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Allele Frequency Difference AFD?An Intuitive Alternative to F_ST for Quantifying Genetic Population Differentiation.

ABSTRACT: Measuring the magnitude of differentiation between populations based on genetic markers is commonplace in ecology, evolution, and conservation biology. The predominant differentiation metric used for this purpose is F_ST. Based on a qualitative survey, numerical analyses, simulations, and empirical data, I here argue that F_ST does not express the relationship to allele frequency differentiation between populations generally considered interpretable and desirable by researchers. In particular, F_ST (1) has low sensitivity when population differentiation is weak, (2) is contingent on the minor allele frequency across the populations, (3) can be strongly affected by asymmetry in sample sizes, and (4) can differ greatly among the available estimators. Together, these features can complicate pattern recognition and interpretation in population genetic and genomic analysis, as illustrated by empirical examples, and overall compromise the comparability of population differentiation among markers and study systems. I argue that a simple differentiation metric displaying intuitive properties, the absolute allele frequency difference AFD, provides a valuable alternative to F_ST. I provide a general definition of AFD applicable to both bi- and multi-allelic markers and conclude by making recommendations on the sample sizes needed to achieve robust differentiation estimates using AFD.

SUBMITTER: Berner D

PROVIDER: S-EPMC6523497 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature

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Allele Frequency Difference AFD⁻An Intuitive Alternative to FST for Quantifying Genetic Population Differentiation.

Berner Daniel D

Genes 20190418 4

Measuring the magnitude of differentiation between populations based on genetic markers is commonplace in ecology, evolution, and conservation biology. The predominant differentiation metric used for this purpose is FST. Based on a qualitative survey, numerical analyses, simulations, and empirical data, I here argue that FST does not express the relationship to allele frequency differentiation between populations generally considered interpretable and desirable by researche ...[more]

PMID: 31003563

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Project description:BackgroundLung adenocarcinoma (LUAD) remains one of the world's most known aggressive malignancies with a high mortality rate. Molecular biological analysis and bioinformatics are of great importance as they have recently occupied a large area in the studies related to the identification of various biomarkers to predict survival for LUAD patients. In our study, we attempted to identify a new prognostic model by developing a new algorithm to calculate the allele frequency deviation (AFD), which in turn may assist in the early diagnosis and prediction of clinical outcomes in LUAD.MethodFirst, a new algorithm was developed to calculate AFD using the whole-exome sequencing (WES) dataset. Then, AFD was measured for 102 patients, and the predictive power of AFD was assessed using Kaplan-Meier analysis, receiver operating characteristic (ROC) curves, and area under the curve (AUC). Finally, multivariable cox regression analyses were conducted to evaluate the independence of AFD as an independent prognostic tool.ResultThe Kaplan-Meier analysis showed that AFD effectively segregated patients with LUAD into high-AFD-value and low-AFD-value risk groups (hazard ratio HR = 1.125, 95% confidence interval CI 1.001-1.26, p = 0.04) in the training group. Moreover, the overall survival (OS) of patients who belong to the high-AFD-value group was significantly shorter than that of patients who belong to the low-AFD-value group with 42.8% higher risk and 10% lower risk of death for both groups respectively (HR for death = 1.10; 95% CI 1.01-1.2, p = 0.03) in the training group. Similar results were obtained in the validation group (HR = 4.62, 95% CI 1.22-17.4, p = 0.02) with 41.6%, and 5.5% risk of death for patients who belong to the high and low-AFD-value groups respectively. Univariate and multivariable cox regression analyses demonstrated that AFD is an independent prognostic model for patients with LUAD. The AUC for 5-year survival were 0.712 and 0.86 in the training and validation groups, respectively.ConclusionAFD was identified as a new independent prognostic model that could provide a prognostic tool for physicians and contribute to treatment decisions.

Project description:BackgroundThe high prevalence of falling among older adults constitutes a major public and clinical health concern. Many elderly persons may develop activities-specific restriction due to the risk of falling. This highlights the need for relevant evaluative tools.MethodsThis cross-sectional study used activities-specific performance frequency indicators to quantify activity restrictions in elderly participants, with all measures based on items from the Activities-Specific Balance Confidence (ABC) scale. Specifically, we tested for correlations between activities-specific performance frequency and balance confidence, functional balance/mobility, and fall history. There were 88 elderly participants, including 28 with stroke, 30 with Parkinson's disease, and 30 with no neurological diseases. In addition to their activities-specific performance frequency measures, we collected a series of demographic and health-related characteristics from each participant. We analyzed between-group differences in activities-specific performance frequency and other demographic and health-related characteristics via the one-way analysis of variance and Kruskal-Wallis test. Next, we used the Spearman's rank correlation test and binary logistic regression to investigate the correlations between activities-specific performance frequency and demographic/other health-related characteristics.ResultsThere were significant group differences in performance frequency for all ABC activity items except for walking around the house, average ABC scores, and functional balance/mobility among normal older adults, participants with strokes and those with Parkinson's disease. Activities-specific performance frequency showed stronger correlations with activities-relevant functional mobility (r=0.250-0.713 for 15 items with significant correlations, 13 activity items with r≧0.4) than with balance confidence (r=0.279-0.668 for 13 items with significant correlations, 10 activity items with r≧0.4). The performance frequency of walking in crowds/bumped was the most sensitive measure for predicting fallers (odd ratio=3.310, p<0.05).ConclusionsThis study proposed and validated the usage of activities-specific performance frequency as an alternative method for quantifying activity restrictions among older adults.

Dataset Information

Allele Frequency Difference AFD?An Intuitive Alternative to F_ST for Quantifying Genetic Population Differentiation.

Publications

Allele Frequency Difference <i>AFD</i>⁻An Intuitive Alternative to <i>F</i><sub>ST</sub> for Quantifying Genetic Population Differentiation.

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Dataset Information

Allele Frequency Difference AFD?An Intuitive Alternative to FST for Quantifying Genetic Population Differentiation.

Publications

Allele Frequency Difference <i>AFD</i>⁻An Intuitive Alternative to <i>F</i><sub>ST</sub> for Quantifying Genetic Population Differentiation.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

Allele Frequency Difference AFD?An Intuitive Alternative to F_ST for Quantifying Genetic Population Differentiation.