ssize.twoSampVaryDelta: Sample Size Calculations for Two-Sample Microarray...
In biran1990/ssizeRNA: Sample Size Calculation for RNA-Seq Experimental Design

Description Usage Arguments Details Value Author(s) References See Also Examples

For given desired power, controlled false discovery rate, and user-specified proportions of non-differentially expressed genes, ssize.twoSampVaryDelta calculates appropriate sample sizes for two-sample microarray experiments in which the differences between mean treatment expression levels (delta.g for gene g) vary among genes. A plot of power versus sample size is generated.

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ssize.twoSampVaryDelta(deltaMean, deltaSE, sigma, fdr = 0.05, power = 0.8,
  pi0 = 0.95, maxN = 35, side = "two-sided", cex.title = 1.15,
  cex.legend = 1)

`deltaMean`	location (mean) parameter of normal distribution followed by each delta.g.
`deltaSE`	scale (standard deviation) parameter of normal distribution followed by each delta.g.
`sigma`	the common standard deviation of expressions for all genes.
`fdr`	the false discovery rate to be controlled.
`power`	the desired power to be achieved.
`pi0`	a vector (or scalar) of proportions of non-differentially expressed genes.
`maxN`	the maximum sample size used for power calculations.
`side`	options are "two-sided", "upper", or "lower".
`cex.title`	controls size of chart titles.
`cex.legend`	controls size of chart legend.

Each delta.g is assumed to follow a Normal distribution with mean deltaMean and standard deviation deltaSE. The standard deviations of expressions are assumed identical for all genes.

If a vector is input for pi0, sample size calculations are performed for each proportion.

`ssize`	sample sizes (for each treatment) at which desired power is first reached.
`power`	power calculations with corresponding sample sizes.
`crit.vals`	critical value calculations with corresponding sample sizes.

Ran Bi biran@iastate.edu, Peng Liu pliu@iastate.edu

Liu, P. and Hwang, J. T. G. (2007) Quick calculation for sample size while controlling false discovery rate with application to microarray analysis. Bioinformatics 23(6): 739-746.

Orr, M. and Liu, P. (2009) Sample size estimation while controlling false discovery rate for microarray experiments using ssize.fdr package. The R Journal, 1, 1, May 2009, 47-53.

ssize.twoSamp, ssize.twoSampVary, ssize.oneSamp, ssize.oneSampVary, ssize.F, ssize.Fvary

dm <- 1.2; ds <- 0.1  ## the delta.g's follow a Normal(1.2, 0.1) distribution
s <- 1                ## common standard deviation
fdr <- 0.05           ## false discovery rate to be controlled
pwr <- 0.8            ## desired power
pi0 <- c(0.5, 0.8, 0.99) ## proportions of non-differentially expressed genes
N <- 35               ## maximum sample size for calculations

size <- ssize.twoSampVaryDelta(deltaMean = dm, deltaSE = ds, sigma = s, 
                               fdr = fdr, power = pwr, pi0 = pi0, 
                               maxN = N, side = "two-sided")
size$ssize                ## first sample size(s) to reach desired power
size$power                ## calculated power for each sample size
size$crit.vals            ## calculated critical value for each sample size