I'm starting working with GAPIT for GWAS. Here is an error that I get while trying to run. the simplest GLM with my data:
"[1] "GD does not mach GM in Manhattan !!!"
Error in [.data.frame(GD, , !is.na(GI.MP[, 3])) :
undefined columns selected
In addition: Warning messages:
1: In rm(eig.L) : object 'eig.L' not found
2: In merge.data.frame(gs.blup, BLUE, by.x = "Taxa", by.y = "Taxa") :
column names ‘NA’, ‘NA’ are duplicated in the result"
Here is the code I've used:
myY <- read.table("populus_alive_pheno.csv", sep = ";", header = TRUE)
myG <- read.table("populus_test_new1.csv", sep= ";", header = FALSE)
dir.create(file.path(main_dir, "/res"))
setwd(paste(main_dir, "/res", sep=""))
myGAPIT_GLM0 <- GAPIT(
Y = myY[, 1:2],
G = myG,
SNP.MAF = 0.05,
SNP.fraction = 0, ## NO kinship
PCA.total = 0, ## no pop struct
Model.selection = FALSE,
model = "GLM",
Geno.View.output = FALSE ## required when too much SNPs
)
After running this code, GAPIT makes some phenotype statistics graphs, makes QQplot and Genomewise Manhattan, but stops when it comes to chromosome wide Manhattan.
I asked my colleague what can be the problem, and I was said that this error occurs due to different number of samples in genotype file and phenotype file. Browsing the internet, I found the same. But I've checked my data, there are 63 rows (samples) in the pheno file, and 74 columns (11 obligatory GAPIT columns + 63 samples) in the genotype file.
I attach screenshots of heads my datasets in case there is still some problem with them.
