{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,28]],"date-time":"2026-01-28T04:12:52Z","timestamp":1769573572807,"version":"3.49.0"},"reference-count":11,"publisher":"Oxford University Press (OUP)","issue":"23","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2012,12,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Summary: Frozen robust multiarray analysis (fRMA) is a single-array preprocessing algorithm that retains the advantages of multiarray algorithms and removes certain batch effects by downweighting probes that have high between-batch residual variance. Here, we extend the fRMA algorithm to two new microarray platforms\u2014Affymetrix Human Exon and Gene 1.0 ST\u2014by modifying the fRMA probe-level model and extending the frma package to work with oligo ExonFeatureSet and GeneFeatureSet objects.<\/jats:p>\n               <jats:p>Availability and implementation: All packages are implemented in R. Source code and binaries are freely available through the Bioconductor project. Convenient links to all software and data packages can be found at http:\/\/mnmccall.com\/software<\/jats:p>\n               <jats:p>Contact: \u00a0mccallm@gmail.com<\/jats:p>","DOI":"10.1093\/bioinformatics\/bts588","type":"journal-article","created":{"date-parts":[[2012,10,9]],"date-time":"2012-10-09T00:42:28Z","timestamp":1349743348000},"page":"3153-3154","source":"Crossref","is-referenced-by-count":41,"title":["fRMA ST: frozen robust multiarray analysis for Affymetrix Exon and Gene ST arrays"],"prefix":"10.1093","volume":"28","author":[{"given":"Matthew N.","family":"McCall","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Harris A.","family":"Jaffee","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rafael A.","family":"Irizarry","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2012,10,7]]},"reference":[{"key":"2023062411494880000_bts588-B1","doi-asserted-by":"crossref","first-page":"2363","DOI":"10.1093\/bioinformatics\/btq431","article-title":"A framework for oligonucleotide microarray preprocessing","volume":"26","author":"Carvalho","year":"2010","journal-title":"Bioinformatics"},{"key":"2023062411494880000_bts588-B2","doi-asserted-by":"crossref","first-page":"943","DOI":"10.1093\/bioinformatics\/btl033","article-title":"A new summarization method for affymetrix probe level data","volume":"22","author":"Hochreiter","year":"2006","journal-title":"Bioinformatics"},{"key":"2023062411494880000_bts588-B3","doi-asserted-by":"crossref","first-page":"249","DOI":"10.1093\/biostatistics\/4.2.249","article-title":"Exploration, normalization, and summaries of high density oligonucleotide array probe level data","volume":"4","author":"Irizarry","year":"2003","journal-title":"Biostatistics"},{"key":"2023062411494880000_bts588-B4","doi-asserted-by":"crossref","first-page":"118","DOI":"10.1093\/biostatistics\/kxj037","article-title":"Adjusting batch effects in microarray expression data using empirical Bayes methods","volume":"8","author":"Johnson","year":"2007","journal-title":"Biostatistics"},{"key":"2023062411494880000_bts588-B5","doi-asserted-by":"crossref","first-page":"e161","DOI":"10.1371\/journal.pgen.0030161","article-title":"Capturing heterogeneity in gene expression studies by surrogate variable analysis","volume":"3","author":"Leek","year":"2007","journal-title":"PLoS Genet."},{"key":"2023062411494880000_bts588-B6","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1073\/pnas.98.1.31","article-title":"Model-based analysis of oligonucleotide arrays: expression index computation and outlier detection","volume":"98","author":"Li","year":"2001","journal-title":"Proc. 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