ArticleBMC bioinformatics2019
sim1000G: a user-friendly genetic variant simulator in R for unrelated individuals and family-based designs.
Article in BMC bioinformatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 1 of them a synthesis that pooled it.
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Who cites it
23 citing papers in PubMed, 1 synthesis or guideline pooled it.
- CARMA is a new Bayesian model for fine-mapping in genome-wide association meta-analyses.Nature genetics · 2023Pooled it
- Separating direct, indirect, and parent-of-origin genetic effects in the human population.Cell genomics · 2026Article
- Reassessing Instrument Strength in Two-Sample Mendelian Randomization Analysis.medRxiv : the preprint server for health sciences · 2026Article
- COBT: a gene-based rare variant burden test for case-only study designs using aggregated genotypes from public reference cohorts.Genome medicine · 2026Article
- scDesignPop generates realistic population-scale single-cell RNA-seq for power analysis, benchmarking, and privacy protection.bioRxiv : the preprint server for biology · 2026Article
- A novel simulation tool for low-coverage whole-genome sequencing using multivariate Gaussian mixture models.BMC bioinformatics · 2026Article
- A novel two-sample Mendelian randomization framework integrating common and rare variants: application to assess the effect of HDL-C on preeclampsia risk.Briefings in bioinformatics · 2026Article
- mfSuSiE enables multi-cell-type fine-mapping and multi-omic integration of chromatin accessibility QTLs in aging brain.bioRxiv : the preprint server for biology · 2025Article
- Separating direct, indirect and parent-of-origin genetic effects in the human population.bioRxiv : the preprint server for biology · 2025Article
- fSuSiE enables fine-mapping of QTLs from genome-scale molecular profiles.bioRxiv : the preprint server for biology · 2025Article
- py_ped_sim: a flexible forward pedigree and genetic simulator for complex family pedigree analysis.BMC bioinformatics · 2025Article
- BEATRICE: Bayesian fine-mapping from summary data using deep variational inference.Bioinformatics (Oxford, England) · 2024Article
- BEATRICE: Bayesian Fine-mapping from Summary Data using Deep Variational Inference.bioRxiv : the preprint server for biology · 2024Article
- HAPNEST: efficient, large-scale generation and evaluation of synthetic datasets for genotypes and phenotypes.Bioinformatics (Oxford, England) · 2023Article
- MATS: a novel multi-ancestry transcriptome-wide association study to account for heterogeneity in the effects of cis-regulated gene expression on complex traits.Human molecular genetics · 2023Article
- COMMUTE: Communication-efficient transfer learning for multi-site risk prediction.Journal of biomedical informatics · 2023Article
- Article
- Integrative transcriptomic, evolutionary, and causal inference framework for region-level analysis: Application to COVID-19.NPJ genomic medicine · 2022Article
- FamEvent: An R Package for Generating and Modeling Time-to-Event Data in Family Designs.Journal of statistical software · 2021Article
- Primo: integration of multiple GWAS and omics QTL summary statistics for elucidation of molecular mechanisms of trait-associated SNPs and detection of pleiotropy in complex traits.Genome biology · 2020Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
backgroundSimulation of genetic variants data is frequently required for the evaluation of statistical methods in the fields of human and animal genetics. Although a number of high-quality genetic simulators have been developed, many of them require advanced knowledge in population genetics or in computation to be used effectively. In addition, generating simulated data in the context of family-based studies demands sophisticated methods and advanced computer programming.
resultsTo address these issues, we propose a new user-friendly and integrated R package, sim1000G, which simulates variants in genomic regions among unrelated individuals or among families. The only input needed is a raw phased Variant Call Format (VCF) file. Haplotypes are extracted to compute linkage disequilibrium (LD) in the simulated genomic regions and for the generation of new genotype data among unrelated individuals. The covariance across variants is used to preserve the LD structure of the original population. Pedigrees of arbitrary sizes are generated by modeling recombination events with sim1000G. To illustrate the application of sim1000G, various scenarios are presented assuming unrelated individuals from a single population or two distinct populations, or alternatively for three-generation pedigree data. Sim1000G can capture allele frequency diversity, short and long-range linkage disequilibrium (LD) patterns and subtle population differences in LD structure without the need of any tuning parameters.
conclusionSim1000G fills a gap in the vast area of genetic variants simulators by its simplicity and independence from external tools. Currently, it is one of the few simulation packages completely integrated into R and able to simulate multiple genetic variants among unrelated individuals and within families. Its implementation will facilitate the application and development of computational methods for association studies with both rare and common variants.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.