[Bioc-devel] any interest in a BiocMatrix core package?
It's a good place to start, though it would be very handy to have a C(++) API that can be linked against. I'm not sure how much work that would entail but it would give downstream developers a lot more options. Sort of like how we can link to Rhtslib, which speeds up a lot of BAM file processing, instead of just relying on Rsamtools. -Aaron
From: Tim Triche, Jr. <tim.triche at gmail.com>
Sent: Saturday, 25 February 2017 8:34:58 AM
To: Aaron Lun
Cc: bioc-devel at r-project.org
Subject: Re: [Bioc-devel] any interest in a BiocMatrix core package?
Sent: Saturday, 25 February 2017 8:34:58 AM
To: Aaron Lun
Cc: bioc-devel at r-project.org
Subject: Re: [Bioc-devel] any interest in a BiocMatrix core package?
yes
the DelayedArray framework that handles HDF5Array, etc. seems like the right choice?
--t
On Fri, Feb 24, 2017 at 1:26 PM, Aaron Lun <alun at wehi.edu.au<mailto:alun at wehi.edu.au>> wrote:
Hi everyone,
I just attended the Human Cell Atlas meeting in Stanford, and people were talking about gene expression matrices for >1 million cells. If we assume that we can get non-zero expression profiles for ~5000 genes, we?d be talking about a 5000 x 1 million matrix for the raw count data. This would be 20-40 GB in size, which would clearly benefit from sparse (via Matrix) or disk-backed representations (bigmatrix, BufferedMatrix, rhdf5, etc.).
I?m wondering whether there is any appetite amongst us for making a consistent BioC API to handle these matrices, sort of like what BiocParallel does for multicore and snow. It goes without saying that the different matrix representations should have consistent functions at the R level (rbind/cbind, etc.) but it would also be nice to have an integrated C/C++ API (accessible via LinkedTo). There?s many non-trivial things that can be done with this type of data, and it is often faster and more memory efficient to do these complex operations in compiled code.
I was thinking of something that you could supply any supported matrix representation to a registered function via .Call; the C++ constructor would recognise the type of matrix during class instantiation; and operations (row/column/random read access, also possibly various ways of writing a matrix) would be overloaded and behave as required for the class. Only the implementation of the API would need to care about the nitty gritty of each representation, and we would all be free to write code that actually does the interesting analytical stuff.
Anyway, just throwing some thoughts out there. Any comments appreciated.
Cheers,
Aaron
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