scholarly journals Description and Power Analysis of Two Tests for Detecting Recent Population Bottlenecks From Allele Frequency Data

Genetics ◽  
1996 ◽  
Vol 144 (4) ◽  
pp. 2001-2014 ◽  
Author(s):  
Jean Marie Cornuet ◽  
Gordon Luikart

When a population experiences a reduction of its effective size, it generally develops a heterozygosity excess at selectively neutral loci, i.e., the heterozygosity computed from a sample of genes is larger than the heterozygosity expected from the number of alleles found in the sample if the population were at mutation drift equilibrium. The heterozygosity excess persists only a certain number of generations until a new equilibrium is established. Two statistical tests for detecting a heterozygosity excess are described. They require measurements of the number of alleles and heterozygosity at each of several loci from a population sample. The first test determines if the proportion of loci with heterozygosity excess is significantly larger than expected at equilibrium. The second test establishes if the average of standardized differences between observed and expected heterozygosities is significantly different from zero. Type I and II errors have been evaluated by computer simulations, varying sample size, number of loci, bottleneck size, time elapsed since the beginning of the bottleneck and level of variability of loci. These analyses show that the most useful markers for bottleneck detection are those evolving under the infinite allele model (IAM) and they provide guidelines for selecting sample sizes of individuals and loci. The usefulness of these tests for conservation biology is discussed.

Author(s):  
Hyun Kang

Appropriate sample size calculation and power analysis have become major issues in research and publication processes. However, the complexity and difficulty of calculating sample size and power require broad statistical knowledge, there is a shortage of personnel with programming skills, and commercial programs are often too expensive to use in practice. The review article aimed to explain the basic concepts of sample size calculation and power analysis; the process of sample estimation; and how to calculate sample size using G*Power software (latest ver. 3.1.9.7; Heinrich-Heine-Universität Düsseldorf, Düsseldorf, Germany) with 5 statistical examples. The null and alternative hypothesis, effect size, power, alpha, type I error, and type II error should be described when calculating the sample size or power. G*Power is recommended for sample size and power calculations for various statistical methods (F, t, χ2, Z, and exact tests), because it is easy to use and free. The process of sample estimation consists of establishing research goals and hypotheses, choosing appropriate statistical tests, choosing one of 5 possible power analysis methods, inputting the required variables for analysis, and selecting the “Calculate” button. The G*Power software supports sample size and power calculation for various statistical methods (F, t, χ2, z, and exact tests). This software is helpful for researchers to estimate the sample size and to conduct power analysis.


2002 ◽  
Vol 55 (1) ◽  
pp. 27-39 ◽  
Author(s):  
H.J. Keselman ◽  
Robert Cribbie ◽  
Burt Holland

Genetics ◽  
1996 ◽  
Vol 142 (4) ◽  
pp. 1357-1362
Author(s):  
François Rousset

Abstract Expected values of Wright'sF-statistics are functions of probabilities of identity in state. These values may be quite different under an infinite allele model and under stepwise mutation processes such as those occurring at microsatellite loci. However, a relationship between the probability of identity in state in stepwise mutation models and the distribution of coalescence times can be deduced from the relationship between probabilities of identity by descent and the distribution of coalescence times. The values of FIS and FST can be computed using this property. Examination of the conditional probability of identity in state given some coalescence time and of the distribution of coalescence times are also useful for explaining the properties of FIS and FST at high mutation rate loci, as shown here in an island model of population structure.


2019 ◽  
Author(s):  
Rob Cribbie ◽  
Nataly Beribisky ◽  
Udi Alter

Many bodies recommend that a sample planning procedure, such as traditional NHST a priori power analysis, is conducted during the planning stages of a study. Power analysis allows the researcher to estimate how many participants are required in order to detect a minimally meaningful effect size at a specific level of power and Type I error rate. However, there are several drawbacks to the procedure that render it “a mess.” Specifically, the identification of the minimally meaningful effect size is often difficult but unavoidable for conducting the procedure properly, the procedure is not precision oriented, and does not guide the researcher to collect as many participants as feasibly possible. In this study, we explore how these three theoretical issues are reflected in applied psychological research in order to better understand whether these issues are concerns in practice. To investigate how power analysis is currently used, this study reviewed the reporting of 443 power analyses in high impact psychology journals in 2016 and 2017. It was found that researchers rarely use the minimally meaningful effect size as a rationale for the chosen effect in a power analysis. Further, precision-based approaches and collecting the maximum sample size feasible are almost never used in tandem with power analyses. In light of these findings, we offer that researchers should focus on tools beyond traditional power analysis when sample planning, such as collecting the maximum sample size feasible.


