M3DropGetExtremes {M3Drop} | R Documentation

## Get outliers from MM curve.

### Description

Identifies outliers left and right of a fitted Michaelis-Menten curve. Functions tagged with "bg__" are not meant for direct usage and are not available in the Bioconductor release.

### Usage

      M3DropGetExtremes(expr_mat, fdr_threshold=0.1, percent=NA, v_threshold=c(0.05,0.95), suppress.plot=FALSE)
      bg__get_extreme_residuals(expr_mat, fit=NA, fdr_threshold=0.1, percent=NA, v_threshold=c(0.05, 0.95), direction="right", suppress.plot=FALSE)

### Arguments

`expr_mat` | a numeric matrix of normalized (not log-transformed) expression values, columns = samples, rows = genes.
`fit` | output from fitting the Michaelis-Menten equation, see `bg__fit_MM`
`fdr_threshold` | the threshold for identifying significant outliers after multiple testing correction.
`percent` | identify this percentage of data that is most extreme in each direction.
`v_threshold` | restrict to this range of dropout rates to avoid poorly fit regions of the data.
`direction` | "left" or "right", which tail of outliers to examine.
`suppress.plot` | logical, whether to plot the fitted Michaelis-Menten curve and highlight to identified most extreme outliers.

### Details

Fits a Michaelis-Menten function to the dropout-rate of the provided data, then identifies the most extreme left and/or right outliers from the curve. Horizontal residuals are calculated as :

log_10(S) - log_10( (K * (1 - P)) / P )

. Extreme left[right] outliers are identified either as the `percent` smallest[largest] horizontal residuals. If `percent` is undefined (default) a normal distribution is fitted to the horizontal residuals and a Z-test is used to identify significant outliers after FDR multiple testing correction.

Only genes with dropout rates within v_threshold will be considered to avoid the skewing of residuals due to the exponential parts of the MM curve near P = 0 & P = 1.

`M3DropGetExtremes` identifies both left and right residuals using the provided thresholds in each direction. Eg. will return the `percent` smallest and `percent` largest residuals. It also plots the fitted MM curve and highlights the left and right extreme outliers unless suppress.plot=TRUE . `bg__get_extreme_residuals` identifies one-sided extreme outliers.

### Value

`M3DropGetExtremes` List containing elements left and right, vectors of the names of the extreme genes to the left and right of the curve respectively. `bg__get_extreme_residuals` A vector of names of the extreme genes in the specified direction.

### Examples

      library(M3DExampleData)
      norm <- M3DropConvertData(Mmus_example_list$data, is.counts=TRUE)
      extreme_gene_lists <- M3DropGetExtremes(norm, fdr_threshold=0.1)
      extreme_gene_lists <- M3DropGetExtremes(norm, percent=0.01)
    #  Lextremes <- bg__get_extreme_residuals(norm, fdr_threshold=0.1, direction="left")

[Package M3Drop version 1.16.0 Index]