xinghuq
commented
2 years ago Hi, most likely your "pop_code" in the "pop_code <- read.gdsn(index.gdsn(genofile, "sample.annot"))" ”pop_code <- read.gdsn(index.gdsn(genofile, path="sample.annot/pop_file"))“ are not uniquely pop factors. Please check these pop_code first, and see what are they. Please use your own real pop labels instead from "”pop_code <- read.gdsn(index.gdsn(genofile, path="sample.annot/pop_file"))“", make sure that knn < the minimum number of individuals in a pop.
Cheers,
Xinghu
MarcGose
Hello,
I wanted to try out klfdapc on my SNP dataset, following the tutorial on this Github. Everything seems to work fine until the kfldapc step, where I get the error "Error in matrix(1, N, M) : non-numeric matrix extent"
I tried assigning random labels as in the SARS-Cov-2 tutorial and this worked, so I reckon it must be something with my population codes, but I can't seem to figure out what it is. I would greatly appreciate any help with this.
This is my code:
popsex <- read.table("pop_file.info") pop_file <- popsex$V1
samp.annot <- data.frame(pop_file)
snpgdsVCF2GDS(vcf.fn = "C:/Users/MarcG/OneDrive/Desktop/VCF/WSD_GLs.vcf", out.fn = "WSD_GLs_GDS")
(genofile <- snpgdsOpen("WSD_GLs_GDS", readonly = FALSE))
read.gdsn(index.gdsn(genofile, "sample.id")) read.gdsn(index.gdsn(genofile, "snp.rs.id")) read.gdsn(index.gdsn(genofile, "genotype")) add.gdsn(genofile, "sample.annot", samp.annot) pop_code <- read.gdsn(index.gdsn(genofile, "sample.annot")) pop_code <- read.gdsn(index.gdsn(genofile, path="sample.annot/pop_file")) pop_code=factor(pop_code,levels=unique(pop_code))
pcadata <- SNPRelate::snpgdsPCA(genofile, autosome.only = FALSE)
snpgdsClose(genofile)
normalize <- function(x) { return ((x - min(x)) / (max(x) - min(x))) }
pcanorm=apply(pcadata$eigenvect[,1:20], 2, normalize)
kmat <- kmatrixGauss(pcanorm,sigma=5)
klfdapc=KLFDA(kmat, pop_code, r=3, knn = 2) Error in matrix(1, N, M) : non-numeric matrix extent