Rare Variant Association Testing by Adaptive Combination of P-values

Lin, Wan-Yu; Lou, Xiang‐Yang; Gao, Guimin; Liu, Nianjun

doi:10.1371/journal.pone.0085728

Cited by 31 publications

(78 citation statements)

References 43 publications

(91 reference statements)

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“…It would be appropriate to use methods more powerful for rare variants, such as burden tests and gene-based SNP-set (Sequence) Kernel Association Test (SKAT) tests. Burden tests analyze multiple rare variants, pool signals of these rare variants within a functional unit (e.g., a gene or a region), and then test for the association between the pooled signal and the phenotype [28]. Burden tests illustrate more power compared with studying individual variants one at a time [29].…”

Section: Discussionmentioning

confidence: 99%

Convergent Genetic and Expression Datasets Highlight TREM2 in Parkinson’s Disease Susceptibility

Liu

Liu²,

Jiang

et al. 2015

Mol Neurobiol

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A rare TREM2 missense mutation (rs75932628-T) was reported to confer a significant Alzheimer's disease (AD) risk. A recent study indicated no evidence of the involvement of this variant in Parkinson's disease (PD). Here, we used the genetic and expression data to reinvestigate the potential association between TREM2 and PD susceptibility. In stage 1, using 10 independent studies (N = 89,157; 8787 cases and 80,370 controls), we conducted a subgroup meta-analysis. We identified a significant association between rs75932628 and PD (P = 3.10E-03, odds ratio (OR) = 3.88, 95 % confidence interval (CI) 1.58-9.54) in No-Northern Europe subgroup, and significantly increased PD risks (P = 0.01 for Mann-Whitney test) in No-Northern Europe subgroup than in Northern Europe subgroup. In stage 2, we used the summary results from a large-scale PD genome-wide association study (GWAS; N = 108,990; 13,708 cases and 95,282 controls) to search for other TREM2 variants contributing to PD susceptibility. We identified 14 single-nucleotide polymorphisms (SNPs) associated with PD within 50-kb upstream and downstream range of TREM2. In stage 3, using two brain expression GWAS datasets (N = 773), we identified 6 of the 14 SNPs regulating increased expression of TREM2. In stage 4, using the whole human genome microarray data (N = 50), we further identified significantly increased expression of TREM2 in PD cases compared with controls in human prefrontal cortex. In summary, convergent genetic and expression datasets demonstrate that TREM2 is a potent risk factor for PD and may be a therapeutic target in PD and other neurodegenerative diseases.

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Section: Discussionmentioning

confidence: 99%

Convergent Genetic and Expression Datasets Highlight TREM2 in Parkinson’s Disease Susceptibility

Liu

Liu²,

Jiang

et al. 2015

Mol Neurobiol

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“…However, the test statistics will increase as the window size increases using the approach of Zaykin et al [3] . Although top SNPs have been found to be the same irrespective of the windows size, larger windows sizes may lead to anticonservative results [26] .…”

