Unlocking the potential of publicly available microarray data using inSilicoDb and inSilicoMerging R/Bioconductor packages

Background With an abundant amount of microarray gene expression data sets available through public repositories, new possibilities lie in combining multiple existing data sets. In this new context, analysis itself is no longer the problem, but retrieving and consistently integrating all this data b...

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Veröffentlicht in:BMC bioinformatics Jg. 13; H. 1; S. 335
Hauptverfasser: Taminau, Jonatan, Meganck, Stijn, Lazar, Cosmin, Steenhoff, David, Coletta, Alain, Molter, Colin, Duque, Robin, Schaetzen, Virginie de, Weiss Solís, David Y, Bersini, Hugues, Nowé, Ann
Format: Journal Article
Sprache:Englisch
Veröffentlicht: London BioMed Central 24.12.2012
BioMed Central Ltd
Springer Nature B.V
BMC
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ISSN:1471-2105, 1471-2105
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Abstract Background With an abundant amount of microarray gene expression data sets available through public repositories, new possibilities lie in combining multiple existing data sets. In this new context, analysis itself is no longer the problem, but retrieving and consistently integrating all this data before delivering it to the wide variety of existing analysis tools becomes the new bottleneck. Results We present the newly released inSilicoMerging R/Bioconductor package which, together with the earlier released inSilicoDb R/Bioconductor package, allows consistent retrieval, integration and analysis of publicly available microarray gene expression data sets. Inside the inSilicoMerging package a set of five visual and six quantitative validation measures are available as well. Conclusions By providing (i) access to uniformly curated and preprocessed data, (ii) a collection of techniques to remove the batch effects between data sets from different sources, and (iii) several validation tools enabling the inspection of the integration process, these packages enable researchers to fully explore the potential of combining gene expression data for downstream analysis. The power of using both packages is demonstrated by programmatically retrieving and integrating gene expression studies from the InSilico DB repository [ https://insilicodb.org/app/ ].
AbstractList With an abundant amount of microarray gene expression data sets available through public repositories, new possibilities lie in combining multiple existing data sets. In this new context, analysis itself is no longer the problem, but retrieving and consistently integrating all this data before delivering it to the wide variety of existing analysis tools becomes the new bottleneck. We present the newly released inSilicoMerging R/Bioconductor package which, together with the earlier released inSilicoDb R/Bioconductor package, allows consistent retrieval, integration and analysis of publicly available microarray gene expression data sets. Inside the inSilicoMerging package a set of five visual and six quantitative validation measures are available as well. By providing (i) access to uniformly curated and preprocessed data, (ii) a collection of techniques to remove the batch effects between data sets from different sources, and (iii) several validation tools enabling the inspection of the integration process, these packages enable researchers to fully explore the potential of combining gene expression data for downstream analysis. The power of using both packages is demonstrated by programmatically retrieving and integrating gene expression studies from the InSilico DB repository [https://insilicodb.org/app/].
