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

Linkage analysis is used routinely to map genes for human diseases and conditions. However, the existing linkage-analysis methods require that the diseases or conditions either be dichotomized or measured by a quantitative trait, such as blood pressure for hypertension. In the latter case, normality is generally assumed for the trait. However, many diseases and conditions, such as cancer and mental and behavioral conditions, are rated on ordinal scales. The objective of this study was to establish a framework to conduct linkage analysis for ordinal traits. We propose a latent-variable, proportional-odds logistic model that relates inheritance patterns to the distribution of the ordinal trait. We use the likelihood-ratio test for testing evidence of linkage. By means of simulation studies, we find that the power of our proposed model is substantially higher than that of the binary-trait-based linkage analysis and that our test statistic is robust with regard to certain parameter misspecifications. By using our proposed method, we performed a genome scan of the hoarding phenotype in a data set with 53 nuclear families, which were collected by the Tourette Syndrome Association International Consortium for Genetics (TSAICG). Standard linkage scans using hoarding as a dichotomous trait were also performed by using GENEHUNTER and ALLEGRO. Both GENEHUNTER and ALLEGRO failed to reveal any marker significantly linked to the binary hoarding phenotypes. However, our method identified three markers at 4q34-35 (P = 0.0009), 5q35.2-35.3 (P = 0.0001), and 17q25 (P = 0.0005) that manifest significant allele sharing.

Linkage analysis of ordinal traits for pedigree data