conda - smartpca stalling issue

Hi,

I am having a few issues with running smartpca, which I have installed using conda. The software initially runs successfully, but stalls after the total number of snps killed in pass:xxxxx step.

Please find below the command line transcript in its entirety:

smartpca -p  test.L.pca.par
parameter file: test.L.pca.par
THE INPUT PARAMETERS
PARAMETER NAME: VALUE
genotypename: test.geno
snpname: test.snp
indivname: test.ind
evecoutname: test.pca.evec
evaloutname: test.eval
lsqproject: YES
numoutevec: 4
numthreads: 8
smartpca version: 13050
norm used

lsqproject used
test.snp: genetic distance set from physical distance
nodata:          15:80297900
nodata:          19:27961945
number of samples used: 15 number of snps used: 299440
Using 8 threads, and partial sum lookup algorithm.
 snp            1:1599161 ignored . allelecnt:     0  missing:     2
 snp            1:1780878 ignored . allelecnt:     0  missing:     1
 snp            1:1793071 ignored . allelecnt:     0  missing:     3
 snp            1:1793786 ignored . allelecnt:     0  missing:     1
 snp            1:2222583 ignored . allelecnt:     0  missing:     1
 snp            1:2236697 ignored . allelecnt:     0  missing:     4
 snp            1:3098715 ignored . allelecnt:     0  missing:     1
 snp            1:3168280 ignored . allelecnt:     0  missing:     1
 snp            1:3356405 ignored . allelecnt:     0  missing:     0
 snp            1:3512516 ignored . allelecnt:     0  missing:     0
total number of snps killed in pass: 10948  used: 288492

I have attempted to run smartpca on a number of different datasets, of differing sizes and origins, but the result/lack of result is the same. I have left the program running for a number of weeks, but the command line output does not differ after thirty minutes or so of running.

Is this a known issue? And if so how might I remedy?

Thanks,

William

The report names the smartpca command, parameter file test.L.pca.par, and inputs test.geno, test.snp, and test.ind. Start by reproducing the command and checking where processing stops after the total number of SNPs killed message; done means identifying the cause of the stall and confirming a remedy on the reported datasets.