{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,31]],"date-time":"2025-10-31T21:26:10Z","timestamp":1761945970705,"version":"build-2065373602"},"reference-count":32,"publisher":"Oxford University Press (OUP)","issue":"8","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2007,4,15]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Motivation: Increases in microarray feature density allow the construction of so-called tiling microarrays. These arrays, or sets of arrays, contain probes targeting regions of sequenced genomes at regular genomic intervals. The unbiased nature of this approach allows for the identification of novel transcribed sequences, the localization of transcription factor binding sites (ChIP-chip), and high resolution comparative genomic hybridization, among other uses. These applications are quickly growing in popularity as tiling microarrays become more affordable. To reach maximum utility, the tiling microarray platform needs be developed to the point that 1\u2009nt resolutions are achieved and that we have confidence in individual measurements taken at this fine of resolution. Any biases in tiling array signals must be systematically removed to achieve this goal.<\/jats:p><jats:p>Results: Towards this end, we investigated the importance of probe sequence composition on the efficacy of tiling microarrays for identifying novel transcription and transcription factor binding sites. We found that intensities are highly sequence dependent and can greatly influence results. We developed three metrics for assessing this sequence dependence and use them in evaluating existing sequence-based normalizations from the tiling microarray literature. In addition, we applied three new techniques for addressing this problem; one method, adapted from similar work on GeneChip brand microarrays, is based on modeling array signal as a linear function of probe sequence, the second method extends this approach by iterative weighting and re-fitting of the model, and the third technique extrapolates the popular quantile normalization algorithm for between-array normalization to probe sequence space. These three methods perform favorably to existing strategies, based on the metrics defined here.<\/jats:p><jats:p>Availability: \u00a0http:\/\/tiling.gersteinlab.org\/sequence_effects\/<\/jats:p><jats:p>Contact: \u00a0mark.gerstein@yale.edu<\/jats:p><jats:p>Supplementary information: Supplementary data are available at Bioinformatics online.<\/jats:p>","DOI":"10.1093\/bioinformatics\/btm052","type":"journal-article","created":{"date-parts":[[2007,3,27]],"date-time":"2007-03-27T00:27:57Z","timestamp":1174955277000},"page":"988-997","source":"Crossref","is-referenced-by-count":31,"title":["Assessing the need for sequence-based normalization in tiling microarray experiments"],"prefix":"10.1093","volume":"23","author":[{"given":"Thomas E.","family":"Royce","sequence":"first","affiliation":[{"name":"1 Interdepartmental Program in Computational Biology and Bioinformatics, 2Department of Molecular Biophysics and Biochemistry and 3Department of Computer Science, Yale University, New Haven, CT 06520, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Joel S.","family":"Rozowsky","sequence":"additional","affiliation":[{"name":"1 Interdepartmental Program in Computational Biology and Bioinformatics, 2Department of Molecular Biophysics and Biochemistry and 3Department of Computer Science, Yale University, New Haven, CT 06520, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mark B.","family":"Gerstein","sequence":"additional","affiliation":[{"name":"1 Interdepartmental Program in Computational Biology and Bioinformatics, 2Department of Molecular Biophysics and Biochemistry and 3Department of Computer Science, Yale University, New Haven, CT 06520, USA"},{"name":"1 Interdepartmental Program in Computational Biology and Bioinformatics, 2Department of Molecular Biophysics and Biochemistry and 3Department of Computer Science, Yale University, New Haven, CT 06520, USA"},{"name":"1 Interdepartmental Program in Computational Biology and Bioinformatics, 2Department of Molecular Biophysics and Biochemistry and 3Department of Computer Science, Yale University, New Haven, CT 06520, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2007,3,25]]},"reference":[{"key":"2023041107553078300_","doi-asserted-by":"crossref","first-page":"147","DOI":"10.1080\/00401706.1974.10489171","article-title":"The fitting of power series, meaning polynomials, illustrated on band-spectroscopic data","volume":"16","author":"Beaton","year":"1974","journal-title":"Technometrics"},{"key":"2023041107553078300_","doi-asserted-by":"crossref","first-page":"2242","DOI":"10.1126\/science.1103388","article-title":"Global identification of human transcribed sequences with genome tiling arrays","volume":"306","author":"Bertone","year":"2004","journal-title":"Science"},{"key":"2023041107553078300_","doi-asserted-by":"crossref","first-page":"185","DOI":"10.1093\/bioinformatics\/19.2.185","article-title":"A comparison of normalization methods for high density oligonucleotide array data based on variance and bias","volume":"19","author":"Bolstad","year":"2003","journal-title":"Bioinformatics"},{"key":"2023041107553078300_","doi-asserted-by":"crossref","first-page":"499","DOI":"10.1016\/S0092-8674(04)00127-8","article-title":"Unbiased mapping of transcription factor binding sites along human chromosomes 21 and 22 points to widespread regulation of noncoding RNAs","volume":"116","author":"Cawley","year":"2004","journal-title":"Cell"},{"key":"2023041107553078300_","doi-asserted-by":"crossref","first-page":"610","DOI":"10.1126\/science.274.5287.610","article-title":"Accessing genetic information with high-density DNA arrays","volume":"274","author":"Chee","year":"1996","journal-title":"Science"},{"key":"2023041107553078300_","doi-asserted-by":"crossref","first-page":"829","DOI":"10.1080\/01621459.1979.10481038","article-title":"Robust locally weighted regression and smoothing scatterplots","volume":"74","author":"Cleveland","year":"1979","journal-title":"J. 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