wu-yc / scMetabolism

Quantifying metabolism activity at the single-cell resolution
BSD 3-Clause "New" or "Revised" License
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Error in "Computing differential signature tests..." step #21

Open JunyanKan opened 1 year ago

JunyanKan commented 1 year ago

While running sc.metabolism.Seurat function, I encountered an error in "Computing differential signature tests..." step. It mentioned that Error in [<-.data.frame(*tmp*, , 2, value = 0) : 替换数据里有1行,但数据有0.

The input data was a standard Seurat object and parameters were set by default.

The specific running processes were listed below:

Your choice is: KEGG
Start quantify the metabolism activity...
Loading data from C:/Tools/R/R_Library/scMetabolism/data/KEGG_metabolism_nc.gmt ...

Using 10087/10105 genes detected in 0.10% of cells for signature analysis.
See the `sig_gene_threshold` input to change this behavior.

Beginning Analysis

Computing a latent space for expression data...

Determining projection genes...
    Applying Threshold filter...removing genes detected in less than 2043 cells
      Genes Retained: 5178
    Applying Fano filter...removing genes with Fano < 2.0 MAD in each of 30 bins
      Genes Retained: 811

Clustering cells...completed

Projecting data into 2 dimensions...
  Running method 1/1: tSNE30 ...

Evaluating signature scores on cells...

as(<matrix>, "dgeMatrix") is deprecated since Matrix 1.5-0; do as(as(as(., "dMatrix"), "generalMatrix"), "unpackedMatrix") instead
  |=========================================================================================| 100%, Elapsed 00:01Evaluating signature-gene importance...

  |=========================================================================================| 100%, Elapsed 00:01Creating 5 background signature groups with the following parameters:
  sigSize sigBalance
1       7          1
2      14          1
3      22          1
4      36          1
5      78          1
  signatures per group: 3000
Computing KNN Cell Graph in the Latent Space...

Evaluating local consistency of signatures in latent space...

  |=========================================================================================| 100%, Elapsed 00:00Clustering signatures...

Computing differential signature tests...

  |                                                                                                |   0%, ETA NAError in `[<-.data.frame`(`*tmp*`, , 2, value = 0) : 
  替换数据里有1行,但数据有0
In addition: Warning messages:
1: In asMethod(object) :
  sparse->dense coercion: allocating vector of size 3.1 GiB
2: In readSignaturesInput(signatures) : NAs introduced by coercion
3: In asMethod(object) :
  sparse->dense coercion: allocating vector of size 3.1 GiB
4: In pbmclapply(sigBatches, function(sigBatch) { :
  mc.cores > 1 is not supported on Windows due to limitation of mc*apply() functions.
  mc.core is set to 1.
5: In pbmclapply(setNames(sigs, sigs), sigGene) :
  mc.cores > 1 is not supported on Windows due to limitation of mc*apply() functions.
  mc.core is set to 1.
6: In asMethod(object) :
  sparse->dense coercion: allocating vector of size 3.1 GiB
7: In pbmclapply(fgSigBatches, function(ii) { :
  mc.cores > 1 is not supported on Windows due to limitation of mc*apply() functions.
  mc.core is set to 1.
8: In pbmclapply(randomSigBatches, function(randomSigSubset) { :
  mc.cores > 1 is not supported on Windows due to limitation of mc*apply() functions.
  mc.core is set to 1.
9: In pbmclapply(factorMeta, function(metaName) { :
  mc.cores > 1 is not supported on Windows due to limitation of mc*apply() functions.
  mc.core is set to 1.
decade2020 commented 1 year ago

同遇到过,后面通过更换vision的版本解决的

Rainjie-afk commented 1 year ago

同遇到过,后面通过更换vision的版本解决的 H got the same error, Which VERSION of vision did you use?

460350 commented 1 year ago

I had the same error. I solved it by updating VISION to 3.0.1 with the suggestions in #17 using devtools::install_github("YosefLab/VISION"). However, it seems against what is recommended in README.md.

wangyasen615 commented 1 week ago

against what is recommended in README.md