calcPvalues: Calculate p-values

Description Usage Arguments Details Value See Also Examples

View source: R/calcPvalues.R

Description

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 p-value which defines if the distributions are the same or not. Standard two sided Kolmogorov-Smirnov test is used to calculate the (adjusted) p-values.

Usage

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calcPvalues(data, samples, adjusted=TRUE, method="fdr", 
BPPARAM=bpparam())

Arguments

data

a data.table with one column indicating the sample, one the features and a value column indicating the beta value

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 p-values be adjusted or not, see "method" for available adjustment methods.

method

adjustment method for p-value adjustment (if TRUE), default method is "false discovery rate adjustment", for other available methods see the description of the used standard R package p.adjust.

BPPARAM

An instance of the BiocParallelParam-class that determines how to parallelisation of the functions will be evaluated.

Details

calcPvalues

Value

a matrix containing p-values for all genes in all batches, the column names define the batch numbers, row names are the same gene names as contained in the input matrix. If there are only missing values present for a gene in a batch, a p-values of 0 is returned

See Also

ks.test

p.adjust

correctBatchEffect

Examples

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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.

## Calculate fdr-adjusted p-values in non-parallel mode
data(BEclearData)
ex.data <- ex.data[31:90,7:26]
ex.samples <- ex.samples[7:26,]
 
library(data.table)
samples <- data.table(ex.samples)
data <- data.table(feature=rownames(ex.data), ex.data)
data <- melt(data = data, id.vars = "feature", variable.name = "sample", 
value.name = "beta.value")
setkey(data, "feature", "sample")

pvals <- calcPvalues(data=data, samples=samples,method="fdr")

BEclear documentation built on Nov. 1, 2018, 4:29 a.m.