In kridsadakorn/ipcaps2: Iterative Pruning to Capture Population Structure version 2

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

Here set up

library(IPCAPS2)
library(KRIS)

BED.file <- system.file("extdata", "ipcaps_example.bed", package = "IPCAPS2")
BIM.file <- system.file("extdata", "ipcaps_example.bim", package = "IPCAPS2")
FAM.file <- system.file("extdata", "ipcaps_example.fam", package = "IPCAPS2")
LABEL.file <- system.file("extdata", "ipcaps_example_individuals.txt.gz", package = "IPCAPS2")

simsnp <- read.bed(BED.file, BIM.file, FAM.file)
PCs <- cal.pc.linear(simsnp$snp, data.type = "snp", no.pc = 3)
to_plot = as.data.frame(PCs$PC[,1:2])
colnames(to_plot) <- c("PC1", "PC2")

There cluster

res1 <- ipcaps2(bed = BED.file, 
                label.file = LABEL.file, 
                lab.col = 2, 
                out = tempdir(), 
                silence = TRUE, 
                method = "mix")

table(res1$cluster$label, res1$cluster$group)

plot3views.ipcaps(res1)

Here all methods

#res1 <- ipcaps2(bed = BED.file, label.file = LABEL.file, lab.col = 2, out = tempdir(), silence = TRUE, method = "mix")
res2 <- ipcaps2(bed = BED.file, 
                label.file = LABEL.file, 
                lab.col = 2, 
                out = tempdir(), 
                silence = TRUE, 
                method = "pam")

table(res2$cluster$label, res2$cluster$group)

plot3views.ipcaps(res2)

res3 <- ipcaps2(bed = BED.file, 
                label.file = LABEL.file, 
                lab.col = 2, 
                out = tempdir(), 
                silence = TRUE, 
                method = "mixmod")

table(res3$cluster$label, res3$cluster$group)

plot3views.ipcaps(res3)

res4 <- ipcaps2(bed = BED.file, 
                label.file = LABEL.file, 
                lab.col = 2, 
                out = tempdir(), 
                silence = TRUE, 
                method = "meanshift")

table(res4$cluster$label, res4$cluster$group)

plot3views.ipcaps(res4)

res5 <- ipcaps2(bed = BED.file, 
                label.file = LABEL.file, 
                lab.col = 2, 
                out = tempdir(), 
                silence = TRUE, 
                method = "apcluster")

table(res5$cluster$label, res5$cluster$group)

plot3views.ipcaps(res5)

res6 <- ipcaps2(bed = BED.file, 
                label.file = LABEL.file, 
                lab.col = 2, 
                out = tempdir(), 
                silence = TRUE, 
                method = "hclust")

table(res6$cluster$label, res6$cluster$group)

plot3views.ipcaps(res6)

res7 <- ipcaps2(bed = BED.file, 
                label.file = LABEL.file, 
                lab.col = 2, 
                out = tempdir(), 
                silence = TRUE, 
                method = "rubikclust")

table(res7$cluster$label, res7$cluster$group)

plot3views.ipcaps(res7)

res8 <- ipcaps2(bed = BED.file, 
                label.file = LABEL.file, 
                lab.col = 2, 
                out = tempdir(), 
                silence = TRUE, 
                method = "clara")

table(res8$cluster$label, res8$cluster$group)

plot3views.ipcaps(res8)

res9 <- ipcaps2(bed = BED.file, 
                label.file = LABEL.file, 
                lab.col = 2, 
                out = tempdir(), 
                silence = TRUE, 
                method = "kmeans")

table(res9$cluster$label, res9$cluster$group)

plot3views.ipcaps(res9)

res10 <- ipcaps2(bed = BED.file, 
                 label.file = LABEL.file, 
                 lab.col = 2, 
                 out = tempdir(), 
                 silence = TRUE, 
                 method = "dbscan")

table(res10$cluster$label, res10$cluster$group)

plot3views.ipcaps(res10)

kridsadakorn/ipcaps2 documentation built on June 11, 2022, 8:35 p.m.