How do I assess the quality control of Clariom_S_Human CEL files? Preferably using R.
Does the oligo::rma normalization consider the positive and negative controls along with the ERCCs? Can I assume after RMA the normalized arrays are valid? Does the RMA function inform if there is a problem?
After annotation according to the Clariom_S_Human: (“all.eset <- annotateEset(normData, annotation(normData))”) I get the following object:
> ExpressionSet (storageMode: lockedEnvironment) assayData: 27189
> features, 25 samples element names: exprs protocolData rowNames:
> G200 1a G200 2a ... U87 UOV 2 (25 total) varLabels: exprs dates
> varMetadata: labelDescription channel phenoData rowNames: G200 1a
> G200 2a ... U87 UOV 2 (25 total) varLabels: index varMetadata:
> labelDescription channel featureData featureNames: 23064070 23064071
> ... TSUnmapped00000823.hg.1 (27189 total) fvarLabels: PROBEID ID
> SYMBOL GENENAME fvarMetadata: labelDescription experimentData: use
> 'experimentData(object)' Annotation: pd.clariom.s.human
There are different featureData that have various names. These is a list of examples from each of these types:
23064070, AFFX-BioB-3_at, ERCCmix1step1, HTA2-neg-47419077_st, HTA2-pos-2824546_st, TC0100007254.hg.1, TSUnmapped00000823.hg.1
Which of these probes are relevant for differential expression analysis? And which ones can I remove? Only the TC0100007254.hg.1, TSUnmapped00000823.hg.1? How do I need to treat the other probes?
Thank you very much in advance, Kerem
Hello, I have the same problem with the same kinds of probes: I am not sure which probes are relevant for differential expression analysis. Did you end up finding an answer to your question? Thank you in advance.