Background With an abundant amount of microarray gene expression data sets available through public repositories, new possibilities lie in combining multiple existing data sets. In this new context, analysis itself is no longer the problem, but retrieving and consistently integrating all this data before delivering it to the wide variety of existing analysis tools becomes the new bottleneck. Results We present the newly released inSilicoMerging R/Bioconductor package which, together with the earlier released inSilicoDb R/Bioconductor package, allows consistent retrieval, integration and analysis of publicly available microarray gene expression data sets. Inside the inSilicoMerging package a set of five visual and six quantitative validation measures are available as well. Conclusions By providing (i) access to uniformly curated and preprocessed data, (ii) a collection of techniques to remove the batch effects between data sets from different sources, and (iii) several validation tools enabling the inspection of the integration process, these packages enable researchers to fully explore the potential of combining gene expression data for downstream analysis. The power of using both packages is demonstrated by programmatically retrieving and integrating gene expression studies from the InSilico DB repository [ Keywords: Batch effect removal, Data integration, Gene expression, Microarray repositories, InSilico DB, Reproducibility
With an abundant amount of microarray gene expression data sets available through public repositories, new possibilities lie in combining multiple existing data sets. In this new context, analysis itself is no longer the problem, but retrieving and consistently integrating all this data before delivering it to the wide variety of existing analysis tools becomes the new bottleneck. We present the newly released inSilicoMerging R/Bioconductor package which, together with the earlier released inSilicoDb R/Bioconductor package, allows consistent retrieval, integration and analysis of publicly available microarray gene expression data sets. Inside the inSilicoMerging package a set of five visual and six quantitative validation measures are available as well. By providing (i) access to uniformly curated and preprocessed data, (ii) a collection of techniques to remove the batch effects between data sets from different sources, and (iii) several validation tools enabling the inspection of the integration process, these packages enable researchers to fully explore the potential of combining gene expression data for downstream analysis. The power of using both packages is demonstrated by programmatically retrieving and integrating gene expression studies from the InSilico DB repository [https://insilicodb.org/app/].
With an abundant amount of microarray gene expression data sets available through public repositories, new possibilities lie in combining multiple existing data sets. In this new context, analysis itself is no longer the problem, but retrieving and consistently integrating all this data before delivering it to the wide variety of existing analysis tools becomes the new bottleneck.BACKGROUNDWith an abundant amount of microarray gene expression data sets available through public repositories, new possibilities lie in combining multiple existing data sets. In this new context, analysis itself is no longer the problem, but retrieving and consistently integrating all this data before delivering it to the wide variety of existing analysis tools becomes the new bottleneck.We present the newly released inSilicoMerging R/Bioconductor package which, together with the earlier released inSilicoDb R/Bioconductor package, allows consistent retrieval, integration and analysis of publicly available microarray gene expression data sets. Inside the inSilicoMerging package a set of five visual and six quantitative validation measures are available as well.RESULTSWe present the newly released inSilicoMerging R/Bioconductor package which, together with the earlier released inSilicoDb R/Bioconductor package, allows consistent retrieval, integration and analysis of publicly available microarray gene expression data sets. Inside the inSilicoMerging package a set of five visual and six quantitative validation measures are available as well.By providing (i) access to uniformly curated and preprocessed data, (ii) a collection of techniques to remove the batch effects between data sets from different sources, and (iii) several validation tools enabling the inspection of the integration process, these packages enable researchers to fully explore the potential of combining gene expression data for downstream analysis. The power of using both packages is demonstrated by programmatically retrieving and integrating gene expression studies from the InSilico DB repository [https://insilicodb.org/app/].CONCLUSIONSBy providing (i) access to uniformly curated and preprocessed data, (ii) a collection of techniques to remove the batch effects between data sets from different sources, and (iii) several validation tools enabling the inspection of the integration process, these packages enable researchers to fully explore the potential of combining gene expression data for downstream analysis. The power of using both packages is demonstrated by programmatically retrieving and integrating gene expression studies from the InSilico DB repository [https://insilicodb.org/app/].
Doc number: 335 Abstract Background: With an abundant amount of microarray gene expression data sets available through public repositories, new possibilities lie in combining multiple existing data sets. In this new context, analysis itself is no longer the problem, but retrieving and consistently integrating all this data before delivering it to the wide variety of existing analysis tools becomes the new bottleneck. Results: We present the newly released inSilicoMerging R/Bioconductor package which, together with the earlier released inSilicoDb R/Bioconductor package, allows consistent retrieval, integration and analysis of publicly available microarray gene expression data sets. Inside the inSilicoMerging package a set of five visual and six quantitative validation measures are available as well. Conclusions: By providing (i) access to uniformly curated and preprocessed data, (ii) a collection of techniques to remove the batch effects between data sets from different sources, and (iii) several validation tools enabling the inspection of the integration process, these packages enable researchers to fully explore the potential of combining gene expression data for downstream analysis. The power of using both packages is demonstrated by programmatically retrieving and integrating gene expression studies from the InSilico DB repository [https://insilicodb.org/app/ ].
