OmicSelector_differential_expression_ttest: OmicSelector_differential_expression_ttest

In kstawiski/OmicSelector: OmicSelector - a package for biomarker selection based on high-throughput experiments.

OmicSelector_differential_expression_ttest

Description

The variable performes standard differential expression analysis using unpaired t-test with BH and Bonferonni correction. It requires 'ttpm_features' object, which is e.g. a matrix of log-transformed TPM-normalized miRNAs counts with miRNAs placed in 'ttpm' design (i.e. columns and cases placed as rows). Classess should be passed as 'classes' and this should be a vector of length equal to number of rows in 'ttpm_polfiltrze' and contain only "Case" or "Control" labels!! The function returns the miRNAs sorted by BH-corrected p-value.

Usage

OmicSelector_differential_expression_ttest(
  ttpm_features,
  classes,
  mode = "auto"
)

Arguments

ttpm_features	matrix of log-transformed TPM-normalized miRNAs counts or other feature matrix with miRNAs/features placed in 'ttpm' design (i.e. columns and cases placed as rows)
classes	vector describing label for each case. It should contain only "Case" and "Control" labeles!!!!
mode	use 'logtpm' for log(TPM) data or 'deltact' for qPCR deltaCt values. This parameters sets how the fold-change is calculated. Setting it to "auto" will try to read settings from var_type.txt (used in docker).

Value

Data frame with results.

kstawiski/OmicSelector documentation built on April 10, 2024, 11:11 p.m.