[Bioc-devel] any interest in a BiocMatrix core package?

Tim Triche, Jr. tim.triche at gmail.com
Fri Feb 24 22:34:58 CET 2017


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> 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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>
>
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