mm_Phenotype: Generate Phenotypes

View source: R/explore.R

mm_PhenotypeR Documentation

Generate Phenotypes

Description

Partition sample into clusters, based on information from

Usage

mm_Phenotype(dat, kgrps, cuttree_h = NULL, cuttree_k = NULL, plot_figs = TRUE)

Arguments

dat

Either an Array of shape data, an mmPCA object, or an mmDiag object.

kgrps

A non-negative integer of sub-groups to draw. kgrps=1 will provide results for the whole input dat.

cuttree_h

Optional. Draw clusters by splitting the tree at a given height, h.

cuttree_k

Optional. Draw clsuters by splitting the tree into number of branches, k

plot_figs

Optional. Default = TRUE, plot phenotypes for each set(s) of subgroups.

Value

If plot_figs=TRUE (Default), plot associated graphs and return a list containing:

  • ALN - an array containing aligned and scaled landmark data, the output of mm_ArrayData

  • PCA - PC scores, eigenvalues, and shape visualizations, the output of mm_CalcShapespace

  • TREE - Dendrogram of PC scores, the output of mm_Diagnostics

  • k_grps - If kgrps is specified, a vector defining group membership (as integer); the results of k-means clustering based on PC scores.

  • cth_grps - If cth_grps is specified, a vector defining group membership (as integer); the results of clustering using stats::cutree for a given height.

  • ctk_grps - If ctk_grps is specified, a vector defining group membership (as integer); the results of clustering using stats::cutree for a given number of clusters.


moRphomenses documentation built on April 3, 2025, 7:51 p.m.