cor_plot {GWAS.BAYES} | R Documentation

## cor_plot(SNPs,significant,info = FALSE)

### Description

A function that creates correlation heatmaps for given significant SNPs from a SNP dataframe.

### Usage

    cor_plot(SNPs,significant,info = FALSE)

### Arguments

`SNPs` | A standardized SNP matrix where the columns take on the values of 0 or 1.
`significant` | A vector of 0's or 1's that contain which significant SNP's to look at.
`info` | Default is FALSE. If information such as the chromosome and the position is known, then that can be entered here and will return a correlation heatmap with the labels chromosome - position. The format for this entry is the 2 row dataframe or matrix, where the first row is the chromosome and the second row is the position.

### Value

A correlation heatmap with the axis labels either SNP1 ... or chromosome - position

### Examples

    data("vignette_lm_dat")
    Y <- vignette_lm_dat$Phenotype
    SNPs <- vignette_lm_dat[,-1]
    fullPreprocess <- preprocess_SNPs(SNPs = SNPs,Y = Y,MAF = 0.01,number_cores = 1)
    SNPs <- fullPreprocess$SNPs
    Y <- fullPreprocess$Y
    fullPreprocess$SNPs_Dropped
    principal_comp <- pca_function(SNPs = SNPs,number_components = 1,plot_it = FALSE)
    Significant_SNPs <- preselection(Y = Y, SNPs = SNPs,number_cores = 1, principal_components = principal_comp,frequentist = TRUE,controlrate = "bonferroni",threshold = .05,kinship = FALSE,info = FALSE)

    cor_plot(SNPs = SNPs,significant = Significant_SNPs$Significant,info = FALSE)

[Package GWAS.BAYES version 1.1.0 Index]