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Differential analysis of combinatorial protein complexes with CompleXChange

BACKGROUND: Although a considerable number of proteins operate as multiprotein complexes and not on their own, organism-wide studies so far are only able to quantify individual proteins or protein-coding genes in a condition-specific manner for a sizeable number of samples, but not their assemblies....

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Autores principales: Will, Thorsten, Helms, Volkhard
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6547514/
https://www.ncbi.nlm.nih.gov/pubmed/31159772
http://dx.doi.org/10.1186/s12859-019-2852-z
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author Will, Thorsten
Helms, Volkhard
author_facet Will, Thorsten
Helms, Volkhard
author_sort Will, Thorsten
collection PubMed
description BACKGROUND: Although a considerable number of proteins operate as multiprotein complexes and not on their own, organism-wide studies so far are only able to quantify individual proteins or protein-coding genes in a condition-specific manner for a sizeable number of samples, but not their assemblies. Consequently, there exist large amounts of transcriptomic data and an increasing amount of data on proteome abundance, but quantitative knowledge on complexomes is missing. This deficiency impedes the applicability of the powerful tool of differential analysis in the realm of macromolecular complexes. Here, we present a pipeline for differential analysis of protein complexes based on predicted or manually assigned complexes and inferred complex abundances, which can be easily applied on a whole-genome scale. RESULTS: We observed for simulated data that results obtained by our complex abundance estimation algorithm were in better agreement with the ground truth and physicochemically more reasonable compared to previous efforts that used linear programming while running in a fraction of the time. The practical usability of the method was assessed in the context of transcription factor complexes in human monocyte and lymphoblastoid samples. We demonstrated that our new method is robust against false-positive detection and reports deregulated complexomes that can only be partially explained by differential analysis of individual protein-coding genes. Furthermore we showed that deregulated complexes identified by the tool potentially harbor significant yet unused information content. CONCLUSIONS: CompleXChange allows to analyze deregulation of the protein complexome on a whole-genome scale by integrating a plethora of input data that is already available. A platform-independent Java binary, a user guide with example data and the source code are freely available at https://sourceforge.net/projects/complexchange/. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12859-019-2852-z) contains supplementary material, which is available to authorized users.
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spelling pubmed-65475142019-06-06 Differential analysis of combinatorial protein complexes with CompleXChange Will, Thorsten Helms, Volkhard BMC Bioinformatics Software BACKGROUND: Although a considerable number of proteins operate as multiprotein complexes and not on their own, organism-wide studies so far are only able to quantify individual proteins or protein-coding genes in a condition-specific manner for a sizeable number of samples, but not their assemblies. Consequently, there exist large amounts of transcriptomic data and an increasing amount of data on proteome abundance, but quantitative knowledge on complexomes is missing. This deficiency impedes the applicability of the powerful tool of differential analysis in the realm of macromolecular complexes. Here, we present a pipeline for differential analysis of protein complexes based on predicted or manually assigned complexes and inferred complex abundances, which can be easily applied on a whole-genome scale. RESULTS: We observed for simulated data that results obtained by our complex abundance estimation algorithm were in better agreement with the ground truth and physicochemically more reasonable compared to previous efforts that used linear programming while running in a fraction of the time. The practical usability of the method was assessed in the context of transcription factor complexes in human monocyte and lymphoblastoid samples. We demonstrated that our new method is robust against false-positive detection and reports deregulated complexomes that can only be partially explained by differential analysis of individual protein-coding genes. Furthermore we showed that deregulated complexes identified by the tool potentially harbor significant yet unused information content. CONCLUSIONS: CompleXChange allows to analyze deregulation of the protein complexome on a whole-genome scale by integrating a plethora of input data that is already available. A platform-independent Java binary, a user guide with example data and the source code are freely available at https://sourceforge.net/projects/complexchange/. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12859-019-2852-z) contains supplementary material, which is available to authorized users. BioMed Central 2019-06-03 /pmc/articles/PMC6547514/ /pubmed/31159772 http://dx.doi.org/10.1186/s12859-019-2852-z Text en © The Author(s) 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Software
Will, Thorsten
Helms, Volkhard
Differential analysis of combinatorial protein complexes with CompleXChange
title Differential analysis of combinatorial protein complexes with CompleXChange
title_full Differential analysis of combinatorial protein complexes with CompleXChange
title_fullStr Differential analysis of combinatorial protein complexes with CompleXChange
title_full_unstemmed Differential analysis of combinatorial protein complexes with CompleXChange
title_short Differential analysis of combinatorial protein complexes with CompleXChange
title_sort differential analysis of combinatorial protein complexes with complexchange
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6547514/
https://www.ncbi.nlm.nih.gov/pubmed/31159772
http://dx.doi.org/10.1186/s12859-019-2852-z
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