Adjusting removeBatchEffect from limma
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@djie-tjwan-thung-5053
Last seen 9.6 years ago
Dear Gordon Smyth, bioconductor list, In the limma package we found a function called, removeBatchEffect, which removes the effects of batch effects or other technical variables on a gene expression matrix. The code of this removeBatchEffect is as follows: function (x, batch, batch2 = NULL, design = matrix(1, ncol(x), 1)) { x <- as.matrix(x) batch <- as.factor(batch) contrasts(batch) <- contr.sum(levels(batch)) if (is.null(batch2)) { X <- model.matrix(~batch)[, -1, drop = FALSE] } else { batch2 <- as.factor(batch2) contrasts(batch2) <- contr.sum(levels(batch2)) X <- model.matrix(~batch + batch2)[, -1, drop = FALSE] } X <- qr.resid(qr(design), X) t(qr.resid(qr(X), t(x))) } Now we have an ‘expression’ matrix coming from a methylation array. As bisulfite conversion efficiency (BSCE) is a known confounder for this type of array, we’d like to adjust the matrix for the confounding effects of BSCE. BSCE is a numerical variable, however the removeBatchEffect expects a categorical variable as it handles the batch variable as a factor. We were wondering if its valid to remove the following lines of code in this function regarding, batch and batch2, so the function treats these variables as numerical variables: batch <- as.factor(batch) contrasts(batch) <- contr.sum(levels(batch)) If someone is willing, you can test out this altered version by loading the .RData in the following link: http://good.net/dl/au/fa43/contTechnicalVar.RData and using the following demo script: ### #removeNumericBatchEffect(): altered version of removeBatchEffect(), with the as.factor() and contrasts() lines commented out #mod: model matrix containing variables of interest (intercept, age and gender) # head(mod) will give: # (Intercept) as.factor(pheno$gender)v pheno$age #1 1 1 55.9 #2 1 1 32.0 #create random intensity values for bisulfite conversion bisulfite.conversion <- sample(6000:10000, 95) #Run adjusted removeBatchEffect function removeNumericBatchEffect(expr, batch = bisulfite.conversion, design = mod) We’d appreciate any input. We’ve also considered ComBat from the sva package as an alternative, but as this function also only accepts categorical variables, this limma function seems like a better option to modify its code for our purpose. Regards, Djie Thung Bioinformatics intern at UMC Utrecht Dept. of Medical Genetics [[alternative HTML version deleted]]
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@gordon-smyth
Last seen 1 hour ago
WEHI, Melbourne, Australia

Dear Djie,

I have generalized the removeBatchEffect() function so that it will now accept continuous covariates as well as batch factors. Just enter BSCE as the 'covariates' argument.

Gordon

Note: this question was originally answered here: Adjusting removeBatchEffect from limma

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