Open TeodoraTockovska opened 2 years ago
I discovered the error -- it was due to using sctransform's vst() function. It resulted in NA values. I am closing the issue.
I've reopened the issue. I am trying to understand the BiocParallel errors. Scone is able to run for all of my user-defined functions except for sctransform's vst() normalization function.
My user-defined function is below:
SCT_VST_FN <- function(expression_data){
return(sctransform::vst(expression_data)$y)
}
Below are the messages while running scone():
Negative controls will not be used in evaluation (correlations with negative controls will be returned as NA)
Imputation step...
Scaling step...
Calculating cell attributes from input UMI matrix: log_umi
Variance stabilizing transformation of count matrix of size 706 by 15
Model formula is y ~ log_umi
Get Negative Binomial regression parameters per gene
Using 706 genes, 15 cells
|===========================================================================================================================================| 100%
Found 84 outliers - those will be ignored in fitting/regularization step
Second step: Get residuals using fitted parameters for 706 genes
|===========================================================================================================================================| 100%
Calculating gene attributes
Wall clock passed: Time difference of 0.8297551 secs
Computing RUV factors...
Computing factors for evaluation...
Factor adjustment and evaluation...
...including re-zero step...
Processed: none,none,no_uv,no_bio,no_batch
Error: BiocParallel errors
element index: 2, 3, 4, 5, 6
first error: NA/Inf/NaN Expression Values.
It seems that scone() breaks after line 570.
Fortunately, the normalization using SCT_VST_FN() returns the normalized matrix, however I don't understand how to fix this issue.
Hi! I am trying to run scone() on a very small expression dataset (~2000 genes and 15 cells) to test out my user-defined functions and see the results. I ran into the following error, which I don't know how to resolve:
The expression data were pre-preprocessed and I removed genes that were not expressed in the cells. My scaling list includes user-defined functions for a few normalization methods (Seurat's simple norm, sctransform's vst(), SCnorm, and scran). The user-defined functions (besides scran) all return the normalized matrices, not scaled. My user-defined functions return normalized matrices when I call them on their own.
This is how I am calling the scone() function:
How could I resolve this error? Thank you!