MIDAS: software for analysis and visualisation of interallelic disequilibrium between multiallelic markers

BackgroundVarious software tools are available for the display of pairwise linkage disequilibrium across multiple single nucleotide polymorphisms. The HapMap project also presents these graphics within their website. However, these approaches are limited in their use of data from multiallelic markers and provide limited information in a graphical form.ResultsWe have developed a software package (MIDAS – Multiallelic Interallelic Disequilibrium Analysis Software) for the estimation and graphical display of interallelic linkage disequilibrium. Linkage disequilibrium is analysed for each allelic combination (of one allele from each of two loci), between all pairwise combinations of any type of multiallelic loci in a contig (or any set) of many loci (including single nucleotide polymorphisms, microsatellites, minisatellites and haplotypes). Data are presented graphically in a novel and informative way, and can also be exported in tabular form for other analyses. This approach facilitates visualisation of patterns of linkage disequilibrium across genomic regions, analysis of the relationships between different alleles of multiallelic markers and inferences about patterns of evolution and selection.ConclusionMIDAS is a linkage disequilibrium analysis program with a comprehensive graphical user interface providing novel views of patterns of linkage disequilibrium between all types of multiallelic and biallelic markers.AvailabilityAvailable from http://www.genes.org.uk/software/midas and http://www.sgel.humgen.soton.ac.uk/midas

[1]  Gonçalo R. Abecasis,et al.  GOLD-Graphical Overview of Linkage Disequilibrium , 2000, Bioinform..

[2]  C Zapata,et al.  Spectrum of nonrandom associations between microsatellite loci on human chromosome 11p15. , 2001, Genetics.

[3]  Lon R. Cardon,et al.  GOLDsurfer: three dimensional display of linkage disequilibrium , 2004, Bioinform..

[4]  Sandra D. O'Dell,et al.  Evidence of multiple causal sites affecting weight in the IGF2-INS-TH region of human chromosome 11 , 2002, Human Genetics.

[5]  C. ZAPATA,et al.  Sampling variance and distribution of the D′ measure of overall gametic disequilibrium between multiallelic loci , 2001, Annals of human genetics.

[6]  L. Kruglyak,et al.  Patterns of linkage disequilibrium in the human genome , 2002, Nature Reviews Genetics.

[7]  B. Weir.  Inferences about linkage disequilibrium. , 1979, Biometrics.

[8]  L. Jorde,et al.  Linkage disequilibrium and the search for complex disease genes. , 2000, Genome research.

[9]  Jakob C. Mueller,et al.  Linkage disequilibrium for different scales and applications , 2004, Briefings Bioinform..

[10]  Mark Daly,et al.  Haploview: analysis and visualization of LD and haplotype maps , 2005, Bioinform..

[11]  W. G. Hill,et al.  Estimation of linkage disequilibrium in randomly mating populations , 1974, Heredity.

[12]  Bradley N. Miller,et al.  The Python Programming Language , 2006 .

[13]  Jiannis Ragoussis,et al.  Genetically indistinguishable SNPs and their influence on inferring the location of disease-associated variants. , 2005, Genome research.

[14]  Tom R. Gaunt,et al.  Haplotypic analyses of the IGF2-INS-TH gene cluster in relation to cardiovascular risk traits. , 2004, Human molecular genetics.

[15]  Tom R. Gaunt,et al.  Late life metabolic syndrome, early growth, and common polymorphism in the growth hormone and placental lactogen gene cluster. , 2004, The Journal of clinical endocrinology and metabolism.

[16]  Carlos Zapata,et al.  Distribution of nonrandom associations between pairs of protein loci along the third chromosome of Drosophila melanogaster. , 2002, Genetics.

[17]  M. Curie-Cohen,et al.  Estimates of inbreeding in a natural population: a comparison of sampling properties. , 1982, Genetics.

[18]  M. Olivier.  A haplotype map of the human genome , 2003, Nature.

[19]  W. G. Hill,et al.  Deviations from Hardy-Weinberg proportions: sampling variances and use in estimation of inbreeding coefficients. , 1984, Genetics.

[20]  B S Weir,et al.  Testing Hypotheses about Linkage Disequilibrium with Multiple Alleles. , 1978, Genetics.

[21]  Tom R. Gaunt,et al.  Positive associations between single nucleotide polymorphisms in the IGF2 gene region and body mass index in adult males. , 2001, Human molecular genetics.

[22]  I. Day,et al.  Associations of IGF2 ApaI RFLP and INS VNTR class I allele size with obesity , 1999, European Journal of Human Genetics.

[23]  P. Hedrick,et al.  Gametic disequilibrium measures: proceed with caution. , 1987, Genetics.

[24]  Antonio Salas,et al.  Human genome-wide screen of haplotype-like blocks of reduced diversity. , 2005, Gene.

[25]  Toshihiro Tanaka.  The International HapMap Project , 2003, Nature.

[26]  Tom R. Gaunt,et al.  Replication of IGF2-INS-TH*5 haplotype effect on obesity in older men and study of related phenotypes , 2006, European Journal of Human Genetics.

[27]  Guido van Rossum,et al.  Python Programming Language , 2007, USENIX Annual Technical Conference.

[28]  M. Olivier.  A haplotype map of the human genome. , 2003, Nature.

[29]  R. Lewontin.  The Interaction of Selection and Linkage. I. General Considerations; Heterotic Models. , 1964, Genetics.

[30]  S Karlin,et al.  Statistical methods for assessing linkage disequilibrium at the HLA‐A, B, C loci , 1981, Annals of human genetics.

[31]  S. Humphries,et al.  Apal polymorphism in insulin-like growth factor II (IGF2) gene and weight in middle-aged males , 1997, International Journal of Obesity.