The three common genetic models(or modes of inheritance)in association analysis are the dominant,additive,and recessive models.It is known that the Cochran-Armitage trend test(CATT)which correctly incorporates informa...The three common genetic models(or modes of inheritance)in association analysis are the dominant,additive,and recessive models.It is known that the Cochran-Armitage trend test(CATT)which correctly incorporates information from genetic models,is more powerful than the commonly used Pearson’s chi-square test.However,the true genetic model is usually unknown in practice,and the power of the CAT test could be substantially reduced with a wrongly specified genetic model.To achieve a power that is close to that of a correctly specified CAT test,it is natural to apply trend tests under different possible genetic models and to report the most significant test result.This results in a MAX-type testing procedure,and it was found that this test is usually more powerful than the Pearson’s chi-square test.Although the signi-ficance(i.e.,p value)of the MAX-type test can be accessed by either large sample approximation or permutation methods,requirements for sample size or simulation replicates are demanding with respect to accuracy and efficiency.This paper proposes an approach to calculate the exact p values of MAX-type tests based on the combinatorial counting method.The simulation results show that the exact method is more accurate than the large sample approximation methods and more computationally efficient than the permutation method,and our method can be readily applied to genome-wide association studies(GWASs).The proposed methodis built in an R package,MaXact,which is available at the https://github.com/Myuan 2019/MaXact/.展开更多
It is unknown whether oxygen uptake(VO_(2))sampling intervals influence the efficacy of a verification stage following a graded exercise test(GXT).Fifteen females and 14 males(18-25 years)completed a maximal treadmill...It is unknown whether oxygen uptake(VO_(2))sampling intervals influence the efficacy of a verification stage following a graded exercise test(GXT).Fifteen females and 14 males(18-25 years)completed a maximal treadmill GXT.After a 5min recovery,the verification stage began at the speed and grade corresponding with the penultimate stage from the GXT.Maximal oxygen consumption(VO_(2max))from the incremental GXT(iVO_(2max))and VO_(2max)from the verification stage(verVO_(2max))were determined using 10 seconds(s),30s,and 60s from breath×breath averages.There was no main effect for VO_(2max)measure(iVO_(2max)vs.verVO_(2max))10s([47.9±8.31]ml∙kg^(−1)∙min^(−1)vs[48.85±7.97]ml∙kg^(−1)∙min^(−1)),30s([46.94±8.62]ml∙kg^(−1)∙min^(−1)vs[47.28±7.97]ml∙kg^(−1)∙min^(−1)),and 60s([46.17±8.62]ml∙kg^(−1)∙min^(−1)vs[46.00±8.00]ml∙kg^(−1)∙min^(−1)].There was a stage×sampling interval interaction as the difference between(verVO_(2max)−iVO_(2max))was greater for 10-s than 60-s sampling intervals.The verVO_(2max)was>4%higher than iVO_(2max)in 31%,31%,and 17%of the tests for the 10-s,30-s,and 60-s sampling intervals respectively.Sensitivity for the plateau was<30%for 10-s,30-s,and 60-s sampling intervals.Specificity ranged from 44%to 60%for all sampling intervals.Sensitivity for heart rate+respiratory exchange ratio was>90%for all sampling intervals;while specificity was<25%.Findings from the present study suggest that the efficacy of verification stages for eliciting a higher VO_(2max)may be influenced by the sampling interval utilized.展开更多
基金This work was supported by the Natural Science Foundation of Anhui Province(2008085MA09)the National Natural Science Foundation of China(11671375).
文摘The three common genetic models(or modes of inheritance)in association analysis are the dominant,additive,and recessive models.It is known that the Cochran-Armitage trend test(CATT)which correctly incorporates information from genetic models,is more powerful than the commonly used Pearson’s chi-square test.However,the true genetic model is usually unknown in practice,and the power of the CAT test could be substantially reduced with a wrongly specified genetic model.To achieve a power that is close to that of a correctly specified CAT test,it is natural to apply trend tests under different possible genetic models and to report the most significant test result.This results in a MAX-type testing procedure,and it was found that this test is usually more powerful than the Pearson’s chi-square test.Although the signi-ficance(i.e.,p value)of the MAX-type test can be accessed by either large sample approximation or permutation methods,requirements for sample size or simulation replicates are demanding with respect to accuracy and efficiency.This paper proposes an approach to calculate the exact p values of MAX-type tests based on the combinatorial counting method.The simulation results show that the exact method is more accurate than the large sample approximation methods and more computationally efficient than the permutation method,and our method can be readily applied to genome-wide association studies(GWASs).The proposed methodis built in an R package,MaXact,which is available at the https://github.com/Myuan 2019/MaXact/.
文摘It is unknown whether oxygen uptake(VO_(2))sampling intervals influence the efficacy of a verification stage following a graded exercise test(GXT).Fifteen females and 14 males(18-25 years)completed a maximal treadmill GXT.After a 5min recovery,the verification stage began at the speed and grade corresponding with the penultimate stage from the GXT.Maximal oxygen consumption(VO_(2max))from the incremental GXT(iVO_(2max))and VO_(2max)from the verification stage(verVO_(2max))were determined using 10 seconds(s),30s,and 60s from breath×breath averages.There was no main effect for VO_(2max)measure(iVO_(2max)vs.verVO_(2max))10s([47.9±8.31]ml∙kg^(−1)∙min^(−1)vs[48.85±7.97]ml∙kg^(−1)∙min^(−1)),30s([46.94±8.62]ml∙kg^(−1)∙min^(−1)vs[47.28±7.97]ml∙kg^(−1)∙min^(−1)),and 60s([46.17±8.62]ml∙kg^(−1)∙min^(−1)vs[46.00±8.00]ml∙kg^(−1)∙min^(−1)].There was a stage×sampling interval interaction as the difference between(verVO_(2max)−iVO_(2max))was greater for 10-s than 60-s sampling intervals.The verVO_(2max)was>4%higher than iVO_(2max)in 31%,31%,and 17%of the tests for the 10-s,30-s,and 60-s sampling intervals respectively.Sensitivity for the plateau was<30%for 10-s,30-s,and 60-s sampling intervals.Specificity ranged from 44%to 60%for all sampling intervals.Sensitivity for heart rate+respiratory exchange ratio was>90%for all sampling intervals;while specificity was<25%.Findings from the present study suggest that the efficacy of verification stages for eliciting a higher VO_(2max)may be influenced by the sampling interval utilized.
