zscoreUMI4C {UMI4Cats} | R Documentation

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

### Description

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

### Usage

    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.

### 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

### Value

DDS object with zscore,pvalue and padjusted assays

[Package UMI4Cats version 1.4.0 Index]