False discovery proportion
A Tight Prediction Interval for False Discovery Proportion under Dependence
... The false discovery proportion (FDP) is a useful measure of abundance of false positives when a large number of hy- potheses are being tested ...the false dis- covery rate (FDR), have ...
9
False discovery proportion estimation by permutations: confidence for significance analysis of microarrays
... When multiple hypotheses are tested, interest is often in estimating the false discovery proportion (FDP), the number of false positives divided by the total number of rejections. When there ...
29
Asymptotic Results on Adaptive False Discovery Rate Controlling Procedures Based on Kernel Estimators
... The False Discovery Rate (FDR) is a commonly used type I error rate in multiple testing ...expected False Discovery Proportion (FDP), that is, the expected fraction of false ...
37
Controlling false discovery rates in factorial experiments with between subjects and within subjects tests
... Background: The False Discovery Rate (FDR) controls the expected number of false positives among the positive test results. It is not straightforward how to conduct a FDR controlling procedure in ...
5
Coordinate based meta analysis of functional neuroimaging data: false discovery control and diagnostics
... Control of type 1 statistical error in neuroimaging is of huge importance, and the adaptive FDR control (BH-FDR) introduced by Benjamini and Hochberg [14] is often employed. The scheme estimates the number of falsely ...
12
Application of the False Discovery Rate to Quantitative Trait Loci Interval Mapping With Multiple Traits
... definition false for traits the multiple-trait test, the number of QTL detected for that have been shown by prior biometrical analyses to carcass weight and last rib back fat at the 10% level have nonzero ...the ...
10
The effect of photofit type faces on recognition memory : a thesis presented in partial fulfillment of the requirement for the degree of Master of Arts in psychology at Massey University
... The three measures most frequently used are hits the proportion of "target" responses for faces previously seen in the study phase, false alarms the proportion of "target" responses for [r] ...
85
Detecting multiple associations in genome-wide studies
... the false discovery variance is relatively high in relation to the target rate, and the FDR approach may not be reliable for controlling the error rate within ...
8
A biplot correlation range for group-wise metabolite selection in mass spectrometry
... The discovery of discriminating metabolites related to sphingosine was unantici- pated but reasonable in terms of what is known about ceramide metabolism. Cer- amide is an endogenous mediator of apoptotic cell ...
24
Discrete False-Discovery Rate Improves Identification of Differentially Abundant Microbes
... discrete false-discovery rate (DS-FDR), that greatly improves the power to detect differential taxa by exploiting the discreteness of the ...a false-discovery rate that is up to threefold more ...
15
Preventing false discovery of heterogeneous treatment effect subgroups in randomized trials
... an effect estimate within each node as the proportion ex- periencing the outcome in the treated group minus the proportion experiencing the outcome in the control sub- set of the trial. Using similar logic ...
15
False Discovery Rate in Linkage and Association Genome Screens for Complex Disorders
... 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 ...
6
Usage of Machine Learning for Intrusion Detection in a Network
... It is evident from the above table 1 that RandomForest offer highest detection rate and lowest false alarms in comparison to other 14 algorithms. RandomForest takes significant time in building model because it ...
9
A New Approach to the Problem of Multiple Comparisons in the Genetic Dissection of Complex Traits
... “false discovery rate,” that is, the expected proportion of true null hypotheses within the class of rejected null ...the false discovery rate, power to detect true effects is not ...
8
What p-value must be used as the Statistical Significance Threshold? P
... Are False” [4] has been commented by Jager & Leek [17] who reported a substantial reduction of the “false discovery rate” to 14% leading to the conclusion that “the medical literature remains a ...
9
Comparative Proteomic Analysis of Candida albicans and Candida glabrata
... as determined by Pro Group algorithm were used for further analysis. We used false discovery rate analysis by PSPEP software that is in-built into ProteinPilot 3.0. The data generated by LC-MS/MS analysis ...
11
TCC GUI: a Shiny based application for differential expression analysis of RNA Seq count data
... Similar to the original TCC , TCC-GUI can generate simulation data with various conditions in Step 0. The generated data can, of course, be used as input for DE analysis within TCC-GUI, as well as other tools. The ...
6
c83b84d6e5ab7821f60a15c55f422d70c7e272fb.pdf
... Figure 1: The Poisson-multivariate normal hierarchical model outperforms SparCC and glasso in a synthetic experiment. a) Frobenius norm of the difference between the partial correlation transformed true precision matrix ...
11
Optimal likelihood-ratio multiple testing with application to Alzheimer’s disease and questionable dementia
... ratio-based false discovery rate method can control the false discovery rate, giving the smallest false non-discovery rate (for a one-sided test) or the smallest expected number ...
11
A non-parametric maximum for number of selected features: objective optima for FDR and significance threshold with application to ordinal survey analysis
... High-dimensionality is one of the attributes of big data in many fields. As stated by Dutheil and Hobolth [7], the shift from genetics to genomics brings to new challenges in data analysis. For example, when tests are ...
19