Not getting output from Inspect AnnData tool

I want to use the Inspect AnnData tool to generate a matrix from my data.
The annotation file that I give to this tool as input is about 26 GB and every time the output of this tool turns red.
Is it because of the large amount of data? And if so, is there a way for me to get a matrix from my annotation data?
Thank you in advance for your advice

Hi @maryam-gh99

You started to ask a question in this thread Problem using Import Anndata tool - #2 by jennaj but there wasn’t any followup. I’ll close that thread and we can continue here. We can’t help without more details. Many things can contribute to job failures.

If you think the data might be corrupted, or too large to process (unlikely if you are working at, these are a few items to try:

  1. Check to make sure that this very large file is intact. The Inspect AnnData tool can be used to collect general information as a sanity check.

  2. Try converting just parts of the file to a matrix, or other summaries, instead of all of it. The errors (if any) from this might inform more about what might be wrong.

  3. After running more checks, if you have an error that you don’t understand, you can post that back with information from your checks so people can help you to troubleshoot. This can include job parameters, error messages, and (optionally) a shared history.

More help is in the single cell tutorials here, including more QA/QC checks:

Please ask new questions in new topics. See Normalize with scanpy

I followed up on the previous problem with the topic of “problem using the Import Anndata tool”, but I realized that my message was not approved because it contained a link to my history, but fortunately, both the problems of the Import Anndata tool and the Inspect AnnData tool were solved with your instructions. Thank you very much
Now I have another question
In the article that referenced the data that I am currently processing, it used the computeSumFactors method to normalize them.
And with my studies, I realized that this method is better for normalizing sparse count data
But I don’t know if the tool introduced in the tutorial on Clustering 3K PBMCs with Scanpy for normalization (Normalize with scanpy) uses the same normalization method or not?
And if this is not the case, due to the fact that my data is a type of sparse data and normalization by the computeSumFactors method is mandatory for them.
Does Galaxy have a tool to normalize my data in this way?

Since I am not sure if this message will reach you, I asked the same question in the Help Galaxy section.

‫‪Jennifer Hillman-Jackson via Galaxy Community Help‬‏ <‪‬‏> در تاریخ سه‌شنبه ۱۳ سپتامبر ۲۰۲۲ ساعت ۵:۳۵ نوشت:‬