| Title: | FINEMAP-miss: fine-mapping genome-wide association studies with missing genotype information |
| Journal: | Bioinformatics |
| Published: | 9 Nov 2025 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/41206934/ |
| DOI: | https://doi.org/10.1093/bioinformatics/btaf616 |
| URL: | https://academic.oup.com/bioinformatics/article-pdf/41/12/btaf616/65248494/btaf616.pdf |
Publication 18979
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Abstract
MOTIVATION: The most informative genome-wide association studies (GWAS) are meta-analyses that have combined multiple studies to increase the GWAS sample size. Statistical fine-mapping is a key downstream analysis of GWAS to jointly evaluate the probability of causality of all variants in a genomic region of interest. Current fine-mapping methods are miscalibrated in the meta-analysis setting due to variation in sample size across the variants.</p>
RESULTS: We introduce FINEMAP-miss, a new fine-mapping method that extends the FINEMAP model to account for variant-specific missingness. We show that FINEMAP-miss is well-calibrated in meta-analysis simulations where the standard fine-mapping fails. Compared to the summary statistics imputation approach, FINEMAP-miss provides clear improvement when the causal variants have low imputation information or when the sample size or complexity of the meta-analysis setting increase. We successfully apply FINEMAP-miss on a breast cancer GWAS meta-analysis where neither the standard fine-mapping nor the summary statistics imputation are applicable.</p>
AVAILABILITY: An open source implementation of FINEMAP-miss as an R package ("finemapmiss") is available at https://github.com/JoonasKartau/finemapmiss. The archived version of FINEMAP-miss used for this publication can be found on Zenodo at https://doi.org/10.5281/zenodo.17492622.</p>
SUPPLEMENTARY INFORMATION: is available at the journal's web site.</p>
8 Keywords
- Breast Neoplasms
- Chromosome Mapping
- Genome-Wide Association Study
- Genotype
- Humans
- Meta-Analysis as Topic
- Polymorphism, Single Nucleotide
- Software
2 Authors
- Joonas Kartau
- Matti Pirinen
1 Application
| Application ID | Title |
|---|---|
| 22627 | Fine-mapping genotype-phenotype associations |
Enabling scientific discoveries that improve human health