{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,27]],"date-time":"2025-10-27T10:12:32Z","timestamp":1761559952025},"reference-count":20,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2005,3,31]],"date-time":"2005-03-31T00:00:00Z","timestamp":1112227200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/2.0\/"},{"start":{"date-parts":[[2005,3,31]],"date-time":"2005-03-31T00:00:00Z","timestamp":1112227200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/2.0\/"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BMC Bioinformatics"],"abstract":"<jats:title>Abstract<\/jats:title><jats:sec>\n                        <jats:title>Background<\/jats:title>\n                        <jats:p>There are currently a number of competing techniques for low-level processing of oligonucleotide array data. The choice of technique has a profound effect on subsequent statistical analyses, but there is no method to assess whether a particular technique is appropriate for a specific data set, without reference to external data.<\/jats:p>\n                     <\/jats:sec><jats:sec>\n                        <jats:title>Results<\/jats:title>\n                        <jats:p>We analyzed coregulation between genes in order to detect insufficient normalization between arrays, where coregulation is measured in terms of statistical correlation. In a large collection of genes, a random pair of genes should have on average zero correlation, hence allowing a correlation test. For all data sets that we evaluated, and the three most commonly used low-level processing procedures including MAS5, RMA and MBEI, the housekeeping-gene normalization failed the test. For a real clinical data set, RMA and MBEI showed significant correlation for absent genes. We also found that a second round of normalization on the probe set level improved normalization significantly throughout.<\/jats:p>\n                     <\/jats:sec><jats:sec>\n                        <jats:title>Conclusion<\/jats:title>\n                        <jats:p>Previous evaluation of low-level processing in the literature has been limited to artificial spike-in and mixture data sets. In the absence of a known gold-standard, the correlation criterion allows us to assess the appropriateness of low-level processing of a specific data set and the success of normalization for subsets of genes.<\/jats:p>\n                     <\/jats:sec>","DOI":"10.1186\/1471-2105-6-80","type":"journal-article","created":{"date-parts":[[2005,3,31]],"date-time":"2005-03-31T06:16:05Z","timestamp":1112249765000},"update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":37,"title":["Correlation test to assess low-level processing of high-density oligonucleotide microarray data"],"prefix":"10.1186","volume":"6","author":[{"given":"Alexander","family":"Ploner","sequence":"first","affiliation":[]},{"given":"Lance D","family":"Miller","sequence":"additional","affiliation":[]},{"given":"Per","family":"Hall","sequence":"additional","affiliation":[]},{"given":"Jonas","family":"Bergh","sequence":"additional","affiliation":[]},{"given":"Yudi","family":"Pawitan","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2005,3,31]]},"reference":[{"key":"405_CR1","doi-asserted-by":"publisher","first-page":"20","DOI":"10.1038\/4447","volume":"21","author":"R Lipshutz","year":"1999","unstructured":"Lipshutz R, Fodor S, Gingeras T, Lockhart D: High density synthetic oligonucleotide arrays. 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