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plevritis-lab / CELESTA

Automate unsupervised machine learning cell type identification using both protein expressions and cell spatial neighborhood information for multiplexed in situ imaging data. No training dataset with cell type labels is required.
Apache License 2.0
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NAs error #12

Open afshinmoradi opened 2 years ago

afshinmoradi commented 2 years ago

Dear,

I got this error Do you have any idea how to fix it

Your help is appreciated .

Best regards

Error in current_scoring_matrix[unassigned_cells, cell_type_num[i]] <- GetScore(activation_prob_to_use, : NAs are not allowed in subscripted assignments In addition: Warning messages: 1: In lineage_info$Cell_type_number == previous_level_type : longer object length is not a multiple of shorter object length 2: In current_cell_type_assignment[, previous_level_round] == previous_level_type : longer object length is not a multiple of shorter object length

andrewjUTSW commented 2 years ago

Hi there! I think I also encountered this. And I think I may have fixed the issue with this pull request: https://github.com/plevritis-lab/CELESTA/pull/11 You can check my forked repo for the corrected code: https://github.com/andrewjUTSW/CELESTA

afshinmoradi commented 2 years ago

Thanks for that

weiruo16 commented 2 years ago

Hi, we have fixed the issue with empty unassigned cells in the main branch. Please try it again. In addition, the warning messages may indicate that the input cell-type signature has some formatting errors, which may actually cause the error.

matthew-lee1 commented 9 months ago

Hello,

I have recently installed the latest version of CELESTA and am still getting the following error: 

Error in current_scoring_matrix[unassigned_cells, cell_type_num[i]] <- GetScore(activation_prob_to_use,  : 
  NAs are not allowed in subscripted assignments
In addition: Warning message:
In lineage_info$Cell_type_number == previous_level_type :
  longer object length is not a multiple of shorter object length

If needed i can provide code, however it is essentially identical to the code given in README.