49:I[23239,["/_next/static/chunks/aa1a2743392bfcbb.js","/_next/static/chunks/4447f3339d08ae84.js","/_next/static/chunks/f8fa3df985368694.js","/_next/static/chunks/ee345200f5d8149d.js","/_next/static/chunks/c7812d1a97f89367.js","/_next/static/chunks/961a013e79359552.js","/_next/static/chunks/8ebb9ba197847521.js","/_next/static/chunks/a6dcd9d6660135b1.js","/_next/static/chunks/9158ee4689f965d9.js","/_next/static/chunks/edbe86711d0424a5.js"],"RepoExportButton"] 43:["$","div",null,{"children":["Updated on ","Feb 23, 2026"]}] 4a:T4d7,Hi, If I use RUV_III_PRPS helper function with my data. I got error. ``` > ruviii.norm <- RUV_III_PRPS(Y = t(log2(ruv.data.input + 1)), + M = ruv.rep.matrix, + ctl = negative.control.gene, + k = 20, + eta = NULL, + return.info = TRUE) Error in RUV_III_PRPS(Y = t(log2(ruv.data.input + 1)), M = ruv.rep.matrix, : object 'W' not found ``` I walk through the code of the helper functions and found that the following code cause the error. ``` if (ncol(M) >= m) newY <- Y else if (is.null(k)) { ycyctinv <- solve(Y[, ctl] %*% t(Y[, ctl])) newY <- (M %*% solve(t(M) %*% ycyctinv %*% M) %*% (t(M) %*% ycyctinv)) %*% Y fullalpha <- NULL } else if (k == 0) { newY <- Y fullalpha <- NULL } else { if (is.null(fullalpha) ) { Y0 <- ruv::residop(Y, M) fullalpha <- t(svd(Y0 %*% t(Y0))$u[, 1:min(m - ncol(M), sum(ctl)), drop = FALSE]) %*% Y } alpha <- fullalpha[1:min(k, nrow(fullalpha)), , drop = FALSE] ac <- alpha[, ctl, drop = FALSE] W <- Y_stand[, ctl] %*% t(ac) %*% solve(ac %*% t(ac)) newY <- Y - W %*% alpha } ``` Is this a bug?4b:T43a,Hi @RMolania, thank you for developing this elaborate approach to batch correction. I am currently testing RUV-III on a merged dataset comprising TCGA-KIRC bulk RNA-seq and another study. However, after running the `RUV_III_PRPS `function, I find that the 'batch corrected' dataset is actually the exact same as the raw counts dataset. I am running this function as follows: ``` ruviii.norm <- RUV_III_PRPS( Y = t(log2(ruv.data.input + 1)), M = ruv.rep.matrix, ctl = negative.control.genes, k = 0, average = TRUE, return.info = FALSE) ruviii.prps.norm <- t(ruviii.norm[1:ncol(dds),]) ``` Prior to this, ~950 negative control genes are selected across my biological condition of interest, and I cannot see any issues in the pseudo-replicates part. I also found that the `RUV_III_PRPS `function returned errors when `return.info = TRUE`. I checked the function code and am not sure that it is capturing every possible eventuality that an end-user may try, which results in errors. Any thoughts? Kind regards, Kevin4c:T8e6,

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