plot_maker: Function to plot matches from match_maker output

In PCAmatchR: Match Cases to Controls Based on Genotype Principal Components

Function to plot matches from match_maker output

Description

Function to plot matches from match_maker output

Usage

plot_maker(
  data = NULL,
  x_var = NULL,
  y_var = NULL,
  case_control = NULL,
  line = T,
  ...
)

Arguments

data	match_maker output
x_var	Principal component 1
y_var	Principal component 2
case_control	Case or control status
line	draw line
...	Arguments passed to plot

Value

None

Examples

# run match_maker()
# Create PC data frame by subsetting provided example dataset
pcs <- as.data.frame(PCs_1000G[,c(1,5:24)])
# Create eigenvalues vector using example dataset
eigen_vals <- c(eigenvalues_1000G)$eigen_values
# Create full eigenvalues vector using example dataset
all_eigen_vals<- c(eigenvalues_all_1000G)$eigen_values
# Create Covarite data frame
cov_data <- PCs_1000G[,c(1:4)]
# Generate a case status variable using ESN 1000 Genome population
cov_data$case <- ifelse(cov_data$pop=="ESN", c(1), c(0))
# With 1 to 1 matching
 if(requireNamespace("optmatch", quietly = TRUE)){
 library(optmatch)
 match_maker_output<- match_maker(PC = pcs,
                                 eigen_value = eigen_vals,
                                 data = cov_data,
                                 ids = c("sample"),
                                 case_control = c("case"),
                                 num_controls = 1,
                                 eigen_sum = sum(all_eigen_vals),
                                 weight_dist=TRUE
                                 )

# run plot_maker()
 plot_maker(data=match_maker_output,
            x_var="PC1",
            y_var="PC2",
            case_control="case",
            line=TRUE)
 }

PCAmatchR documentation built on Dec. 1, 2022, 1:33 a.m.