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.

numeric value between 0 and 1, assumed proportion of genes which are differentially expressed

numeric vector of length 2, assumed lower and upper limits for the standard deviation of log2-fold-changes for differentially expressed genes

logical, should an intensity-trend be allowed for the prior variance? Default is that the prior variance is constant.

logical, should the estimation of df.prior and var.prior be robustified against outlier sample variances?

numeric vector of length 1 or 2, giving left and right tail proportions of x to Winsorize. Used only when robust=TRUE.

numeric vector or matrix of moderated t-statistics

numeric vector of p-values corresponding to the t-statistics

estimated prior value for sigma^2. A vector if covariate is non-NULL, otherwise a scalar.

degrees of freedom associated with s2.prior

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.

numeric vector giving the posterior values for sigma^2

numeric vector or matrix giving the log-odds of differential expression (natural log scale).

estimated prior value for the variance of the log2-fold-change for differentially expressed gene