A modified Benjamini–Hochberg multiple comparisons procedure for controlling the false discovery rate

2002 ◽  
Vol 104 (2) ◽  
pp. 351-362 ◽  
Author(s):  
Koon Shing Kwong ◽  
Burt Holland ◽  
Siu Hung Cheung
Keyword(s):  
False Discovery Rate ◽  
Multiple Comparisons ◽  
False Discovery

Replication of Candidate Gene Single Nucleotide Polymorphisms (SNPs) Previously Reported As Associated with Venous Thromboembolism (VTE)

Blood ◽  
2011 ◽  
Vol 118 (21) ◽  
pp. 1238-1238
Author(s):  
Anita D'Souza ◽  
Sebastian M. Armasu ◽  
Mariza de Andrade ◽  
John A. Heit
Keyword(s):  
Candidate Gene ◽  
False Discovery Rate ◽  
Population Stratification ◽  
Multiple Comparisons ◽  
Blood Type ◽  
European Ancestry ◽  
Q Value ◽  
False Discovery Rates ◽  
False Discovery ◽  
Discovery Rates

Abstract Abstract 1238 Background: SNPs within genes encoding factor XI (F11), fibrinogen genes (FGA, FGG) and other candidate genes within the procoagulant, anticoagulant, fibrinolytic, innate immunity and endocrine pathways have been reported as associated with VTE. However, the independent risk of VTE associated with many of these SNPs after controlling for factor V Leiden, Prothrombin G20210A and ABO blood group non-O carrier status is uncertain. Objective: To replicate candidate gene SNPs previously reported as associated with VTE. Methods: As part of a large replication study, we included 17 SNPs previously reported as associated with VTE in a custom Illumina Golden gate (total n=1093 SNPs) genotyping array. We genotyped 1270 non-Hispanic adults of European ancestry with objectively-diagnosed VTE (cases; no cancer, venous catheter or antiphospholipid antibodies) and 1302 controls (frequency-matched on case age, gender, race, MI/stroke status). Genotyping results from high-quality control DNA (SNP call rate ≥ 95%) was used to generate a cluster algorithm. The primary outcome was VTE status, a binary measure. The covariates were age at interview or blood sample collection, sex, stroke and/or MI status, and state of residence. To adjust for population stratification, we performed the multidimensional scaling (MDS) analysis option in PLINK v 1.07 to identify outliers in our population using the ancestry informative markers. We tested for an association between each SNP and VTE using unconditional logistic regression, adjusting for age, sex, stroke/MI status, state of residence and ABO rs514659 (in high linkage disequilibrium with non-O blood type). The analyses were corrected for multiple comparisons using an extension of false discovery rates. The false discovery rate (reported as a Q-value) is an analogue measure of the p-value that takes into account the number of statistical tests and estimates the expected proportion of false positive tests incurred when a particular SNP is significant. All analyses were performed using PLINK v 1.07. Results: MDS gave no evidence of population stratification. Genotyping was unsuccessful for two of the 17 SNPs. We found significant associations between VTE and SNPs in F11, FGG, TC2D and FGA (Table). However, the false discovery rates for all significant SNPs except F11 rs3756008 were >0.05, suggesting that the observed associations were likely falsely positive due to multiple comparisons. Even at a false discovery rate of Q-value=0.0099, one would expect ∼13 SNPs (0.0099 × 1302 SNPs) to be falsely associated with VTE due to multiple comparisons. Consequently, even our observed association between F11 rs3756008 and VTE remains tentative. Conclusions: We were unable to replicate reported associations between 15 SNPs and VTE. Our results emphasize the necessity of replication studies in different populations to confirm reported associations of SNPs with VTE. Disclosures: Heit: Daiichi Sankyo: Consultancy, Honoraria.

