{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2022,6,7]],"date-time":"2022-06-07T21:20:33Z","timestamp":1654636833835},"reference-count":21,"publisher":"Springer Science and Business Media LLC","issue":"1","content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BMC Bioinformatics"],"published-print":{"date-parts":[[2012,12]]},"abstract":"<jats:title>Abstract<\/jats:title>\n          <jats:sec>\n            <jats:title>Background<\/jats:title>\n            <jats:p>Hybridization differences caused by target sequence differences can be a confounding factor in analyzing gene expression on microarrays, lead to false positives and reduce power to detect real expression differences. We prepared an R Bioconductor compatible package to detect, characterize and remove such probes in Affymetrix 3\u2019IVT and exon-based arrays on the basis of correlation of signal intensities from probes within probe sets.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Results<\/jats:title>\n            <jats:p>Using completely mouse genomes we determined type 1 (false negatives) and type 2 (false positives) errors with high accuracy and we show that our method routinely outperforms previous methods. When detecting 76.2% of known SNP\/indels in mouse expression data, we obtain at most 5.5% false positives. At the same level of false positives, best previous method detected 72.6%. We also show that probes with differing binding affinity both hinder differential expression detection and introduce artifacts in cancer-healthy tissue comparison.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Conclusions<\/jats:title>\n            <jats:p>Detection and removal of such probes should be a routine step in Affymetrix data preprocessing. We prepared a user friendly R package, compatible with Bioconductor, that allows the filtering and improving of data from Affymetrix microarrays experiments.<\/jats:p>\n          <\/jats:sec>","DOI":"10.1186\/1471-2105-13-56","type":"journal-article","created":{"date-parts":[[2012,4,16]],"date-time":"2012-04-16T20:13:59Z","timestamp":1334607239000},"update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["'maskBAD' - a package to detect and remove Affymetrix probes with binding affinity differences"],"prefix":"10.1186","volume":"13","author":[{"given":"Michael","family":"Dannemann","sequence":"first","affiliation":[]},{"given":"Michael","family":"Lachmann","sequence":"additional","affiliation":[]},{"given":"Anna","family":"Lorenc","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2012,4,16]]},"reference":[{"issue":"2","key":"5358_CR1","doi-asserted-by":"crossref","first-page":"747","DOI":"10.1093\/genetics\/165.2.747","volume":"165","author":"WP Hsieh","year":"2003","unstructured":"Hsieh WP, Chu TM, Wolfinger RD, Gibson G: Mixed-model reanalysis of primate data suggests tissue and species biases in oligonucleotide-based gene expression profiles. 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