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MODalyseR—a novel s...
MODalyseR—a novel software for inference of disease module hub regulators identified a putative multiple sclerosis regulator supported by independent eQTL data
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- de Weerd, Hendrik A. (author)
- Linköpings universitet,Högskolan i Skövde,Institutionen för biovetenskap,Forskningsmiljön Systembiologi,Department of Physics, Chemistry and Biology, Linköping University, Sweden,Translational Bioinformatics,Bioinformatik,Tekniska fakulteten,School of Bioscience, Systems Biology Research Center, University of Skövde, Skövde, Sweden
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- Åkesson, Julia (author)
- Linköpings universitet,Högskolan i Skövde,Institutionen för biovetenskap,Forskningsmiljön Systembiologi,Department of Physics, Chemistry and Biology, Linköping University, Sweden,Translational Bioinformatics,Bioinformatik,Tekniska fakulteten,School of Bioscience, Systems Biology Research Center, University of Skövde, Skövde, Sweden
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- Guala, Dimitri (author)
- Department of Biochemistry and Biophysics, Stockholm University, Solna, Sweden ; Merck AB, Solna, Sweden
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- Gustafsson, Mika, 1977- (author)
- Linköpings universitet,Bioinformatik,Tekniska fakulteten
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- Lubovac-Pilav, Zelmina (author)
- Högskolan i Skövde,Institutionen för biovetenskap,Forskningsmiljön Systembiologi,Translational Bioinformatics,School of Bioscience, Systems Biology Research Center, University of Skövde, Skövde, Sweden
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(creator_code:org_t)
- 2022-01-25
- 2022
- English.
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In: Bioinformatics Advances. - : Oxford University Press. - 2635-0041. ; 2:1
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Abstract
Subject headings
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- MotivationNetwork-based disease modules have proven to be a powerful concept for extracting knowledge about disease mechanisms, predicting for example disease risk factors and side effects of treatments. Plenty of tools exist for the purpose of module inference, but less effort has been put on simultaneously utilizing knowledge about regulatory mechanisms for predicting disease module hub regulators.ResultsWe developed MODalyseR, a novel software for identifying disease module regulators and reducing modules to the most disease-associated genes. This pipeline integrates and extends previously published software packages MODifieR and ComHub and hereby provides a user-friendly network medicine framework combining the concepts of disease modules and hub regulators for precise disease gene identification from transcriptomics data. To demonstrate the usability of the tool, we designed a case study for multiple sclerosis that revealed IKZF1 as a promising hub regulator, which was supported by independent ChIP-seq data.Availability and implementationMODalyseR is available as a Docker image at https://hub.docker.com/r/ddeweerd/modalyser with user guide and installation instructions found at https://gustafsson-lab.gitlab.io/MODalyseR/.Supplementary informationSupplementary data are available at Bioinformatics Advances online.
Subject headings
- NATURVETENSKAP -- Biologi -- Bioinformatik och systembiologi (hsv//swe)
- NATURAL SCIENCES -- Biological Sciences -- Bioinformatics and Systems Biology (hsv//eng)
Keyword
- Bioinformatik
- Bioinformatics
Publication and Content Type
- ref (subject category)
- art (subject category)
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