Background: With an abundant amount of microarray gene expression data sets available through public repositories, new possibilities lie in combining multiple existing data sets. In this new context, analysis itself is no longer the problem, but retrieving and consistently integrating all this data before delivering it to the wide variety of existing analysis tools becomes the new bottleneck. Results: We present the newly released inSilicoMerging R/Bioconductor package which, together with the earlier released inSilicoDb R/Bioconductor package, allows consistent retrieval, integration and analysis of publicly available microarray gene expression data sets. Inside the inSilicoMerging package a set of five visual and six quantitative validation measures are available as well. Conclusions: By providing (i) access to uniformly curated and preprocessed data, (ii) a collection of techniques to remove the batch effects between data sets from different sources, and (iii) several validation tools enabling the inspection of the integration process, these packages enable researchers to fully explore the potential of combining gene expression data for downstream analysis. The power of using both packages is demonstrated by programmatically retrieving and integrating gene expression studies from the InSilico DB repository [ https://insilicodb.org/app/ ].
Abstract Background With an abundant amount of microarray gene expression data sets available through public repositories, new possibilities lie in combining multiple existing data sets. In this new context, analysis itself is no longer the problem, but retrieving and consistently integrating all this data before delivering it to the wide variety of existing analysis tools becomes the new bottleneck. Results We present the newly released inSilicoMerging R/Bioconductor package which, together with the earlier released inSilicoDb R/Bioconductor package, allows consistent retrieval, integration and analysis of publicly available microarray gene expression data sets. Inside the inSilicoMerging package a set of five visual and six quantitative validation measures are available as well. Conclusions By providing (i) access to uniformly curated and preprocessed data, (ii) a collection of techniques to remove the batch effects between data sets from different sources, and (iii) several validation tools enabling the inspection of the integration process, these packages enable researchers to fully explore the potential of combining gene expression data for downstream analysis. The power of using both packages is demonstrated by programmatically retrieving and integrating gene expression studies from the InSilico DB repository [https://insilicodb.org/app/].
Background With an abundant amount of microarray gene expression data sets available through public repositories, new possibilities lie in combining multiple existing data sets. In this new context, analysis itself is no longer the problem, but retrieving and consistently integrating all this data before delivering it to the wide variety of existing analysis tools becomes the new bottleneck. Results We present the newly released inSilicoMerging R/Bioconductor package which, together with the earlier released inSilicoDb R/Bioconductor package, allows consistent retrieval, integration and analysis of publicly available microarray gene expression data sets. Inside the inSilicoMerging package a set of five visual and six quantitative validation measures are available as well. Conclusions By providing (i) access to uniformly curated and preprocessed data, (ii) a collection of techniques to remove the batch effects between data sets from different sources, and (iii) several validation tools enabling the inspection of the integration process, these packages enable researchers to fully explore the potential of combining gene expression data for downstream analysis. The power of using both packages is demonstrated by programmatically retrieving and integrating gene expression studies from the InSilico DB repository [ https://insilicodb.org/app/ ].
