There is a DispatchClass  -  FilePath -  That will download the file and give 
you the path to the file in the cache location rather than loading it to the R 
session -  You then can use the file path in whatever read/load/etc method you 
deem fit.

RDataClass  - I would either say character or matrix - knowing that there will 
be instructions on how to load the data somewhere in your package -



Lori Shepherd

Bioconductor Core Team

Roswell Park Cancer Institute

Department of Biostatistics & Bioinformatics

Elm & Carlton Streets

Buffalo, New York 14263

________________________________
From: Bioc-devel <bioc-devel-boun...@r-project.org> on behalf of Lu, Dongyi 
(Lambda) <d...@caltech.edu>
Sent: Wednesday, December 19, 2018 8:42:39 PM
To: bioc-devel@r-project.org
Subject: [Bioc-devel] New ExperimentHub resource and some related questions

Hi everyone,

I�m writing a package (biocViews SinigleCell) that converts files of the BUS 
format (standing for Barcode, UMI, Set, see 
https://www.biorxiv.org/content/early/2018/11/21/472571) into a sparse matrix 
in R that can be used in Seurat and SingleCellExperiment. In order to write the 
examples and the vignette, I�m also putting the data itself into a package for 
ExperimentHub. The data used here are some mixed human and mouse cells from 
10x. Here are my questions:


  1.  In the documentation for `ExperimentHubData::makeExperimentHubMetadata`, 
the fields `RDataClass` and `DispatchClass` are required. However, this 
accompanying dataset package is meant to download text files (generated by 
command line tools outside R) to disk rather than into the R session, and it�s 
the job of the SingleCell package to converts the text files into a sparse 
matrix. There is a website documenting how the command line tools were used to 
generate the text files. So is this dataset still appropriate for ExperimentHub?
  2.  If it is appropriate, then what shall I put in `RDataClass` and 
`DispatchClass`?

Thanks,
Lambda

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