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HRS_plotting.Rmd
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---
title: "HRS plotting"
author:
- name: Alex Diaz-Papkovich
affiliation:
- &cruk Quantitative Life Sciences, McGill University, Montreal, Canada
date: '`r format(Sys.Date(), "%Y-%B-%d")`'
output:
html_notebook:
df_print: paged
code_folding: show
toc: yes
toc_float:
collapsed: false
smooth_scroll: false
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```
## HRS admixture plots
teeeeeext
## Including Plots
```{r}
library(tidyverse)
library(ggplot2)
library(Ternary)
library(dplyr)
```
# Import the HRS auxiliary data and projection to use.
```{r}
# Auxiliary data
hrs_aux_data <- read.csv("/Volumes/Stockage/alex/hrs/aux/HRS_aux.csv")
# Projection
fname <- "HRS_1000G_NP1_UMAP_PC10_NC2_NN15_MD0.5_pca_1kgp_onto_hrs_umap_1kgp_onto_hrs_2018112221116"
proj_dir <- "/Volumes/Stockage/alex/gt-dimred/np1/projections"
hrs_1kgp_proj <- read.table(paste(proj_dir, fname, sep="/"))
# This is HRS+1KGP data; first 12,454 are HRS
hrs_proj <- hrs_1kgp_proj[1:12454,]
# Merge the tables
hrs_full_data <- cbind(hrs_aux_data, hrs_proj)
# RGB colours from admixture
hrs_full_data$rgb_vals <- rgb(hrs_full_data$ADMIX1*255,
hrs_full_data$ADMIX2*255,
hrs_full_data$ADMIX3*255,
maxColorValue = 255)
```
```{r}
# legends
require(RColorBrewer)
#pcol=brewer.pal(9, "Set1")
AncCol=c("#FF0000","#00FF00","#0000FF")
AncRGB=col2rgb(AncCol)/255
#pdf("UMAP_ternary_plot_legend.pdf",height=2.375,width=2.375,pointsize=10)
par(mar=c(2.1,2.1,0.1,0.1))
TernaryPlot(alab=expression(''%->% "African ancestry (%)" %->% ''),blab=expression(''%->%"European ancestry (%)" %->% ''),clab=expression(''%<-% "Asian/Native American ancestry (%)" %<-% ''),lab.cex=1,axis.cex = 0.8)
dx=0.01;
cnt=0
bk=0;
for(xi in seq(0,1,length=round(1/dx))){
for(yi in seq(0,1,length=round(1/dx))){
for(zi in seq(0,1,length=round(1/dx))){
if(abs(1-(xi+yi+zi)) < 1e-8){
ired = xi*AncRGB[1,1] + yi*AncRGB[1,2] + zi*AncRGB[1,3]
igreen = xi*AncRGB[2,1] + yi*AncRGB[2,2] + zi*AncRGB[2,3]
iblue = xi*AncRGB[3,1] + yi*AncRGB[3,2] + zi*AncRGB[3,3]
AddToTernary(points,c(xi,yi,zi),col=rgb(ired,igreen,iblue,1),pch=20)
cnt=cnt+1
}
}
}
}
# legends
require(RColorBrewer)
#pcol=brewer.pal(9, "Set1")
AncCol=c("#FF0000","#0000FF","#00FF00")
AncRGB=col2rgb(AncCol)/255
#pdf("UMAP_ternary_plot_legend.pdf",height=2.375,width=2.375,pointsize=10)
par(mar=c(2.1,2.1,0.1,0.1))
TernaryPlot(alab=expression(''%->% "African ancestry (%)" %->% ''),blab=expression(''%->%"European ancestry (%)" %->% ''),clab=expression(''%<-% "Asian/Native American ancestry (%)" %<-% ''),lab.cex=1,axis.cex = 0.8)
dx=0.01;
cnt=0
bk=0;
for(xi in seq(0,1,length=round(1/dx))){
for(yi in seq(0,1,length=round(1/dx))){
for(zi in seq(0,1,length=round(1/dx))){
if(abs(1-(xi+yi+zi)) < 1e-8){
ired = xi*AncRGB[1,1] + yi*AncRGB[1,2] + zi*AncRGB[1,3]
igreen = xi*AncRGB[2,1] + yi*AncRGB[2,2] + zi*AncRGB[2,3]
iblue = xi*AncRGB[3,1] + yi*AncRGB[3,2] + zi*AncRGB[3,3]
AddToTernary(points,c(xi,yi,zi),col=rgb(ired,igreen,iblue,1),pch=20)
cnt=cnt+1
}
}
}
}
