| Title: | Exploration of weighting schemes based on allele frequency and annotation for weighted burden association analysis of complex phenotypes |
| Journal: | Gene |
| Published: | 22 Oct 2021 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/34688815/ |
| DOI: | https://doi.org/10.1016/j.gene.2021.146039 |
| URL: | https://discovery.ucl.ac.uk/10139274/3/Curtis_UKBB.annot.unmarked.20211012.pdf |
| Citations: | 6 (5 in last 2 years) as of 8 Aug 2024 |
Publication 4832
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Abstract
Weighted burden analysis can incorporate variants with different frequencies and annotations into a combined test for association between a gene and a phenotype. However there has not been a systematic exploration of which weighting schemes provide maximum power to detect association. Here we assess different weighting schemes using a number of genes for which exome-wide evidence of association with common phenotypes was obtained in 200,000 exome-sequenced UK Biobank participants. We find that there are marked differences in optimal weighting schemes between genes, both with respect to allele frequency and to annotation, implying that there is no "one-size-fits-all" scheme which is generally optimal. It seems helpful to weight rare variants more highly than common ones, to give loss of function variants higher weights than protein-altering variants and to assign higher weights to protein-altering variants predicted to have more severe effects. However with the data currently available it does not seem possible to make more specific recommendations. This research has been conducted using the UK Biobank Resource.1 Author
- David Curtis
Enabling scientific discoveries that improve human health