The <b>poolr</b> Package for Combining Independent and Dependent  <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns="http://www.w3.org/1998/Math/MathML"> <mml:mrow><mml:mi>p</mml:mi></mml:mrow> </mml:math>  Values

Cinar, Ozan; Viechtbauer, Wolfgang

doi:10.18637/jss.v101.i01

Cited by 58 publications

(38 citation statements)

References 49 publications

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“…We used the largest cohort (ALSPAC) to derive the correlation structure. According to the Li and Ji (2005) method, as implemented in poolR (Cinar & Viechtbauer, n.d.), the number of independent tests is 99, resulting in a Bonferroni adjusted threshold of p < .05/99 < 5.0 × 10 −4 . We express the variance explained as the difference in R 2 compared with a covariates only model without PRSs.…”

Section: Methodsmentioning

confidence: 99%

Combined polygenic risk scores of different psychiatric traits predict general and specific psychopathology in childhood

Neumann

Jolicoeur-Martineau

Székely

et al. 2021

Child Psychology Psychiatry

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Background: Polygenic risk scores (PRSs) operationalize genetic propensity toward a particular mental disorder and hold promise as early predictors of psychopathology, but before a PRS can be used clinically, explanatory power must be increased and the specificity for a psychiatric domain established. To enable early detection, it is crucial to study these psychometric properties in childhood. We examined whether PRSs associate more with general or with specific psychopathology in school-aged children. Additionally, we tested whether psychiatric PRSs can be combined into a multi-PRS score for improved performance. Methods: We computed 16 PRSs based on GWASs of psychiatric phenotypes, but also neuroticism and cognitive ability, in mostly adult populations. Study participants were 9,247 school-aged children from three population-based cohorts of the DREAM-BIG consortium: ALSPAC (UK), The Generation R Study (Netherlands), and MAVAN (Canada). We associated each PRS with general and specific psychopathology factors, derived from a bifactor model based on self-report and parental, teacher, and observer reports. After fitting each PRS in separate models, we also tested a multi-PRS model, in which all PRSs are entered simultaneously as predictors of the general psychopathology factor. Results: Seven PRSs were associated with the general psychopathology factor after multiple testing adjustment, two with specific externalizing and five with specific internalizing psychopathology. PRSs predicted general psychopathology independently of each other, with the exception of depression and depressive symptom PRSs. Most PRSs associated with a specific psychopathology domain, were also associated with general child psychopathology. Conclusions: The results suggest that PRSs based on current GWASs of psychiatric phenotypes tend to be associated with general psychopathology, or both general and specific psychiatric domains, but not with one specific psychopathology domain only. Furthermore, PRSs can be combined to improve predictive ability. PRS users should therefore be conscious of nonspecificity and consider using multiple PRSs simultaneously, when predicting psychiatric disorders.

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Section: Methodsmentioning

confidence: 99%

Combined polygenic risk scores of different psychiatric traits predict general and specific psychopathology in childhood

Neumann

Jolicoeur-Martineau

Székely

et al. 2021

Child Psychology Psychiatry

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“…While the unadjusted methods show no noteworthy increase in computational times as a function of the gene size, the results show that the use of the adjustments does come at the cost of increased computational times, less so for the Li & Ji adjustment and more so when using the Brown and Strube methods. Finally, as expected, the empirical methods demand the highest amount of computer time (although this can be mitigated to some extent; see Cinar and Viechtbauer (2022) for details). The computation times for the different test types, however, did not appear to vary substantially.…”

Section: Resultsmentioning

confidence: 79%

A Comparison of Methods for Gene-Based Testing That Account for Linkage Disequilibrium

Cinar

Viechtbauer

2022

Front. Genet.

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Controlling the type I error rate while retaining sufficient power is a major concern in genome-wide association studies, which nowadays often examine more than a million single-nucleotide polymorphisms (SNPs) simultaneously. Methods such as the Bonferroni correction can lead to a considerable decrease in power due to the large number of tests conducted. Shifting the focus to higher functional structures (e.g., genes) can reduce the loss of power. This can be accomplished via the combination of p-values of SNPs that belong to the same structural unit to test their joint null hypothesis. However, standard methods for this purpose (e.g., Fisher’s method) do not account for the dependence among the tests due to linkage disequilibrium (LD). In this paper, we review various adjustments to methods for combining p-values that take LD information explicitly into consideration and evaluate their performance in a simulation study based on data from the HapMap project. The results illustrate the importance of incorporating LD information into the methods for controlling the type I error rate at the desired level. Furthermore, some methods are more successful in controlling the type I error rate than others. Among them, Brown’s method was the most robust technique with respect to the characteristics of the genes and outperformed the Bonferroni method in terms of power in many scenarios. Examining the genetic factors of a phenotype of interest at the gene-rather than SNP-level can provide researchers benefits in terms of the power of the study. While doing so, one should be careful to account for LD in SNPs belonging to the same gene, for which Brown’s method seems the most robust technique.

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“…These methods assume independence among the tests being compared; however, the p -values obtained from the marginal distributions of order statistics are highly correlated. We therefore use the Tippett method as implemented in the poolr package for R (v1.1-1; Cinar and Viechtbauer 2022) to account for the dependency structure among the values in X . We use the “empirical” Tippett method in poolr , which samples sets of p -values using an estimate of their dependency structure.…”

Section: Methodsmentioning

confidence: 99%

Using genome scans to identify genes used repeatedly for adaptation

Booker

Yeaman

Whitlock

2022

Preprint

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Adaptation occurring in similar genes or genomic regions in distinct lineages provides evolutionary biologists with a glimpse at the fundamental opportunities for and constraints to diversification. With the widespread availability of high throughput sequencing technologies and the development of population genetic methods to identify the genetic basis of adaptation, studies have begun to compare the evidence for adaptation at the molecular level among distinct lineages. However, methods to study repeated adaptation are often oriented towards genome-wide testing to identify a set of genes with signatures of repeated use, rather than evaluating the significance at the level of an individual gene. In this study, we propose PicMin, a novel statistical method derived from the theory of order statistics that can test for repeated molecular evolution to estimate significance at the level of an individual gene, using the results of genome scans. This method is generalizable to any number of lineages and indeed, statistical power to detect repeated adaptation increases with the number of lineages that have signals of repeated adaptation of a given gene in multiple lineages. An implementation of the method written for R can be downloaded from https://github.com/TBooker/PicMin.

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The poolr Package for Combining Independent and Dependent p Values

Cited by 58 publications

References 49 publications

Combined polygenic risk scores of different psychiatric traits predict general and specific psychopathology in childhood

Combined polygenic risk scores of different psychiatric traits predict general and specific psychopathology in childhood

A Comparison of Methods for Gene-Based Testing That Account for Linkage Disequilibrium

Using genome scans to identify genes used repeatedly for adaptation

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