```
```{r}
out_dir <- "/Volumes/Stockage/alex/hrs_1000G/images/for_export/alt_colours"
fname <- "HRS_1000G_NP1_UMAP_PC10_NC2_NN15_MD05_pca_1kgp_onto_hrs_umap_1kgp_onto_hrs_2018112221116_birth"
p_hrs_birth <- ggplot(hrs_full_data, aes(x=V1, y=V2, col=BirthRegionName)) +
geom_point(alpha=0.6, size=0.1) +
theme(
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.background = element_rect(fill = "transparent",colour = NA),
plot.background = element_rect(fill = "transparent",colour = NA),
axis.title.y=element_blank(),
axis.text.y=element_blank(),
axis.ticks.y=element_blank(),
axis.title.x=element_blank(),
axis.text.x=element_blank(),
axis.ticks.x=element_blank(),
legend.position="bottom",
legend.title=element_blank()) +
guides(colour = guide_legend(override.aes = list(size=4, alpha = 1)))
p_hrs_birth
ggsave(paste(out_dir, "/", fname, ".jpeg", sep=""), height=h, width=w, units=u)
```
```{r}
p_hrs <- ggplot(hrs_full_data, aes(x=V1, y=V2, col=rgb(hrs_full_data$ADMIX1*255,
hrs_full_data$ADMIX2*255,
hrs_full_data$ADMIX3*255,
maxColorValue = 255))) +
geom_point(alpha=0.6, size=0.1) +
scale_color_identity() +
theme(
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.background = element_rect(fill = "transparent",colour = NA),
plot.background = element_rect(fill = "transparent",colour = NA),
axis.title.y=element_blank(),
axis.text.y=element_blank(),
axis.ticks.y=element_blank(),
axis.title.x=element_blank(),
axis.text.x=element_blank(),
axis.ticks.x=element_blank())
p_hrs
```
# Alternate colourings
```{r}
out_dir <- "/Volumes/Stockage/alex/hrs_1000G/images/for_export/alt_colours"
fname <- "HRS_1000G_NP1_UMAP_PC10_NC2_NN15_MD05_pca_1kgp_onto_hrs_umap_1kgp_onto_hrs_2018112221116_admix"
# dimensions
h <- 120.4
w <- 186.0
# units
u <- "mm"
p_hrs <- ggplot(hrs_full_data, aes(x=V1, y=V2, col=rgb(hrs_full_data$ADMIX1*255,
hrs_full_data$ADMIX2*255,
hrs_full_data$ADMIX3*255,
maxColorValue = 255))) +
geom_point(alpha=0.6, size=0.1) +
scale_color_identity() +
theme(
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.background = element_rect(fill = "transparent",colour = NA),
plot.background = element_rect(fill = "transparent",colour = NA),
axis.title.y=element_blank(),
axis.text.y=element_blank(),
axis.ticks.y=element_blank(),
axis.title.x=element_blank(),
axis.text.x=element_blank(),
axis.ticks.x=element_blank())
p_hrs
ggsave(paste(out_dir, "/", fname, "123.jpeg", sep=""), height=h, width=w, units=u)
p_hrs <- ggplot(hrs_full_data, aes(x=V1, y=V2, col=rgb(hrs_full_data$ADMIX1*255,
hrs_full_data$ADMIX3*255,
hrs_full_data$ADMIX2*255,
maxColorValue = 255))) +
geom_point(alpha=0.6, size=0.1) +
scale_color_identity() +
theme(
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.background = element_rect(fill = "transparent",colour = NA),
plot.background = element_rect(fill = "transparent",colour = NA),
axis.title.y=element_blank(),
axis.text.y=element_blank(),
axis.ticks.y=element_blank(),
axis.title.x=element_blank(),
axis.text.x=element_blank(),
axis.ticks.x=element_blank())
p_hrs
ggsave(paste(out_dir, "/", fname, "132.jpeg", sep=""), height=h, width=w, units=u)