2020 ◽  
Vol 6 (12) ◽  
Author(s):  
Katlego Kopotsa ◽  
Nontombi M. Mbelle ◽  
John Osei Sekyere

Carbapenem-resistant Klebsiella pneumoniae (CRKP) remains a major clinical pathogen and public health threat with few therapeutic options. The mobilome, resistome, methylome, virulome and phylogeography of CRKP in South Africa and globally were characterized. CRKP collected in 2018 were subjected to antimicrobial susceptibility testing, screening by multiplex PCR, genotyping by repetitive element palindromic (REP)-PCR, plasmid size, number, incompatibility and mobility analyses, and PacBio’s SMRT sequencing (n=6). There were 56 multidrug-resistant CRKP, having bla OXA-48-like and bla NDM-1/7 carbapenemases on self-transmissible IncF, A/C, IncL/M and IncX3 plasmids endowed with prophages, traT, resistance islands, and type I and II restriction modification systems (RMS). Plasmids and clades detected in this study were respectively related to globally established/disseminated plasmids clades/clones, evincing transboundary horizontal and vertical dissemination. Reduced susceptibility to colistin occurred in 23 strains. Common clones included ST307, ST607, ST17, ST39 and ST3559. IncFIIk virulent plasmid replicon was present in 56 strains. Whole-genome sequencing of six strains revealed least 41 virulence genes, extensive ompK36 mutations, and four different K- and O-loci types: KL2, KL25, KL27, KL102, O1, O2, O4 and O5. Types I, II and III RMS, conferring m6A (G A TC, G A TGNNNNNNTTG, CA A NNNNNNCATC motifs) and m4C (C C WGG) modifications on chromosomes and plasmids, were found. The nature of plasmid-mediated, clonal and multi-clonal dissemination of blaOXA-48-like and blaNDM-1 mirrors epidemiological trends observed for closely related plasmids and sequence types internationally. Worryingly, the presence of both bla OXA-48 and bla NDM-1 in the same isolates was observed. Plasmid-mediated transmission of RMS, virulome and prophages influence bacterial evolution, epidemiology, pathogenicity and resistance, threatening infection treatment. The influence of RMS on antimicrobial and bacteriophage therapy needs urgent investigation.


1976 ◽  
Vol 73 (11) ◽  
pp. 4164-4168 ◽  
Author(s):  
M. Nei ◽  
R. Chakraborty ◽  
P. A. Fuerst

2013 ◽  
Vol 58 (No. 2) ◽  
pp. 71-78 ◽  
Author(s):  
A. Galov ◽  
K. Byrne ◽  
T. Gomerčić ◽  
M. Duras ◽  
H. Arbanasić ◽  
...  

The Posavina and Croatian Coldblood are Croatian autochthonous horse breeds with interwoven breeding histories for which studbooks have only recently been established. The Lipizzan breed has the oldest formalized breeding and no record of recent genetic introgression from other breeds in Croatia. We analyzed the genetic structure, interbreeding, and breed characteristics by genotyping nine dinucleotide microsatellite loci for 53 Posavina, 37 Croatian Coldblood, and 33 Lipizzan horses and showed that differing breeding schemes and histories have had a strong and measurable impact on the population genetic structure within and between the three breeds. A Bayesian clustering method demonstrated that two population clusters best explain the genetic structure. Samples from the pre-defined breeds of the Posavina and Croatian Coldblood were assigned to a separate genetic cluster, while Lipizzan specimens were assigned to another distinct genetic group. Twelve samples of the Posavina/Croatian Coldblood cluster (13%) showed admixed ancestry with Lipizzan horses. A test for heterozygosity excess, allele frequency distribution mode-shift, and M-ratio test were used to detect genetic evidence of recent population bottlenecks, none of which provided evidence for bottlenecks in the Posavina and Croatian Coldblood populations. In contrast, although somewhat ambiguous, evidence suggests a genetic bottleneck in the Lipizzan population in Croatia.


