View source: R/preprocessBEclear.R
preprocessBEclear | R Documentation |
this methods does some preprocessing steps for the later methods like removing rows containing only missing values
preprocessBEclear(data, samples)
data |
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. |
samples |
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". |
Here we describe the preprocessing steps in the order they are executed:
Values below 0 or above 1 are set to NA
, as the other methods
expect methylation beta values
columns that only contain NA
s are removed
rows that only contain NA
s are removed
samples that are present in the data, but are not annoted in the samples are removed. If this is the case with your data-set, please check those samples.
samples that are annoted but not in the data matrix are removed
if there are duplicate sample names in the data matrix, all sample names
get replaced through a new unique ID. In this case a data.table
containing the mapping is returned as well
a list containing the processed data and samples and a
data.table
containing mappings from the original
sample names to the new ones. If sample names weren't changed this third
object is NULL
data(BEclearData)
res <- preprocessBEclear(ex.data, ex.samples)
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