{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,5]],"date-time":"2026-10-05T20:31:44Z","timestamp":1791232304434,"version":"4.1.0"},"reference-count":12,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2005,7,1]],"date-time":"2005-07-01T00:00:00Z","timestamp":1120176000000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/2.0\/"},{"start":{"date-parts":[[2005,7,1]],"date-time":"2005-07-01T00:00:00Z","timestamp":1120176000000},"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>Quality-control is an important issue in the analysis of gene expression microarrays. One type of problem is regional bias, in which one region of a chip shows artifactually high or low intensities (or ratios in a two-channel array) relative to the majority of the chip. Current practice in quality assessment for microarrays does not address regional biases.<\/jats:p>\n                     <\/jats:sec><jats:sec>\n                        <jats:title>Results<\/jats:title>\n                        <jats:p>We present methods implemented in R for visualizing regional biases and other spatial artifacts on spotted microarrays and Affymetrix chips. We also propose a statistical index to quantify regional bias and investigate its typical distribution on spotted and Affymetrix arrays.<\/jats:p>\n                        <jats:p>We demonstrate that notable regional biases occur on both Affymetrix and spotted arrays and that they can make a significant difference in the case of spotted microarray results. Although strong biases are also seen at the level of individual probes on Affymetrix chips, the gene expression measures are less affected, especially when the RMA method is used to summarize intensities for the probe sets. A web application program for visualization and quantitation of regional bias is provided at <jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" ext-link-type=\"uri\" xlink:href=\"http:\/\/www.discover.nci.nih.gov\/affytools\">http:\/\/www.discover.nci.nih.gov\/affytools<\/jats:ext-link>.<\/jats:p>\n                     <\/jats:sec><jats:sec>\n                        <jats:title>Conclusion<\/jats:title>\n                        <jats:p>Researchers should visualize and measure the regional biases and should estimate their impact on gene expression measurements obtained. Here, we (i) introduce pictorial visualizations of the spatial biases; (ii) present for Affymetrix chips a useful resolution of the biases into two components, one related to background, the other to intensity scale factor; (iii) introduce a single parameter to reflect the global bias present across an array. We also examine the pattern distribution of such biases and conclude that algorithms based on smoothing are unlikely to compensate adequately for them.<\/jats:p>\n                     <\/jats:sec>","DOI":"10.1186\/1471-2105-6-166","type":"journal-article","created":{"date-parts":[[2005,7,2]],"date-time":"2005-07-02T11:24:58Z","timestamp":1120303498000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":40,"title":["Quality assessment of microarrays: Visualization of spatial artifacts and quantitation of regional biases"],"prefix":"10.1186","volume":"6","author":[{"given":"Mark","family":"Reimers","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"John N","family":"Weinstein","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2005,7,1]]},"reference":[{"key":"491_CR1","doi-asserted-by":"publisher","first-page":"31","DOI":"10.1073\/pnas.98.1.31","volume":"98","author":"C Li","year":"2001","unstructured":"Li C, Wong WH: Model-based analysis of oligonucleotide arrays: expression index computation and outlier detection. Proc Natl Acad Sci U S A 2001, 98: 31\u201336. 10.1073\/pnas.011404098","journal-title":"Proc Natl Acad Sci U S A"},{"key":"491_CR2","doi-asserted-by":"publisher","first-page":"e15","DOI":"10.1093\/nar\/gng015","volume":"31","author":"RA Irizarry","year":"2003","unstructured":"Irizarry RA, Bolstad BM, Collin F, Cope LM, Hobbs B, Speed TP: Summaries of Affymetrix GeneChip probe level data. Nucleic Acids Res 2003, 31: e15. 10.1093\/nar\/gng015","journal-title":"Nucleic Acids Res"},{"key":"491_CR3","doi-asserted-by":"publisher","first-page":"1341","DOI":"10.1093\/bioinformatics\/btg154","volume":"19","author":"X Wang","year":"2003","unstructured":"Wang X, Hessner MJ, Wu Y, Pati N, Ghosh S: Quantitative quality control in microarray experiments and the application in data filtering, normalization and false positive rate prediction. Bioinformatics 2003, 19: 1341\u20131347. 