Loading…

affyPara - a Bioconductor Package for Parallelized Preprocessing Algorithms of Affymetrix Microarray Data

Markus Schmidberger, Esmeralda Vicedo and Ulrich MansmannDivision of Biometrics and Bioinformatics, IBE, University of Munich, 81377 Munich, Germany. AbstractMicroarray data repositories as well as large clinical applications of gene expression allow to analyse several hundreds of microarrays at one...

Full description

Saved in:
Bibliographic Details
Published in:Bioinformatics and biology insights 2009, Vol.2009 (3), p.BBI.S3060-87
Main Authors: Schmidberger, Markus, Vicedo, Esmeralda, Mansmann, Ulrich
Format: Article
Language:English
Subjects:
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by cdi_FETCH-LOGICAL-c3700-fc6314f2965c43b5828b7eb78e4174d8e0abc7b370c0182b322d49d85d6210c73
cites cdi_FETCH-LOGICAL-c3700-fc6314f2965c43b5828b7eb78e4174d8e0abc7b370c0182b322d49d85d6210c73
container_end_page 87
container_issue 3
container_start_page BBI.S3060
container_title Bioinformatics and biology insights
container_volume 2009
creator Schmidberger, Markus
Vicedo, Esmeralda
Mansmann, Ulrich
description Markus Schmidberger, Esmeralda Vicedo and Ulrich MansmannDivision of Biometrics and Bioinformatics, IBE, University of Munich, 81377 Munich, Germany. AbstractMicroarray data repositories as well as large clinical applications of gene expression allow to analyse several hundreds of microarrays at one time. The preprocessing of large amounts of microarrays is still a challenge. The algorithms are limited by the available computer hardware. For example, building classification or prognostic rules from large microarray sets will be very time consuming. Here, preprocessing has to be a part of the cross-validation and resampling strategy which is necessary to estimate the rule's prediction quality honestly. This paper proposes the new Bioconductor package affyPara for parallelized preprocessing of Affymetrix microarray data. Partition of data can be applied on arrays and parallelization of algorithms is a straightforward consequence. The partition of data and distribution to several nodes solves the main memory problems and accelerates preprocessing by up to the factor 20 for 200 or more arrays. affyPara is a free and open source package, under GPL license, available form the Bioconductor project at www.bioconductor.org. A user guide and examples are provided with the package.
doi_str_mv 10.4137/BBI.S3060
format article
fullrecord <record><control><sourceid>gale_doaj_</sourceid><recordid>TN_cdi_doaj_primary_oai_doaj_org_article_73dfc37aa1df407aa1a9caf2057314d6</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><galeid>A295551690</galeid><sage_id>10.4137_BBI.S3060</sage_id><doaj_id>oai_doaj_org_article_73dfc37aa1df407aa1a9caf2057314d6</doaj_id><sourcerecordid>A295551690</sourcerecordid><originalsourceid>FETCH-LOGICAL-c3700-fc6314f2965c43b5828b7eb78e4174d8e0abc7b370c0182b322d49d85d6210c73</originalsourceid><addsrcrecordid>eNptUU1r3DAQNaGBpmkP_Qc6FXrwVrIsyb4EdtOkXUjJQtKzGOvD0cZehZED3f76KOtQ2hJ0mGH05s3Me0XxkdFFzbj6slqtFzecSnpUnDCmVNnyqnrzV_62eJfSllLJGiVPigDe7zeAQEoCZBWiiTv7aKaIZAPmHnpH_CFHGAY3hN_Okg26B4zGpRR2PVkOfcQw3Y2JRE-WmW50E4Zf5EcwGAER9uQrTPC-OPYwJPfhJZ4WPy8vbs-_l1fX39bny6vScEVp6Y3krPZVK4WpeSeaqumU61TjaqZq2zgKnVFdxhrKmqrLJ9m6tY2wsmLUKH5arGdeG2GrHzCMgHsdIehDIWKvAadgBqcVtz5PBWDW1_Q5QmvAV1SovIOVmWsxc_WQ4WHn44Rg8rNuDFkp50OuL6tWCMFkS3PD57khn54SOv9nAUb1s0E6G6QPBmXspxmbssp6Gx9xl3V5FXg2A4fQOZwgvSwA_1z336cBbeKomRCSPwE_t6ZE</addsrcrecordid><sourcetype>Open Website</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype></control><display><type>article</type><title>affyPara - a Bioconductor Package for Parallelized Preprocessing Algorithms of Affymetrix Microarray Data</title><source>SAGE Open Access</source><source>Publicly Available Content Database</source><source>PubMed Central</source><creator>Schmidberger, Markus ; Vicedo, Esmeralda ; Mansmann, Ulrich</creator><creatorcontrib>Schmidberger, Markus ; Vicedo, Esmeralda ; Mansmann, Ulrich</creatorcontrib><description>Markus Schmidberger, Esmeralda Vicedo and Ulrich MansmannDivision of Biometrics and Bioinformatics, IBE, University of Munich, 81377 Munich, Germany. AbstractMicroarray data repositories as well as large clinical applications of gene expression allow to analyse several hundreds of microarrays at one time. The preprocessing of large amounts of microarrays