2020 ◽  
Vol 17 (5) ◽  
pp. 507-521
Author(s):  
Xiaotian Chen ◽  
Xin Wang ◽  
Kun Chen ◽  
Yeya Zheng ◽  
Richard J Chappell ◽  
...  

Background In randomized clinical trials with censored time-to-event outcomes, the logrank test is known to have substantial statistical power under the proportional hazards assumption and is widely adopted as a tool to compare two survival distributions. However, the proportional hazards assumption is impossible to validate in practice until the data are unblinded. However, the statistical analysis plan of a randomized clinical trial and in particular its primary analysis method must be pre-specified before any unblinded information may be reviewed. Purpose The purpose of this article is to guide applied biostatisticians in the prespecification of a desired primary analysis method when a treatment effect with nonproportional hazards is anticipated. While articles proposing alternate statistical tests are aplenty, to the best of our knowledge, there is no article available that attempts to simplify the choice and prespecification of a primary statistical test under specific expected patterns on nonproportional hazards. We provide such guidance by reviewing various tests proposed as more powerful alternatives to the standard logrank test under nonproportional hazards and simultaneously comparing their performance under a wide variety of nonproportional hazards scenarios to elucidate their advantages and disadvantages. Method In order to select the most preferable test for detecting specific differences between survival distributions of interest while controlling false positive rates, we review and assess the performance of weighted and adaptively weighted logrank tests, weighted and adaptively weighted Kaplan–Meier tests and versatile tests under various patterns of nonproportional hazards treatment effects through simulation. Conclusion We validate some of the claimed properties of the proposed extensions and identify tests that may be more preferable under specific expected pattern of nonproportional hazards when such knowledge is available. We show that versatile tests, while achieving robustness to departures from proportional hazards, may lose interpretation of directionality (superiority or inferiority) and can only be seen to test departures from equality. Detailed summary and discussion of the performance of each test in terms of type I error rate and power are provided to formulate specific guidance about their applicability and use.


Blood ◽  
2010 ◽  
Vol 116 (21) ◽  
pp. 2931-2931 ◽  
Author(s):  
Mikkael A. Sekeres ◽  
Mohit Narang ◽  
Rami S. Komrokji ◽  
Jaroslaw P Maciejewski ◽  
Alan F. List ◽  
...  

