SimulationStudy1: Synthetic normalised gene expression data for 20 genes

In MarcelaCespedes/FSPmix: Exploratory tool for fast unsupervised features selection and clustering using mixture models

Description

As described in xx paper

Usage

SimulationStudy1(sEEd = 999, no.ppl= 1000)

Arguments

sEED	Positive integer; denoting the random generator state for number random generation (see ?set.seed).
no.ppl	Positive integer; Number of participants to simulate normalised gene expression data.

Details

First simulation for FSPmix as described in xx.

Value

dat	data.frame object of the 20 simulated gene expressions (columns) for no.ppl (rows). Additional columns include participant identifier and latent classification as group.
plot.ColouredCoded.genes	ggplot object of the density of the 20 features coloured coded into 2 classifications.
plot.WhatFSPmixSees	ggplot object of uncoloured densities of the distributions that FSPmix will categorise into either 'A' or 'B' groups.

Author(s)

Marcela Cespedes

Examples

op<- SimulationStudy1(sEEd = 487, no.ppl = 1000)

head(op$dat)

# View 20 simulated genes (features) coloured coded into groups 'A' and 'B'
op$plot.ColouredCoded.genes

# View 20 simulated genes (features) densities
op$plot.WhatFSPmixSees

MarcelaCespedes/FSPmix documentation built on May 12, 2020, 5:49 p.m.