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Starlitnightly / omicverse

A python library for multi omics included bulk, single cell and spatial RNA-seq analysis.
https://starlitnightly.github.io/omicverse/
GNU General Public License v3.0
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When using bulk2single, should the bulk data use counts, tpm, deseq_normalize, or other types of data? #94

Closed Hennery02 closed 4 hours ago

Hennery02 commented 1 week ago

Dear Omicverse Team,

First of all, I would like to extend my sincere congratulations on the amazing work you have done with Omicverse. It has been incredibly helpful for my research, and I appreciate all the effort you have put into developing this tool.

I have a question regarding the use of the bulk2single function. When using bulk2single, should the bulk data be in the form of counts, TPM, DESeq normalized values, or some other type of data?

Thank you very much for your assistance and for your continuous contributions to the scientific community. I look forward to your guidance.

Best regards

Starlitnightly commented 1 week ago

Hi,

You need to make sure that Bulk and scRNA-seq use the same form of normalisation, e.g. in our tutorials, both use counts.

Zehua

Hennery02 commented 1 week ago

Thank you very much for your prompt response to my previous question.

I noticed that when running CellFractionPrediction = model.predicted_fraction(), the following message appears: "Normalizing raw single cell data with scanpy.pp.normalize_total". I am unsure whether the bulk data requires the same normalization treatment.

Thank you once again for your valuable assistance.

Starlitnightly commented 1 week ago

Thank you very much for your prompt response to my previous question.

I noticed that when running CellFractionPrediction = model.predicted_fraction(), the following message appears: "Normalizing raw single cell data with scanpy.pp.normalize_total". I am unsure whether the bulk data requires the same normalization treatment.

Thank you once again for your valuable assistance.

Hi,

I double-checked the input to bulk2single and it does ask for the raw unprocessed COUNT, which is the requirement for the cell fraction prediction.

Zehua