A function that simply sets all values to NA which were previously found by median value comparison and p-value calculation and are stored in a summary. The summary defines which values in the data matrix are set to NA.
any matrix filled with beta values, column names have to be sample_ids corresponding to the ids listed in "samples", row names have to be gene names.
data frame with two columns, the first column has to contain the sample numbers, the second column has to contain the corresponding batch number. Colnames have to be named as "sample_id" and "batch_id".
a summary data.frame containing the columns "gene", "batch",
"median" and "p-value" and consists of all genes which were found in the
median and p-value calculations, see
All entries belonging to genes stated in the summary are set to NA
for the corresponding batches in the data matrix. Please look at the
more detailed information about the data which should be contained in the
A data matrix with the same dimensions as well as the same column and row names as the input data matrix is returned, all entries which are defined in the summary are now set to NA.
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## Shortly running example. For a more realistic example that takes ## some more time, run the same procedure with the full BEclearData ## dataset. ## Whole procedure that has to be done to use this function. data(BEclearData) ex.data <- ex.data[31:90, 7:26] ex.samples <- ex.samples[7:26, ] ## Calculate the batch effects batchEffects <- calcBatchEffects(data = ex.data, samples = ex.samples, adjusted = TRUE, method = "fdr") meds <- batchEffects$med pvals <- batchEffects$pval ## Summarize p-values and median differences for batch affected genes sum <- calcSummary(medians = meds, pvalues = pvals) ## Set values for summarized BEgenes to NA clearedMatrix <- clearBEgenes(data = ex.data, samples = ex.samples, summary = sum)
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