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Issue: ReX can only handle datasets in which there is identical number of replicates across timepoints (perhaps across states also?).
This may be quite a common issue as there can be missed timepoints in certain datasets; different number of non-deuterated experiments; different number of replicates between states, which cannot be handled here.
Might be something to do with matrix being defined by number of timepoints and number of replicates, rather than by distinct experiments? It seems to be an error in error_prediction function, but can imagine there may also be other implications across different functions too as we also defined number of timepoints elsewhere.
Warning: 'package:stats' may not be available when loadingWarning: 'package:stats' may not be available when loadingFold 1 ... Fold 2 ... Fold 3 ... Fold 4 ... Fold 5 ...
Warning in res$Uptake[res$Sequence == unique(res$Sequence)[j]] - rep(mu, :
longer object length is not a multiple of shorter object length
Fold 1 ... Fold 2 ... Fold 3 ... Fold 4 ... Fold 5 ...
Warning in res$Uptake[res$Sequence == unique(res$Sequence)[j]] - rep(mu, :
longer object length is not a multiple of shorter object length
Error: BiocParallel errors
2 remote errors, element index: 1, 2
0 unevaluated and other errors
first remote error:
Error in .sd[j, ] <- rep(tCoef * numExch[[j]] * sqrt(sigmasq), each = numRep): number of items to replace is not a multiple of replacement length
The text was updated successfully, but these errors were encountered:
nlgittens
changed the title
[BUG] A short description of the bug
[BUG] Differing number of replicates in datasets
Apr 29, 2024
ococrook
changed the title
[BUG] Differing number of replicates in datasets
[Feature Request] Differing number of replicates in datasets
Apr 29, 2024
Thanks Nathan, I had this one on my list. It's more of an enchancement than a bug. There are two ways to deal with this:
Impute them
model them
Modelling them is quite computationally intensive but if there's lots of imputation then that can cause bias. I suggest I write a simpel imputation script that has a warning if there are lots of missing values?
Issue: ReX can only handle datasets in which there is identical number of replicates across timepoints (perhaps across states also?).
This may be quite a common issue as there can be missed timepoints in certain datasets; different number of non-deuterated experiments; different number of replicates between states, which cannot be handled here.
Might be something to do with matrix being defined by number of timepoints and number of replicates, rather than by distinct experiments? It seems to be an error in error_prediction function, but can imagine there may also be other implications across different functions too as we also defined number of timepoints elsewhere.
Reproducible example:
Warning: 'package:stats' may not be available when loadingWarning: 'package:stats' may not be available when loadingFold 1 ... Fold 2 ... Fold 3 ... Fold 4 ... Fold 5 ...
Warning in res$Uptake[res$Sequence == unique(res$Sequence)[j]] - rep(mu, :
longer object length is not a multiple of shorter object length
Fold 1 ... Fold 2 ... Fold 3 ... Fold 4 ... Fold 5 ...
Warning in res$Uptake[res$Sequence == unique(res$Sequence)[j]] - rep(mu, :
longer object length is not a multiple of shorter object length
Error: BiocParallel errors
2 remote errors, element index: 1, 2
0 unevaluated and other errors
first remote error:
Error in .sd[j, ] <- rep(tCoef * numExch[[j]] * sqrt(sigmasq), each = numRep): number of items to replace is not a multiple of replacement length
The text was updated successfully, but these errors were encountered: