countValuesToPredict: Count NA entries in a matrix

In David-J-R/BEclear: Correction of batch effects in DNA methylation data

Count NA entries in a matrix

Description

Simple function that counts all values in a matrix which are NA

Usage

countValuesToPredict(data)

Arguments

data	any kind of matrix

Details

countValuesToPredict

Value

Returns a data frame with the number of NA entries per column. Since the function is mainly written for the usage in batch effect correction of DNA methylation data, the column names of the data frame are set to "sample" and "num_pred_values". Nevertheless, the function can be used with any other matrix containing anything but beta values.

See Also

clearBEgenes

correctBatchEffect

correctBatchEffect

Examples

## 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)
clearedMatrix <- clearBEgenes(data = ex.data, samples = ex.samples, summary = sum)
numberOfEntries <- countValuesToPredict(data = clearedMatrix)

David-J-R/BEclear documentation built on April 17, 2023, 2:19 p.m.