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updated 6.6 years ago by
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Comment: Best practice for handling large data (matrix with >2^31-1 non-zero elements) in
by
James W. MacDonald
68k
Oh.
```
> z <- read10xCounts(c(tmpdir, tmpdir), mtx.class = "SVT_SparseMatrix", delayed = TRUE)
> class(counts(z))
[1] "DelayedMatrix"
att…
Comment: Best practice for handling large data (matrix with >2^31-1 non-zero elements) in
by
James W. MacDonald
68k
That's weird. Using the example data works for me.
```
> example(read10xCounts)
rd10xC> # Mocking up some 10X genomics output.
rd10xC> ex…
Comment: Join BOC Sciences at Drug Discovery Chemistry
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teamardigen
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0
Sounds like an exciting event for anyone passionate about small molecule innovation. The focus on discovery and optimization really drives …
Comment: Best practice for handling large data (matrix with >2^31-1 non-zero elements) in
by
dan.gatti
•
0
I am, but perhaps I'm not understanding how it should work.
> sse = DropletUtils::read10xCounts(curr_files[1], mtx.class = 'SVT_Sparse…
Comment: Best practice for handling large data (matrix with >2^31-1 non-zero elements) in
by
James W. MacDonald
68k
Did you use the development version as Aaron suggested? There is an argument to read the market matrix file directly into an `SVT_SparseMat…
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