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HACSim: an R package to estimate intraspecific sample sizes for genetic diversity assessment using haplotype accumulation curves.

ABSTRACT: Assessing levels of standing genetic variation within species requires a robust sampling for the purpose of accurate specimen identification using molecular techniques such as DNA barcoding; however, statistical estimators for what constitutes a robust sample are currently lacking. Moreover, such estimates are needed because most species are currently represented by only one or a few sequences in existing databases, which can safely be assumed to be undersampled. Unfortunately, sample sizes of 5-10 specimens per species typically seen in DNA barcoding studies are often insufficient to adequately capture within-species genetic diversity. Here, we introduce a novel iterative extrapolation simulation algorithm of haplotype accumulation curves, called HACSim (Haplotype Accumulation Curve Simulator) that can be employed to calculate likely sample sizes needed to observe the full range of DNA barcode haplotype variation that exists for a species. Using uniform haplotype and non-uniform haplotype frequency distributions, the notion of sampling sufficiency (the sample size at which sampling accuracy is maximized and above which no new sampling information is likely to be gained) can be gleaned. HACSim can be employed in two primary ways to estimate specimen sample sizes: (1) to simulate haplotype sampling in hypothetical species, and (2) to simulate haplotype sampling in real species mined from public reference sequence databases like the Barcode of Life Data Systems (BOLD) or GenBank for any genomic marker of interest. While our algorithm is globally convergent, runtime is heavily dependent on initial sample sizes and skewness of the corresponding haplotype frequency distribution.

SUBMITTER: Phillips JD

PROVIDER: S-EPMC7924493 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Background: the impact of knee osteoarthritis (OA) poses a formidable challenge to older adults. Studies have reported that genetic factors, such as MMP1, are one of important risk factors for knee OA. Although the relationship between the genetic polymorphism of MMP1 rs1799750 and the risk of knee OA has been explored, conclusions have been nonunanimous and pending due to research sample sizes, one of determinants in studying genetic polymorphisms associated with disease. Objective: to establish a model to assess whether the genetic polymorphism of MMP1 rs1799750 is associated with knee OA based on an estimation of sample sizes. Methods: samples were collected from a case−control and meta-analysis study. In the case−control study, patients who underwent knee X-ray examinations based on the Kellgren−Lawrence Grading System (KL) as diagnostic criteria were recruited at the Health Examination Center of the Tri-Service General Hospital from 2015 to 2019. Gene sequencing was conducted using iPLEX Gold. Those with unsuccessful gene sequencing were excluded. Finally, there were 569 patients in the knee OA group (KL ≥ 2) and 534 participants in the control group (KL < 2). In the meta-analysis, we used the databases PubMed, EMBASE, and Cochrane to search for studies on the relationship between MMP1 rs1799750 and knee OA. Next, we adopted the trial sequential analysis (TSA) method to assess whether sample sizes were sufficient or not to determine the risk of the genetic polymorphism of MMP1 rs1799750 on knee OA in Caucasians and Asians. Results: in Caucasians, the MMP1 rs1799750 was not significantly associated with knee OA with an odds ratios (OR) of 1.10 (95% confidence interval, CI: 0.45−2.68). Some extra 8559 samples were needed to conclude this relationship in Caucasians by the TSA model. In Asians, neither our case−control study results (n = 1103) nor a combination of samples from the case−control and meta-analysis results showed an association between MMP1 rs1799750 and knee OA. The OR (95% CI) was 1.10 (0.81−1.49) in a combination of Asian samples. Some extra 5517 samples were needed to justify this relationship in Asians by the TSA model. Conclusions: this research shows that an extra 8559 and 5517 samples are needed in Caucasians and Asians, respectively, in order to justify the association between MMP1 rs1799750 and knee OA.

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HACSim: an R package to estimate intraspecific sample sizes for genetic diversity assessment using haplotype accumulation curves.

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