Are data from different gene expression microarray platforms comparable?
Many commercial and custom-made microarray formats are routinely used for large-scale gene expression surveys. Here, we sought to determine the level of concordance between microarray platforms by analyzing breast cancer cell lines with in situ synthesized oligonucleotide arrays (Affymetrix HG-U95v2...
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Veröffentlicht in: | Genomics (San Diego, Calif.) Calif.), 2004-06, Vol.83 (6), p.1164-1168 |
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container_title | Genomics (San Diego, Calif.) |
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creator | JÄRVINEN, Anna-Kaarina HAUTANIEMI, Sampsa EDGREN, Henrik AUVINEN, Petri SAARELA, Janna KALLIONIEMI, Olli-P MONNI, Outi |
description | Many commercial and custom-made microarray formats are routinely used for large-scale gene expression surveys. Here, we sought to determine the level of concordance between microarray platforms by analyzing breast cancer cell lines with in situ synthesized oligonucleotide arrays (Affymetrix HG-U95v2), commercial cDNA microarrays (Agilent Human 1 cDNA), and custom-made cDNA microarrays from a sequence-validated 13K cDNA library. Gene expression data from the commercial platforms showed good correlations across the experiments (r = 0.78-0.86), whereas the correlations between the custom-made and either of the two commercial platforms were lower (r = 0.62-0.76). Discrepant findings were due to clone errors on the custom-made microarrays, old annotations, or unknown causes. Even within platform, there can be several ways to analyze data that may influence the correlation between platforms. Our results indicate that combining data from different microarray platforms is not straightforward. Variability of the data represents a challenge for developing future diagnostic applications of microarrays. |
doi_str_mv | 10.1016/j.ygeno.2004.01.004 |
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Here, we sought to determine the level of concordance between microarray platforms by analyzing breast cancer cell lines with in situ synthesized oligonucleotide arrays (Affymetrix HG-U95v2), commercial cDNA microarrays (Agilent Human 1 cDNA), and custom-made cDNA microarrays from a sequence-validated 13K cDNA library. Gene expression data from the commercial platforms showed good correlations across the experiments (r = 0.78-0.86), whereas the correlations between the custom-made and either of the two commercial platforms were lower (r = 0.62-0.76). Discrepant findings were due to clone errors on the custom-made microarrays, old annotations, or unknown causes. Even within platform, there can be several ways to analyze data that may influence the correlation between platforms. Our results indicate that combining data from different microarray platforms is not straightforward. 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Obstetrics</subject><subject>Humans</subject><subject>Mammary gland diseases</subject><subject>Medical sciences</subject><subject>Molecular and cellular biology</subject><subject>Molecular genetics</subject><subject>Oligonucleotide Array Sequence Analysis - instrumentation</subject><subject>Oligonucleotide Array Sequence Analysis - methods</subject><subject>Quality Control</subject><subject>Tumors</subject><issn>0888-7543</issn><issn>1089-8646</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2004</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqFkEtrGzEUhUVIqZ20vyAQZpPsZnr1GEmzKsYkdSHQTbsWN5qrMGZelcZQ__sotaHdZXU23zlwPsZuOFQcuP6yr44vNE6VAFAV8CrHBVtzsE1ptdKXbA3W2tLUSq7YVUp7AGikFR_ZitfcmFo3a7bbRCpaXLAIcRqKtguBIo1LkaepoD9zpJS6aSyGzscJY8RjMfe4hCkOqfDTMGPE556-fmIfAvaJPp_zmv16fPi53ZVPP759326eSi-1WEpSEgQKbxRpq7E1IqCwVhtqaq1Do4TwVoW6Ni0Fn0kgQ1YoK1FzE4K8Zven3TlOvw-UFjd0yVPf40jTITmTdQgt4V2QW6iVFTyD8gTmgylFCm6O3YDx6Di4N9Nu7_6adm-mHXCXI7duz_OH54Haf52z2gzcnQFMHvsQcfRd-o8zxtYNyFcVLYgg</recordid><startdate>20040601</startdate><enddate>20040601</enddate><creator>JÄRVINEN, Anna-Kaarina</creator><creator>HAUTANIEMI, Sampsa</creator><creator>EDGREN, Henrik</creator><creator>AUVINEN, Petri</creator><creator>SAARELA, Janna</creator><creator>KALLIONIEMI, Olli-P</creator><creator>MONNI, Outi</creator><general>Elsevier</general><scope>IQODW</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>8FD</scope><scope>FR3</scope><scope>P64</scope><scope>RC3</scope><scope>7X8</scope></search><sort><creationdate>20040601</creationdate><title>Are data from different gene expression microarray platforms comparable?</title><author>JÄRVINEN, Anna-Kaarina ; HAUTANIEMI, Sampsa ; EDGREN, Henrik ; AUVINEN, Petri ; SAARELA, Janna ; KALLIONIEMI, Olli-P ; MONNI, Outi</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c362t-e4302a2c74e686ad72fa28867e9566f9422c84f557defc2a20e7e82483a617ff3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2004</creationdate><topic>Biological and medical sciences</topic><topic>Cell Line, Tumor</topic><topic>Data Interpretation, Statistical</topic><topic>Fundamental and applied biological sciences. 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subjects | Biological and medical sciences Cell Line, Tumor Data Interpretation, Statistical Fundamental and applied biological sciences. Psychology Gene Expression Profiling - instrumentation Gene Expression Profiling - methods Gene Expression Regulation, Neoplastic - genetics Gene Library Genes. Genome Genetics of eukaryotes. Biological and molecular evolution Gynecology. Andrology. Obstetrics Humans Mammary gland diseases Medical sciences Molecular and cellular biology Molecular genetics Oligonucleotide Array Sequence Analysis - instrumentation Oligonucleotide Array Sequence Analysis - methods Quality Control Tumors |
title | Are data from different gene expression microarray platforms comparable? |
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