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iSanXoT: A standalone application for the integrative analysis of mass spectrometry-based quantitative proteomics data.

dc.contributor.authorRodriguez, Jose Manuel
dc.contributor.authorJorge, Inmaculada
dc.contributor.authorMartinez-Val, Ana
dc.contributor.authorBarrero-Rodríguez, Rafael
dc.contributor.authorMagni, Ricardo
dc.contributor.authorNunez, Estefania
dc.contributor.authorLaguillo, Andrea
dc.contributor.authorDevesa, Cristina A
dc.contributor.authorLopez, Juan Antonio
dc.contributor.authorCamafeita, Emilio
dc.contributor.authorVazquez, Jesus
dc.contributor.funderMinisterio de Ciencia, Innovación y Universidades (España)es_ES
dc.contributor.funderInstituto de Salud Carlos IIIes_ES
dc.contributor.funderComunidad de Madrid (España)es_ES
dc.contributor.funderFundación La Caixaes_ES
dc.contributor.funderFundación ProCNICes_ES
dc.contributor.funderMinisterio de Ciencia e Innovación. Centro de Excelencia Severo Ochoa (España)es_ES
dc.contributor.funderMinisterio de Educación, Cultura y Deporte (España)es_ES
dc.date.accessioned2024-03-21T14:23:51Z
dc.date.available2024-03-21T14:23:51Z
dc.date.issued2024-12
dc.description.abstractMany bioinformatics tools are available for the quantitative analysis of proteomics experiments. Most of these tools use a dedicated statistical model to derive absolute quantitative protein values from mass spectrometry (MS) data. Here, we present iSanXoT, a standalone application that processes relative abundances between MS signals and then integrates them sequentially to upper levels using the previously published Generic Integration Algorithm (GIA). iSanXoT offers unique capabilities that complement conventional quantitative software applications, including statistical weighting and independent modeling of error distributions in each integration, aggregation of technical or biological replicates, quantification of posttranslational modifications, and analysis of coordinated protein behavior. iSanXoT is a standalone, user-friendly application that accepts output from popular proteomics pipelines and enables unrestricted creation of quantification workflows and fully customizable reports that can be reused across projects or shared among users. Numerous publications attest the successful application of diverse integrative workflows constructed using the GIA for the analysis of high-throughput quantitative proteomics experiments. iSanXoT has been tested with the main operating systems. Download links for the corresponding distributions are available at https://github.com/CNIC-Proteomics/iSanXoT/releases.es_ES
dc.description.peerreviewedes_ES
dc.description.sponsorshipThis study was supported by competitive grants from the Spanish Ministry of Science, Innovation and Universities (PGC2018–097019-BI00, PID2021–122348NB-I00, PLEC2022–009235 and PLEC2022–009298), the Instituto de Salud Carlos III (Fondo de Investigacion ´ Sanitaria grant PRB3 (PT17/0019/0003- ISCIII-SGEFI / ERDF, ProteoRed), Comunidad de Madrid (IMMUNO-VAR, P2022/BMD7333), the Spanish Ministry of Education, Culture and Sports (FPU18/ 03882, FPU20/03365 and PRE2019-090019), and the “la Caixa” Banking Foundation (project codes HR17–00247 and HR22–00253). The CNIC is supported by the Instituto de Salud Carlos III (ISCIII), the Ministerio de Ciencia e Innovacion ´ (MCIN), and the Pro CNIC Foundation) and is a Severo Ochoa Center of Excellence (grant CEX2020–001041-S funded by MICIN/AEI/10.13039/501100011033).es_ES
dc.format.page452es_ES
dc.format.volume23es_ES
dc.identifier.citationComput Struct Biotechnol J. 2023 Dec 26:23:452-459.es_ES
dc.identifier.doi10.1016/j.csbj.2023.12.034es_ES
dc.identifier.issn2001-0370es_ES
dc.identifier.journalComputational and structural biotechnology journales_ES
dc.identifier.pubmedID38235360es_ES
dc.identifier.urihttp://hdl.handle.net/20.500.12105/19035
dc.language.isoenges_ES
dc.publisherElsevieres_ES
dc.relation.projectFECYTinfo:eu-repo/grantAgreement/ES/PGC2018–097019-BI00es_ES
dc.relation.projectFECYTinfo:eu-repo/grantAgreement/ES/PID2021–122348NB-I00es_ES
dc.relation.projectFECYTinfo:eu-repo/grantAgreement/ES/PLEC2022–009235es_ES
dc.relation.projectFECYTinfo:eu-repo/grantAgreement/ES/PLEC2022–009298es_ES
dc.relation.projectFECYTinfo:eu-repo/grantAgreement/ES/PT17/0019/0003es_ES
dc.relation.projectFECYTinfo:eu-repo/grantAgreement/ES/P2022/BMD7333es_ES
dc.relation.projectFECYTinfo:eu-repo/grantAgreement/ES/PU18/03882es_ES
dc.relation.projectFECYTinfo:eu-repo/grantAgreement/ES/FPU20/03365es_ES
dc.relation.projectFECYTinfo:eu-repo/grantAgreement/ES/PRE2019-090019es_ES
dc.relation.projectFECYTinfo:eu-repo/grantAgreement/ES/HR17–00247es_ES
dc.relation.projectFECYTinfo:eu-repo/grantAgreement/ES/HR22–00253es_ES
dc.relation.projectFECYTinfo:eu-repo/grantAgreement/ES/MICIN/AEI/10.13039/501100011033/CEX2020–001041-Ses_ES
dc.relation.publisherversion10.1016/j.csbj.2023.12.034es_ES
dc.repisalud.institucionCNICes_ES
dc.repisalud.orgCNICCNIC::Grupos de investigación::Proteómica cardiovasculares_ES
dc.rights.accessRightsopen accesses_ES
dc.rights.licenseAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.titleiSanXoT: A standalone application for the integrative analysis of mass spectrometry-based quantitative proteomics data.es_ES
dc.typejournal articlees_ES
dc.type.hasVersionVoRes_ES
dspace.entity.typePublication
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relation.isAuthorOfPublication.latestForDiscovery63e55d34-c1c9-439c-bc46-f5b9830e538a

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