Literature DB >> 33571195

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

Martín Garrido-Rodriguez1,2,3,4, Daniel Lopez-Lopez1,5, Francisco M Ortuno1,5, María Peña-Chilet1,5,6, Eduardo Muñoz2,3,4, Marco A Calzado2,3,4, Joaquin Dopazo1,5,6,7.   

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.

Entities:  

Mesh:

Year:  2021        PMID: 33571195      PMCID: PMC7904194          DOI: 10.1371/journal.pcbi.1008748

Source DB:  PubMed          Journal:  PLoS Comput Biol        ISSN: 1553-734X            Impact factor:   4.475


  41 in total

1.  featureCounts: an efficient general purpose program for assigning sequence reads to genomic features.

Authors:  Yang Liao; Gordon K Smyth; Wei Shi
Journal:  Bioinformatics       Date:  2013-11-13       Impact factor: 6.937

2.  Gene Expression Integration into Pathway Modules Reveals a Pan-Cancer Metabolic Landscape.

Authors:  Cankut Cubuk; Marta R Hidalgo; Alicia Amadoz; Miguel A Pujana; Francesca Mateo; Carmen Herranz; Jose Carbonell-Caballero; Joaquin Dopazo
Journal:  Cancer Res       Date:  2018-08-22       Impact factor: 12.701

3.  HISAT: a fast spliced aligner with low memory requirements.

Authors:  Daehwan Kim; Ben Langmead; Steven L Salzberg
Journal:  Nat Methods       Date:  2015-03-09       Impact factor: 28.547

4.  A method and server for predicting damaging missense mutations.

Authors:  Ivan A Adzhubei; Steffen Schmidt; Leonid Peshkin; Vasily E Ramensky; Anna Gerasimova; Peer Bork; Alexey S Kondrashov; Shamil R Sunyaev
Journal:  Nat Methods       Date:  2010-04       Impact factor: 28.547

5.  Gaining comprehensive biological insight into the transcriptome by performing a broad-spectrum RNA-seq analysis.

Authors:  Sayed Mohammad Ebrahim Sahraeian; Marghoob Mohiyuddin; Robert Sebra; Hagen Tilgner; Pegah T Afshar; Kin Fai Au; Narges Bani Asadi; Mark B Gerstein; Wing Hung Wong; Michael P Snyder; Eric Schadt; Hugo Y K Lam
Journal:  Nat Commun       Date:  2017-07-05       Impact factor: 14.919

6.  High throughput estimation of functional cell activities reveals disease mechanisms and predicts relevant clinical outcomes.

Authors:  Marta R Hidalgo; Cankut Cubuk; Alicia Amadoz; Francisco Salavert; José Carbonell-Caballero; Joaquin Dopazo
Journal:  Oncotarget       Date:  2017-01-17

7.  Salmon provides fast and bias-aware quantification of transcript expression.

Authors:  Rob Patro; Geet Duggal; Michael I Love; Rafael A Irizarry; Carl Kingsford
Journal:  Nat Methods       Date:  2017-03-06       Impact factor: 28.547

8.  Fibroblast activation and abnormal extracellular matrix remodelling as common hallmarks in three cancer-prone genodermatoses.

Authors:  E Chacón-Solano; C León; F Díaz; F García-García; M García; M J Escámez; S Guerrero-Aspizua; C J Conti; Á Mencía; L Martínez-Santamaría; S Llames; M Pévida; J Carbonell-Caballero; J A Puig-Butillé; R Maseda; S Puig; R de Lucas; E Baselga; F Larcher; J Dopazo; M Del Río
Journal:  Br J Dermatol       Date:  2019-04-15       Impact factor: 9.302

9.  Rail-RNA: scalable analysis of RNA-seq splicing and coverage.

Authors:  Abhinav Nellore; Leonardo Collado-Torres; Andrew E Jaffe; José Alquicira-Hernández; Christopher Wilks; Jacob Pritt; James Morton; Jeffrey T Leek; Ben Langmead
Journal:  Bioinformatics       Date:  2017-12-15       Impact factor: 6.937

Review 10.  A comparison of mechanistic signaling pathway activity analysis methods.

Authors:  Alicia Amadoz; Marta R Hidalgo; Cankut Çubuk; José Carbonell-Caballero; Joaquín Dopazo
Journal:  Brief Bioinform       Date:  2019-09-27       Impact factor: 11.622

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  2 in total

1.  SEAseq: a portable and cloud-based chromatin occupancy analysis suite.

Authors:  Modupeore O Adetunji; Brian J Abraham
Journal:  BMC Bioinformatics       Date:  2022-02-23       Impact factor: 3.169

2.  A toolkit for enhanced reproducibility of RNASeq analysis for synthetic biologists.

Authors:  Benjamin J Garcia; Joshua Urrutia; George Zheng; Diveena Becker; Carolyn Corbet; Paul Maschhoff; Alexander Cristofaro; Niall Gaffney; Matthew Vaughn; Uma Saxena; Yi-Pei Chen; D Benjamin Gordon; Mohammed Eslami
Journal:  Synth Biol (Oxf)       Date:  2022-08-23
  2 in total

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