Description Usage Arguments Details Value See Also Examples
View source: R/calcBatchEffects.R
Calculates for each gene in every batch the median distance to the other batches and the pvalue resulting from the KolmogorovSmirnov test.
1 2  calcBatchEffects(data, samples, adjusted=TRUE, method="fdr",
BPPARAM=SerialParam())

data 
a 
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". 
adjusted 
should the pvalues be adjusted or not, see "method" for available adjustment methods. 
method 
adjustment method for pvalue adjustment (if TRUE), default
method is "false discovery rate adjustment", for other available methods
see the description of the used standard R package 
BPPARAM 
An instance of the

calcBatchEffects
medians Compares the median value of all beta values belonging to one batch with the median value of all beta values belonging to all other batches. Returns a matrix containing this median difference value for every gene in every batch, columns define the batch numbers, rows the gene names.
pvalues Compares the distribution of all beta values corresponding to one batch with the distribution of all beta values corresponding to all other batches and returns a pvalue which defines if the distributions are the same or not. Standard two sided KolmogorovSmirnov test is used to calculate the (adjusted) pvalues.
a matrix containing medians and pvalues for all genes in all batches
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24  ## Shortly running example. For a more realistic example that takes
## some more time, run the same procedure with the full BEclearData
## dataset.
## Calculate fdradjusted pvalues in nonparallel mode
data(BEclearData)
ex.data < ex.data[31:90, 7:26]
ex.samples < ex.samples[7:26, ]
res < calcBatchEffects(data = ex.data, samples = ex.samples, method = "fdr")
## How to handle datasets without defined batches
## https://github.com/DavidJR/BEclear/issues/22
library(data.table)
data(BEclearData)
DT < data.table(ex.samples)[, .(sample_id)]
## set the batch_id equal to the sample_id
## this way samples are treated as batches
DT[, batch_id := sample_id]
res < calcBatchEffects(data = ex.data, samples = DT)

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