Generic single matrix analysis

Source: R/generic_individual_analysis.R

Evaluates matrix data row-wise. This function is useful when the matrix consists on relative measures (i.e a matrix of log2 fold changes) or to analyze other features such as normal distribution.

singleMatrixTest(
  mat,
  metricFun = function(x) mean(x, na.rm = TRUE),
  statFun = nsTestT,
  sigFun = nsTestPValue,
  allowNa = TRUE,
  pAdjustMethod = "BH",
  featName = "feature",
  metricName = "logFc",
  statName = "t",
  pValName = "pValue",
  pAdjName = "pAdj"
)

Arguments

mat

Matrix containing data to be analyzed.
metricFun

Function to calculate metric of change. Defaults to log2(ratio of means).
statFun

Function to calculate statistic of change. Defaults to a non-sensitive T-Test T value.
sigFun

Function to calculate significance of change. Defaults to a non-sensitive T-Test P value.
allowNa

Allow NAs on input matrix?
pAdjustMethod

Method used to adjust P values.
featName

Name of the column containing the compared features (rows).
metricName

Name of the column containing the metric.
statName

Name of the column containing the statistic.
pValName

Name of the column containing the p values.
pAdjName

Name of the column containing the adjusted p values.

Value

A data frame with the row-wise statistical results.