bioRxivBioinformaticsPreprint
DEAR-OWL: a fully browser-based hybrid resource for instant or precise differential gene expression analysis
Abstract
MotivationDifferential gene expression analysis (DEA) via RNA sequencing (RNA-seq) is essential but remains challenging for wet-lab biologists due to command-line complexities. Centralized web platforms democratize this process but suffer from server congestion, long queuing delays, data privacy risks with proprietary datasets, and limited long-term sustainability due to hosting fees. ResultsWe present DEAR-OWL (Differential Expression Analysis Resource on the Web (Lite)), a fully serverless, privacy-preserving web application that performs the DEA locally inside the users web browser. To combine instant exploratory speed with rigorous verification, the application runs two distinct analysis options. The first option is a fast screening tool written in native browser language (JavaScript) that delivers immediate, genome-wide fold-change calculations and statistical screening based on an edgeR-equivalent logic. The second option is a heavy-duty statistical tool that brings the standard R package (DESeq2) directly into the browser using WebR and WebAssembly technology, ensuring publication-grade validation without needing server power. Interactive visual plots (volcano plots, minus-average plots, and heatmaps) are seamlessly generated from the results of either analysis choice. Benchmarking proved its hardware compatibility: the browser-based DESeq2 engine completed the analysis in [~]30 seconds on a 64 GB RAM workstation and in [~]3 minutes on an 8 GB RAM laptop without crashing. DEAR-OWL can utilize the Grass Expression Atlas (GExA) data as built-in and supports secure local file uploads, ensuring total data privacy with neither queuing delays nor cloud infrastructure costs. Availability and implementationDEAR-OWL is freely accessible at https://webpark2116.sakura.ne.jp/deseq2/. The source code is available at https://github.com/kota200/DEAR-OWL.
- assay: bulk RNA-seq
- research focus: differential expression
- approach: statistical model
- approach: experimental assay
- Citations
- 0
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