ebayes {limma} | R Documentation

## Empirical Bayes Statistics for Differential Expression (Deprecated)

### Description

Given a microarray linear model fit, compute moderated t-statistics, moderated F-statistic, and log-odds of differential expression by empirical Bayes moderation of the standard errors towards a common value. This function is now deprecated. Please use `eBayes` instead.

### Usage

    ebayes(fit, proportion=0.01, stdev.coef.lim=c(0.1,4),
           trend=FALSE, robust=FALSE, winsor.tail.p=c(0.05,0.1))

### Arguments

`fit` | an `MArrayLM` fitted model object produced by `lmFit` or `contrasts.fit`. For `ebayes` only, `fit` can alternatively be an unclassed list produced by `lm.series`, `gls.series` or `mrlm` containing components `coefficients`, `stdev.unscaled`, `sigma` and `df.residual`.
`proportion` | numeric value between 0 and 1, assumed proportion of genes which are differentially expressed
`stdev.coef.lim` | numeric vector of length 2, assumed lower and upper limits for the standard deviation of log2-fold-changes for differentially expressed genes
`trend` | logical, should an intensity-trend be allowed for the prior variance? Default is that the prior variance is constant.
`robust` | logical, should the estimation of `df.prior` and `var.prior` be robustified against outlier sample variances?
`winsor.tail.p` | numeric vector of length 1 or 2, giving left and right tail proportions of `x` to Winsorize. Used only when `robust=TRUE`.

### Details

This function is now deprecated. Please use `eBayes` instead.

### Value

A list with components:

`t` | numeric vector or matrix of moderated t-statistics
`p.value` | numeric vector of p-values corresponding to the t-statistics
`s2.prior` | estimated prior value for `sigma^2`. A vector if `covariate` is non-`NULL`, otherwise a scalar.
`df.prior` | degrees of freedom associated with `s2.prior`
`df.total` | numeric vector of total degrees of freedom associated with t-statistics and p-values. Equal to `df.prior+df.residual` or `sum(df.residual)`, whichever is smaller.
`s2.post` | numeric vector giving the posterior values for `sigma^2`
`lods` | numeric vector or matrix giving the log-odds of differential expression (natural log scale).
`var.prior` | estimated prior value for the variance of the log2-fold-change for differentially expressed gene

### Author(s)

Gordon Smyth

### References

Phipson, B, Lee, S, Majewski, IJ, Alexander, WS, and Smyth, GK (2016). Robust hyperparameter estimation protects against hypervariable genes and improves power to detect differential expression. Annals of Applied Statistics 10, 946-963. http://projecteuclid.org/euclid.aoas/1469199900

Smyth, G. K. (2004). Linear models and empirical Bayes methods for assessing differential expression in microarray experiments. Statistical Applications in Genetics and Molecular Biology 3, Article 3. http://www.statsci.org/smyth/pubs/ebayes.pdf

### See Also

`eBayes`

[Package limma version 3.36.5 Index]