Yan Holtz, Zhihong Zhu, Julanne Frater, Perry Bartlett, Jian Yang, John McGrath

This file is the first part of the vitamin-D GWAS analysis. What it does:

Create a Phenotype file with vitamin-D + other traits of interest like sex, BMI, height, vitaminD nutrition
Describe Vitamin-D dataset: seasonality, distribution etc.
Create a Phenotype file with the IPAQ Score of UKB people

# We will need a few library to run this document
library(tidyverse)
library(rmarkdown)    # You need this library to run this template.
library(epuRate)      # Install with devtools: install_github("holtzy/epuRate", force=TRUE)
library(xtable)
library(knitr)

Get vitamin-D data and related

The first step is to read the UKB phenotype file and output only a few fields that will interest me. I will keep only:

individual ids (f.eid, column 1)
sex (f.31.0.0, column 8)
height (f.50.0.0, column 22)
bmi (f.21001.0.0, column 4069)
Diastolic blood pressure (f.4079.0.0, column 706)

This work is done on the Inode server, the file I get is transfered locally using ssh.

# good repertory
ssh uqyholtz@inode.qbi.uq.edu.au
cd /ibscratch/wrayvisscher/Yan_Holtz/4_UKB_GWAS/3_BLOOD_GWAS/0_DATA

# Get the good column + repeat the ID + change header to respect plink format
zcat /references/UKBiobank/pheno/download/9280_12505_UKBiobank.tab.gz | awk '{print $1,$1,$8,$22,$4069,$706}' | sed '1 s/^.*$/FID IID f.31.0.0 f.50.0.0 f.21001.0.0 f.4079.0.0/' > pheno.txt
gzip pheno.txt

This make me a file with about 500k lines. (~7M). I transfer it locally.

# Transfert locally
cd /Users/y.holtz/Dropbox/QBI/4_UK_BIOBANK_GWAS_PROJECT/VitaminD-GWAS/0_DATA
scp uqyholtz@inode.qbi.uq.edu.au:/ibscratch/wrayvisscher/Yan_Holtz/4_UKB_GWAS/3_BLOOD_GWAS/0_DATA/pheno.txt.gz .

From my local computer I transfert it on the delta cluster where I will run the GWAS.

# Transfert on Delta
cd /Users/y.holtz/Dropbox/QBI/4_UK_BIOBANK_GWAS_PROJECT/VitaminD-GWAS/0_DATA
scp pheno.txt.gz y.holtz@delta.imb.uq.edu.au:/home/y.holtz/BLOOD_GWAS/0_DATA

Describe Vitamin-D

#Load the file in R
data <- read.table("0_DATA/pheno.txt.gz", header=T, sep=" ")

Dimension

tot <- nrow(data)
blood <- nrow(data[which(!is.na(data$f.4079.0.0)),])

I have 502629 people in the UKB.
Among them 468182 people have info concerning their blood pressure (93.146635 %)

Distribution

Distribution of the distolic blood pressure:

data %>%
  ggplot( aes(x=f.4079.0.0)) +
    geom_density( fill="skyblue", color="skyblue") +
    xlab("Diastolic blood pressure")

IPAQ score phenotype

The IPAQ score is an estimate of outdoor activities. (International Physical Activity Questionnaire Score). It takes into account:

Walking: Number of days/week walked 10+ minutes (Field 864.00) and Duration of walk (field 874.00).
Moderate: Number of days/week of moderate physical activity 10+ minutes (Field 884.00) and Duration of moderate activity (Field 894.00).
Vigorous: Number of days/week of vigorous physical activity 10+ minutes (Field 904.00) and Duration of vigorous activity (Field 914.00).

The sum of them gives the IPAQ score. Let’s compute it in R.

This work is done on the Inode server, the file I get is transfered locally using ssh.

# good repertory
ssh uqyholtz@inode.qbi.uq.edu.au
cd /ibscratch/wrayvisscher/Yan_Holtz/4_UKB_GWAS/3_BLOOD_GWAS/0_DATA

# Get the good column + repeat the ID + change header to respect plink format
zcat /references/UKBiobank/pheno/download/9280_12505_UKBiobank.tab.gz | awk '{print $1,$1,$8,$22,$280,$283,$286,$289,$292,$295}' > tmp

# Transfert locally
cd /Users/y.holtz/Desktop
scp uqyholtz@inode.qbi.uq.edu.au:/ibscratch/wrayvisscher/Yan_Holtz/0_DATA/tmp .

# Open this file in R, and compute IPAQ
R
data <- read.table("tmp.gz",  header=T, sep=" ")
a <- data$`f.864.0.0` * data$`f.874.0.0` * 3.3
b <- data$`f.884.0.0` * data$`f.894.0.0` * 4
c <- data$`f.904.0.0` * data$`f.914.0.0` * 8
data$IPAQ <- a + b + c
colnames(data)[c(1,2)] <- c("FID", "IID")
  
# Number of missing data?
length(which(is.na(data$IPAQ)))

# Save with new score
write.table(data, file="UKB_IPAQ_score.txt", row.names=FALSE, quote=FALSE)

# Send it on Delta
scp  UKB_IPAQ_score.txt  y.holtz@delta.imb.uq.edu.au:/shares/compbio/Group-Wray/YanHoltz/DATA/PHENOTYPE/UKB

A work by Yan Holtz

Yan.holtz.data@gmail.com

Vitamin D blood concentration: phenotype description

Get vitamin-D data and related

Describe Vitamin-D

Dimension

Distribution

Other Vitamin D related traits

IPAQ score phenotype