ReviewJournal of computational biology : a journal of computational molecular cell biology2012
An overview of population genetic data simulation.
Review in Journal of computational biology : a journal of computational molecular cell biology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
36 citing papers in PubMed.
- Article
- Human ancestries simulation and inference: a review of ancestral recombination graph-based approaches.Frontiers in bioinformatics · 2026Review
- Accurate Predictive Modeling of Conservation Status in Animal Species Using Supervised Learning.Ecology and evolution · 2025Article
- HAP-SAMPLE2: data-based resampling for association studies with admixture.Bioinformatics (Oxford, England) · 2025Article
- Fast simulation of identity-by-descent segments.Bulletin of mathematical biology · 2025Article
- Maximizing the accuracy of genetic variance estimation and using a novel generalized effective sample size to improve simulations.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025Article
- Fast simulation of identity-by-descent segments.bioRxiv : the preprint server for biology · 2025Article
- Population genetic simulation: Benchmarking frameworks for non-standard models of natural selection.Molecular ecology resources · 2024Article
- Mate selection: A useful approach to maximize genetic gain and control inbreeding in genomic and conventional oil palm (Elaeis guineensis Jacq.) hybrid breeding.PLoS computational biology · 2023Article
- Learning the kernel for rare variant genetic association test.Frontiers in genetics · 2023Article
- Demes: a standard format for demographic models.Genetics · 2022Article
- A spatially aware likelihood test to detect sweeps from haplotype distributions.PLoS genetics · 2022Article
- Efficient ancestry and mutation simulation with msprime 1.0.Genetics · 2022Article
- svBreak: A New Approach for the Detection of Structural Variant Breakpoints Based on Convolutional Neural Network.BioMed research international · 2022Article
- AdmixSim 2: a forward-time simulator for modeling complex population admixture.BMC bioinformatics · 2021Article
- CIRCNV: Detection of CNVs Based on a Circular Profile of Read Depth from Sequencing Data.Biology · 2021Article
- A novel machine learning approach (svmSomatic) to distinguish somatic and germline mutations using next-generation sequencing data.Zoological research · 2021Article
- HBOS-CNV: A New Approach to Detect Copy Number Variations From Next-Generation Sequencing Data.Frontiers in genetics · 2021Article
- Article
- OPENMENDEL: a cooperative programming project for statistical genetics.Human genetics · 2020Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Simulation studies in population genetics play an important role in helping to better understand the impact of various evolutionary and demographic scenarios on sequence variation and sequence patterns, and they also permit investigators to better assess and design analytical methods in the study of disease-associated genetic factors. To facilitate these studies, it is imperative to develop simulators with the capability to accurately generate complex genomic data under various genetic models. Currently, a number of efficient simulation software packages for large-scale genomic data are available, and new simulation programs with more sophisticated capabilities and features continue to emerge. In this article, we review the three basic simulation frameworks--coalescent, forward, and resampling--and some of the existing simulators that fall under these frameworks, comparing them with respect to their evolutionary and demographic scenarios, their computational complexity, and their specific applications. Additionally, we address some limitations in current simulation algorithms and discuss future challenges in the development of more powerful simulation tools.
Indexed as
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What OpenQuestion holds
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 OpenQuestion graph.