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I am trying to process the raw data downloaded from:
http://www.ebi.ac.uk/arrayexpress/experiments/E-MTAB-380
At the moment of using the function neqc I get the following error:
Error in if (sigma <= 0) stop("sigma must be positive") :
missing value where TRUE/FALSE needed
The problem seems to be in this line:
In sqrt(weighted.mean(v, freq) * n/(n - 1))
of the function normexp.fit.detection.p
This is generated by the fact that in this function, the difference
among p-values is computed, and some of those differences turn out to
be negative.
Following is the code with which I am trying to process the data.
library(rstudio)
library(beadarray)
library(limma)
sample.name <-
strsplit(dir("~/Workspaces/data/E-MTAB-380/E-MTAB-380.raw.1/"),
".txt")
group <- sapplysample.name, function(x)
ifelse(length(grep("RR",x))>0,"MT","WT"))
setwd("~/Workspaces/data/E-MTAB-380/E-MTAB-380.raw.1/")
maqc <-
read.ilmn(files=dir("~/Workspaces/data/E-MTAB-380/E-MTAB-380.raw.1/"),
probeid = "Reporter name", other.columns = c("Detection",
"Avg_NBEADS"))
colnames(maqc$E) <- sample.name
colnames(maqc$other$Detection) <- sample.name
colnames(maqc$other$Avg_NBEADS) <- sample.name
maqc$targets <- unlistsample.name)
maqc.norm <- neqc(maqc, detection.p='Detection')
How can I overcome this?
