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zhanghao-njmu avatar zhanghao-njmu commented on June 8, 2024

I'm not sure if the problem is caused by "CPU time limit". If it is, you can try specifying BPPARAM = BiocParallel::MulticoreParam(workers = 10) to adjust the number of workers. Hope this helps!

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bio-visualisation avatar bio-visualisation commented on June 8, 2024

The same error pops up.
failed with the error: reached CPU time limit

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zhanghao-njmu avatar zhanghao-njmu commented on June 8, 2024

There is no problem when calculating the dynamic features of Lineage3, but the issue arises during the 91% stage of calculating the dynamic features of Lineage7. If it's not due to too many threads, it could be because the original counts contain some Inf or missing values or other reasons. My suggestion is that you can try to calculate the dynamic features of Lineage3 and Lineage7 separately to see if only Lineage7 has this issue. In addition, you can specify n_candidates=100 or feature names. For example, if calculating 100 candidate features or manually specified features works fine, then it is likely an issue with the counts of certain features.

Most importantly, if BiocParallel encounters "unevaluated" errors, you must use .rs.restartR() or manually restart the Rsession; otherwise, the error will persist regardless of whether there is a problem with the code.

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bio-visualisation avatar bio-visualisation commented on June 8, 2024

I did not find any problem when I ran n_candidates=50. How do I get rid of those missing values?

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zhanghao-njmu avatar zhanghao-njmu commented on June 8, 2024

You can use the following code to count and find infinite or missing values in the counts/data slot:

Matrix::rowSums(is.infinite(srt@assays$RNA@counts))
Matrix::rowSums(is.na(srt@assays$RNA@counts))

If infinite/missing values are found, you can temporarily remove these features using the subset() function and create a new Seurat object for calculation purposes.

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bio-visualisation avatar bio-visualisation commented on June 8, 2024

Thanks.

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