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tmixture

Estimate Scale Factor in Mixture of t-Distributions


Description

These functions estimate the unscaled standard deviation of the true (unobserved) log fold changes for differentially expressed genes. They are used by the functions ebayes and eBayes and are not intended to be called directly by users.

Usage

tmixture.vector(tstat, stdev.unscaled, df, proportion, v0.lim = NULL)
tmixture.matrix(tstat, stdev.unscaled, df, proportion, v0.lim = NULL)

Arguments

tstat

numeric vector or matrix of t-statistics. tmixture.vector assumes a vector while tmixture.matrix assumes a matrix.

stdev.unscaled

numeric vector or matrix, conformal with tstat, containing the unscaled standard deviations of the coefficients used to compute the t-statistics.

df

numeric vector giving the degrees of freedom associated with tstat.

proportion

assumed proportion of genes that are differentially expressed.

v0.lim

numeric vector of length 2 giving the lower and upper limits for the estimated unscaled standard deviations.

Details

The values in each column of tstat are assumed to follow a mixture of an ordinary t-distribution, with mixing proportion 1-proportion, and (v0+v1)/v1 times a t-distribution, with mixing proportion proportion. Here v1 is stdev.unscaled^2 and v0 is the value to be estimated.

Value

Numeric vector, of length equal to the number of columns of tstat, containing estimated v0 values.

Author(s)

Gordon Smyth

See Also


limma

Linear Models for Microarray Data

v3.46.0
GPL (>=2)
Authors
Gordon Smyth [cre,aut], Yifang Hu [ctb], Matthew Ritchie [ctb], Jeremy Silver [ctb], James Wettenhall [ctb], Davis McCarthy [ctb], Di Wu [ctb], Wei Shi [ctb], Belinda Phipson [ctb], Aaron Lun [ctb], Natalie Thorne [ctb], Alicia Oshlack [ctb], Carolyn de Graaf [ctb], Yunshun Chen [ctb], Mette Langaas [ctb], Egil Ferkingstad [ctb], Marcus Davy [ctb], Francois Pepin [ctb], Dongseok Choi [ctb]
Initial release
2020-10-19

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