Milne, I. | Search bioRxiv

bioRxiv2026

EoRNA2: Autonomous Data Discovery and Processing for Databasing of Gene Expression Data

We describe a major new release of the EoRNA database, a gene expression database for barley based on public data, first published in 20211. EoRNA v.2 (https://ics.hutton.ac.uk/eorna2/index.html) features an order of magnitude more samples and is based on a new automated workflow of sample discovery and processing which has enabled a dramatic scale-up the original database. EoRNA v.2 also features a major rebuild of the web user interface with rich new functionality. All infrastructure-related code and database schemas and web components are now species agnostic and publicly available for reuse with other taxa. A dedicated new reference transcript dataset has been created for EoRNA v.2 which is largely based on the recently published barley pan-transcriptome and represents the most comprehensive dataset of its kind to date.

bioinformatics↗

bioRxiv2019

3D RNA-seq - a powerful and flexible tool for rapid and accurate differential expression and alternative splicing analysis of RNA-seq data for biologists

RNA-seq analysis of gene expression and alternative splicing should be routine and robust but is often a bottleneck for biologists because of reliance on specialized bioinformatics skills. Thus, we have developed "3D RNA-seq", an R shiny App and web based service which provides an easy-to-use, flexible and powerful tool for three-component analysis of RNA-seq data: Differential Expression, Differential Alternative Splicing and Differential Transcript Usage. 3D RNA-seq integrates state-of-the-art, highly rated differential expression analysis tools and adopts best practice for RNA-seq analysis. It operates through a user-friendly graphical interface, can handle complex experimental designs, allows setting of statistical parameters, tracks results through graphics and tables, and generates figures and a comprehensive report that will guarantee reproducibility. 3D RNA-seq can be applied to any species and is designed to be run by biologists with no programming skills (or by bioinformaticians) allowing lab scientists to perform rapid and accurate analysis of RNA-seq data.

bioinformatics↗