ArticleNumber 335
Audience Academic
Author Weiss Solís, David Y
Molter, Colin
Bersini, Hugues
Meganck, Stijn
Duque, Robin
Lazar, Cosmin
Steenhoff, David
Schaetzen, Virginie de
Taminau, Jonatan
Coletta, Alain
Nowé, Ann
AuthorAffiliation 1 AI (CoMo), Vrije Universiteit Brussel, 1050 Brussels, Pleinlaan 2, Belgium
2 IRIDIA, Université Libre de Bruxelles, Avenue F. D. Roosevelt 50, 1050 Brussels, Belgium
AuthorAffiliation_xml – name: 1 AI (CoMo), Vrije Universiteit Brussel, 1050 Brussels, Pleinlaan 2, Belgium
– name: 2 IRIDIA, Université Libre de Bruxelles, Avenue F. D. Roosevelt 50, 1050 Brussels, Belgium
Author_xml – sequence: 1
  givenname: Jonatan
  surname: Taminau
  fullname: Taminau, Jonatan
  email: jtaminau@vub.ac.be
  organization: AI (CoMo), Vrije Universiteit Brussel
– sequence: 2
  givenname: Stijn
  surname: Meganck
  fullname: Meganck, Stijn
  organization: AI (CoMo), Vrije Universiteit Brussel
– sequence: 3
  givenname: Cosmin
  surname: Lazar
  fullname: Lazar, Cosmin
  organization: AI (CoMo), Vrije Universiteit Brussel
– sequence: 4
  givenname: David
  surname: Steenhoff
  fullname: Steenhoff, David
  organization: AI (CoMo), Vrije Universiteit Brussel
– sequence: 5
  givenname: Alain
  surname: Coletta
  fullname: Coletta, Alain
  organization: IRIDIA, Université Libre de Bruxelles
– sequence: 6
  givenname: Colin
  surname: Molter
  fullname: Molter, Colin
  organization: IRIDIA, Université Libre de Bruxelles
– sequence: 7
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  surname: Duque
  fullname: Duque, Robin
  organization: IRIDIA, Université Libre de Bruxelles
– sequence: 8
  givenname: Virginie de
  surname: Schaetzen
  fullname: Schaetzen, Virginie de
  organization: AI (CoMo), Vrije Universiteit Brussel
– sequence: 9
  givenname: David Y
  surname: Weiss Solís
  fullname: Weiss Solís, David Y
  organization: IRIDIA, Université Libre de Bruxelles
– sequence: 10
  givenname: Hugues
  surname: Bersini
  fullname: Bersini, Hugues
  organization: IRIDIA, Université Libre de Bruxelles
– sequence: 11
  givenname: Ann
  surname: Nowé
  fullname: Nowé, Ann
  organization: AI (CoMo), Vrije Universiteit Brussel
BackLink https://www.ncbi.nlm.nih.gov/pubmed/23259851$$D View this record in MEDLINE/PubMed
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Cites_doi 10.1093/nar/gkq1040
10.1093/bioinformatics/btm254
10.1038/nbt1106-1322
10.1186/gb-2012-13-11-r104
10.1214/aoms/1177704472
10.2144/04362MT04
10.1158/1078-0432.565.11.2
10.1093/bioinformatics/btn083
10.1186/1471-2105-6-214
10.1111/j.1365-2141.2004.05017.x
10.1186/1471-2105-12-467
10.1093/biostatistics/kxp059
10.1186/1755-8794-1-42
10.1289/ehp.6787
10.1186/1471-2105-3-4
10.1093/nar/gkq1184
10.1198/004017008000000334
10.1093/bioinformatics/btr529
10.1186/gb-2004-5-10-r80
10.1093/bioinformatics/btg385
10.1093/nar/30.1.207
10.1002/9780470685983
10.1093/bioinformatics/bts096
10.1093/gerona/59.4.B306
10.1038/nrg2825
10.1093/biostatistics/kxj037
ContentType Journal Article
Copyright Taminau et al.; licensee BioMed Central Ltd. 2012
COPYRIGHT 2012 BioMed Central Ltd.
2012 Taminau et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License(http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright ©2012 Taminau et al.; licensee BioMed Central Ltd. 2012 Taminau et al.; licensee BioMed Central Ltd.
Copyright_xml – notice: Taminau et al.; licensee BioMed Central Ltd. 2012
– notice: COPYRIGHT 2012 BioMed Central Ltd.
– notice: 2012 Taminau et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License(http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
– notice: Copyright ©2012 Taminau et al.; licensee BioMed Central Ltd. 2012 Taminau et al.; licensee BioMed Central Ltd.
