BibTex format
@misc{Andrew,
author = {Andrew, T},
title = {Genome-wide linkage scans and basic bioinformatics implemented using Stata/SE},
type = {Scholarly edition},
}
Publications
Citation
RIS format (EndNote, RefMan)
TY - GEN
AB - Searches for genes using linkage analyses with genetic markers placed acrossthe entire human genome are hypothesis-free experiments, which represent anextreme form of multiple testing. As such, the low p-values required to obtainnominal significance make accurate diagnostics essential to assess model fitand to eliminate naive incorrect results. In hypothesis-driven single tests,researchers usually take good care to assess model fit and the validity ofmodel assumptions, but such concerns are usually ignored when it comes tolinkage analysis. This is particularly problematic where low thresholds (p > 0.0001)can result in extreme sensitivity to outlying observations and for somemodels (e.g. standard variance component analysis), greater sensitivity toviolation of model assumptions.Here we attempt to address these problems for genomic data based on 1300healthy sib-pairs (dizygotic twins) using modified Haseman-Elstonregression-based linkage analysis for quantitative traits, in which sib-pairphenotypic covariance is correlated with genetic marker covariance. Thestatistical theory underpinning the implementation of tests for linkage usinggeneralized linear models (GLM) (Author-Email: glm in Stata) is documented in detail elsewhere. In brief, the advantage ofanalysing sib-pairs using GLM is that the approach shares all of the strengthsof OLS and variance components, but none of their weaknesses. These are that(1) unlike OLS, the residual errors are correctly specified with a gammadistribution and known heteroscedasticity is accounted for; (2) unlike standardvariance components, by freely estimating the coefficient of variation, GLM is robust tophenotypic deviations from multivariate normality.Just as important are the practical advantages. With the release ofStata8/Special Edition for large datasets, we have been able to store and checkgenetic markers for all 22 pairs of autosomal chromosomes plus sex chromosomes. In addition, we have generated 2-pointand multipoint al
AU - Andrew,T
TI - Genome-wide linkage scans and basic bioinformatics implemented using Stata/SE
ER -