is still a challenge. The algorithms are limited by the available computer hardware. For example, building classification or prognostic rules from large microarray sets will be very time consuming. Here, preprocessing has to be a part of the cross-validation and resampling strategy which is necessary to estimate the rule's prediction quality honestly. This paper proposes the new Bioconductor package affyPara for parallelized preprocessing of Affymetrix microarray data. Partition of data can be applied on arrays and parallelization of algorithms is a straightforward consequence. The partition of data and distribution to several nodes solves the main memory problems and accelerates preprocessing by up to the factor 20 for 200 or more arrays. affyPara is a free and open source package, under GPL license, available form the Bioconductor project at www.bioconductor.org. A user guide and examples are provided with the package.</description><identifier>ISSN: 1177-9322</identifier><identifier>EISSN: 1177-9322</identifier><identifier>DOI: 10.4137/BBI.S3060</identifier><language>eng</language><publisher>London, England: SAGE Publishing</publisher><subject>Algorithms</subject><ispartof>Bioinformatics and biology insights, 2009, Vol.2009 (3), p.BBI.S3060-87</ispartof><rights>2009 SAGE Publications.</rights><rights>COPYRIGHT 2009 Sage Publications Ltd. (UK)</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3700-fc6314f2965c43b5828b7eb78e4174d8e0abc7b370c0182b322d49d85d6210c73</citedby><cites>FETCH-LOGICAL-c3700-fc6314f2965c43b5828b7eb78e4174d8e0abc7b370c0182b322d49d85d6210c73</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://journals.sagepub.com/doi/pdf/10.4137/BBI.S3060$$EPDF$$P50$$Gsage$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://journals.sagepub.com/doi/10.4137/BBI.S3060$$EHTML$$P50$$Gsage$$Hfree_for_read</linktohtml><link.rule.ids>314,780,784,4022,21965,27852,27922,27923,27924,44944,45332</link.rule.ids></links><search><creatorcontrib>Schmidberger, Markus</creatorcontrib><creatorcontrib>Vicedo, Esmeralda</creatorcontrib><creatorcontrib>Mansmann, Ulrich</creatorcontrib><title>affyPara - a Bioconductor Package for Parallelized Preprocessing Algorithms of Affymetrix Microarray Data</title><title>Bioinformatics and biology insights</title><description>Markus Schmidberger, Esmeralda Vicedo and Ulrich MansmannDivision of Biometrics and Bioinformatics, IBE, University of Munich, 81377 Munich, Germany. AbstractMicroarray data repositories as well as large clinical applications of gene expression allow to analyse several hundreds of microarrays at one time. The preprocessing of large amounts of microarrays is still a challenge. The algorithms are limited by the available computer hardware. For example, building classification or prognostic rules from large microarray sets will be very time consuming. Here, preprocessing has to be a part of the cross-validation and resampling strategy which is necessary to estimate the rule's prediction quality honestly. This paper proposes the new Bioconductor package affyPara for parallelized preprocessing of Affymetrix microarray data. Partition of data can be applied on arrays and parallelization of algorithms is a straightforward consequence. The partition of data and distribution to several nodes solves the main memory problems and accelerates preprocessing by up to the factor 20 for 200 or more arrays. affyPara is a free and open source package, under GPL license, available form the Bioconductor project at www.bioconductor.org. A user guide and examples are provided with the package.</description><subject>Algorithms</subject><issn>1177-9322</issn><issn>1177-9322</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2009</creationdate><recordtype>article</recordtype><sourceid>AFRWT</sourceid><sourceid>DOA</sourceid><recordid>eNptUU1r3DAQNaGBpmkP_Qc6FXrwVrIsyb4EdtOkXUjJQtKzGOvD0cZehZED3f76KOtQ2hJ0mGH05s3Me0XxkdFFzbj6slqtFzecSnpUnDCmVNnyqnrzV_62eJfSllLJGiVPigDe7zeAQEoCZBWiiTv7aKaIZAPmHnpH_CFHGAY3hN_Okg26B4zGpRR2PVkOfcQw3Y2JRE-WmW50E4Zf5EcwGAER9uQrTPC-OPYwJPfhJZ4WPy8vbs-_l1fX39bny6vScEVp6Y3krPZVK4WpeSeaqumU61TjaqZq2zgKnVFdxhrKmqrLJ9m6tY2wsmLUKH5arGdeG2GrHzCMgHsdIehDIWKvAadgBqcVtz5PBWDW1_Q5QmvAV1SovIOVmWsxc_WQ4WHn44Rg8rNuDFkp50OuL6tWCMFkS3PD57khn54SOv9nAUb1s0E6G6QPBmXspxmbssp6Gx9xl3V5FXg2A4fQOZwgvSwA_1z336cBbeKomRCSPwE_t6ZE</recordid><startdate>2009</startdate><enddate>2009</enddate><creator>Schmidberger, Markus</creator><creator>Vicedo, Esmeralda</creator><creator>Mansmann, Ulrich</creator><general>SAGE