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Can't make sva comparison despite very distinct batch effects

I continuously receive this error when I try to run sva with my count data

R code for sva:

# Loading all variables 
library(sva)
dat  <- dds_matrix
idx  <- rowMeans(dat) > 1
dat  <- dat[idx,]
mod  <- model.matrix(~batch, colData(dds))
mod0 <- model.matrix(~1, colData(dds))
svseq <- svaseq(dat, mod, mod0)

I receive this error message.

Error in solve.default(t(mod) %*% mod) : Lapack routine dgesv: system is exactly singular: U[4,4] = 0

I have very distinct batches which can be seen in this plot.

PCA plot of my data set, the colors indicate my batches

I have clearly dictated the batches as factors and this exact process has worked before. This is with a new, but very similar data set.

If it is simply not possible to remove these batch effects, how would I go about bringing these two batches closer together, they are definitely the same condition and the variance is likely due to batch effects, not biological significance.

sva batch-effect

what is your contrast of interest? if you model sva on your known batch, it will look for covariates that are independet of it.

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