p_hrs <- ggplot(hrs_full_data, aes(x=V1, y=V2, col=rgb(hrs_full_data$ADMIX2*255,
hrs_full_data$ADMIX1*255,
hrs_full_data$ADMIX3*255,
maxColorValue = 255))) +
geom_point(alpha=0.6, size=0.1) +
scale_color_identity() +
theme(
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.background = element_rect(fill = "transparent",colour = NA),
plot.background = element_rect(fill = "transparent",colour = NA),
axis.title.y=element_blank(),
axis.text.y=element_blank(),
axis.ticks.y=element_blank(),
axis.title.x=element_blank(),
axis.text.x=element_blank(),
axis.ticks.x=element_blank())
p_hrs
ggsave(paste(out_dir, "/", fname, "213.jpeg", sep=""), height=h, width=w, units=u)
p_hrs <- ggplot(hrs_full_data, aes(x=V1, y=V2, col=rgb(hrs_full_data$ADMIX2*255,
hrs_full_data$ADMIX3*255,
hrs_full_data$ADMIX1*255,
maxColorValue = 255))) +
geom_point(alpha=0.6, size=0.1) +
scale_color_identity() +
theme(
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.background = element_rect(fill = "transparent",colour = NA),
plot.background = element_rect(fill = "transparent",colour = NA),
axis.title.y=element_blank(),
axis.text.y=element_blank(),
axis.ticks.y=element_blank(),
axis.title.x=element_blank(),
axis.text.x=element_blank(),
axis.ticks.x=element_blank())
p_hrs
ggsave(paste(out_dir, "/", fname, "231.jpeg", sep=""), height=h, width=w, units=u)
p_hrs <- ggplot(hrs_full_data, aes(x=V1, y=V2, col=rgb(hrs_full_data$ADMIX3*255,
hrs_full_data$ADMIX1*255,
hrs_full_data$ADMIX2*255,
maxColorValue = 255))) +
geom_point(alpha=0.6, size=0.1) +
scale_color_identity() +
theme(
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.background = element_rect(fill = "transparent",colour = NA),
plot.background = element_rect(fill = "transparent",colour = NA),
axis.title.y=element_blank(),
axis.text.y=element_blank(),
axis.ticks.y=element_blank(),
axis.title.x=element_blank(),
axis.text.x=element_blank(),
axis.ticks.x=element_blank())
p_hrs
ggsave(paste(out_dir, "/", fname, "312.jpeg", sep=""), height=h, width=w, units=u)
p_hrs <- ggplot(hrs_full_data, aes(x=V1, y=V2, col=rgb(hrs_full_data$ADMIX3*255,
hrs_full_data$ADMIX2*255,
hrs_full_data$ADMIX1*255,
maxColorValue = 255))) +
geom_point(alpha=0.6, size=0.1) +
scale_color_identity() +
theme(
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.background = element_rect(fill = "transparent",colour = NA),
plot.background = element_rect(fill = "transparent",colour = NA),
axis.title.y=element_blank(),
axis.text.y=element_blank(),
axis.ticks.y=element_blank(),
axis.title.x=element_blank(),
axis.text.x=element_blank(),
axis.ticks.x=element_blank())
p_hrs
ggsave(paste(out_dir, "/", fname, "321.jpeg", sep=""), height=h, width=w, units=u)
```
# Same, but for Hispanic data
```{r}
# Auxiliary data
#hrs_aux_data <- read.csv("/Volumes/Stockage/alex/hrs/aux/HRS_aux.csv")
# Projection
fname <- "HRS_1000G_NP1_UMAP_PC7_NC2_NN15_MD0.5_pca_hrshisp_added1kgp_2018115153245"
proj_dir <- "/Volumes/Stockage/alex/gt-dimred/np1/projections"
hrs_hisp_1kgp_proj <- read.table(paste(proj_dir, fname, sep="/"))
# Only the first 12,454 are HRS.
# Note that we did the projection with all the HRS (so we can also project the other HRS onto Hisps)
hrs_hisp_1kgp_proj <- hrs_hisp_1kgp_proj[1:12454,]
# Merge the tables
hrs_hisp_data <- cbind(hrs_aux_data, hrs_hisp_1kgp_proj)
# Reduce to just Hispanic individuals
hrs_hisp_data <- subset(hrs_hisp_data, HispanicStatus=="Hispanic")
# RGB colours from admixture
hrs_hisp_data$rgb_vals <- rgb(hrs_hisp_data$ADMIX1*255,
hrs_hisp_data$ADMIX2*255,
hrs_hisp_data$ADMIX3*255,
maxColorValue = 255)
```
# Create beautiful plots!
```{r}
out_dir <- "/Volumes/Stockage/alex/hrs_1000G/images/for_export/alt_colours"
fname <- "HRS_1000G_NP1_UMAP_PC7_NC2_NN15_MD05_pca_hrshisp_added1kgp_2018115153245_admix"
# dimensions
h <- 154.6
w <- 169.2
# units
u <- "mm"
# point size
s <- 0.5
p_hrs <- ggplot(hrs_hisp_data, aes(x=V1, y=V2, col=rgb(hrs_hisp_data$ADMIX1*255,
hrs_hisp_data$ADMIX2*255,
hrs_hisp_data$ADMIX3*255,
maxColorValue = 255))) +
geom_point(alpha=0.6, size=s) +
scale_color_identity() +
theme(
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.background = element_rect(fill = "transparent",colour = NA),
plot.background = element_rect(fill = "transparent",colour = NA),
axis.title.y=element_blank(),
axis.text.y=element_blank(),
axis.ticks.y=element_blank(),
axis.title.x=element_blank(),
axis.text.x=element_blank(),
axis.ticks.x=element_blank())
p_hrs
ggsave(paste(out_dir, "/", fname, "123_hisp.jpeg", sep=""), height=h, width=w, units=u)
p_hrs <- ggplot(hrs_hisp_data, aes(x=V1, y=V2, col=rgb(hrs_hisp_data$ADMIX1*255,
hrs_hisp_data$ADMIX3*255,
hrs_hisp_data$ADMIX2*255,
maxColorValue = 255))) +
geom_point(alpha=0.6, size=s) +
scale_color_identity() +
theme(
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.background = element_rect(fill = "transparent",colour = NA),
plot.background = element_rect(fill = "transparent",colour = NA),
axis.title.y=element_blank(),
axis.text.y=element_blank(),
axis.ticks.y=element_blank(),
axis.title.x=element_blank(),
axis.text.x=element_blank(),
axis.ticks.x=element_blank())
p_hrs
ggsave(paste(out_dir, "/", fname, "132_hisp.jpeg", sep=""), height=h, width=w, units=u)
p_hrs <- ggplot(hrs_hisp_data, aes(x=V1, y=V2, col=rgb(hrs_hisp_data$ADMIX2*255,
hrs_hisp_data$ADMIX1*255,
hrs_hisp_data$ADMIX3*255,
maxColorValue = 255))) +
geom_point(alpha=0.6, size=s) +
scale_color_identity() +
theme(
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.background = element_rect(fill = "transparent",colour = NA),
plot.background = element_rect(fill = "transparent",colour = NA),
axis.title.y=element_blank(),
axis.text.y=element_blank(),
axis.ticks.y=element_blank(),
axis.title.x=element_blank(),
axis.text.x=element_blank(),
axis.ticks.x=element_blank())
p_hrs
ggsave(paste(out_dir, "/", fname, "213_hisp.jpeg", sep=""), height=h, width=w, units=u)
p_hrs <- ggplot(hrs_hisp_data, aes(x=V1, y=V2, col=rgb(hrs_hisp_data$ADMIX2*255,
hrs_hisp_data$ADMIX3*255,
hrs_hisp_data$ADMIX1*255,
