Linkage analysis HaploView

The LOD score (logarithm (base 10) of odds), developed by Newton E. Morton, is a statistical test often used for linkage analysis in human, animal, and plant populations. The LOD score compares the likelihood of obtaining the test data if the two loci are indeed linked, to the likelihood of observing the same data purely by chance. Positive LOD scores favor the presence of linkage, whereas negative LOD scores indicate that linkage is less likely.

http://en.wikipedia.org/wiki/Genetic_linkage

The deviation of the observed frequency of a haplotype from the expected is a quantity[2] called the linkage disequilibrium[3] and is commonly denoted by a capital D:
D = x11 − p1q1

In the genetic literature the phrase "two alleles are in LD" usually means that D ≠ 0. Contrariwise, "linkage equilibrium" means D = 0.

In summary, linkage disequilibrium reflects the difference between the expected haplotype frequencies under the assumption of independence, and observed haplotype frequencies. A value of 0 for D' indicates that the examined loci are in fact independent of one another, while a value of 1 demonstrates complete dependency.

http://en.wikipedia.org/wiki/Linkage_disequilibrium

Broad HaploView

http://www.broadinstitute.org/science/programs/medical-and-population-genetics/haploview/ld-display


http://www.sciencemag.org/content/296/5576/2225.long


Science. 2002 Jun 21;296(5576):2225-9. Epub 2002 May 23.

The structure of haplotype blocks in the human genome.

Gabriel SB, Schaffner SF, Nguyen H, Moore JM, Roy J, Blumenstiel B, Higgins J,
DeFelice M, Lochner A, Faggart M, Liu-Cordero SN, Rotimi C, Adeyemo A, Cooper R,
Ward R, Lander ES, Daly MJ, Altshuler D.

Whitehead/MIT Center for Genome Research, Cambridge, MA 02139, USA.

Haplotype-based methods offer a powerful approach to disease gene mapping, based
on the association between causal mutations and the ancestral haplotypes on which
they arose. As part of The SNP Consortium Allele Frequency Projects, we
characterized haplotype patterns across 51 autosomal regions (spanning 13
megabases of the human genome) in samples from Africa, Europe, and Asia. We show
that the human genome can be parsed objectively into haplotype blocks: sizable
regions over which there is little evidence for historical recombination and
within which only a few common haplotypes are observed. The boundaries of blocks
and specific haplotypes they contain are highly correlated across populations. We
demonstrate that such haplotype frameworks provide substantial statistical power
in association studies of common genetic variation across each region. Our
results provide a foundation for the construction of a haplotype map of the human
genome, facilitating comprehensive genetic association studies of human disease.


PMID: 12029063 [PubMed - indexed for MEDLINE]