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How to screen for regions under selection based on XPCLR values #106

@lvqiang0120

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@lvqiang0120

Hi, I recently used the Python version of XPCLR to calculate XPCLR scores between two populations, and I have some questions about the results.
First, In the result file with 13 columns: id, chrom, start, stop, pos_start, pos_stop, modelL, nullL, sel_coef, nSNPs, nSNPs_avail, xpclr, and xpclr_norm, is the 12th column (xpclr) the final XPCLR score?

Second, I've noticed in some articles that authors calculated XPCLR scores within non-overlapping 10-kb sliding windows across the genome. And They then merged adjacent windows , but I'm not quite sure why they merged adjacent windows and how to do it. For example, in the Methods section of Reference 1:
"Mean XP-CLR likelihood scores were calculated within nonoverlapping 10-kb sliding windows. Adjacent windows with an average score in the top 20% of the genome-wide average were merged and were further combined if two windows were separated by only one window with a lower score. The maximum window-wise XP-CLR scores were assigned to the merged region as the region-wise score and those with region-wise scores in the top 10% were considered as candidate selective regions."

Can you give me some suggestions? Why the authors merged adjacent windows and how to do it.

Reference 1: Whole-genome resequencing of 445 Lactuca accessions reveals the domestication history of cultivated lettuce; https://doi.org/10.1038/s41588-021-00831-0

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