The Functional False Discovery Rate with Applications to Genomics

Chen, Xiongzhi; Robinson, David G.; Storey, John D.

doi:10.1101/241133

Cited by 9 publications

(8 citation statements)

References 35 publications

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“…Recently, a new class of methods that control the FDR (Figure 1, Additional file 1: Table S1) have been proposed to exploit this variability across tests by combining the standard input (p-values or test statistics) [13,14,26] with a second piece information, referred to as an "informative covariate" [15][16][17][18][19]27]. Intuitively, if a covariate is informative of each test's power or prior probability of being non-null, it can be used to prioritize individual or groups of tests to increase the overall power across the entire experiment [15].…”

Section: Ashmentioning

confidence: 99%

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A practical guide to methods controlling false discoveries in computational biology

Korthauer

Kimes

Duvallet³

et al. 2018

Preprint

106

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Background: In high-throughput studies, hundreds to millions of hypotheses are typically tested. Statistical methods that control the false discovery rate (FDR) have emerged as popular and powerful tools for error rate control. While classic FDR methods use only p-values as input, more modern FDR methods have been shown to increase power by incorporating complementary information as "informative covariates" to prioritize, weight, and group hypotheses. However, there is currently no consensus on how the modern methods compare to one another. We investigated the accuracy, applicability, and ease of use of two classic and six modern FDR-controlling methods by performing a systematic benchmark comparison using simulation studies as well as six case studies in computational biology.Results: Methods that incorporate informative covariates were modestly more powerful than classic approaches, and did not underperform classic approaches, even when the covariate was completely uninformative. The majority of methods were successful at controlling the FDR, with the exception of two modern methods under certain settings. Furthermore, we found the improvement of the modern FDR methods over the classic methods increased with the informativeness of the covariate, total number of hypothesis tests, and proportion of truly non-null hypotheses.Conclusions: Modern FDR methods that use an informative covariate provide advantages over classic FDR-controlling procedures, with the relative gain dependent on the application and informativeness of available covariates. We present our findings as a practical guide and provide recommendations to aid researchers in their choice of methods to correct for false discoveries.

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Section: Ashmentioning

confidence: 99%

“…For FDR methods that can use an informative covariate, we used mean expression across samples, as indicated in the DESeq2 vignette. Full results are provided in Additional files [26][27].…”

Section: Gene Set Analysismentioning

confidence: 99%

A practical guide to methods controlling false discoveries in computational biology

Korthauer

Kimes

Duvallet³

et al. 2018

Preprint

106

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“…Comparisons between groups were determined using a two-tailed Student's t-test or one-way ANOVA with Tukey's post hoc test. Aberrantly expressed lncRNAs were examined based on the Benjamini-Hochberg method ( 23 ). The association between the expression of LINC00319 and the expression of miR-200a-3p was analyzed using Pearson's correlation.…”

Section: Methodsmentioning

confidence: 99%

Upregulated LINC00319 aggravates neuronal injury induced by oxygen‑glucose deprivation via modulating miR‑200a‑3p

et al. 2021

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Ischemic stroke is one of the main causes of physical disability and mortality worldwide. Long non-coding RNAs (lncRNAs) are reported to be dysregulated in various biological progressions and serve important roles in pathological processes of cerebral ischemia. However, their biological actions and potential mechanisms in the progression of ischemic stroke remain unknown. The present study aimed to investigate the functions of LINC00319 on ischemic brain injury. It was identified that LINC00319 was significantly upregulated in the Gene Expression Omnibus profile of ischemic stroke. Furthermore, LINC00319 overexpression elevated caspase-3 activity and increased the apoptotic rate of neuronal cells, as well as decreased cell viability and glucose uptake. It was also demonstrated that LINC00319 participated in oxygen-glucose deprivation (OGD)-induced cerebral ischemic injury. LINC00319 could competitively bind with microRNA (miR)-200a-3p and decrease its expression. Moreover, miR-200a-3p could partly offset the negative effects of LINC00319 overexpression on neuronal injury caused by OGD. Collectively, the present results suggested that LINC00319 promoted apoptosis and aggravated neuronal injury induced by OGD by regulating miR-200a-3p, which may be important for ischemic stroke treatment.

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“…Class IV: methods that employ weights that are induced by an informative covariate and are assumed to be independent of their corresponding p ‐values under the null hypothesis, or that employ an informative variable that is independent of p ‐value under the null hypothesis and a functional proportion of true null hypothesis; see Ignatiadis et al. (2016), Chen, Robinson, and Storey (2019), and Ignatiadis and Huber (2018). More specifically, the “independent hypothesis weighting (IHW)” method of Ignatiadis et al.…”

Section: Introductionmentioning

confidence: 99%