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siggenes (version 1.46.0)

ebamControl: Further EBAM Arguments

Description

Specifies most of the optional arguments of ebam and find.a0.

Usage

ebamControl(p0 = NA, p0.estimation = c("splines", "interval", "adhoc"), lambda = NULL, ncs.value = "max", use.weights = FALSE) find.a0Control(p0.estimation = c("splines", "adhoc", "interval"), lambda = NULL, ncs.value = "max", use.weights = FALSE, n.chunk = 5, n.interval = 139, df.ratio = NULL)

Arguments

p0
a numeric value specifying the prior probability $p0$ that a gene is not differentially expressed. If NA, p0 will be estimated automatically.
p0.estimation
either "splines" (default), "interval", or "adhoc". If "splines", the spline based method of Storey and Tibshirani (2003) is used to estimate $p0$. If "adhoc" ("interval"), the adhoc (interval based) method proposed by Efron et al.\ (2001) is used to estimate $p0$.
lambda
a numeric vector or value specifying the $lambda$ values used in the estimation of $p0$. If NULL, lambda is set to seq(0, 0.95, 0.05) if p0.estimation = "splines", and to 0.5 if p0.estimation = "interval". Ignored if p0.estimation = "adhoc". For details, see pi0.est.
ncs.value
a character string. Only used if p0.estimation = "splines" and lambda is a vector. Either "max" or "paper". For details, see pi0.est.
use.weights
should weights be used in the spline based estimation of $p0$? If TRUE, 1 - lambda is used as weights. For details, see pi0.est.
n.chunk
an integer specifying in how many subsets the B permutations should be split when computing the permuted test scores.
n.interval
the number of intervals used in the logistic regression with repeated observations for estimating the ratio $f0/f$.
df.ratio
integer specifying the degrees of freedom of the natural cubic spline used in the logistic regression with repeated observations.

Value

A list containing the values of the parameters that are used in ebam or find.a0, respectively.

Details

These parameters should only be changed if they are fully understood.

References

Efron, B., Tibshirani, R., Storey, J.D. and Tusher, V. (2001). Empirical Bayes Analysis of a Microarray Experiment. JASA, 96, 1151-1160. Storey, J.D. and Tibshirani, R. (2003). Statistical Significance for Genome-Wide Studies. Proceedings of the National Academy of Sciences, 100, 9440-9445.

See Also

limma2ebam, ebam, find.a0