I wanted to take a moment to express my gratitude for the materials you provided on how to apply machine learning to the UK Biobank dataset. Thank you very much for your informative presentation during the "Cohort Selection and Genomic & Phenotype Data Extraction - Machine Learning 1: Coffee Break" seminar.
Unfortunately, I was unable to find the presentation and code that were shown during the seminar. If possible, could you please share the code with me? I am also interested in any additional resources or reproducible examples of machine learning applied to the UK Biobank dataset that you may have.
Additionally, I would greatly appreciate any guidance or code you could share on how to extract phenotype data, enrich it with genetic data, and prepare the data for subsequent model training.
Thank you again for your time and assistance. I look forward to hearing back from you soon.
Best regards,
Alex.
I think that the codebase for Coffee Break is not published publicly. However, for your code availability and extract phenotype data questions, there is a bunch of newer and updated materials documented in the public repositories that mention this topic:
Also, if you would like to try some particular method from this webinar, it should not be too much work to rewrite the code. Personally, I found rewriting some parts of code as a very useful training, as I get more hands on and understanding how the functionality works.
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Dear Ondrej,
I wanted to express my gratitude for your response and for sharing the valuable resources.
It is unfortunate that there are currently no presentations or accessible code on the topic of machine learning, but I still appreciate your help.
As for my interests, I am currently more interested in classical machine learning, as it is better suited for my work than computer vision. Nonetheless, I will keep the resources you provided in mind for future reference.
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I think that the codebase for Coffee Break is not published publicly. However, for your code availability and extract phenotype data questions, there is a bunch of newer and updated materials documented in the public repositories that mention this topic:
https://github.com/dnanexus/OpenBio/tree/master/UKB_notebooks
https://github.com/dnanexus/UKB_RAP/tree/main/end_to_end_gwas_phewas
Also, if you would like to try some particular method from this webinar, it should not be too much work to rewrite the code. Personally, I found rewriting some parts of code as a very useful training, as I get more hands on and understanding how the functionality works.
Dear Ondrej,
I wanted to express my gratitude for your response and for sharing the valuable resources.
It is unfortunate that there are currently no presentations or accessible code on the topic of machine learning, but I still appreciate your help.
As for my interests, I am currently more interested in classical machine learning, as it is better suited for my work than computer vision. Nonetheless, I will keep the resources you provided in mind for future reference.
Thank you once again for your assistance.
Best regards,
Alex
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