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pi0 (version 1.4-1)

Estimating the Proportion of True Null Hypotheses for FDR

Description

Methods for estimating the proportion of true null hypotheses, i.e., the pi0, when a very large number of hypotheses are simultaneously tested, especially for the purpose of (local) false discovery rate control for microarray data. It also contains functions to estimate the distribution of noncentrality parameters from a large number of parametric tests.

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Install

install.packages('pi0')

Monthly Downloads

84

Version

1.4-1

License

GPL (>= 2)

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Repository

https://github.com/gitlongor/pi0

Maintainer

Last Published

July 9th, 2017

Functions in pi0 (1.4-1)

clean.cdf, save.cdf and load.cdf

Saving, loading or removing pre-computed conditional cdf objects from memory or disk

Extract estimated parameters

Density of noncentrality parameters

INTerpolation of INTeger degrees of freedom noncentral t-density

Estimate Proportion of True Null Hypotheses

Fit a discrete mixture of (noncentral) t-distributions

Randomly Choosing R Combinations of Two Groups of n and n2 Elements Taken m and m2 at a Time

conditional cdf of p-values given noncentrality parameters

(Censored) Beta-Uniform mixture for p-values

Averaged generalized jackknife estimate of pi0

Performs a grid search to minimize the objective function

Histogram estimator of p-value density evaluated at 1

Laplace approximation to the noncentral t-density

Density of noncental t-normal mixture

Histogram estimator of p-value density evaluated at 1

fitted.discTMix

Density evaluated at observed statistics for discTMix class

Density evaluated at observed statistics for ncpest class

Nonparametric estimation of noncentrality parameters

Parametric estimation of noncentrality parameter distribution

Local False Discovery Rates (lfdr), i.e., Posterior Probability of Equivalent Expression (ppee) for gene expression profiling data.

Plotting the Estimated Regression Surface

plot an object of class nparncpt, i.e., nonparametric estiamte of noncentrality parameters

A Simulated Microarray Data Set

Extrapolate the Estimates of P-value Density at 1 from Subsamples to Estimate the Proportion of True Nulls

False Discovery Rate (FDR) Estimation Based on a Given Estimate of Pi0

Estimation of the density of absolute noncentrality parameters

iterative call to the nparncpp function

internal functions not to be used by users directly

internal functions not to be used by users directly

Estimating the proportion of true null hypotheses and False Discovery Rates

Print the Summary of the Subsampling T-tests

dt.sad and pt.sad

Saddle Point Approximation of noncentral t-distribution

Apply a Two Sample T-test to Each Row or Column of a Matrix

Estimated arginal density of t-statistics

pooling adjacent violator algorithm estimate of p-value density at 1

Distance between densities

reflect and fold

Reflection and folding of a function about zero

Simulating a Microarray Data Set

summary.sparncpt

Print summary for an object of class sparncp

Variance of the reflected Bsplines

geomean and harmean

Geometric mean and harmonic mean functions

Generalized jackknife

log likelihood from an object of class ncpest

Plotting the P-value, Q-values, and the Regression Surface

3D Scatter Plot of Subsample Sizes and P-value Density at One.

Print the Summary of the Extrapolation

Printing a Summary of Subsampling-Extrapolation Results

simulatedExtrpi0

A Simulated 'extrpi0' Object

summary.nparncpt

Print summary for an object of class nparncp

summary.parncpt

Print summary for an object of class parncp

Subsampling-Extrapolation Based Estimation of Proportion of True Null Hypotheses and False Discovery Rates for Microarray Data

Subsampling a Microarray Data Set for Estimating Proportion of True Null Hypotheses

Moments of truncated normal distribution and the integral in the noncentral t-distribution

plot an object of class parncpt, i.e., parametric estiamte of noncentrality parameters

plot an object of class sparncpt, i.e., semiparametric estimate of noncentrality parameters

A Simulated 'subt' Object

extract inverse Hessian matrix from ncpest class

Normal-mixture based estimation of LFDR and pi0

t-Statistics and p-Values from a Simulated Microarray Data Set

Semiparametric density estimation for noncentrality parameters

A Simulated 'subex' Object