countValuesToPredict {BEclear} | R Documentation

## 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)

[Package BEclear version 2.10.0 Index]