Abstract

Summary: Research over the last few years has revealed pregnant haplotype structure in the human genome. The characterization of these patterns, peculiarly in the context of medical genetic association studies, is becoming a routine research activity. Haploview is a software parcel that provides computation of linkage disequilibrium statistics and population haplotype patterns from primary genotype data in a visually appealing and interactive interface.

Availability:http://www.broad.mit.edu/mpg/haploview/

Contact:jcbarret@wide.mit.edu

INTRODUCTION

Noesis of local linkage disequilibrium (LD) and common haplotype patterns in disease association and positional cloning studies is becoming increasingly widespread since information technology has get clear ( Van Eerdewegh et al., 2002; Rioux et al., 2001; Geesaman et al., 2003; Stoll et al., 2004) that intelligent use of this data has the potential to make them much more comprehensive and efficient. Early studies identifying unexpected extent of correlation and structure in haplotype patterns ( Reich et al., 2001; Daly et al., 2001; Gabriel et al., 2002) have led to the initiation of the Human Haplotype Map projection (HapMap) to brand this information available to all medical genetics researchers (International HapMap Consortium, 2003). Given the dramatic increment in the size and number of disease association studies worldwide and the enormous corporeality of public genotype data from HapMap, tools for analyzing, interpreting and visualizing these data are of critical importance to researchers everywhere.

Haploview is designed to provide a comprehensive suite of tools for haplotype analysis for a wide variety of dataset sizes. Haploview generates mark quality statistics, LD information, haplotype blocks, population haplotype frequencies and single mark clan statistics in a user-friendly format. All the features are customizable and all computations performed in real fourth dimension, fifty-fifty for datasets with hundreds of individuals and hundreds of markers.

FEATURES

Haploview accepts input in a multifariousness of formats. Pedigree information tin can be loaded equally either partially or fully phased chromosomes or every bit unphased diplotypes in the standard Linkage format. The latter format also allows the user to specify family construction information likewise as affliction amore or case/command status. Marker information, including name and location is loaded separately. Haploview besides directly accepts genotype data dumped from the Human HapMap website (http://www.hapmap.org). A graphical genome browser maintained at that site allows researchers to navigate to a item region of the genome and dump HapMap genotype data for all genotyped markers in the selected region in a format accepted by Haploview.

Upon loading a dataset, the software presents to the user a serial of marker genotyping quality metrics. These include a cheque for conformance with Hardy–Weinberg equilibrium, a tally of Mendelian inheritance errors and the percentage of individuals successfully genotyped for that marker. The program filters out markers which autumn below a preset threshold for these tests. The user can conform these thresholds as well as handpick markers to add or remove from the subsequent steps. At any time later in the process, the user may return to this quality control panel, add or remove additional markers, and have the changes immediately reflected in the ongoing analyses.

Haploview calculates several pairwise measures of LD, which it uses to create a graphical representation (Fig. 1). The user has the option to select i of several normally used cake definitions ( Gabriel et al., 2002; Wang et al., 2002) to partition the region into segments of potent LD. Alternatively, the user may manually select groups of markers for subsequent haplotype assay. This view besides allows a number of different color schemes to represent the LD relationships. Further, the program allows the brandish of an 'analysis track' above the LD plot, to display continuous variables such as recombination charge per unit estimates ( McVean et al., 2004) (Fig. 1).

Once groups of markers are selected (either automatically or manually), the program generates haplotypes and their population frequencies (Fig. one). This display shows lines to betoken transitions from 1 block to the side by side with frequency corresponding to the thickness of the line and also presents Hedrick's multiallelic D′, which represents the degree of LD between two blocks, treating each haplotype within a block as an 'allele' of that region. Again, customization is available for most all aspects of the display, including displaying alleles as letters, numbers or colored boxes and displaying only those haplotypes above an adjustable threshold in the population.

If amore status is included in the input file, Haploview also calculates the standard TDT statistic (for trio data) or simple χ2 (for instance/command data) for each marker that tin can be used for association studies. Future versions will include several haplotype-tag SNP selection methods too as haplotype-based association testing and evaluation of significance using permutation testing. These terminal features allow the user to become from raw genotype data through exploring genetic associations in one easy to use software package. Haploview is maintained every bit an open source projection (http://sourceforge.net/projects/haploview/), which allows external parties to add their own methods in improver to the continuing development by the authors.

Each of these views of the data is shown on a carve up tab (Fig. 1), allowing the user to motility from one to the adjacent, with interactive modifications fabricated by the user in whatever panel reflected in all the others. For example, ane can return at any time to the review of marking quality and manually include or exclude individual markers—these changes are instantly reflected in the LD and haplotype panels. This provides the ability to analyze the data in real-time. The information on each panel is also able to be exported to a PNG for use in presentations or publications or dumped to a text file. Additionally, the plan has a fully functional command-line mode, which allows users to run all the analyses without opening the GUI on one or more files at once.

IMPLEMENTATION

Haploview is written entirely in Java, which means it is usable on any platform with Coffee i.iii or later on installed. Running on a 1.8 GHz Pentium 4 with 1 GB of RAM, Haploview can display a dataset with 200 markers genotyped in 400 individuals and suit parameters with no noticeable delay. The program is also able to be used (from the control line) to do the LD calculations on very big datasets in comparatively pocket-sized amounts of time. Haploview was able to compute 3.3 million pairwise LD values (comparisons of all markers closer than 500 KB in a 45 500 marker dataset) in 30 min.

Haploview uses a two marker EM (ignoring missing data) to estimate the maximum-likelihood values of the four gamete frequencies, from which the D′, LOD and r 2 calculations derive. Haplotype stage and population frequency are inferred using a standard EM algorithm with a partitioning–ligation approach for blocks with greater than 10 markers. Conformance with Hardy–Weinberg equilibrium is computed using an exact examination (1000.Abecasis and J.Wigginton, personal communication).

Fig. 1

Haploview LD display with recombination rate plotted above (left) and haplotypes display (right). Interface developed at MIT Media Lab by B.Fry (http://acg.media.mit.edu/people/fry/).

Haploview LD display with recombination rate plotted to a higher place (left) and haplotypes display (right). Interface adult at MIT Media Lab by B.Fry (http://acg.media.mit.edu/people/fry/).

Fig. 1

Haploview LD display with recombination rate plotted above (left) and haplotypes display (right). Interface developed at MIT Media Lab by B.Fry (http://acg.media.mit.edu/people/fry/).

Haploview LD display with recombination rate plotted to a higher place (left) and haplotypes display (correct). Interface developed at MIT Media Lab by B.Fry (http://acg.media.mit.edu/people/fry/).

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Bioinformatics vol. 21 issue 2 © Oxford University Press 2005; all rights reserved.