RHclust (version 2.0.0)

SimData: GE, CPG, SNP, and Covariate Simulated Data

Description

Simulated data generator containing continuous variables representing gene expression (GE) data and DNA methylation data as M-values (GPG), and categorical variable representing single nucleotide polymorphisms (SNP). GE and CPG data are simulated from a normal distribution and SNP data is simulated from a multinomial distribution. Covariate data can have uniformly distributed data or normally distributed. Cluster separation can also be distinct or non-distinct.

Usage

SimData(seed = NULL, gene = 36,
        k = c(33,33,34),
        GEbar = 5, GEsd = 0.5,
        CPGbar = 4, CPGsd = 0.5,
        SameCPG = FALSE, SameSNP = FALSE,
        ProbDist = NULL, SameGeneDist = TRUE,
        distinct=TRUE)

Value

Clusters

Vector of cluster assignment for each subject.

Vec

Numeric representation of values per cluster used for sensitivity measures.

GE

Simulated continuous data for GE. Means of each cluster changes by a factor of 5 with default standard deviation of 0.5.

CPG

Simulated continuous data for CPG. Means of each cluster changes by a factor of 4 with default standard deviation of 0.5.

SNP

Simulated categorical data for SNP.

GE_Index

Index names for GE.

CPG_Index

Index names for CPG.

SNP_Index

Index names for SNP.

Covariates

Simulated data for covariate data. By default contains 10 columns of cateogrical data and 10 columns of numeric data.

Arguments

seed

Set specified seed for reproducibility

gene

Numeric input that specifies the number genes

k

Cluster pattern/distribution across subjects formatted as a vector, i.e. c(33,33,34) representing 33 subjects in the first cluster, 33 in the second cluster, and 34 in the third cluster.

GEbar

Optional numeric input to change the mean distribution of GE data

GEsd

Optional numeric input to change the standard deviation of GE data

CPGbar

Optional numeric input to change the mean distribution of CPG data

CPGsd

Optional numeric input to change the standard deviation of CPG data

SameCPG

Logical value that if set to True sets the distribution of each CPG cluster around the same mean

SameSNP

Logical value that if set to True changes the probability distribution of SNPs to be the same per cluster

ProbDist

Optional list input that allows the change of SNP probability distributions per cluster. Default list stops at 5 cluster distributions. Default ProbDist = list(c(0.50,0.25,0.25), c(0.20,0.55,0.25), c(0.30,0.15,0.55), c(0.20,0.50,0.30), c(0.45,0.20,0.35))

SameGeneDist

Logical that set the covariates to follow the genetic clustering scheme where the data is uniformly distributed amongst each subgroup in each cluster. Or if set to FALSE sets the covariates to be noisy and have no discernible groups.

distinct

Logical that sets the covariate data clusters to be distinct at default, or non-distance when set to FALSE

Author

[e-mail]

Details

SimData creates simulated data that aims to represent real world data for gene expression (GE), DNA methylations (CPG), and single neucleotide polymorphisms (SNP). Covariate data is used to represent other potentially useful health data to further weight the genetics data. The goal of this function is to allow the user the ability to manipulate their data for testing of the VIP() or VIPcov() functions.

Examples

# \donttest{
# Generating simulated data
sd = SimData()

## Specifying seed, genes, and clusters
# sd = SimData(seed = 42, gene = 18, c(10,40,50))

# Specifying probability distribution of SNP data
l = list( c(10, 35, 55),
          c(60, 20, 20),
          c(25, 50, 25))
sd = SimData(1, g = 36, ProbDist = l)

sd = SimData(1, g = 36, c(33,33,34))

# Same SNP distribution across 2 clusters
ssnp = SimData(g = 36, k = c(10,90), SameSNP = TRUE)

# Same CpG distribution across 2 cluster
scpg = SimData(g = 36, k = c(10,90), SameCPG = TRUE)
# }