Biomedical subjects

Kim W Carter

Publications and source records attributed to Kim W Carter.

3 recordsLinked to original sources

PubMed2006

JLIN: a java based linkage disequilibrium plotter.

BACKGROUND: A great deal of effort and expense are being expended internationally in attempts to detect genetic polymorphisms contributing to susceptibility to complex human disease. Techniques such as Linkage Disequilibrium mapping are being increasingly used to examine and compare markers across increasingly large datasets. Visualisation techniques are becoming essential to analyse the ever-growing volume of data and results available with any given analysis. RESULTS: JLIN (Java LINkage disequilibrium plotter) is a software package designed for customisable, intuitive visualisation of Linkage Disequilibrium (LD) across all common computing platforms. Customisation allows the user to choose particular visualisations, statistical measures and measurement ranges. JLIN also allows the user to export images of the LD visualisation in several common document formats. CONCLUSION: JLIN allows the user to visually compare and contrast the results of a range of statistical measures on the input dataset(s). These measures include the commonly used D' and r2 statistics and empirical p-values. JLIN has a number of unique and novel features that improve on existing LD visualisation tools.

Algorithms↗

PubMed2005

The effect of missing data on linkage disequilibrium mapping and haplotype association analysis in the GAW14 simulated datasets.

We used our newly developed linkage disequilibrium (LD) plotting software, JLIN, to plot linkage disequilibrium between pairs of single-nucleotide polymorphisms (SNPs) for three chromosomes of the Genetic Analysis Workshop 14 Aipotu simulated population to assess the effect of missing data on LD calculations. Our haplotype analysis program, SIMHAP, was used to assess the effect of missing data on haplotype-phenotype association. Genotype data was removed at random, at levels of 1%, 5%, and 10%, and the LD calculations and haplotype association results for these levels of missingness were compared to those for the complete dataset. It was concluded that ignoring individuals with missing data substantially affects the number of regions of LD detected which, in turn, could affect tagging SNPs chosen to generate haplotypes.

Chromosome Mapping↗

PubMed2005

Genome-wide linkage and association mapping of disease genes with the GAW14 simulated datasets.

We combined the results of whole-genome linkage and association analyses to determine which markers were most strongly associated with Kofendrerd Personality Disorder. Using replicate 1 from the Genetic Analysis Workshop 14 Aipotu, Karangar, Danacaa, and New York City simulated populations, we determined that several markers showed significant linkage and association with disease status. We used both SNP and microsatellite markers to determine patterns and chromosomal regions of markers. Three consistently associated markers were C01R0050, C03R0280, and C10R0882. Using generalized linear mixed models, we modelled the effect of the three predefined phenotypic categories on disease status and concluded that the phenotypes defining the "anxiety-related" category best predicted the outcome.

Chromosome Mapping↗