ratiogaddon {bapred}R Documentation

Addon batch effect adjustment for Ratio-G


Performs addon batch effect adjustment for Ratio-G: 1) takes the output of ratiog applied to a training data set together with new batch data; 2) checks whether the training data was also adjusted using Ratio-G and whether the same number of variables is present in training and new data; 3) performs Ratio-G on the new batch data.


ratiogaddon(params, x, batch)



object of class ratiog.


matrix. The covariate matrix of the new data. Observations in rows, variables in columns.


factor. Batch variable of the new data. Currently has to have levels: '1', '2', '3' and so on.


The adjusted covariate matrix of the test data.


Because Ratio-G is performed "batch by batch" the "addon procedure" for Ratio-G consists of plain Ratio-G on the new test batches.


Roman Hornung


Luo, J., Schumacher, M., Scherer, A., Sanoudou, D., Megherbi, D., Davison, T., Shi, T., Tong, W., Shi, L., Hong, H., Zhao, C., Elloumi, F., Shi, W., Thomas, R., Lin, S., Tillinghast, G., Liu, G., Zhou, Y., Herman, D., Li, Y., Deng, Y., Fang, H., Bushel, P., Woods, M., Zhang, J. (2010) A comparison of batch effect removal methods for enhancement of prediction performance using maqc-ii microarray gene expression data. The Pharmacogenomics Journal, 10, 278-291.

Hornung, R., Boulesteix, A.-L., Causeur, D. (2016) Combining location-and-scale batch effect adjustment with data cleaning by latent factor adjustment. BMC Bioinformatics 17:27.



trainind <- which(batch %in% c(1,2))

Xtrain <- X[trainind,]
ytrain <- y[trainind]
batchtrain <- factor(as.numeric(batch[trainind]), levels=c(1,2))

testind <- which(batch %in% c(3,4))

Xtest <- X[testind,]
ytest <- y[testind]

batchtest <- as.numeric(batch[testind])
batchtest[batchtest==3] <- 1
batchtest[batchtest==4] <- 2
batchtest <- factor(batchtest, levels=c(1,2))

params <- ratiog(x=Xtrain, batch=batchtrain)

Xtestaddon <- ratiogaddon(params=params, x=Xtest, batch=batchtest)

[Package bapred version 1.0 Index]