cqc_cluster: Cluster groups based on the result of cqc_check

In RGLab/cytoqc: Quality control and standardization of cytometry data

Cluster groups based on the result of cqc_check

Description

Sets of labels (strings representing channels, markers, keywords, or panels consisting of channel/marker pairs) for each group will be clustered based on the summed distances of their aligned elements. This provides an automated way to look for groups with sets of labels that likely represent the same underlying values but with minor differences or errors.

Usage

cqc_cluster(x, ...)

## S3 method for class 'cqc_cluster'
cqc_plot(y, ...)

Arguments

x	object resulting from a call to cqc_check
...	ngroup: integer specifying number of groups in to which the clusters will be combined height: number between 0 and 1 that specifies a cut height for the tree to determine the groups. Ignored if ngroup is specified. missing_penalty: multiplicative factor used to impose penalty for labels missing from a group. The distance for a missing label will be calculated as missing_penalty times the largest distance between non-missing labels. Defaults to 1.
y	an object of class cqc_cluster resulting from a cqc_cluster call

Value

a cqc_cluster object whose primary value is the tibble in its group_membership slot providing the map between the original groups and the combined groups resulting from clustering.

RGLab/cytoqc documentation built on Jan. 25, 2023, 11:05 p.m.