A performance assessment of relatedness inference methods using genome-wide data from thousands of relatives
Monica D Ramstetter,
Thomas D. Dyer,
Donna M. Lehman,
Joanne E. Curran,
Jason G. Mezey,
Amy L. Williams
Posted 04 Feb 2017
bioRxiv DOI: 10.1101/106013 (published DOI: 10.1534/genetics.117.1122)
Posted 04 Feb 2017
Inferring relatedness from genomic data is an essential component of genetic association studies, population genetics, forensics, and genealogy. While numerous methods exist for inferring relatedness, thorough evaluation of these approaches in real data has been lacking. Here, we report an assessment of 12 state-of-the-art pairwise relatedness inference methods using a dataset with 2,485 individuals contained in several large pedigrees that span up to six generations. We find that all methods have high accuracy (92%-99%) when detecting first and second degree relationships, but their accuracy dwindles to less than 43% for seventh degree relationships. However, most IBD segment-based methods inferred seventh degree relatives correct to within one relatedness degree for more than 76% of relative pairs. Overall, the most accurate methods were ERSA and approaches that compute total IBD sharing using the output from GERMLINE and Refined IBD to infer relatedness. Combining information from the most accurate methods provides little accuracy improvement, indicating that novel approaches--such as new methods that leverage relatedness signals from multiple samples--are needed to achieve a sizeable jump in performance.
- Downloaded 1,044 times
- Download rankings, all-time:
- Site-wide: 9,983 out of 84,201
- In genetics: 684 out of 4,422
- Year to date:
- Site-wide: 40,983 out of 84,201
- Since beginning of last month:
- Site-wide: 34,642 out of 84,201
Downloads over time
Distribution of downloads per paper, site-wide
- 18 Dec 2019: We're pleased to announce PanLingua, a new tool that enables you to search for machine-translated bioRxiv preprints using more than 100 different languages.
- 21 May 2019: PLOS Biology has published a community page about Rxivist.org and its design.
- 10 May 2019: The paper analyzing the Rxivist dataset has been published at eLife.
- 1 Mar 2019: We now have summary statistics about bioRxiv downloads and submissions.
- 8 Feb 2019: Data from Altmetric is now available on the Rxivist details page for every preprint. Look for the "donut" under the download metrics.
- 30 Jan 2019: preLights has featured the Rxivist preprint and written about our findings.
- 22 Jan 2019: Nature just published an article about Rxivist and our data.
- 13 Jan 2019: The Rxivist preprint is live!