PSEUDOMARKER: a powerful program for joint linkage and/or linkage disequilibrium analysis on mixtures of singletons and related individuals. By Hiekkalinna T, Schäffer AA, Lambert B, Norrgrann P, Göring HH, Terwilliger JD.
Abstract:
A decade ago, there was widespread enthusiasm for the prospects of genome-wide association studies to identify common variants related to common chronic diseases using samples of unrelated individuals from populations. Although technological advancements allow us to query more than a million SNPs across the genome at low cost, a disappointingly small fraction of the genetic portion of common disease etiology has been uncovered. This has led to the hypothesis that less frequent variants might be involved, stimulating a renaissance of the traditional approach of seeking genes using multiplex families from less diverse populations. However, by using the modern genotyping and sequencing technology, we can now look not just at linkage, but jointly at linkage and linkage disequilibrium (LD) in such samples. Software methods that can look simultaneously at linkage and LD in a powerful and robust manner have been lacking. Most algorithms cannot jointly analyze datasets involving families of varying structures in a statistically or computationally efficient manner. We have implemented previously proposed statistical algorithms in a user-friendly software package, PSEUDOMARKER. This paper is an announcement of this software package. We describe the motivation behind the approach, the statistical methods, and software, and we briefly demonstrate PSEUDOMARKER’s advantages over other packages by example.
I didn’t set out to find this particular article but was trying to update references on Cri-Map, which is now somewhat data software for:
… rapid, largely automated construction of multilocus linkage maps (and facilitate the attendant tasks of assessing support relative to alternative locus orders, generating LOD tables, and detecting data errors). Although originally designed to handle codominant loci (e.g. RFLPs) scored on pedigrees “without missing individuals”, such as CEPH or nuclear families, it can now (with some caveats described below) be used on general pedigrees, and some disease loci.
Just as background, you may wish to see:
And, Multilocus linkage analysis
With multilocus linkage analysis, more than two loci are simultaneously considered for linkage. When mapping a disease gene relative to a group of markers with known intermarker recombination fractions, it is possible to perform parametric (lod score) as well as nonparametric analysis.
My interest being in the use of additional information (in the lead article “linkage and linkage disequilibrium”) in determining linkage issues.
Not that every issue of subject identification needs or should be probabilistic or richly nuanced.
In a prison there are “free men” and prisoners.
Rather sharp and useful distinction. Doesn’t require a URL. Or a subject identifier. What does your use case require?