Multiple comparisons: philosophies and illustrations

2000 ◽  
Vol 279 (1) ◽  
pp. R1-R8 ◽  
Author(s):  
Douglas Curran-Everett
Keyword(s):  
False Discovery Rate ◽  
Null Hypothesis ◽  
Scientific Discovery ◽  
Multiple Comparisons ◽  
False Discovery Rate Procedure ◽  
False Discovery ◽  
Scientific Disciplines ◽  
Significant Difference ◽  
Statistical Issue ◽  
Promising Development

Statistical procedures underpin the process of scientific discovery. As researchers, one way we use these procedures is to test the validity of a null hypothesis. Often, we test the validity of more than one null hypothesis. If we fail to use an appropriate procedure to account for this multiplicity, then we are more likely to reach a wrong scientific conclusion—we are more likely to make a mistake. In physiology, experiments that involve multiple comparisons are common: of the original articles published in 1997 by the American Physiological Society, ∼40% cite a multiple comparison procedure. In this review, I demonstrate the statistical issue embedded in multiple comparisons, and I summarize the philosophies of handling this issue. I also illustrate the three procedures—Newman-Keuls, Bonferroni, least significant difference—cited most often in my literature review; each of these procedures is of limited practical value. Last, I demonstrate the false discovery rate procedure, a promising development in multiple comparisons. The false discovery rate procedure may be the best practical solution to the problems of multiple comparisons that exist within physiology and other scientific disciplines.

scholarly journals Association between C-Maf-inducing protein gene rs2287112 polymorphism and schizophrenia

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e11907
Author(s):  
Yingli Fu ◽  
Xiaojun Ren ◽  
Wei Bai ◽  
Qiong Yu ◽  
Yaoyao Sun ◽  
...  
Keyword(s):  
Linkage Disequilibrium ◽  
False Discovery Rate ◽  
Chinese Population ◽  
Multiple Comparisons ◽  
Han Chinese ◽  
Type I ◽  
Healthy Controls ◽  
False Discovery Rate Correction ◽  
Han Chinese Population ◽  
False Discovery

Background Schizophrenia is a severely multifactorial neuropsychiatric disorder, and the majority of cases are due to genetic variations. In this study, we evaluated the genetic association between the C-Maf-inducing protein (CMIP) gene and schizophrenia in the Han Chinese population. Methods In this case-control study, 761 schizophrenia patients and 775 healthy controls were recruited. Tag single-nucleotide polymorphisms (SNPs; rs12925980, rs2287112, rs3751859 and rs77700579) from the CMIP gene were genotyped via matrix-assisted laser desorption/ionization time of flight mass spectrometry. We used logistic regression to estimate the associations between the genotypes/alleles of each SNP and schizophrenia in males and females, respectively. The in-depth link between CMIP and schizophrenia was explored through linkage disequilibrium (LD) and further haplotype analyses. False discovery rate correction was utilized to control for Type I errors caused by multiple comparisons. Results There was a significant difference in rs287112 allele frequencies between female schizophrenia patients and healthy controls after adjusting for multiple comparisons (χ2 = 12.296, Padj = 0.008). Females carrying minor allele G had 4.445 times higher risk of schizophrenia compared with people who carried the T allele (OR = 4.445, 95% CI [1.788–11.046]). Linkage-disequilibrium was not observed in the subjects, and people with haplotype TTGT of rs12925980–rs2287112–rs3751859–rs77700579 had a lower risk of schizophrenia (OR = 0.42, 95% CI [0.19–0.94]) when compared with CTGA haplotypes. However, the association did not survive false discovery rate correction. Conclusion This study identified a potential CMIP variant that may confer schizophrenia risk in the female Han Chinese population.

scholarly journals False Discovery Rate in Linkage and Association Genome Screens for Complex Disorders

Genetics ◽  
2003 ◽  
Vol 164 (2) ◽  
pp. 829-833
Author(s):  
Chiara Sabatti ◽  
Susan Service ◽  
Nelson Freimer
Keyword(s):  
Gene Mapping ◽  
False Discovery Rate ◽  
Disease Gene ◽  
Susceptibility Genes ◽  
Complex Disorders ◽  
Disease Gene Mapping ◽  
False Discovery ◽  
Simple Step ◽  
Multiple Comparison Procedure ◽  
Step Down

