sample_test: Test gene expression variations for a given sample

In CDecamps/penda: A R package that performs personalized differential analysis of comics data

Test gene expression variations for a given sample

Description

This function makes the test of the dysregulation of all genes for one patient.

Usage

sample_test(sample, iterations, threshold)

Arguments

sample	A vector with all the genes expressions for one patient.
iterations	The maximal number of iterations for the test. If the dysregulation list no longer changes, iterations are stop before.
threshold	The threshold for regulation_test.

Value

This function return a list with two vectors : D, with TRUE for genes down-regulated U, with TRUE for genes up-regulated.

Examples

# First, load and define the data
dataset = penda::make_dataset(
  penda::penda_data_ctrl[1:10, 1:10],  
  penda::penda_data_case[1:10, 1:2]
)
controls = dataset$data_ctrl
sample = dataset$data_case[,1]
# Second, lower and higher lists are computed
L_H_list = penda::compute_lower_and_higher_lists(controls, threshold = 0.99, s_max = 50)
# Third, test is the expression is deregulated for each gene of a sample.
#When this function is called, quantiles are already computed
quant_test = 0
factor_test = 1
quantile_genes = apply(controls, 1, quantile, c(quant_test,(1-quant_test)), na.rm = TRUE)
quantile_genes[1,] = quantile_genes[1,] / factor_test
quantile_genes[2,] = quantile_genes[2,] * factor_test

res_sample = penda::sample_test(sample,
                                iterations = 20,
                                threshold = 0.03)

CDecamps/penda documentation built on March 29, 2024, 3:26 a.m.