Section: Bt Datasetmentioning

confidence: 99%

Sığır Tüberkülozu İçin Çoklu Hipotez Düzeltmesi ile Genom Tabanlı İlişki Analizi

Karacaören¹

2016

Kafkas Univ Vet Fak Derg

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Citation of This ArticleKaracaören B: Multiple hypothesis testing in a genome wide association study of bovine tuberculosis. Kafkas Univ Vet Fak Derg, 23, 87-94, 2017. DOI: 10.9775/kvfd.2016 Abstract Genome-wide association studies (GWAS) have been used to detect single nucleotide polymorphisms (SNPs) related to various animal traits. The outcome of GWAS is based on quality of the both phenotypic and genotypic datasets. False positive (or negative) associations can be obtained due to multiple hypothesis testing procedures, quality control measures, or an undetected population structure. The objectives of this study were to 1) investigate different multiple hypothesis testing procedures with different quality measures and 2) to detect and correct ancestral stratification using different single SNPs models of the bovine tuberculosis GWA data set. Based on a regression model, SNPs from chromosomes 2, 7, 8 and 13 were detected at a significance level of P<0.001 without correction for multiple hypothesis testing. However, after Bonferroni correction, Hochberg's method and permutation test for multiple hypothesis correction genomic signals, it became non-significant. Only a false discovery rate approach detected weak signals (at level of 0.54) from chromosomes 2, 8, and 13. We used a model that took into account the effect of linkage disequilibrium to the multiple hypothesis testing procedures by combining adjacent SNPs test statistics with windows sizes of 2, 4 and 6. We detected strong genomic signals from chromosomes 13, 8, 6 and 2 at windows size 6. The results of this study showed that multiple hypothesis testing procedures are related to false positive genomic signals. It is difficult to suggest universally acceptable multiple hypothesis testing and QC measures and their thresholds due to sources of variations between species and within populations. However, additional analytical approaches and studies are needed to evaluate the effects of linkage disequilibrium on the multiple hypothesis testing procedures and QC measures (especially for minor allele frequencies) to GWAS under various scenarios including, but not limited to, level of heritability, linkage disequilibrium, population structure, and population size. Keywords: Genome wide association analyses, Multiple hypothesis testing, Quality control procedures Sığır Tüberkülozu İçin Çoklu Hipotez Düzeltmesi İle Genom Tabanlı İlişki Analizi ÖzetGenom tabanlı ilişki çalışmaları (GTİÇ) kullanılarak çiftlik hayvanlarının verimleri ile ilişkili tekil nükleotid polymorfizmler (TNP) belirlenebilmektedir. GTİÇ'den elde edilecek sonuçlar hem fenotip hem de genotip veri setlerinin kalitesine bağlı olacaktır. Populasyon tabakası, çoklu hipotez düzeltim yöntemleri ve kalite kontol süreçleri yanlış pozitif (veya negatif ) ilişki sonuçlarına yol açabilir. Bu çalışmanın amaçları: bir sığır tüberküloz GTİÇ veri setine 1) değişik kalite ölçütleri ve çoklu hipotez düzeltme yöntemlerinin 2) bazı TNP regresyon yöntemleri ile atasal tabakaların belirlenmesi ve düzeltilmesinin etk...

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“…Moreover, each sample can be a vector when multiple sites are considered jointly. Recently, there have been ever-increasing efforts on finding multiple SNVs jointly (DePristo et al 2011;Derkach et al 2013;Evangelou and Ioannidis 2013;Lin et al 2014;Liu et al 2014;Pan et al 2014). Also, we may test whether there is a collective inclining dominance of the representations of case samples over the ones of control samples, or vice versa, with help of the method proposed from Equations (79) and (84), as well as the extension introduced around Equations (87) and (89).…”

Section: Exome Sequencing Analysesmentioning

confidence: 99%

Bi-linear matrix-variate analyses, integrative hypothesis tests, and case-control studies

2015

Appl Inform

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We pursue a threefold purpose in this paper. First, we suggest a Kullback-Leibler formulation for developing a statistics and making discriminative projection for casecontrol studies, based on which existing typical methods are revisited and then further extended to matrix-variate counterparts. Second, we propose a bi-linear matrix form, based on which multivariate discriminative analysis and logistic, Cox, and linear mixed regression are extended into their matrix-variate counterparts. Third, we systematically address the necessity, feasibility, and methodology of integrative hypothesis tests (IHT) from the complementarity of model-based test and boundary-based test (BBT) in the data (D)-space, statistics (S)-space, and probability (P)-space. We elaborate four IHT components (modelling, comparison, classification, and assurance) and summarise four IHT types in the D-space. Then, we extend the existing efforts on multivariate tests to BBTs in the S-space. Particularly, we extend the classic univariate one-tail z-test to the multivariate ones, which is then applied to a multivariate sample-pairing delta (SPD) test for detecting a collective inclining dominance. Also, we propose a SPD discriminative analysis that extends this SPD test. Moreover, we propose a multivariate bi-test that tests the classic null and also a null about the inference reliability due to test space complexity, including a further development of Fisher combination. Finally, we suggest possible applications for gene expression biomarkers and exome-sequencing-based joint single-nucleotide variant (SNV) detection.

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Rare Variant Association Testing by Adaptive Combination of P-values

Cited by 31 publications

References 43 publications

Convergent Genetic and Expression Datasets Highlight TREM2 in Parkinson’s Disease Susceptibility

Convergent Genetic and Expression Datasets Highlight TREM2 in Parkinson’s Disease Susceptibility

Sığır Tüberkülozu İçin Çoklu Hipotez Düzeltmesi ile Genom Tabanlı İlişki Analizi

Bi-linear matrix-variate analyses, integrative hypothesis tests, and case-control studies

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