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ruv (version 0.9.7.1)

invvar: Inverse Method Variances

Description

Estimate the features' variances using the inverse method. This function is usually called from RUVinv and not normally intended for stand-alone use.

Usage

invvar(Y, ctl, XZ = NULL, eta = NULL, lambda = NULL,
       invsvd = NULL)

Arguments

Y

The data. A m by n matrix, where m is the number of samples and n is the number of features.

ctl

The negative controls. A logical vector of length n.

XZ

A m by (p + q) matrix containing both the factor(s) of interest (X) and known covariates (Z).

eta

Gene-wise (as opposed to sample-wise) covariates. These covariates are adjusted for by RUV-1 before any further analysis proceeds. A matrix with n columns.

lambda

Ridge parameter. If specified, the ridged inverse method will be used.

invsvd

Can be included to speed up execution. Generally used when calling invvar many times with different values of lambda.

Value

A list containing

sigma2

Estimates of the features' variances. A vector of length n.

df

The "effective degrees of freedom"

invsvd

Can be used to speed up future calls of invvar.

References

Removing Unwanted Variation from High Dimensional Data with Negative Controls. Gagnon-Bartsch, Jacob, and Speed, 2013. Available at: http://statistics.berkeley.edu/tech-reports/820.

See Also

RUVinv, RUVrinv