[Bioc-devel] About the size limitation of the package

You Zhou youzhou|e@rn|ng @end|ng |rom gm@||@com
Thu May 27 10:07:20 CEST 2021

Hi Stuart,

Thanks for the cool suggestion. I have uploaded the model to bioconductor S3 bucket and now everything work perfectly, but I would also check out your suggestion.

You Zhou

发件人: Stuart Lee <lee.s using wehi.edu.au>
日期: 2021年5月26日 星期三 23:55
收件人: "Kern, Lori" <Lori.Shepherd using roswellpark.org>, You Zhou <youzhoulearning using gmail.com>, "bioc-devel using r-project.org" <bioc-devel using r-project.org>
主题: Re: About the size limitation of the package

Hi You and Lori,

Are fitted models in scope for ExperimentHub? I thought it was more for data. Maybe there should be a ModelHub for developers to include trained models from papers in their packages?

@You: if that model has been fitted in R take a look at https://github.com/tidymodels/butcher for some ways of reducing it’s size.

From: Bioc-devel <bioc-devel-bounces using r-project.org> on behalf of Kern, Lori <Lori.Shepherd using RoswellPark.org>
Sent: Wednesday, 26 May 2021 10:01 PM
To: You Zhou <youzhoulearning using gmail.com>; bioc-devel using r-project.org <bioc-devel using r-project.org>
Subject: Re: [Bioc-devel] About the size limitation of the package

Please consider using Experiment Hub to host the large data file. More information can be found here:


Lori Shepherd

Bioconductor Core Team

Roswell Park Comprehensive Cancer Center

Department of Biostatistics & Bioinformatics

Elm & Carlton Streets

Buffalo, New York 14263

From: Bioc-devel <bioc-devel-bounces using r-project.org> on behalf of You Zhou <youzhoulearning using gmail.com>
Sent: Wednesday, May 26, 2021 5:09 AM
To: bioc-devel using r-project.org <bioc-devel using r-project.org>
Subject: [Bioc-devel] About the size limitation of the package

Dear Bioc team,

I am compiling a package �m6Aboost� and planning to submit it in the Bioconductor. This package using a trained machine learning model to identify the correct m6A signals from the miCLIP2 data set (more detail about this machine learning model can be found in our paper https://www.biorxiv.org/content/10.1101/2020.12.20.423675v1).

Now I meet a problem: the size of this machine learning model is 10 Mb, which is bigger than 5 Mb. Since this model is crucial for the package, I was wondering whether I can ignore the warning message about the size limitation. Thank you : )

Best regards,
You Zhou

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