10.1093\/bioinformatics\/btg154","journal-title":"Bioinformatics"},{"key":"491_CR4","volume-title":"Bioinformatics","author":"A Buness","year":"2004","unstructured":"Buness A, Huber W, Steiner K, Sultmann H, Poustka A: arrayMagic: two-colour cDNA microarray quality control and preprocessing. Bioinformatics 2004."},{"key":"491_CR5","doi-asserted-by":"publisher","first-page":"307","DOI":"10.1093\/bioinformatics\/btg405","volume":"20","author":"L Gautier","year":"2004","unstructured":"Gautier L, Cope L, Bolstad BM, Irizarry RA: affy--analysis of Affymetrix GeneChip data at the probe level. Bioinformatics 2004, 20: 307\u2013315. 10.1093\/bioinformatics\/btg405","journal-title":"Bioinformatics"},{"key":"491_CR6","doi-asserted-by":"publisher","first-page":"4425","DOI":"10.1093\/nar\/gkg485","volume":"31","author":"G Balazsi","year":"2003","unstructured":"Balazsi G, Kay KA, Barabasi AL, Oltvai ZN: Spurious spatial periodicity of co-expression in microarray data due to printing design. Nucleic Acids Res 2003, 31: 4425\u20134433. 10.1093\/nar\/gkg485","journal-title":"Nucleic Acids Res"},{"key":"491_CR7","doi-asserted-by":"publisher","first-page":"1540","DOI":"10.1093\/bioinformatics\/18.11.1540","volume":"18","author":"C Colantuoni","year":"2002","unstructured":"Colantuoni C, Henry G, Zeger S, Pevsner J: SNOMAD (Standardization and NOrmalization of MicroArray Data): web-accessible gene expression data analysis. Bioinformatics 2002, 18: 1540\u20131541. 10.1093\/bioinformatics\/18.11.1540","journal-title":"Bioinformatics"},{"key":"491_CR8","doi-asserted-by":"publisher","first-page":"research0048","DOI":"10.1186\/gb-2002-3-9-research0048","volume":"3","author":"C Workman","year":"2002","unstructured":"Workman C, Jensen LJ, Jarmer H, Berka R, Gautier L, Nielser HB, Saxild HH, Nielsen C, Brunak S, Knudsen S: A new non-linear normalization method for reducing variability in DNA microarray experiments. Genome Biol 2002, 3: research0048. 10.1186\/gb-2002-3-9-research0048","journal-title":"Genome Biol"},{"key":"491_CR9","doi-asserted-by":"crossref","first-page":"42","DOI":"10.2144\/03351bm03","volume":"35","author":"J Qian","year":"2003","unstructured":"Qian J, Kluger Y, Yu H, Gerstein M: Identification and correction of spurious spatial correlations in microarray data. Biotechniques 2003, 35: 42\u20134, 46, 48.","journal-title":"Biotechniques"},{"key":"491_CR10","unstructured":"Smyth GK: Print-order normalization of cDNA microarrays.[http:\/\/www.statsci.org\/smyth\/pubs\/porder\/porder.html]"},{"key":"491_CR11","volume-title":"R Foundation for Statistical Computing, Vienna","author":"R Development Core Team","year":"2004","unstructured":"R Development Core Team: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna 2004."},{"key":"491_CR12","doi-asserted-by":"publisher","first-page":"307","DOI":"10.1093\/bioinformatics\/btg405","volume":"20","author":"L Gautier","year":"2004","unstructured":"Gautier L, Cope L, Bolstad BM, Irizarry RA: Affymetrix GeneChip data at the probe level. Bioinformatics 2004, 20: 307\u2013315. 10.1093\/bioinformatics\/btg405","journal-title":"Bioinformatics"}],"container-title":["BMC Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/1471-2105-6-166.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1186\/1471-2105-6-166\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/1471-2105-6-166.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,7]],"date-time":"2024-10-07T12:14:11Z","timestamp":1728303251000},"score":1,"resource":{"primary":{"URL":"https:\/\/bmcbioinformatics.biomedcentral.com\/articles\/10.1186\/1471-2105-6-166"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2005,7,1]]},"references-count":12,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2005,12]]}},"alternative-id":["491"],"URL":"https:\/\/doi.org\/10.1186\/1471-2105-6-166","relation":{},"ISSN":["1471-2105"],"issn-type":[{"value":"1471-2105","type":"electronic"}],"subject":[],"published":{"date-parts":[[2005,7,1]]},"assertion":[{"value":"23 November 2004","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"1 July 2005","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"1 July 2005","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}],"article-number":"166"}}