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Keywords Microarray repositories
Gene expression
Reproducibility
Data integration
Batch effect removal
InSilico DB
Language English
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References A Sims (5651_CR21) 2008; 1
TM Chu (5651_CR8) 2004; 112
M Bakay (5651_CR13) 2002; 3
M Benito (5651_CR17) 2004; 20
A Coletta (5651_CR6) 2012; 13
J Brettschneider (5651_CR24) 2008; 50
T Barrett (5651_CR2) 2011; 39
ES Han (5651_CR11) 2004; 59
J Rudy (5651_CR28) 2011; 12
H Parkinson (5651_CR3) 2011; 39
H Huang (5651_CR23) 2012; 28
S Zakharkin (5651_CR10) 2005; 6
O Larsson (5651_CR4) 2006; 24
R Edgar (5651_CR1) 2002; 30
5651_CR12
AH Sims (5651_CR16) 2008; 1
A (Ed) Scherer (5651_CR7) 2009
AA Shabalin (5651_CR19) 2008; 24
C Lazar (5651_CR22) 2012
JS Brown (5651_CR14) 2004; 36
JT Leek (5651_CR15) 2010; 11
WE Johnson (5651_CR18) 2007; 8
MN McCall (5651_CR26) 2010; 11
E Parzen (5651_CR25) 1962; 33
J Taminau (5651_CR5) 2011; 27
RC Gentleman (5651_CR20) 2004; 5
KK Dobbin (5651_CR9) 2005; 11
D Sean (5651_CR27) 2007; 23
15701842 - Clin Cancer Res. 2005 Jan 15;11(2 Pt 1):565-72
20097884 - Biostatistics. 2010 Apr;11(2):242-53
15033594 - Environ Health Perspect. 2004 Mar;112(4):449-55
22151536 - BMC Bioinformatics. 2011;12:467
15461798 - Genome Biol. 2004;5(10):R80
22368246 - Bioinformatics. 2012 Apr 15;28(8):1182-3
22851511 - Brief Bioinform. 2013 Jul;14(4):469-90
16124883 - BMC Bioinformatics. 2005;6:214
21937664 - Bioinformatics. 2011 Nov 15;27(22):3204-5
17496320 - Bioinformatics. 2007 Jul 15;23(14):1846-7
20838408 - Nat Rev Genet. 2010 Oct;11(10):733-9
16632515 - Biostatistics. 2007 Jan;8(1):118-27
17093466 - Nat Biotechnol. 2006 Nov;24(11):1322-3
15238145 - Br J Haematol. 2004 Jul;126(2):231-43
18325927 - Bioinformatics. 2008 May 1;24(9):1154-60
15071073 - J Gerontol A Biol Sci Med Sci. 2004 Apr;59(4):306-15
14693816 - Bioinformatics. 2004 Jan 1;20(1):105-14
23158523 - Genome Biol. 2012;13(11):R104
21071405 - Nucleic Acids Res. 2011 Jan;39(Database issue):D1002-4
21097893 - Nucleic Acids Res. 2011 Jan;39(Database issue):D1005-10
11752295 - Nucleic Acids Res. 2002 Jan 1;30(1):207-10
18803878 - BMC Med Genomics. 2008 Sep 21;1:42
14989098 - Biotechniques. 2004 Feb;36(2):324-32
11936955 - BMC Bioinformatics. 2002;3:4
References_xml – volume: 39
  start-page: D1002
  issue: Database issue
  year: 2011
  ident: 5651_CR3
  publication-title: Nucleic Acids Res
  doi: 10.1093/nar/gkq1040
– volume: 23
  start-page: 1846
  issue: 14
  year: 2007
  ident: 5651_CR27
  publication-title: Bioinformatics
  doi: 10.1093/bioinformatics/btm254
– volume: 24
  start-page: 1322
  issue: 11
  year: 2006
  ident: 5651_CR4
  publication-title: Nat Biotechnol
  doi: 10.1038/nbt1106-1322
– volume: 13
  start-page: R104
  issue: 11
  year: 2012
  ident: 5651_CR6
  publication-title: Genome Biol
  doi: 10.1186/gb-2012-13-11-r104
– volume: 33
  start-page: 1065
  issue: 3
  year: 1962
  ident: 5651_CR25
  publication-title: The Ann Math Stat
  doi: 10.1214/aoms/1177704472
– volume: 36
  start-page: 324
  year: 2004
  ident: 5651_CR14
  publication-title: Biotechniques
  doi: 10.2144/04362MT04
– volume: 11
  start-page: 565
