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Affymetrix data in R

Affymetrix data in R. 2006. 2. 25. 생물정보통계연구실. Outline. affy in Biocondutor AffyBatch Preset processing Detailed processing Data exploration Probset. affy in Bioconductor. “affy” library 를 통해 자료의 입출력 루틴을 제공하고 있다 . R library(affy). AffyBatch. CEL 파일을 읽어들여서 원천정보를 담고있는 객체 R

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Affymetrix data in R

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  1. Affymetrix data in R 2006. 2. 25. 생물정보통계연구실

  2. Outline • affy in Biocondutor • AffyBatch • Preset processing • Detailed processing • Data exploration • Probset 생물정보통계연구실 2006 1st Microarray Analysis Workshop

  3. affy in Bioconductor • “affy” library를 통해 자료의 입출력 루틴을 제공하고 있다. • R • library(affy) 생물정보통계연구실 2006 1st Microarray Analysis Workshop

  4. AffyBatch • CEL 파일을 읽어들여서 원천정보를 담고있는 객체 • R • Data <- ReadAffy() 생물정보통계연구실 2006 1st Microarray Analysis Workshop

  5. Preset processing • RMA • eset.rma <- rma(Data) • MAS5 • eset.mas5 <- mas5(Data) 생물정보통계연구실 2006 1st Microarray Analysis Workshop

  6. Detailed processing • eset.general <- expresso(Data, normalize.method = “quantiles”, bg.correct = FALSE, pmcorrect.method = “pmonly”, summary.method = “medianpolish”) • eset.tk <- expresso(Data, widget = TRUE) 생물정보통계연구실 2006 1st Microarray Analysis Workshop

  7. Data exploration • MAplot(Data, pairs = TRUE) • Index <- c(1, 10, 100, 1000) • pm(Data)[Index, ] • mm(Data)[Index, ] • probeNames(Data)[Index] • gn <- geneNames(Data) • hist(Data) • image(Data) • boxplot(Data) 생물정보통계연구실 2006 1st Microarray Analysis Workshop

  8. Probeset • ps <- probeset(Data, gn[Index]) • pm(ps[[4]]) • n.env <- getCdfInfo(Data) • ls(n.env)[Index] • pmindex(Data, gn[Index]) • mmindex(Data, gn[Index]) 생물정보통계연구실 2006 1st Microarray Analysis Workshop

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