English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

With genotyping of high-density single nucleotide polymorphisms (SNPs) replacing that of microsatellite markers in linkage studies, it becomes possible to accurately determine the genomic regions shared identity by descent (IBD) by family members. In addition to evaluating the likelihood of linkage for a region with the underlining disease (the LOD score approach), an appropriate question to ask is what would be the expected number and sizes of IBD regions among the affecteds, as there could be more than one region reaching the maximum achievable LOD score for a given family. Here, we introduce a computer program to allow the prediction of the total number of IBD regions among family members and their sizes. Reversely, it can be used to predict the portion of the genome that can be excluded from consideration according to the family size and user-defined inheritance mode and penetrance. Such information has implications on the feasibility of conducting linkage analysis on a given family of certain size and structure or on a few small families when interfamily homogeneity can be assumed. It can also help determine the most relevant members to be genotyped for such a study. Simulation results showed that the IBD regions containing true mutations are usually larger than regions IBD due to random chance. We have made use of this feature in our program to allow evaluation of the identified IBD regions based on Bayesian probability calculation and simulation results.

Predicting the number and sizes of IBD regions among family members and evaluating the family size requirement for linkage studies