Accurate and Robust Prediction of Genetic Relationship from Whole-Genome Sequences

Hong Li, Gustavo Glusman, Chad Huff, Juan Caballero and Jared C Roach

PLOS ONE, 2014, vol. 9, issue 2, 1-6

Abstract: Computing the genetic relationship between two humans is important to studies in genetics, genomics, genealogy, and forensics. Relationship algorithms may be sensitive to noise, such as that arising from sequencing errors or imperfect reference genomes. We developed an algorithm for estimation of genetic relationship by averaged blocks (GRAB) that is designed for whole-genome sequencing (WGS) data. GRAB segments the genome into blocks, calculates the fraction of blocks sharing identity, and then uses a classification tree to infer 1st- to 5th- degree relationships and unrelated individuals. We evaluated GRAB on simulated and real sequenced families, and compared it with other software. GRAB achieves similar performance, and does not require knowledge of population background or phasing. GRAB can be used in workflows for identifying unreported relationships, validating reported relationships in family-based studies, and detection of sample-tracking errors or duplicate inclusion. The software is available at familygenomics.systemsbiology.net/grab.

Date: 2014
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0085437 (text/html)
https://journals.plos.org/plosone/article/file?id= ... 85437&type=printable (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0085437

DOI: 10.1371/journal.pone.0085437

Access Statistics for this article

More articles in PLOS ONE from Public Library of Science
Bibliographic data for series maintained by plosone ().