SSPA (version 2.12.0)

sampleSize: User friendly interface to class 'SampleSize'

Description

User friendly interface to class "SampleSize"

Usage

sampleSize(PilotData, method = c("deconv", "congrad", "tikhonov", "ferreira"), control = list(from = -6, to = 6, resolution = 2^9))

Arguments

PilotData

object of class 'PilotData'.

method

estimation method one of 'deconv', 'congrad', 'tikhonov' or 'ferreira'. See 'Details'.

control

A list of control parameters. See 'Details'.

Value

object of class SampleSize.

Details

The default method is 'deconv' which is an kernel deconvolution density estimator implementated using fft. The 'nncg' is a nonnegative conjugate gradient algorithm based on R's implementation see optim. 'tikonov' implements ridge-regression with optimal penalty selection using the L-curve approach. Higher order penalties are possible as well using a transformation to standard form (see Hansen).

The 'control' argument is a list that can supply any of the following components. Per method logical checks are performed.

• deconv:
  • method:'deconv', 'ferreira'
  • pi0Method:the pi0 estimation method one of 'Langaas', 'Storey', 'Ferreira', 'Userdefined'
  • pi0:if method = 'ferreira' grid pi0-value need to be suppled e.g. seq(0.1, 0.99, 0.01)
  • adjust:Default TRUE, adjust pi0 esitmate if density of effect size is somewhere negative.
  • a:Adjust pi0 better approach suggested by Efron. Symmetric range around zero of size 0.5.
  • bandwith:Default NULL uses 1/sqrt(log(length(statistics)))
  • kernel:Either 'fan', 'wand', 'sinc' kernels can be used.
  • from:Density of effect sizes should be estimated from = -6
  • to: to = 6
  • resolution:Density of effect sizes should be estimated on 2^9 points.
  • verbose:Default FALSE if TRUE additional information is printed to the console.

congrad:

• integration:'midpoint', 'trapezoidal', 'simpson'
• scale:'pdfstat', 'cdfstat', 'cdfpval'
• trim:0.01, 0.99
• symmetric:TRUE
• bin:'epdf', 'ecdf'
• from:-6
• to:6
• resolution:500
• verbose:Default FALSE if TRUE additional information is printed to the console.

tikhonov:

• integration:'midpoint', 'trapezoidal', 'simpson'
• scale:'pdfstat', 'cdfstat', 'cdfpval'
• trim:0.01, 0.99
• symmetric:TRUE
• bin:'epdf', 'ecdf'
• from:-6
• to:6
• resolution:500
• method:'lcurve', 'gcv', 'aic'
• log:TRUE
• penalty:0
• lambda:10^seq(-10, 10, length=100)
• verbose:Default FALSE if TRUE additional information is printed to the console.

'ferreira:'not yet implemeneted

References

van Iterson, M., P. 't Hoen, P. Pedotti, G. Hooiveld, J. den Dunnen, G. van Ommen, J. Boer, and R. de Menezes (2009): 'Relative power and sample size analysis on gene expression profiling data,' BMC Genomics, 10, 439--449.

Ferreira, J. and A. Zwinderman (2006a): 'Approximate Power and Sample Size Calculations with the Benjamini-Hochberg Method,' The International Journal of Biostatistics, 2, 1.

Ferreira, J. and A. Zwinderman (2006b): 'Approximate Sample Size Calculations with Microarray Data: An Illustration,' Statistical Applications in Genetics and Molecular Biology, 5, 1.

Hansen, P. (2010): Discrete Inverse Problems: Insight and Algorithms, SIAM: Fun- damentals of algorithms series.

Langaas, M., B. Lindqvist, and E. Ferkingstad (2005): 'Estimating the proportion of true null hypotheses, with application to DNA microarray data,' Journal of the Royal Statistical Society Series B, 67, 555--572.

Storey, J. (2003): 'The positive false discovery rate: A bayesian interpretation and the q-value,' Annals of Statistics, 31, 2013--2035.

See Also

optim

Examples

m <- 5000 ##number of genes
J <- 10 ##sample size per group
pi0 <- 0.8 ##proportion of non-differentially expressed genes
m0 <- as.integer(m*pi0)
mu <- rbitri(m - m0, a = log2(1.2), b = log2(4), m = log2(2)) #effect size distribution
data <- simdat(mu, m=m, pi0=pi0, J=J, noise=NULL)
library(genefilter)
stat <- rowttests(data, factor(rep(c(0, 1), each=J)), tstatOnly=TRUE)$statistic
pd <- pilotData(statistics=stat, samplesize=sqrt(J/2), distribution='norm')
ss <- sampleSize(pd, method='deconv')
plot(ss)