Abstract Abstract 2931 Background: The incidence of sMDS is increasing due to improved survival of patients (pts) treated with chemotherapy (CT) or radiotherapy (RT) for other cancers. While studies have demonstrated hematologic improvement (HI) and survival benefits of AZA in pts with primary MDS (pMDS) (Lancet Oncol 2009;10:223), the effects of AZA in sMDS, considered rarer (5-10% of MDS diagnoses) (J Natl Cancer Inst 2008;100:1542) and more difficult to treat, are unknown. AVIDA, a longitudinal, US, multicenter, prospective registry of pts in community-based clinics receiving AZA, is the largest database of AZA-treated pts in the world and includes a large cohort of sMDS pts. We compared the tolerability of and response rates to AZA in sMDS vs pMDS pts in the AVIDA database. Methods: MDS pt data were collected at registry entry (baseline), and then quarterly using electronic data capture, between October, 2006 and July, 2010. Treating physicians determined AZA dose, dosing schedule, and treatment duration. Baseline characteristics of sMDS and pMDS pts were evaluated but formal statistical tests comparing cohorts were intentionally not performed to avoid Type I errors. Rates of IWG-2000-defined HI or possibly better responses (HI+) were assessed centrally and compared between sMDS and pMDS cohorts (each assessment included only pts eligible for improvement). RBC and platelet transfusion independence (TI) were also evaluated between groups using logistic regression analyses with patients stratified by International Prognostic Scoring System (IPSS) scores (higher [score >1] vs lower [score ≤1]) and transfusion status at baseline, with age and months since diagnosis included as covariates. Odds ratios (sMDS to pMDS) and 95% confidence intervals (CI) were reported from these models. Results: At data cut-off in July 2010, 37/417 pts (8.9%) in the registry had sMDS associated with exposure to RT, CT, or radioiodine (n=33), benzene (n=2), or radiation (n=2). Median times since diagnosis for pts with sMDS and pMDS were 1 month (range 0 – 69) and 3 months (0 – 207), and median ages were 71 years (range 41 – 86) and 75 years (29 – 91), respectively. At baseline, for pts with available IPSS scores, a larger proportion of pts with sMDS than pts with pMDS had IPSS higher-risk scores (55% vs 30%) and IPSS poor cytogenetics (59% vs 17%). Additionally, a higher proportion of sMDS vs pMDS pts had chromosome 7 abnormalities (47% vs 11%), 2–3 cytopenias (76% vs 62%), and infections requiring IV antibiotics (41% vs 16%); but similar proportions had >10% blasts (18% of both cohorts) and were dependent on RBC (57% vs 52%) and platelet (22% vs 13%) transfusions at baseline. Median follow-up was 5.9 months (range 0.2 – 24) in the sMDS and 6.7 months (0.1 – 37) in the pMDS cohorts, and median numbers of AZA treatment cycles were 4 (range 1 – 21) and 5 (1 – 26), respectively. In both the sMDS and pMDS groups, the most common treatment dose and schedules were 75 mg/m2 AZA (91% and 83%, respectively) for 5 consecutive days (46% and 55%) in ≤28-day cycles (45% and 54%). Pts with sMDS had a high rate of HI+, which was comparable to that in pts with pMDS (Table). Rates of RBC TI in baseline RBC transfusion-dependent pts with sMDS vs pMDS were 57% vs 61%, and of platelet TI for baseline platelet transfusion-dependent sMDS vs pMDS pts were 50% vs 64% (Table). Odds ratios from the logistic regression models were 1.4 (95%CI: 0.6, 3.5; p=0.47) and 0.6 (95%CI: 0.2, 1.4; p=0.23) for RBC TI and platelet TI, respectively, after adjusting for the other covariates in the model. Grade 3 or 4 adverse events were similar in the 2 groups, with the exception of higher frequencies of thrombocytopenia (27% vs 11%) and infections (24% vs. 12%) in sMDS vs pMDS pts, respectively. Conclusion: Pts with sMDS treated with AZA had rates of HI or better responses comparable to those of pMDS patients, despite worse pretreatment disease characteristics. AZA was well tolerated by pts with sMDS and pMDS. A diagnosis of sMDS alone should not preclude treatment with the disease-modifying drug, azacitidine. Disclosures: Sekeres: Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees. Off Label Use: Azacitidine is approved in the US for treatment of patients with the FAB myelodysplastic syndrome (MDS) subtypes: Refractory anemia (RA) or refractory anemia with ringed sideroblasts (RARS) (if accompanied by neutropenia or thrombocytopenia or requiring transfusions), refractory anemia with excess blasts (RAEB), refractory anemia with excess blasts in transformation (RAEB-T), and chronic myelomonocytic leukemia (CMML); and is approved in the EU for IPSS Int-2 and High risk MDS, CMML with 10–29 percent marrow blasts without myeloproliferative disorder, and AML with 20–30% blasts and multi-lineage dysplasia, according to WHO classification. This abstract describes azacitidine use in secondary MDS. Komrokji:Celgene: Research Funding, Speakers Bureau. Maciejewski:Celgene: Research Funding; Eisai: Research Funding; Alexion: Consultancy. List:Celgene: Research Funding. Street:Celgene: Employment. Swern:Celgene Corporation: Employment. Sullivan:Celgene: Employment, Equity Ownership. Grinblatt:Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau.


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