Z-score calculation using residuals of trend and fit UMI4C counts

Source: R/callInteractions.R

Calculates the z-score and then they are converted into one-sided P-values and adjusted for multiple testing using the method of Benjamini and Hochberg

zscoreUMI4C(
  dds,
  padj_method = "fdr",
  zscore_threshold = 2,
  padj_threshold = 0.1
)

Arguments

dds

DDS object as generated by smoothMonotoneUMI4C with the smooth monotone fit counts
padj_method

The method to use for adjusting p-values, see p.adjust. Default: fdr.
zscore_threshold

Numeric indicating the z-score threshold to use to define significant differential contacts. Default: 2.
padj_threshold

Numeric indicating the adjusted p-value threshold to use to define significant differential contacts. Default: 0.1.

Value

DDS object with zscore,pvalue and padjusted assays

Details

This function calculates the z-score for each fragment over all samples from the residuals of the symmetric monotone fit and the median absolute deviation (mad). Z-scores are then converted into one-sided P-values using the standard Normal cumulative distribution function, and these are adjusted for multiple testing using the method of Benjamini and Hochberg