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HAP-SAMPLE specifications


Unique identifier OMICS_15324
Interface Web user interface
Restrictions to use None
Input data Inputs consist of the disease model file (the various types of specifications are given above) with specific rs#’s for the disease SNPs, and a file listing SNPs to be ‘genotyped’.
Output data Output consists of SNP genotypes, reflecting current typing technologies. In addition, the output contains the simulated haplotypes, which are useful in evaluating the success of haplotype reconstruction approaches.
Computer skills Basic
Stability No
Maintained No


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Publication for HAP-SAMPLE

HAP-SAMPLE citations


High Order SNP Combinations Associated with Complex Diseases: Efficient Discovery, Statistical Power and Functional Interactions

PLoS One
PMCID: 3334940
PMID: 22536319
DOI: 10.1371/journal.pone.0033531

[…] We first used Hap-Sample simulator (http://www.hapsample.org, accessed 2012 Feb 20) to simulate genotype data with the 3404 SNPs from a recent study on multiple myeloma as input, out of which 2172 SNPs are include […]


Validation of a Cost Efficient Multi Purpose SNP Panel for Disease Based Research

PLoS One
PMCID: 3096622
PMID: 21611176
DOI: 10.1371/journal.pone.0019699
call_split See protocol

[…] HAP-SAMPLE , a data based resampling simulation tool, was used to simulate genetically realistic genotypes for SNPs in the three panels plus SNPs in a candidate gene under a null model (in this case, […]


A survey of genetic simulation software for population and epidemiological studies

Hum Genomics
PMCID: 3525177
PMID: 19129092
DOI: 10.1186/1479-7364-3-1-79

[…] iploid chromosomes from phased HapMap data followed by a single round of artificial meiosis, governed by empirical recombination rates also estimated from HapMap. This idea has been put to use in the HAP-SAMPLE software,[] with an additional option to boost the baseline recombination rate (x100 recommended) to reduce long-range linkage disequilibrium. Durrant et al. [] proposed an alternative idea […]


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HAP-SAMPLE institution(s)
Department of Biostatistics, University of North Carolina, Chapel Hill, NC, USA; Center for Genome Sciences, University of North Carolina, Chapel Hill, NC, USA; Center for Environmental Bioinformatics, University of North Carolina, Chapel Hill, NC, USA; Renaissance Computing Institute, Europa Drive, University of North Carolina Chapel Hill, NC, USA; School of Pharmacy, University of North Carolina Chapel Hill, NC, USA; Department of Genetics, University of North Carolina Chapel Hill, NC, USA
HAP-SAMPLE funding source(s)
This work was supported by the Carolina Center for Exploratory Genetic Analysis (P20 RR020751), the Carolina Environmental Bioinformatics Research Center (EPA RD-83272001), NIH grants P30ES10126, P50 GM076468, R01 GM074175 and R01 HL068890, and CF Foundation Zou05P0.

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