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multi-omics tutorial #8

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dorothyzh opened this issue Mar 19, 2024 · 6 comments
Closed

multi-omics tutorial #8

dorothyzh opened this issue Mar 19, 2024 · 6 comments

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@dorothyzh
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For the tutorial, only shows the single omics analysis using Stabl, but the cyto_ool and other datasets were not used in the tutorial. So could I find the tutorial or the codes for multi-omics elsewhere?

@xavdurand
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Hello @dorothyzh ,

Thank you for your comment. We added a quick explanation of the 3 ways of handling multi-omic datas: https://github.com/gregbellan/Stabl/blob/main/Notebook%20examples/Handling%20Multi-omics.docx

I closed the issue with this file.

@dorothyzh
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Thanks, but if I would like to use the third way, which function should I use for stable? And for multi_omic_stabl_cv function, the plotting always have some bugs inside, could you provide a multi-omics tutorial similar as the "STABL in single-omic" one in the tutorial, then we could directly get the stabl object and omit plotting issues.

@xavdurand xavdurand reopened this Mar 20, 2024
@xavdurand
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xavdurand commented Mar 20, 2024

Thank you @dorothyzh for your comment.
I advise you to look for the scripts named run_*.py for an example of run.

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@dorothyzh
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dorothyzh commented Apr 2, 2024

Thanks for the comment, and may I ask for some detailed description of the results, for instance, is there any more detailed results other than feature names that we can get from the object "stabl_regression". Such as the predicted values or p value or any statistics for these features?

@xavdurand
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xavdurand commented Apr 2, 2024

Hi @dorothyzh ,

You have multiple attributes of the Stabl object that you can use. For example, the parameter stabl_scores_ contains the statistical score of each feature calculated by Stabl. These scores are not properly p-values but frequencies of selection. You can take a look here for more attributes: https://github.com/gregbellan/Stabl/blob/30039a573d072c4604396197466768951458ca3f/stabl/stabl.py#L807C3-L838C69

Stabl's main purpose is the feature selection so a predicted value is not meaningful, as it implements SelectorMixin scikit-learn object. You can use Stabl as a selector/transformer before the modelization step.

@xavdurand
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As the issue seems resolved. I close the github issue.

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