Dear all, I?m a bioinformatics PhD student at UCL who?s recently been trying to develop an R package that has some python dependencies. Specifically, areas of my current pipeline are written in python for speed and any ML has been implemented through sklearn. I was wondering what you would advise as the best practice of integrating python code into Bioconductor/R p packages? E.g. R to python interfaces (such as reticulate) or advising package users to call python scripts independently or re-writing python code in R? Any advice would be much appreciated. Many thanks in advance, David
[Bioc-devel] Integrating python into an R package
3 messages · Zhang, David, Turaga, Nitesh, Vincent Carey
Take a look at BiocSklearn. Nitesh
On Feb 18, 2020, at 8:11 AM, Zhang, David <david.zhang.12 at ucl.ac.uk> wrote: Dear all, I?m a bioinformatics PhD student at UCL who?s recently been trying to develop an R package that has some python dependencies. Specifically, areas of my current pipeline are written in python for speed and any ML has been implemented through sklearn. I was wondering what you would advise as the best practice of integrating python code into Bioconductor/R p packages? E.g. R to python interfaces (such as reticulate) or advising package users to call python scripts independently or re-writing python code in R? Any advice would be much appreciated. Many thanks in advance, David
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I would advise that you do not reimplement working methods but interface to them. Bioconductor's BiocSklearn package exposes aspects of scikit and you could have a look at that for one approach. The basilisk package <https://github.com/LTLA/basilisk> in development is a more systematic way of governing interoperability with python and should also be examined. On Tue, Feb 18, 2020 at 10:53 AM Zhang, David <david.zhang.12 at ucl.ac.uk> wrote:
Dear all, I?m a bioinformatics PhD student at UCL who?s recently been trying to develop an R package that has some python dependencies. Specifically, areas of my current pipeline are written in python for speed and any ML has been implemented through sklearn. I was wondering what you would advise as the best practice of integrating python code into Bioconductor/R p packages? E.g. R to python interfaces (such as reticulate) or advising package users to call python scripts independently or re-writing python code in R? Any advice would be much appreciated. Many thanks in advance, David
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