  issue: 2
  year: 2005
  ident: 5651_CR9
  publication-title: Clinical Cancer Research
  doi: 10.1158/1078-0432.565.11.2
– volume: 24
  start-page: 1154
  issue: 9
  year: 2008
  ident: 5651_CR19
  publication-title: Bioinformatics
  doi: 10.1093/bioinformatics/btn083
– volume: 6
  start-page: 214
  year: 2005
  ident: 5651_CR10
  publication-title: BMC Bioinformatics
  doi: 10.1186/1471-2105-6-214
– ident: 5651_CR12
  doi: 10.1111/j.1365-2141.2004.05017.x
– volume: 12
  start-page: 467
  year: 2011
  ident: 5651_CR28
  publication-title: BMC Bioinformatics
  doi: 10.1186/1471-2105-12-467
– volume: 11
  start-page: 242
  issue: 2
  year: 2010
  ident: 5651_CR26
  publication-title: Biostatistics
  doi: 10.1093/biostatistics/kxp059
– volume: 1
  start-page: 42
  year: 2008
  ident: 5651_CR16
  publication-title: BMC medical genomics
  doi: 10.1186/1755-8794-1-42
– volume: 112
  start-page: 449
  issue: 4
  year: 2004
  ident: 5651_CR8
  publication-title: Environ Health Perspect
  doi: 10.1289/ehp.6787
– volume: 3
  start-page: 4
  year: 2002
  ident: 5651_CR13
  publication-title: BMC Bioinformatics
  doi: 10.1186/1471-2105-3-4
– volume: 1
  start-page: 42
  year: 2008
  ident: 5651_CR21
  publication-title: BMC Medical Genomics
  doi: 10.1186/1755-8794-1-42
– volume: 39
  start-page: D1005
  issue: Database issue
  year: 2011
  ident: 5651_CR2
  publication-title: Nucleic Acids Res
  doi: 10.1093/nar/gkq1184
– volume: 50
  start-page: 241
  issue: 3
  year: 2008
  ident: 5651_CR24
  publication-title: Technometrics
  doi: 10.1198/004017008000000334
– volume: 27
  start-page: 3204
  issue: 22
  year: 2011
  ident: 5651_CR5
  publication-title: Bioinformatics
  doi: 10.1093/bioinformatics/btr529
– volume: 5
  start-page: R80
  issue: 10
  year: 2004
  ident: 5651_CR20
  publication-title: Genome Biol
  doi: 10.1186/gb-2004-5-10-r80
– volume-title: Briefings in Bioinf
  year: 2012
  ident: 5651_CR22
– volume: 20
  start-page: 105
  year: 2004
  ident: 5651_CR17
  publication-title: Bioinformatics
  doi: 10.1093/bioinformatics/btg385
– volume: 30
  start-page: 207
  year: 2002
  ident: 5651_CR1
  publication-title: Nucleic Acids Res
  doi: 10.1093/nar/30.1.207
– volume-title: Batch Effects and Noise in Microarray Experiments: Sources and Solutions
  year: 2009
  ident: 5651_CR7
  doi: 10.1002/9780470685983
– volume: 28
  start-page: 1182
  issue: 8
  year: 2012
  ident: 5651_CR23
  publication-title: Bioinformatics
  doi: 10.1093/bioinformatics/bts096
– volume: 59
  start-page: B306
  issue: 4
  year: 2004
  ident: 5651_CR11
  publication-title: The Journals of Gerontology Series A: Biological Sciences and Medical Sciences
  doi: 10.1093/gerona/59.4.B306
– volume: 11
  start-page: 733
  issue: 10
  year: 2010
  ident: 5651_CR15
  publication-title: Nat Rev Genet
  doi: 10.1038/nrg2825
– volume: 8
  start-page: 118
  year: 2007
  ident: 5651_CR18
  publication-title: Biostatistics
  doi: 10.1093/biostatistics/kxj037
– reference: 20838408 - Nat Rev Genet. 2010 Oct;11(10):733-9
– reference: 20097884 - Biostatistics. 2010 Apr;11(2):242-53
– reference: 22151536 - BMC Bioinformatics. 2011;12:467
– reference: 17496320 - Bioinformatics. 2007 Jul 15;23(14):1846-7
