Thanks Martin, I'll give the ExperimentHub package method a try then, if I can use it for vignette-only processed data. I think I was getting confused with annotationHub (which I gather is intended for useful-for-other-packages-or-applications raw data). Time should be ok - I just want to skip the long step on full-sized data. Sarah.
On 27 July 2018 at 19:30, Martin Morgan <martin.mor...@roswellpark.org> wrote: > Remember also that there are overall evaluation time limits. > > One strategy might use existing stable publicly available SC data sets > from e.g., > > http://imlspenticton.uzh.ch:3838/conquer/ > https://hemberg-lab.github.io/scRNA.seq.datasets/ > > These could be downloaded using BiocFileCache as a first step in the > vignette ; the download cost would be 'paid' the first time, but subsequent > use would be from the locally cached data. > > A second approach would be to create an ExperimentHub package, and to use > that in your examples. > > http://bioconductor.org/packages/devel/ExperimentHub > > http://bioconductor.org/packages/devel/bioc/vignettes/Experi > mentHub/inst/doc/CreateAnExperimentHubPackage.html > > The submission process would start by submitting the EH package, and then > adding, once the kinks in the experiment data package are worked out, the > software package to the issue. The data and software packages would be > accepted together. > > Martin > > > On 07/27/2018 02:38 AM, Sarah Williams via Bioc-devel wrote: > >> Hi, >> >> I'm preparing a package for submission to bioconductor, but hitting the >> 4mb >> size limit due to examples in my vignette. >> >> I do have a demo toy sized dataset which I use for the bulk of the >> vignette. But I wanted to show real-data examples at the end because >> approach doesn't work well on toy-sized data. >> >> Conceivably everything except for the 'examples' section would make a >> 'complete' vignette (but probably not a very helpful one...). I'm >> wondering >> if I should static-ify just those examples? Might hit the 50% runnable >> code-chunk limit then though. Unfortunately its a rank-based approach so i >> can't really take the top 100 genes for these particuar objects. >> >> Not sure how best to solve this, any tips/suggestions? Thanks! >> >> (The problematic vignette is here: >> https://bioinformatics.erc.monash.edu/home/sarah.williams/pr >> ojects/cell_groupings/doco/celaref_doco.html >> ) >> >> NB: To make matters worse this is a tool for comparing datasets - so I >> have >> multiples! They are public datasets and I haven't done anything exciting >> with them (nor would anyone else want to reuse processed objects) - so I >> don't think that I should make a data package. >> >> NB: Using xz compression and some cleanup I got it down to 21mb, from 49mb >> - So its not huge but I don't think I can get to <4mb this way. >> >> [[alternative HTML version deleted]] >> >> _______________________________________________ >> Bioc-devel@r-project.org mailing list >> https://stat.ethz.ch/mailman/listinfo/bioc-devel >> >> > > This email message may contain legally privileged and/or confidential > information. If you are not the intended recipient(s), or the employee or > agent responsible for the delivery of this message to the intended > recipient(s), you are hereby notified that any disclosure, copying, > distribution, or use of this email message is prohibited. If you have > received this message in error, please notify the sender immediately by > e-mail and delete this email message from your computer. Thank you. > [[alternative HTML version deleted]] _______________________________________________ Bioc-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/bioc-devel
