OmicSelector_differential_expression_ttest — OmicSelector_differential_expression

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.