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 Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

We present an approach, called the "Shadow Method," for the identification ofdisease loci from dense genetic marker maps in complex, potentially incompletepedigrees. "Shadow" is a simple method based on an analysis of the patterns ofobligate meiotic recombination events in genotypic data. This method can beapplied to any high density marker map and was specifically designed to exploitthe fact that extremely dense marker maps are becoming more readily available.We also describe how to interpret and associate meaningful P-Values to theresults. Shadow has significant advantages over traditional parametric linkageanalysis methods in that it can be readily applied even in cases in which thetopology of a pedigree or pedigrees can only be partially determined. Inaddition, Shadow is robust to variability in a range of parameters and inparticular does not require prior knowledge of mode of inheritance, penetranceor clinical misdiagnosis rate. Shadow can be used for any SNP data, but isespecially effective when applied to dense samplings. Our primary example usesdata from Affymetrix 100k SNPChip samples in which we illustrate our approachby analyzing simulated data as well as genome-wide SNP data from two pedigreeswith inherited forms of kidney failure, one of which is compared with a typicalLOD score analysis.

A simple computational method for the identification of disease-associated loci in complex, incomplete pedigrees