# External LD Matrices and Fine-Mapping **URL:** https://isgw-forum.colorado.edu/t/external-ld-matrices-and-fine-mapping/912 **Category:** Day 8 **Created:** [June 11, 2026, 10:47pm UTC](https://isgw-forum.colorado.edu/t/external-ld-matrices-and-fine-mapping/912 "2026-06-11T22:47:12Z") **Posts on this page:** 1 **Page:** 1
### Author: ![anonymous](https://isgw-forum.colorado.edu/letter_avatar_proxy/v4/letter/a/8491ac/32.png) [@anonymous](https://isgw-forum.colorado.edu/u/anonymous) #### Post date: [June 11, 2026, 10:47pm UTC](https://isgw-forum.colorado.edu/t/external-ld-matrices-and-fine-mapping/912/1 "2026-06-11T22:47:12Z")
If you don’t have access to the within-sample LD matrix (e.g., using 23andMe sum stats), how can you control for false positives generated by using an external LD matrix. For example: European 23andMe GWAS sum stats LD matrix: 1000 Genomes European HapMap3 LD matrix. > Replying to “If you don’t have access to the within-sample LD m…”: This is a great question and one that regularly crops up - unfortunately there isn’t a way to guarantee that it will be well matched - there is a related issue that meta-analysis can cause some challenges in the behavior of the relationship with LD [related to Simpson’s paradox] - which is nicely laid out in this paper: [Meta-analysis fine-mapping is often miscalibrated at single-variant resolution - PubMed](https://pubmed.ncbi.nlm.nih.gov/36643910/) > Replying to “If you don’t have access to the within-sample LD m…”: You may want to check out the PolyFun paper [Functionally informed fine-mapping and polygenic localization of complex trait heritability | Nature Genetics](https://www.nature.com/articles/s41588-020-00735-5) . They have given good benchmarking for how to choose the best matching LD matrices, and how to mitigate false positives. For example setting the number of causal variants to a lower number, like 2-3, can lower false positive rates. There’s always the option of using ABF > Replying to “If you don’t have access to the within-sample LD m…”: Matching on genetic ancestry as much as possible is important but in general in sample LD is very important