignment, CRAM compression, reference alignment QC, data normalization, multivariate data visualization, identification of differentially expressed genes, heatmaps, co-expressed gene clusters, enriched pathways, and a series of custom visualizations.The framework outputs a file collection that includes a dynamically generated PDF report using R, knitr, and LaTeX, as well as publication-ready table and figure files.A user-friendly configuration file handles sample metadata entry, processing, analysis, and reporting options.
The configuration supports time series RNA-Seq apac1/60/1/cw experimental designs with at least one pre- and one post-treatment sample for each subject, as well as multiple treatment groups and specimen types.All RSEQREP analyses components are built using open-source R code and R/Bioconductor packages allowing for further customization.As a use case, we provide RSEQREP results for a trivalent influenza vaccine (TIV) RNA-Seq study that collected 1 pre-TIV and 10 post-TIV vaccination samples (days 1-10) for 5 subjects and two specimen types (peripheral blood mononuclear cells and B-cells).