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KNeMAP : A network mapping approach for knowledge-driven comparison of transcriptomic profiles

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dc.contributor Landspitali - The National University Hospital of Iceland
dc.contributor.author Pavel, Alisa
dc.contributor.author Del Giudice, Giusy
dc.contributor.author Fratello, Michele
dc.contributor.author Ghemtio, Leo
dc.contributor.author Di Lieto, Antonio
dc.contributor.author Yli-Kauhaluoma, Jari
dc.contributor.author Xhaard, Henri
dc.contributor.author Federico, Antonio
dc.contributor.author Serra, Angela
dc.contributor.author Greco, Dario
dc.date.accessioned 2023-08-15T01:07:03Z
dc.date.available 2023-08-15T01:07:03Z
dc.date.issued 2023-06-01
dc.identifier.citation Pavel , A , Del Giudice , G , Fratello , M , Ghemtio , L , Di Lieto , A , Yli-Kauhaluoma , J , Xhaard , H , Federico , A , Serra , A & Greco , D 2023 , ' KNeMAP : A network mapping approach for knowledge-driven comparison of transcriptomic profiles ' , Bioinformatics , vol. 39 , no. 6 , btad341 . https://doi.org/10.1093/bioinformatics/btad341
dc.identifier.issn 1367-4803
dc.identifier.other 173673671
dc.identifier.other f5384606-a0c7-4112-976c-8af1e712e64c
dc.identifier.other 85162083942
dc.identifier.other 37225400
dc.identifier.uri https://hdl.handle.net/20.500.11815/4417
dc.description Funding Information: This work was supported by the Academy of Finland [322761]; European Research Council (ERC) programme, Consolidator project “ARCHIMEDES” [101043848]; and the Tampere Institute for Advanced Study (to A.S. and A.F.). Publisher Copyright: © 2023 The Author(s). Published by Oxford University Press.
dc.description.abstract MOTIVATION: Transcriptomic data can be used to describe the mechanism of action (MOA) of a chemical compound. However, omics data tend to be complex and prone to noise, making the comparison of different datasets challenging. Often, transcriptomic profiles are compared at the level of individual gene expression values, or sets of differentially expressed genes. Such approaches can suffer from underlying technical and biological variance, such as the biological system exposed on or the machine/method used to measure gene expression data, technical errors and further neglect the relationships between the genes. We propose a network mapping approach for knowledge-driven comparison of transcriptomic profiles (KNeMAP), which combines genes into similarity groups based on multiple levels of prior information, hence adding a higher-level view onto the individual gene view. When comparing KNeMAP with fold change (expression) based and deregulated gene set-based methods, KNeMAP was able to group compounds with higher accuracy with respect to prior information as well as is less prone to noise corrupted data. RESULT: We applied KNeMAP to analyze the Connectivity Map dataset, where the gene expression changes of three cell lines were analyzed after treatment with 676 drugs as well as the Fortino et al. dataset where two cell lines with 31 nanomaterials were analyzed. Although the expression profiles across the biological systems are highly different, KNeMAP was able to identify sets of compounds that induce similar molecular responses when exposed on the same biological system. AVAILABILITY AND IMPLEMENTATION: Relevant data and the KNeMAP function is available at: https://github.com/fhaive/KNeMAP and 10.5281/zenodo.7334711.
dc.format.extent 1773515
dc.language.iso en
dc.relation.ispartofseries Bioinformatics; 39(6)
dc.rights info:eu-repo/semantics/openAccess
dc.subject Geðsjúkdómafræði
dc.subject Transcriptome
dc.subject Gene Expression Profiling
dc.subject Computational Mathematics
dc.subject Molecular Biology
dc.subject Biochemistry
dc.subject Statistics and Probability
dc.subject Computer Science Applications
dc.subject Computational Theory and Mathematics
dc.title KNeMAP : A network mapping approach for knowledge-driven comparison of transcriptomic profiles
dc.type /dk/atira/pure/researchoutput/researchoutputtypes/contributiontojournal/article
dc.description.version Peer reviewed
dc.identifier.doi 10.1093/bioinformatics/btad341
dc.relation.url http://www.scopus.com/inward/record.url?scp=85162083942&partnerID=8YFLogxK

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