Help with error Ecotyper failed: Error in RunJobQueue()

[WJRDW]

Dear EcoTyper team,

Thank you for the amazing tool!
I've been trying to perform de novo discovery of cell states and ecotypes in scRNA-seq data (tutorial 5), but keep encountering the same error and can not figure out its origin. Th error message doesn't really help trying to find the root of the issue.

At first I thought the size of my input matrix (16GB) might be the problem, but I'm running the analysis remotely on a HPC cluster so don't think the issue lies there. Would it be a possibility to provide you with my input matrix, annotation and configuration file to see if you are running into the same problem and the error is reproducible?
Thank you very much!

Best,
Wout

[annalamaria]

I am having the same issue, is there a working solution for this? In addition to the RunJobQueue() error I receive the following warning:

In fread(file.path(input_dir, paste0("data.txt")), data.table = F) :
Detected 39292 column names but the data has 39293 columns (i.e. invalid file). Added 1 extra default column name for the first column which is guessed to be row names or an index. Use setnames() afterwards if this guess is not correct, or fix the file write command that created the file to create a valid file.

I have constructed the annotation and data files like the example files, so I don't know what causes this issue. In addition, if I add the gene column Ecotyper will not run since it cannot find the column in the annotation file. If I run the example data, none of these errors appear but I cannot locate the origin of these issues.

[jiwoo-lim2]

In my case,

Step 1: Cell types with cell counts below 50 were flagged as warnings.
Step 2: These same cell types were marked as Errors and prompted exclusion from the dataset.

The error Ecotyper failed: Error in RunJobQueue() suggests the pipeline halts entirely upon encountering any error. Thus, resolving pre-existing errors (before RunJobQueue()) is critical.

Excluding the error-causing cell types from the dataset resolved the issue.

If there are future updates, it might be beneficial to output a warning for cell types with insufficient cell counts rather than generating an error. Additionally, automatically excluding these cell types from the analysis could be a good approach.