Publishing</general><general>SAGE Publications</general><general>Sage Publications Ltd. (UK)</general><scope>AFRWT</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>DOA</scope></search><sort><creationdate>2009</creationdate><title>affyPara - a Bioconductor Package for Parallelized Preprocessing Algorithms of Affymetrix Microarray Data</title><author>Schmidberger, Markus ; Vicedo, Esmeralda ; Mansmann, Ulrich</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3700-fc6314f2965c43b5828b7eb78e4174d8e0abc7b370c0182b322d49d85d6210c73</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2009</creationdate><topic>Algorithms</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Schmidberger, Markus</creatorcontrib><creatorcontrib>Vicedo, Esmeralda</creatorcontrib><creatorcontrib>Mansmann, Ulrich</creatorcontrib><collection>SAGE Open Access</collection><collection>CrossRef</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>Bioinformatics and biology insights</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Schmidberger, Markus</au><au>Vicedo, Esmeralda</au><au>Mansmann, Ulrich</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>affyPara - a Bioconductor Package for Parallelized Preprocessing Algorithms of Affymetrix Microarray Data</atitle><jtitle>Bioinformatics and biology insights</jtitle><date>2009</date><risdate>2009</risdate><volume>2009</volume><issue>3</issue><spage>BBI.S3060</spage><epage>87</epage><pages>BBI.S3060-87</pages><issn>1177-9322</issn><eissn>1177-9322</eissn><abstract>Markus Schmidberger, Esmeralda Vicedo and Ulrich MansmannDivision of Biometrics and Bioinformatics, IBE, University of Munich, 81377 Munich, Germany. AbstractMicroarray data repositories as well as large clinical applications of gene expression allow to analyse several hundreds of microarrays at one time. The preprocessing of large amounts of microarrays is still a challenge. The algorithms are limited by the available computer hardware. For example, building classification or prognostic rules from large microarray sets will be very time consuming. Here, preprocessing has to be a part of the cross-validation and resampling strategy which is necessary to estimate the rule's prediction quality honestly. This paper proposes the new Bioconductor package affyPara for parallelized preprocessing of Affymetrix microarray data. Partition of data can be applied on arrays and parallelization of algorithms is a straightforward consequence. The partition of data and distribution to several nodes solves the main memory problems and accelerates preprocessing by up to the factor 20 for 200 or more arrays. affyPara is a free and open source package, under GPL license, available form the Bioconductor project at www.bioconductor.org. A user guide and examples are provided with the package.</abstract><cop>London, England</cop><pub>SAGE Publishing</pub><doi>10.4137/BBI.S3060</doi><tpages>5</tpages><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 1177-9322
ispartof Bioinformatics and biology insights, 2009, Vol.2009 (3), p.BBI.S3060-87
issn 1177-9322
1177-9322
language eng
recordid cdi_doaj_primary_oai_doaj_org_article_73dfc37aa1df407aa1a9caf2057314d6
source SAGE Open Access; Publicly Available Content Database; PubMed Central
subjects Algorithms
title affyPara - a Bioconductor Package for Parallelized Preprocessing Algorithms of Affymetrix Microarray Data
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-11T14%3A51%3A53IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_doaj_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=affyPara%20-%20a%20Bioconductor%20Package%20for%20Parallelized%20Preprocessing%20Algorithms%20of%20Affymetrix%20Microarray%20Data&rft.jtitle=Bioinformatics%20and%20biology%20insights&rft.au=Schmidberger,%20Markus&rft.date=2009&rft.volume=2009&rft.issue=3&rft.spage=BBI.S3060&rft.epage=87&rft.pages=BBI.S3060-87&rft.issn=1177-9322&rft.eissn=1177-9322&rft_id=info:doi/10.4137/BBI.S3060&rft_dat=%3Cgale_doaj_%3EA295551690%3C/gale_doaj_%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c3700-fc6314f2965c43b5828b7eb78e4174d8e0abc7b370c0182b322d49d85d6210c73%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_id=info:pmid/&rft_galeid=A295551690&rft_sage_id=10.4137_BBI.S3060&rfr_iscdi=true