– reference: 15461798 - Genome Biol. 2004;5(10):R80
– reference: 23158523 - Genome Biol. 2012;13(11):R104
– reference: 22368246 - Bioinformatics. 2012 Apr 15;28(8):1182-3
– reference: 15033594 - Environ Health Perspect. 2004 Mar;112(4):449-55
– reference: 11752295 - Nucleic Acids Res. 2002 Jan 1;30(1):207-10
– reference: 17093466 - Nat Biotechnol. 2006 Nov;24(11):1322-3
– reference: 15071073 - J Gerontol A Biol Sci Med Sci. 2004 Apr;59(4):306-15
– reference: 16632515 - Biostatistics. 2007 Jan;8(1):118-27
– reference: 18803878 - BMC Med Genomics. 2008 Sep 21;1:42
– reference: 15701842 - Clin Cancer Res. 2005 Jan 15;11(2 Pt 1):565-72
– reference: 15238145 - Br J Haematol. 2004 Jul;126(2):231-43
– reference: 18325927 - Bioinformatics. 2008 May 1;24(9):1154-60
– reference: 21097893 - Nucleic Acids Res. 2011 Jan;39(Database issue):D1005-10
– reference: 14989098 - Biotechniques. 2004 Feb;36(2):324-32
– reference: 16124883 - BMC Bioinformatics. 2005;6:214
– reference: 21937664 - Bioinformatics. 2011 Nov 15;27(22):3204-5
– reference: 21071405 - Nucleic Acids Res. 2011 Jan;39(Database issue):D1002-4
– reference: 11936955 - BMC Bioinformatics. 2002;3:4
– reference: 22851511 - Brief Bioinform. 2013 Jul;14(4):469-90
– reference: 14693816 - Bioinformatics. 2004 Jan 1;20(1):105-14
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Snippet Background With an abundant amount of microarray gene expression data sets available through public repositories, new possibilities lie in combining multiple...
With an abundant amount of microarray gene expression data sets available through public repositories, new possibilities lie in combining multiple existing...
Background With an abundant amount of microarray gene expression data sets available through public repositories, new possibilities lie in combining multiple...
Doc number: 335 Abstract Background: With an abundant amount of microarray gene expression data sets available through public repositories, new possibilities...
Background: With an abundant amount of microarray gene expression data sets available through public repositories, new possibilities lie in combining multiple...
Abstract Background With an abundant amount of microarray gene expression data sets available through public repositories, new possibilities lie in combining...
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StartPage 335
SubjectTerms Access to Information
Algorithms
Analysis
Anopheles
Batch effect removal
Bioinformatics
Biomedical and Life Sciences
Computational Biology/Bioinformatics
Computer Appl. in Life Sciences
Data integration
Gene expression
Gene Expression Profiling - statistics & numerical data
Genes
Hostages
Humans
InSilico DB
Life Sciences
Microarray repositories
Microarrays
Oligonucleotide Array Sequence Analysis - statistics & numerical data
Reproducibility
Software
Transcriptome analysis
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Title Unlocking the potential of publicly available microarray data using inSilicoDb and inSilicoMerging R/Bioconductor packages
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Volume 13
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