.png){kind=icon}
.png){kind=icon}
Return
REDAC: RNA-seq expression data analysis chatbot
.png){kind=icon}
OA
AI
DOI：10.1093/bioadv/vbaf321.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Motivation To date, due to the complexity of both the analytical processes and the result interpretation of RNA-seq expression data analyses, researchers often require the support of bioinformaticians expertise. Selecting appropriate statistical tests and performing essential data manipulations, such as normalization and filtering, in a rigorous and reproducible manner remains a significant challenge for many users.Results We developed REDAC, a web-based R application that offers an interactive platform designed to simplify and enhance RNA-seq expression data exploration and analysis. REDAC provides a straightforward approach to perform differentially RNA-seq analysis rapidly, easily, and transparently through natural language queries from users. Moreover, it allows to run complete analyses, generate comprehensive visualizations, and obtain biological interpretation of pathway enrichment results via two popular Large Language Models: Gemma and LLaMA guided by a PubMed based Retrieval-Augmented Generation module. Finally, REDAC promotes reproducibility through the automated generation of analysis reports.Availability and implementation REDAC is available for local (https://github.com/franruss/REDAC) and online use (https://frusso.shinyapps.io/REDAC). User manual: https://github.com/franruss/REDAC/blob/main/docs/REDAC_user_manual.pdf
Keywords:
RNA-seq analysis
bioinformatics
differential expression
natural language processing
reproducible research
Journal
B
IF:
2.8
Papers:
131
Citations:
0
Organization
View more organizations