Cargando…

MAPPI-DAT: data management and analysis for protein–protein interaction data from the high-throughput MAPPIT cell microarray platform

SUMMARY: Protein-protein interaction (PPI) studies have dramatically expanded our knowledge about cellular behaviour and development in different conditions. A multitude of high-throughput PPI techniques have been developed to achieve proteome-scale coverage for PPI studies, including the microarray...

Descripción completa

Detalles Bibliográficos
Autores principales: Gupta, Surya, De Puysseleyr, Veronic, Van der Heyden, José, Maddelein, Davy, Lemmens, Irma, Lievens, Sam, Degroeve, Sven, Tavernier, Jan, Martens, Lennart
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5408788/
https://www.ncbi.nlm.nih.gov/pubmed/28453684
http://dx.doi.org/10.1093/bioinformatics/btx014
_version_ 1783232363792171008
author Gupta, Surya
De Puysseleyr, Veronic
Van der Heyden, José
Maddelein, Davy
Lemmens, Irma
Lievens, Sam
Degroeve, Sven
Tavernier, Jan
Martens, Lennart
author_facet Gupta, Surya
De Puysseleyr, Veronic
Van der Heyden, José
Maddelein, Davy
Lemmens, Irma
Lievens, Sam
Degroeve, Sven
Tavernier, Jan
Martens, Lennart
author_sort Gupta, Surya
collection PubMed
description SUMMARY: Protein-protein interaction (PPI) studies have dramatically expanded our knowledge about cellular behaviour and development in different conditions. A multitude of high-throughput PPI techniques have been developed to achieve proteome-scale coverage for PPI studies, including the microarray based Mammalian Protein-Protein Interaction Trap (MAPPIT) system. Because such high-throughput techniques typically report thousands of interactions, managing and analysing the large amounts of acquired data is a challenge. We have therefore built the MAPPIT cell microArray Protein Protein Interaction-Data management & Analysis Tool (MAPPI-DAT) as an automated data management and analysis tool for MAPPIT cell microarray experiments. MAPPI-DAT stores the experimental data and metadata in a systematic and structured way, automates data analysis and interpretation, and enables the meta-analysis of MAPPIT cell microarray data across all stored experiments. AVAILABILITY AND IMPLEMENTATION: MAPPI-DAT is developed in Python, using R for data analysis and MySQL as data management system. MAPPI-DAT is cross-platform and can be ran on Microsoft Windows, Linux and OS X/macOS. The source code and a Microsoft Windows executable are freely available under the permissive Apache2 open source license at https://github.com/compomics/MAPPI-DAT. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
format Online
Article
Text
id pubmed-5408788
institution National Center for Biotechnology Information
language English
publishDate 2017
publisher Oxford University Press
record_format MEDLINE/PubMed
spelling pubmed-54087882017-05-03 MAPPI-DAT: data management and analysis for protein–protein interaction data from the high-throughput MAPPIT cell microarray platform Gupta, Surya De Puysseleyr, Veronic Van der Heyden, José Maddelein, Davy Lemmens, Irma Lievens, Sam Degroeve, Sven Tavernier, Jan Martens, Lennart Bioinformatics Applications Notes SUMMARY: Protein-protein interaction (PPI) studies have dramatically expanded our knowledge about cellular behaviour and development in different conditions. A multitude of high-throughput PPI techniques have been developed to achieve proteome-scale coverage for PPI studies, including the microarray based Mammalian Protein-Protein Interaction Trap (MAPPIT) system. Because such high-throughput techniques typically report thousands of interactions, managing and analysing the large amounts of acquired data is a challenge. We have therefore built the MAPPIT cell microArray Protein Protein Interaction-Data management & Analysis Tool (MAPPI-DAT) as an automated data management and analysis tool for MAPPIT cell microarray experiments. MAPPI-DAT stores the experimental data and metadata in a systematic and structured way, automates data analysis and interpretation, and enables the meta-analysis of MAPPIT cell microarray data across all stored experiments. AVAILABILITY AND IMPLEMENTATION: MAPPI-DAT is developed in Python, using R for data analysis and MySQL as data management system. MAPPI-DAT is cross-platform and can be ran on Microsoft Windows, Linux and OS X/macOS. The source code and a Microsoft Windows executable are freely available under the permissive Apache2 open source license at https://github.com/compomics/MAPPI-DAT. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2017-05-01 2017-01-17 /pmc/articles/PMC5408788/ /pubmed/28453684 http://dx.doi.org/10.1093/bioinformatics/btx014 Text en © The Author 2017. Published by Oxford University Press. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Applications Notes
Gupta, Surya
De Puysseleyr, Veronic
Van der Heyden, José
Maddelein, Davy
Lemmens, Irma
Lievens, Sam
Degroeve, Sven
Tavernier, Jan
Martens, Lennart
MAPPI-DAT: data management and analysis for protein–protein interaction data from the high-throughput MAPPIT cell microarray platform
title MAPPI-DAT: data management and analysis for protein–protein interaction data from the high-throughput MAPPIT cell microarray platform
title_full MAPPI-DAT: data management and analysis for protein–protein interaction data from the high-throughput MAPPIT cell microarray platform
title_fullStr MAPPI-DAT: data management and analysis for protein–protein interaction data from the high-throughput MAPPIT cell microarray platform
title_full_unstemmed MAPPI-DAT: data management and analysis for protein–protein interaction data from the high-throughput MAPPIT cell microarray platform
title_short MAPPI-DAT: data management and analysis for protein–protein interaction data from the high-throughput MAPPIT cell microarray platform
title_sort mappi-dat: data management and analysis for protein–protein interaction data from the high-throughput mappit cell microarray platform
topic Applications Notes
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5408788/
https://www.ncbi.nlm.nih.gov/pubmed/28453684
http://dx.doi.org/10.1093/bioinformatics/btx014
work_keys_str_mv AT guptasurya mappidatdatamanagementandanalysisforproteinproteininteractiondatafromthehighthroughputmappitcellmicroarrayplatform
AT depuysseleyrveronic mappidatdatamanagementandanalysisforproteinproteininteractiondatafromthehighthroughputmappitcellmicroarrayplatform
AT vanderheydenjose mappidatdatamanagementandanalysisforproteinproteininteractiondatafromthehighthroughputmappitcellmicroarrayplatform
AT maddeleindavy mappidatdatamanagementandanalysisforproteinproteininteractiondatafromthehighthroughputmappitcellmicroarrayplatform
AT lemmensirma mappidatdatamanagementandanalysisforproteinproteininteractiondatafromthehighthroughputmappitcellmicroarrayplatform
AT lievenssam mappidatdatamanagementandanalysisforproteinproteininteractiondatafromthehighthroughputmappitcellmicroarrayplatform
AT degroevesven mappidatdatamanagementandanalysisforproteinproteininteractiondatafromthehighthroughputmappitcellmicroarrayplatform
AT tavernierjan mappidatdatamanagementandanalysisforproteinproteininteractiondatafromthehighthroughputmappitcellmicroarrayplatform
AT martenslennart mappidatdatamanagementandanalysisforproteinproteininteractiondatafromthehighthroughputmappitcellmicroarrayplatform