experiment$ms #> <SOMACollection> -#> uri: file:///tmp/RtmpEx4fcP/soma-exp-pbmc-small/ms +#> uri: file:///tmp/RtmpNLpVQS/soma-exp-pbmc-small/ms #> groups: RNA
To use larger (or smaller) buffer sizes:
diff --git a/articles/soma-objects.html b/articles/soma-objects.html index db6223e3b9..4e829df300 100644 --- a/articles/soma-objects.html +++ b/articles/soma-objects.html @@ -26,7 +26,7 @@ tiledbsoma - 1.12.1 + 1.12.2 @@ -95,7 +95,7 @@ Example data uri <- extract_dataset("soma-exp-pbmc-small") uri -#> [1] "/tmp/RtmpBGJcN2/soma-exp-pbmc-small"
uri <- extract_dataset("soma-exp-pbmc-small") uri -#> [1] "/tmp/RtmpBGJcN2/soma-exp-pbmc-small"
experiment <- SOMAExperimentOpen(uri) experiment #> <SOMAExperiment> -#> uri: /tmp/RtmpBGJcN2/soma-exp-pbmc-small +#> uri: /tmp/RtmpYxRyMn/soma-exp-pbmc-small #> arrays: obs #> groups: ms
Note that opening a SOMAExperiment (or any SOMA object) only returns a pointer to the object on disk. No data is actually read into memory until it’s requested. This is important as the full experiment may be too large to fit in memory.
SOMAExperiment
experiment$ms #> <SOMACollection> -#> uri: file:///tmp/RtmpBGJcN2/soma-exp-pbmc-small/ms +#> uri: file:///tmp/RtmpYxRyMn/soma-exp-pbmc-small/ms #> groups: RNA
This returns the SOMACollection of measurements. We’ll take a closer look at this later.
SOMACollection
To access the obs field containing the observation annotations:
obs
experiment$obs #> <SOMADataFrame> -#> uri: file:///tmp/RtmpBGJcN2/soma-exp-pbmc-small/obs +#> uri: file:///tmp/RtmpYxRyMn/soma-exp-pbmc-small/obs #> dimensions: soma_joinid #> attributes: orig.ident, nCount_RNA, nFeature_RNA, RNA_snn_res.0.8, letter.idents, groups,...
In this case, we have one member: RNA, which is a SOMAMeasurement. A specific measurement can be accessed by name with the get() method:
RNA
SOMAMeasurement
get()
experiment$ms$get("RNA") #> <SOMAMeasurement> -#> uri: file:///tmp/RtmpBGJcN2/soma-exp-pbmc-small/ms/RNA +#> uri: file:///tmp/RtmpYxRyMn/soma-exp-pbmc-small/ms/RNA #> arrays: var #> groups: obsm, obsp, varm, X
This collection contains 3 layers corresponding to the raw, normalized, and scaled slots from the original Seurat object.
Any of these X layers can be accessed using get():
X
This returns a SOMASparseNDArray. As we did before, we can inspect the array’s schema:
SOMASparseNDArray
## <SOMASparseNDArray> -## uri: file:///tmp/Rtmp62d4sU/soma-exp-pbmc-small/ms/RNA/X/counts +## uri: file:///tmp/RtmpyyUTYu/soma-exp-pbmc-small/ms/RNA/X/counts ## dimensions: soma_dim_0, soma_dim_1 ## attributes: soma_data
Similar to SOMADataFrame, we can load the data into memory as an Arrow Table:
SOMADataFrame
Wolen A, Eddelbuettel D, Hoffman P, Kerl J (2024). tiledbsoma: 'TileDB' Stack of Matrices, Annotated ('SOMA'). -R package version 1.12.1, https://github.com/single-cell-data/TileDB-SOMA. +R package version 1.12.2, https://github.com/single-cell-data/TileDB-SOMA.
@Manual{, title = {tiledbsoma: 'TileDB' Stack of Matrices, Annotated ('SOMA')}, author = {Aaron Wolen and Dirk Eddelbuettel and Paul Hoffman and John Kerl}, year = {2024}, - note = {R package version 1.12.1}, + note = {R package version 1.12.2}, url = {https://github.com/single-cell-data/TileDB-SOMA}, }
NEWS.md