Efficient strategies for genomic searching using the
affected-pedigree-member method of linkage analysis
D.L. Brown, M.B. Gorin, D.E. Weeks
American Journal of Human Genetics, 54(3),544-552
(Mar 1994)
Abstract
The affected-pedigree-member (APM) method of linkage analysis is a
nonparametric statistic that tests for nonrandom cosegregation of a
disease and marker loci. The APM statistic is based on the
observation that if a marker locus is near a disease-susceptibility
locus, then affected individuals within a family should be more
similar at the marker locus than is expected by chance. The APM
statistic measures marker similarity in terms of identity by state
(IBS) of marker alleles; that is, two alleles are IBS if they are
the same, regardless of their ancestral origin. Since the APM
statistic measures increased marker similarity, it makes no
assumptions concerning how the disease is inherited; this can be an
advantage when dealing with complex diseases for which the mode of
inheritance is difficult to determine. We investigate here the power
of the APM statistic to detect linkage in the context of a
genomewide search. In such a search, the APM statistic is evaluated
at a grid of markers. Then regions with high APM statistics are
investigated more thoroughly by typing more markers in the region.
Using simulated data, we investigate various search strategies and
recommend an optimal search strategy that maximizes the power to
detect linkage while minimizing the false-positive rate and number
of markers. We determine an optimal series of three increasing
cut-points and an independent criterion for significance.
Allele-sharing linkage analysis