Index of papers in PLOS Comp. Biol. that mention
  • false discovery rate
Peter Klimek, Alexandra Kautzky-Willer, Anna Chmiel, Irmgard Schiller-Frühwirth, Stefan Thurner
Data
To correct for these multiple comparisons we apply the Benjamini-Hoch-berg procedure [17] to control for the false discovery rate a.
Data
For example, if 100 comorbidities are identified with a false discovery rate a of a = 0.01, the eXpected number of false positives among these comorbidities is one.
Data
We Will therefore be interested in the recall R(a) as a function of the false discovery rate a. R(a) is the probability that a diabetic comorbidity listed in Table 1 is also identified by our co-occurrence analysis at a given level of a.
Results/Discussion
Each diagnosis where the null hypothesis of statistical independence with either DM1 or DMZ can be rejected with a given value of the false discovery rate in at least one of the age groups is identified as a comorbidity.
Results/Discussion
A false discovery rate of a = 0.001 gives a list of 75 significant comorbidities and a recall of R(a = 0.001) = 0.59.
false discovery rate is mentioned in 5 sentences in this paper.
Topics mentioned in this paper:
Alan L. Hutchison, Mark Maienschein-Cline, Andrew H. Chiang, S. M. Ali Tabei, Herman Gudjonson, Neil Bahroos, Ravi Allada, Aaron R. Dinner
Abstract
We find that ANOVA, F24, and JTK_CYCLE consistently outperform the other three methods when data are limited and noisy; empirical JTK_CYCLE with asymmetry search gives the greatest sensitivity while controlling for the false discovery rate .
Conclusions
This enables control of the false discovery rate and testing waveforms beyond sinusoidal ones.
E 3 A A g Time s 'r r a E A AA Time Time
A common alternative to the Bonferroni correction is the Benjamini-Hochberg procedure [36], which seeks to control the false discovery rate (FDR).
Simulated data benchmarks
6C and D, we see that the performance of the methods differs considerably when controlling for the false discovery rate (FDR).
Supporting Information
The vertical axis shows the number of genes With a p-value (P) (A and B) or false discovery rate (FDR, the Benjamini-Hochberg adjusted p-value) (C and D) below or equal to a significance threshold, shown on
false discovery rate is mentioned in 5 sentences in this paper.
Topics mentioned in this paper:
Fan Yang, Evangelia Petsalaki, Thomas Rolland, David E. Hill, Marc Vidal, Frederick P. Roth
Cancer-type-specific domain mutation landscapes across 21 cancer types
We identified ~ 100 cancer-type-specific significantly mutated domain instances (SMDs) in 21 cancer types (S2 Table; P-value = 10—7, Fisher’s Exact test, False Discovery Rate (FDR) <0.05).
Cancer-type-specific significantly-mutated domain instance analyses
We chose a P-value threshold (OL = 10—7) yielding a false discovery rate (FDR) of less than 0.05.
Cancer-type-specific significantly-mutated position based mutational hotspot analyses
False discovery rate analysis was performed using Benjamini & Hochberg FDR[142].
false discovery rate is mentioned in 3 sentences in this paper.
Topics mentioned in this paper: