invvar: Inverse Method Variances

In ruv: Detect and Remove Unwanted Variation using Negative Controls

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.

Author(s)

Johann Gagnon-Bartsch [e-mail]

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

ruv documentation built on Aug. 31, 2019, 1:04 a.m.