maxColorValue = 255))) +
geom_point(alpha=0.6, size=s) +
scale_color_identity() +
theme(
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.background = element_rect(fill = "transparent",colour = NA),
plot.background = element_rect(fill = "transparent",colour = NA),
axis.title.y=element_blank(),
axis.text.y=element_blank(),
axis.ticks.y=element_blank(),
axis.title.x=element_blank(),
axis.text.x=element_blank(),
axis.ticks.x=element_blank())
p_hrs
ggsave(paste(out_dir, "/", fname, "231_hisp.jpeg", sep=""), height=h, width=w, units=u)
p_hrs <- ggplot(hrs_hisp_data, aes(x=V1, y=V2, col=rgb(hrs_hisp_data$ADMIX3*255,
hrs_hisp_data$ADMIX1*255,
hrs_hisp_data$ADMIX2*255,
maxColorValue = 255))) +
geom_point(alpha=0.6, size=s) +
scale_color_identity() +
theme(
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.background = element_rect(fill = "transparent",colour = NA),
plot.background = element_rect(fill = "transparent",colour = NA),
axis.title.y=element_blank(),
axis.text.y=element_blank(),
axis.ticks.y=element_blank(),
axis.title.x=element_blank(),
axis.text.x=element_blank(),
axis.ticks.x=element_blank())
p_hrs
ggsave(paste(out_dir, "/", fname, "312_hisp.jpeg", sep=""), height=h, width=w, units=u)
p_hrs <- ggplot(hrs_hisp_data, aes(x=V1, y=V2, col=rgb(hrs_hisp_data$ADMIX3*255,
hrs_hisp_data$ADMIX2*255,
hrs_hisp_data$ADMIX1*255,
maxColorValue = 255))) +
geom_point(alpha=0.6, size=s) +
scale_color_identity() +
theme(
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.background = element_rect(fill = "transparent",colour = NA),
plot.background = element_rect(fill = "transparent",colour = NA),
axis.title.y=element_blank(),
axis.text.y=element_blank(),
axis.ticks.y=element_blank(),
axis.title.x=element_blank(),
axis.text.x=element_blank(),
axis.ticks.x=element_blank())
p_hrs
ggsave(paste(out_dir, "/", fname, "321_hisp.jpeg", sep=""), height=h, width=w, units=u)
```
```{r}
library('Ternary')
require(RColorBrewer)
#pcol=brewer.pal(9, "Set1")
AncCol=c("#4DAF4A","#E41A1C","#377EB8")
AncRGB=col2rgb(AncCol)/255
#pdf("UMAP_ternary_plot_legend.pdf",height=2.375,width=2.375,pointsize=10)
par(mar=c(2.1,2.1,0.1,0.1))
TernaryPlot(alab=expression(''%->% "African ancestry (%)" %->% ''),blab=expression(''%->%"European ancestry (%)" %->% ''),clab=expression(''%<-% "Native American ancestry (%)" %<-% ''),lab.cex=0.6,axis.cex = 0.5)
dx=0.01;
cnt=0
bk=0;
for(xi in seq(0,1,length=round(1/dx))){
for(yi in seq(0,1,length=round(1/dx))){
for(zi in seq(0,1,length=round(1/dx))){
if(abs(1-(xi+yi+zi)) < 1e-8){
ired = xi*AncRGB[1,1] + yi*AncRGB[1,2] + zi*AncRGB[1,3]
igreen = xi*AncRGB[2,1] + yi*AncRGB[2,2] + zi*AncRGB[2,3]
iblue = xi*AncRGB[3,1] + yi*AncRGB[3,2] + zi*AncRGB[3,3]
AddToTernary(points,c(xi,yi,zi),col=rgb(ired,igreen,iblue,1),pch=20)
cnt=cnt+1
}
}
}
}
```
```{r}
tern_data <- select(hrs_full_data,ADMIX1*255,ADMIX2*255,ADMIX3*255)
p_tern <- ggtern() +
geom_point(data=data.frame(x=255,y=255,z=255), aes(x,y,z))
p_tern
```