I am new to microarray data, currently using Affymetrix microarrays expression data for my experiments. Essentially, I have Affymetrix microarrays expression data matrix (Affymetrix probe-sets in rows (32830 probesets), and RNA samples in columns (735 samples)). I also have pheno data which contains metadata information of the above expression matrix (735 in rows (sample identifiers), and 6 description elements in columns).
load("data/HTA20_RMA.RData") row_medArray <- Biobase::rowMedians(eset_HTA20) RLE_data <- base::sweep(eset_HTA20,1,row_medArray) RLE_data <- base::as.data.frame(RLE_data)
I find the limma case study is helpful but not whole. Basically, I am going to try the following steps:
- how to make summarization of Affymetrix microarray expression matrix at gene level?
- how to list out probsets intensities per gene?
- how to filter out probsets and genes per sample?
- how to add gene-level annotation to Affymetrix expression set?
I am wondering how to make this happen above steps? can anyone point me out how to lay out above workflow in R easily? any idea? Thanks