I have whole genome sequence (human) data (SNP data), but don't have phenotype data ready for any traits yet. Hopefully, I will get real phenotype data soon. To run GWAS (genome-wide-association study) or any other analysis, i want to create artificial/dummy data for any trait, let's say human height. Could anyone please recommend what is best option? Does plink generate any dummy phenotype data? or any other programme?
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2$\begingroup$ You just need to create some random values (either integer for height, or categorical for "disease" or any other trait you want to "test"). What have you tried so far? Why do you need to create it now? If for learning process you might be able to download some GWAS data (take into considerations that it is identifying information so you might find restrictions to download data). $\endgroup$– llrsFeb 19, 2018 at 11:55
1 Answer
Using wakefield package it is pretty easy, here is an example from GitHub page. This will create 500 dummy variables for id, race, age, etc. :
library(wakefield)
myDummyPheno <- r_data_frame(
n = 500,
id,
race,
age,
sex,
hour,
iq,
height,
died
)
# result
myDummyPheno
# # A tibble: 500 x 8
# ID Race Age Sex Hour IQ Height Died
# <chr> <fct> <int> <fct> <S3: times> <dbl> <dbl> <lgl>
# 1 001 Bi-Racial 27 Male 00:00:00 93.0 71.0 F
# 2 002 White 28 Female 00:00:00 104 64.0 T
# 3 003 Black 28 Male 00:00:00 111 67.0 T
# 4 004 Hispanic 35 Male 00:00:00 90.0 67.0 T
# 5 005 Hispanic 21 Female 00:00:00 94.0 70.0 T
# 6 006 Black 35 Male 00:00:00 74.0 73.0 F
# 7 007 Black 27 Male 00:00:00 102 68.0 T
# 8 008 White 28 Female 00:00:00 95.0 70.0 F
# 9 009 White 30 Female 00:00:00 80.0 71.0 F
# 10 010 White 30 Female 00:00:00 114 66.0 T
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