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No sel_coef #59
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Hmm- seems like SNPs are being skipped- but your min SNPs seems very low. Can you share the std out, and maybe a couple of lines from your output file? |
Here is the first couple of the lines from the output file:
Here is what xpclr outputs when its running: This is from the analysis for the first chromosome. The amount of SNPs being excluded is a bit worrying. The vcf files for the phased data is straight from SHAPEIT and I'm wondering if something funky happened when it tried to impute the phased SNPs. |
Yes- that's the issue I think, lack of SNPs. What you need from population 2 is a good estimate of true ancestral allele frequencies. This allows the model to identify large deviations in pop 1 from the "original" frequency. ie fast drift. When this happens several times in the same window- that's good evidence for selection. If you have few samples in pop 2, you don't get a good estimate of ancestral AFs, and your deviations are very stochastic. Here it seems like the majority of your SNPs are fixed in population 2, which gives us no (useful) information about the true ancestral allele frequencies. The only way you can get from 0.0 or 1.0 to an AF between is via a mutation, not via drift. Therefore they are of no value to XPCLR. You probably need larger samples, or alternatively to infer selection perhaps look at something like PBS, which requires an outgroup. |
That makes total sense! Thanks a ton for all of your help. |
Hi @hardingnj, I just have a quick question about the output of xpclr. Whenever I run xpclr I'm not getting a lot of the columns in the output file, mainly the selection coefficient. Xpclr seems to be outputting everything up until the nullL column and then dropping everything else. I just wanted to check with you to see if this is normal or not.
input code:
xpclr --input popn_chr1_phased.vcf --samplesA popn_benthic.txt --samplesB popn_pelagic.txt --chr 1 --minsnps 2 --maxsnps 100 --size 200000 --step 1000 --phased --ld 0.95 --rrate 0.00000008 --out ./popn_sweep_chr1
Any advice would be greatly appreciated!
Matt
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