how to rank affy probesets by their probe-effect magnitude
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Leo Lahti ▴ 30
@leo-lahti-5304
Last seen 10 weeks ago
Finland
Dear Robert, Below is an example script for ordering the probes based on the probe effect for the 'Dilution' affybatch using the Bioconductor RPA<http: www.bioconductor.org="" packages="" release="" bioc="" html="" rpa.html="">pa ckage. The Robust Probabilistic Averaging (RPA) model estimates probe-specific affinity and variance terms (with respect to the probeset-level summary estimate). The model was originally developed and used to assess the effect of known probe-level error sources on probe performance in TCBB/IEEE 2011<http: www.computer.org="" portal="" web="" csdl="" doi="" 10.1109="" tcbb.2009.38="">(GC-content, SNPs, probe position, crosshyb). Technical summary of the method is available in the package vignette<http: www.bioconductor.org="" packages="" release="" bioc="" vignettes="" r="" pa="" inst="" doc="" rpa.pdf=""> . with kind regards Leo Lahti, Finland / Netherlands # Probe affinity and variance estimation # (C) Leo Lahti 2012. FreeBSD license. # Install libraries source("http://www.bioconductor.org/biocLite.R") biocLite(c("affy", "affydata", "RPA")) # Load libraries require(affy) require(affydata) require(RPA) # Load example data data(Dilution) # Define the probesets to check sets <- geneNames(Dilution)[1:2] # Robust Probabilistic Averaging model rpa.results <- RPA.pointestimate(Dilution, sets) # Probe affinity effects af <- unlist(lapply(sets, function (set) {rpa.results[[set]]$affinity})) # Probe-specific noise (variance) s2 <- unlist(lapply(sets, function (set) {rpa.results[[set]]$sigma2})) # PM probe indices pmind <- unlist(pmindex(Dilution)[sets]) # Probe effect table df <- data.frame(list(pmindex = pmind, affinity = af, variance = s2)) # Probe effect table ordered by absolute affinity effects df <- df[order(abs(df$affinity), decreasing = TRUE),] # Investigate the output print(head(df)) Date: Mon, 05 Mar 2012 19:22:24 +0100 From: Robert Castelo <robert.castelo@upf.edu> To: Bioconductor mailing list <bioconductor@r-project.org> Subject: [BioC] how to rank affy probesets by their probe-effect magnitude Message-ID: <1330971744.2703.40.camel@llull.imim.es> Content-Type: text/plain; charset="UTF-8" dear list, i'm searching for a way to rank affy probesets from classical 3' affy arrays by their probe effect magnitude. i mean that i would like to know if a probeset is has a larger probe-specific effect than another one. [[alternative HTML version deleted]]
probe affy RPA probe affy RPA • 557 views
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