Transcriptomic is a common tool to asses differential gene expression in order to compare multiple conditions.
Most of the transcriptomic facilities offers a service for acquisition and statistical analysis of transcriptomic data (DNA chips, RNA-seq, ChIP-Seq). The data analyses are performed using R scripts from raw data pretreatments to statistical analysis. It is noted that statistical analyses define arbtirary filtering criteria to select relevant genes. Hence biologists are led to reconsider these criteria according to their own scientific question.
In order to allow biologists to explore their own datasets in autonomy and generate graphical representations, we have deployed a turnkey solution built with the shiny framework.
The main contributors to MATRiX
Yannick Lippi (Initiator, beta-testing, feature suggestions)
Franck Soubès (Coding, Unit testing, documentation, packaging, deployment of the web service, feature suggestions)
Thanks to the Toxalim's team BioToMyc & TIM and especially to the following people for their helps reporting errors, proposing new features and beta testing of MATRiX:
Laura Costes, Anne Fougerat, Claire Naylies, Philippe Pinton, Arnaud Polizzi, Marion Regnier, Sandrine Ellero-Simatos, Sarra Smati.
Special Thanks to Didier Laborie for installing the virtual machine with Ubuntu and for answering my questions.
MATRiX leverages the cumulative functionalities of 47 R (ggplot2, gplots, RDAVIDWebService ...) and 3 js (Jvenn, Highchart and Jquery) libraries.
The application was deployed with Shiny Open Source.
The source code can be found in the ForgeMIA.Source code
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