I want to analyze two color .GPR files from Agilent 4x44K array downloaded from GEO. This data set is a nucleosomal ChIP-ChIP experiment where channel 1 and 2 are labeled with two different antibodies. I am a newbie to ChIP-ChIP data analysis, though I could manage to create the RGlist and ExpressionSet using limma and Ringo package. Further I tried using CMARRT algorithm from Starr package to find Chip-enriched regions. But it throws error "Error in density.default(logR) : 'x' contains missing values". Please point out the mistake in the script I am using for analysis.
targets <- readTargets("targets.txt", row.names="Name") RG <- read.maimages(targets,columns=list(R="F635 Mean",G="F532 Mean",Rb="B635 Median",Gb="B532 Median"), wt.fun=wtflags(weight=0,cutoff=-50), annotation=c("Block","Row","Column","ID","Name")) eSetB <- preprocess(RG, method="loess", ChIPChannel="R", inputChannel="G", returnMAList=FALSE, idColumn="ID", backgroundCorrect(RG, method="subtract"))
peaks = cmarrt.ma(eSetB, GPL_probeAnno, chr = NULL, M= NULL, frag.length = 300)
"Error in density.default(logR) : 'x' contains missing values"
I have noticed that if i avoid mentioning Rb="B635 Median",Gb="B532 Median" in the limma package's read.maimages command
, The script does not throw any error, and i get the peaks as list object. It would be great If someone could point out the mistake and help in troubleshooting.
R version 3.2.0 (2015-04-16)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 8 x64 (build 9200)
 LC_COLLATE=English_United States.1252 LC_CTYPE=English_United States.1252
 LC_MONETARY=English_United States.1252 LC_NUMERIC=C
 LC_TIME=English_United States.1252
attached base packages:
 grid parallel stats graphics grDevices utils datasets methods base
other attached packages:
 Starr_1.24.0 affxparser_1.40.0 affy_1.46.1 Ringo_1.32.0 lattice_0.20-31
 Matrix_1.2-1 limma_3.24.12 RColorBrewer_1.1-2 Biobase_2.28.0 BiocGenerics_0.14.0
loaded via a namespace (and not attached):
 AnnotationDbi_1.30.1 MASS_7.3-42 splines_3.2.0 zlibbioc_1.14.0
 IRanges_2.2.5 pspline_1.0-17 xtable_1.7-4 GenomeInfoDb_1.4.1
 tools_3.2.0 DBI_0.3.1 genefilter_1.50.0 survival_2.38-3
 preprocessCore_1.30.0 affyio_1.36.0 S4Vectors_0.6.1 RSQLite_1.0.0
 BiocInstaller_1.18.3 stats4_3.2.0 XML_3.98-1.3 annotate_1.46.0