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A versatile workflow to integrate RNA-seq genomic and transcriptomic data into mechanistic models of signaling pathways

Martín Garrido‐Rodríguez, Daniel López-López, Francisco Ortuño, María Peña-Chilet, Eduardo Muñóz, Marco A. Calzado, Joaquı́n Dopazo

2021PLoS Computational Biology18 citationsDOIOpen Access PDF

Abstract

MIGNON is a workflow for the analysis of RNA-Seq experiments, which not only efficiently manages the estimation of gene expression levels from raw sequencing reads, but also calls genomic variants present in the transcripts analyzed. Moreover, this is the first workflow that provides a framework for the integration of transcriptomic and genomic data based on a mechanistic model of signaling pathway activities that allows a detailed biological interpretation of the results, including a comprehensive functional profiling of cell activity. MIGNON covers the whole process, from reads to signaling circuit activity estimations, using state-of-the-art tools, it is easy to use and it is deployable in different computational environments, allowing an optimized use of the resources available.

Topics & Concepts

WorkflowRNA-SeqComputational biologyTranscriptomeComputer scienceProfiling (computer programming)BiologyGeneGene expressionGeneticsDatabaseOperating systemGenomics and Phylogenetic StudiesRNA and protein synthesis mechanismsBioinformatics and Genomic Networks
A versatile workflow to integrate RNA-seq genomic and transcriptomic data into mechanistic models of signaling pathways | Litcius