Abstract We explore the implications of the false discovery rate (FDR) controlling procedure in disease gene mapping. With the aid of simulations, we show how, under models commonly used, the simple step-down procedure introduced by Benjamini and Hochberg controls the FDR for the dependent tests on which linkage and association genome screens are based. This adaptive multiple comparison procedure may offer an important tool for mapping susceptibility genes for complex diseases.

scholarly journals P14.21 Tehila Kaisman-Elbaz MD/PhD

2019 ◽  
Vol 21 (Supplement_3) ◽  
pp. iii71-iii71
Author(s):  
T Kaisman-Elbaz ◽  
Y Elbaz ◽  
V Merkin ◽  
L Dym ◽  
A Noy ◽  
...  
Keyword(s):  
Overall Survival ◽  
Multivariate Analysis ◽  
False Discovery Rate ◽  
Medical Center ◽  
Tumor Resection ◽  
Multiple Hypothesis Testing ◽  
Hemoglobin Level ◽  
Distribution Width ◽  
False Discovery ◽  
Dismal Prognosis

Abstract BACKGROUND Glioblastoma is known for its dismal prognosis though its dependency on patients’ readily available RBCs parameters defining the patient’s anemic status such as hemoglobin level and Red blood cells distribution Width (RDW) is not fully established. Several works demonstrated a connection between low hemoglobin level or high RDW values to overall glioblastoma patient’s survival, but in other works, a clear connection was not found. This study addresses this unclarity. MATERIAL AND METHODS In this work, 170 glioblastoma patients, diagnosed and treated in Soroka University Medical Center (SUMC) in the last 12 years were retrospectively inspected for their survival dependency on pre-operative RBCs parameters using multivariate analysis followed by false discovery rate procedure due to the multiple hypothesis testing. A survival stratification tree and Kaplan-Meier survival curves that indicate the patient’s prognosis according to these parameters were prepared. RESULTS Beside KPS>70 and tumor resection supplemented by oncological treatment, age<70 (HR=0.4, 95% CI 0.24–0.65), low hemoglobin level (HR=1.79, 95% CI 1.06–2.99) and RDW<14% (HR=0.57, 95% CI 0.37–0.88) were found to be prognostic to patients’ overall survival in multivariate analysis, accounting for false discovery rate of less than 5%. CONCLUSION A survival stratification highlighted a non-anemic subgroup of nearly 30% of the cohort’s patients whose median overall survival was 21.1 months (95% CI 16.2–27.2) - higher than the average Stupp protocol overall median survival of about 15 months. A discussion on the beneficial or detrimental effect of RBCs parameters on glioblastoma prognosis and its possible causes is given.

scholarly journals Associations Between Genetically Predicted Protein Levels and COVID-19 Severity

2020 ◽  
Vol 223 (1) ◽  
pp. 19-22
Author(s):  
Jingjing Zhu ◽  
Chong Wu ◽  
Lang Wu
Keyword(s):  
False Discovery Rate ◽  
Drug Repurposing ◽  
Bonferroni Correction ◽  
Host Genetics ◽  
Protein Levels ◽  
False Discovery

Abstract It is critical to identify potential causal targets for SARS-CoV-2, which may guide drug repurposing options. We assessed the associations between genetically predicted protein levels and COVID-19 severity. Leveraging data from the COVID-19 Host Genetics Initiative comparing 6492 hospitalized COVID-19 patients and 1 012 809 controls, we identified 18 proteins with genetically predicted levels to be associated with COVID-19 severity at a false discovery rate of &lt;0.05, including 12 that showed an association even after Bonferroni correction. Of the 18 proteins, 6 showed positive associations and 12 showed inverse associations. In conclusion, we identified 18 candidate proteins for COVID-19 severity.

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