flowReMixPFS: perSubsetPFS Compute the PFS (polyfunctionality score) per...

In RGLab/flowReMix: Generalized Linear Modeling of FCM Data With Clustered Coefficients

Description

perSubsetPFS Compute the PFS (polyfunctionality score) per subject and stimulation group

Usage

flowReMixPFS(x, M, stimVar = NULL, parentVar = NULL, outcomeVar = NULL,
  subsetVar = NULL, ...)

Arguments

x	flowReMix model object
M	numeric the max possible cell subset degree, the number of functions measured.
stimVar	name Unquoted name of the stimulation variable in the data. e.g. stim
parentVar	name Unquoted name of the parent cell population variable in the data. e.g. parent
outcomeVar	name Unquoted name of the outcome variable in the data. If provided, the scores will be merged with the data using the subject_id
...	additional arguments passed to weightForPFS.

Details

Requires that the data table has a variable for stimulation and for cell population parent.

The user can pass in a function to the argument parser=. This function parses a cell subset name string and returns the degree of functionality for the cell subset. The default is degreeFromStringFun

Value

data.frame of polyfunctionality scores for each cell subset and subject, weighted appropriately.

Note

Uses rlang quosures to pass variable information. PFS are NOT normalized to the total number of possible subsets (n*(n+1)/2), like in COMPASS.

See Also

degreeFromStringFun weightForPFS

Examples

data(fit505)
flowReMixPFS(fit505,M=5, stimVar = stimGroup, parentVar = parent)
flowReMixPFS(fit505,M=5,stimVar=stimGroup,parentVar=parent,outcomeVar=infection)
## Not run: 
flowReMixPFS(rv144_aggregate,M=6,stimVar=stim,parentVar=parent,split=",")

## End(Not run)

RGLab/flowReMix documentation built on May 8, 2019, 5:55 a.m.