[BioC] About beadarray Quality Assessment and Detection P value

[Matt Ritchie]

Dear Alex,

To filter probes based on some cut-off of the detection p-value score, try 
the code below (note, this assumes the detection scores are available. In 
this example, I have selected those with scores greater than 0.99 in each 
sample - you may need to adjust this for your dataset).

ind = apply(Detection(BSData)>0.99, 1, all)
BSData.filt = BSData[ind,]

As for your plot, negative intensities produce a warning after you log2 and 
will be missing from the boxplot, however you should still see a figure of 
the remaining data.

Best wishes,

Matt

>*Hi BioC list,
>**
>**In package beadarray, when I do boxplot of raw data,
>do I really have to do log2 transformation according
>to the example code in the tutorial:
>> boxplot(as.data.frame(log2(exprs(BSData))),
>+ las = 2, outline = FALSE, ylab = "log2(intensity)")?
>
>The reason I asked this question is because I find some
>negative intensity values, which should prevent the log2
>transformation.
>
>Another question is that whether there is an option in beadarray
>to filter out some probes across samples whose Detection P
>value is significantly lower than a threshold.
>
>Thanks a lot for your suggestion!
>
>Alex