Gene‐based sequential burden association test

Chen, Zhongxue; Wang, Kai

doi:10.1002/sim.8111

Cited by 8 publications

(7 citation statements)

References 28 publications

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“…In this study, variant association analysis indicated the existence of moderate genomic inflation between these two cattle breeds, and no associated SNPs were detected. Therefore, based on advantages in detecting associations such as higher efficiency (greater detection power, and lower criteria for multiple testing) (Chen and Wang, 2019), a gene-based association strategy was used to identify physical traits associated with specific genes. Three gene-based methods (SKAT, SKATO, and Burden) showed there was moderate genomic inflation and that no gene could pass the threshold of the Bonferroni correction P-value.…”

Section: Discussionmentioning

confidence: 99%

Whole Transcriptome Analysis Identifies the Taxonomic Status of a New Chinese Native Cattle Breed and Reveals Genes Related to Body Size

et al. 2020

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Wandong (WD) cattle has recently been identified as a new Chinese native cattle breed by the National Commission for Livestock and Poultry Genetic Resources. The population size of this breed is less than 10,000. WD cattle and Dabieshan (DB) cattle are sympatric but are raised in different ecological environments, on mountains and plains, respectively, and the body sizes of these two breeds are markedly different. Blood samples were obtained from 8 adult female WD cattle and 7 adult female DB cattle (24 months old). The total RNA was extracted from leukocyte cells, and sequencing experiments were conducted on the Illumina HiSeq TM 4000 platform. After the removal of one outlier sample from the WD cattle breed as determined by principal component analysis (PCA), phylogenetic and population structure analyses indicated that WD and DB cattle formed a distinct Central China cattle group and showed evidence of hybridization between Bos. taurus and Bos. indicus. The immune-regulator CD48 (P = 1.3E-6) was associated with breed-specific traits according to loss-offunction variant enrichment analysis. In addition, 113 differentially expressed genes were identified between the two breeds, many of which are associated with the regulation of body growth, which is the major difference between the two breeds. This study showed that WD cattle belong to the group of hybrids between Bos. Taurus and Bos. indicus, and one novel gene associated with breed traits and multiple differentially expressed genes between these two closely related breeds was identified. The results provide insights into the genetic mechanisms that underlie economically important traits, such as body size, in cattle.

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Section: Discussionmentioning

confidence: 99%

Whole Transcriptome Analysis Identifies the Taxonomic Status of a New Chinese Native Cattle Breed and Reveals Genes Related to Body Size

et al. 2020

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“…As a secondary data analysis, we also considered sex as the only covariate to be adjusted in the logistic regression model. For comparison, we also reported the p-values from the score test S(x) (x = 0, 1 2 , and 1) and the LRT. Table 4 summarizes the results.…”

Section: Real Data Applicationmentioning

confidence: 99%

“…The goal of a genetic association study is to identify candidate genetic factors that are associated with specific disease status [1][2][3][4][5][6]. Toward this goal, a variety of statistical methods have been developed to test the association between disease and genetic variants [7][8][9][10][11][12].…”

Section: Introductionmentioning

confidence: 99%

CMAX3: A Robust Statistical Test for Genetic Association Accounting for Covariates

Chen

Zang

2021

Genes

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The additive genetic model as implemented in logistic regression has been widely used in genome-wide association studies (GWASs) for binary outcomes. Unfortunately, for many complex diseases, the underlying genetic models are generally unknown and a mis-specification of the genetic model can result in a substantial loss of power. To address this issue, the MAX3 test (the maximum of three separate test statistics) has been proposed as a robust test that performs plausibly regardless of the underlying genetic model. However, the original implementation of MAX3 utilizes the trend test so it cannot adjust for any covariates such as age and gender. This drawback has significantly limited the application of the MAX3 in GWASs, as covariates account for a considerable amount of variability in these disorders. In this paper, we extended the MAX3 and proposed the CMAX3 (covariate-adjusted MAX3) based on logistic regression. The proposed test yielded a similar robust efficiency as the original MAX3 while easily adjusting for any covariate based on the likelihood framework. The asymptotic formula to calculate the p-value of the proposed test was also developed in this paper. The simulation results showed that the proposed test performed desirably under both the null and alternative hypotheses. For the purpose of illustration, we applied the proposed test to re-analyze a case-control GWAS dataset from the Collaborative Studies on Genetics of Alcoholism (COGA). The R code to implement the proposed test is also introduced in this paper and is available for free download.

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“…With recent advancements in biotechnologies, huge amount of data has been generated in genetics and genomics studies. For instance, in genomewide association studies (GWAS) to identify genetic risk factors associated with given disease, many gene-or set-based association tests have been developed which utilize the approaches for combining p-values [10][11][12][13][14] . How to combine these p-values is still a challenging topic in the area.…”

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confidence: 99%

Robust tests for combining p-values under arbitrary dependency structures

Chen

2022

Sci Rep

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Recently Liu and Xie proposed a p-value combination test based on the Cauchy distribution (CCT). They showed that when the significance levels are small, CCT can control type I error rate and the resulting p-value can be simply approximated using a Cauchy distribution. One very special and attractive property of CCT is that it is applicable to situations where the p-values to be combined are dependent. However, in this paper, we show that under some conditions the commonly used MinP test is much more powerful than CCT. In addition, under some other situations, CCT is powerless at all. Therefore, we should use CCT with caution. We also proposed new robust p-value combination tests using a second MinP/CCT to combine the dependent p-values obtained from CCT and MinP applied to the original p-values. We call the new tests MinP-CCT-MinP (MCM) and CCT-MinP-CCT (CMC). We study the performance of the new tests by comparing them with CCT and MinP using comprehensive simulation study. Our study shows that the proposed tests, MCM and CMC, are robust and powerful under many conditions, and can be considered as alternatives of CCT or MinP.

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Gene‐based sequential burden association test

Cited by 8 publications

References 28 publications

Whole Transcriptome Analysis Identifies the Taxonomic Status of a New Chinese Native Cattle Breed and Reveals Genes Related to Body Size

Whole Transcriptome Analysis Identifies the Taxonomic Status of a New Chinese Native Cattle Breed and Reveals Genes Related to Body Size

CMAX3: A Robust Statistical Test for Genetic Association Accounting for Covariates

Robust tests for combining p-values under arbitrary dependency structures

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