fsva: A function for performing frozen surrogate variable analysis...

Description Usage Arguments Value

View source: R/fsva.R


This function performs frozen surrogate variable analysis as described in Parker, Corrada Bravo and Leek 2013. The approach uses a training database to create surrogate variables which are then used to remove batch effects both from the training database and a new data set for prediction purposes. For inferential analysis see sva, svaseq, with low level functionality available through irwsva.build and ssva.


fsva(dbdat, mod, sv, newdat = NULL, method = c("fast", "exact"))



A m genes by n arrays matrix of expression data from the database/training data


The model matrix for the terms included in the analysis for the training data


The surrogate variable object created by running sva on dbdat using mod.


(optional) A set of test samples to be adjusted using the training database


If method ="fast" then the SVD is calculated using an online approach, this may introduce slight bias. If method="exact" the exact SVD is calculated, but will be slower


db An adjusted version of the training database where the effect of batch/expression heterogeneity has been removed

new An adjusted version of the new samples, adjusted one at a time using the fsva methodology.

newsv Surrogate variables for the new samples

sva documentation built on May 20, 2017, 9:56 p.m.

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