ArticleBMC bioinformatics2013
SeqSIMLA: a sequence and phenotype simulation tool for complex disease studies.
Article in BMC bioinformatics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.
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Who cites it
13 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A unified method for rare variant analysis of gene-environment interactions.Statistics in medicine · 2020Pooled it
- Comparative analysis of genetic risk scores for predicting biochemical recurrence in prostate cancer patients after radical prostatectomy.BMC urology · 2024Article
- Revisit Population-based and Family-based Genotype Imputation.Scientific reports · 2019Article
- Simulating autosomal genotypes with realistic linkage disequilibrium and a spiked-in genetic effect.BMC bioinformatics · 2018Article
- cophesim: a comprehensive phenotype simulator for testing novel association methods.F1000Research · 2017Article
- GCORE-sib: An efficient gene-gene interaction tool for genome-wide association studies based on discordant sib pairs.BMC bioinformatics · 2016Article
- Efficient Coalescent Simulation and Genealogical Analysis for Large Sample Sizes.PLoS computational biology · 2016Article
- A combined association test for rare variants using family and case-control data.BMC proceedings · 2016Article
- Generation of sequence-based data for pedigree-segregating Mendelian or Complex traits.Bioinformatics (Oxford, England) · 2015Article
- A multi-SNP association test for complex diseases incorporating an optimal P-value threshold algorithm in nuclear families.BMC genomics · 2015Article
- Article
- Family-based association test using both common and rare variants and accounting for directions of effects for sequencing data.PloS one · 2014Article
- Adaptive combination of P-values for family-based association testing with sequence data.PloS one · 2014Article
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Abstract
backgroundAssociation studies based on next-generation sequencing (NGS) technology have become popular, and statistical association tests for NGS data have been developed rapidly. A flexible tool for simulating sequence data in either unrelated case-control or family samples with different disease and quantitative trait models would be useful for evaluating the statistical power for planning a study design and for comparing power among statistical methods based on NGS data.
resultsWe developed a simulation tool, SeqSIMLA, which can simulate sequence data with user-specified disease and quantitative trait models. We implemented two disease models, in which the user can flexibly specify the number of disease loci, effect sizes or population attributable risk, disease prevalence, and risk or protective loci. We also implemented a quantitative trait model, in which the user can specify the number of quantitative trait loci (QTL), proportions of variance explained by the QTL, and genetic models. We compiled recombination rates from the HapMap project so that genomic structures similar to the real data can be simulated.
conclusionsSeqSIMLA can efficiently simulate sequence data with disease or quantitative trait models specified by the user. SeqSIMLA will be very useful for evaluating statistical properties for new study designs and new statistical methods using NGS. SeqSIMLA can be downloaded for free at http://seqsimla.sourceforge.net.
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