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Inpreppi: An Integrated Evaluation Method Based On Genomic Context For Predicting Protein-Protein Interactions In Prokaryotic Genomes, Jingchun Sun, Yan Sun, Guohui Ding, Qi Liu, Chuan Wang, Youyu He, Tieliu Shi, Yixue Li, Zhongming Zhao

Psychiatry Publications

Background Although many genomic features have been used in the prediction of protein-protein interactions (PPIs), frequently only one is used in a computational method. After realizing the limited power in the prediction using only one genomic feature, investigators are now moving toward integration. So far, there have been few integration studies for PPI prediction; one failed to yield appreciable improvement of prediction and the others did not conduct performance comparison. It remains unclear whether an integration of multiple genomic features can improve the PPI prediction and, if it can, how to integrate these features.

Results In this study, we first …

An Ordered Subset Approach To Including Covariates In The Transmission Disequilibrium Test, Herve Perdry, Brion S. Maher, Marie-Claude Babron, Toby Mchenry, Francoise Clerget-Darpoux, Mary L. Marazita

Psychiatry Publications

Clinical heterogeneity of a disease may reflect an underlying genetic heterogeneity, which may hinder the detection of trait loci. Consequently, many statistical methods have been developed that allow for the detection of linkage and/or association signals in the presence of heterogeneity.

This report describes the work of two parallel investigations into similar approaches to ordered subset analysis, based on an observed covariate, in the framework of family-based association analysis using Genetic Analysis Workshop 15 simulated data.

With an appropriate choice of covariate, both approaches allow detection of two loci that are undetectable by the classical transmission-disequilibrium test. For a third …

Estimating The Number And Size Of The Main Effects In Genome-Wide Case-Control Association Studies, Po-Hsiu Kuo, Jozsef Bukszar, Edwin J.C.G. Van Den Oord

Psychiatry Publications

It has recently become possible to screen thousands of markers to detect genetic causes of common diseases. Along with this potential comes analytical challenges, and it is important to develop new statistical tools to identify markers with causal effects and accurately estimate their effect sizes. Knowledge of the proportion of markers without true effects (p₀) and the effect sizes of markers with effects provides information to control for false discoveries and to design follow-up studies. We apply newly developed methods to simulated Genetic Analysis Workshop 15 genome-wide case-control data sets, including a maximum likelihood (ML) and a …

Linkage Analysis Of A Model Quantitative Trait In Humans: Finger Ridge Count Shows Significant Multivariate Linkage To 5q14.1, Sarah E. Medland, Danuta Z. Loesch, Bogdan Mdzewski, Gu Zhu, Grant W. Montgomery, Nicholas G. Martin

Psychiatry Publications

The finger ridge count (a measure of pattern size) is one of the most heritable complex traits studied in humans and has been considered a model human polygenic trait in quantitative genetic analysis. Here, we report the results of the first genome-wide linkage scan for finger ridge count in a sample of 2,114 offspring from 922 nuclear families. Both univariate linkage to the absolute ridge count (a sum of all the ridge counts on all ten fingers), and multivariate linkage analyses of the counts on individual fingers, were conducted. The multivariate analyses yielded significant linkage to 5q14.1 (Logarithm of odds …