experiment$ms
#> <SOMACollection>
-#> uri: file:///tmp/RtmpES12uG/soma-exp-pbmc-small/ms
+#> uri: file:///tmp/RtmpOfs479/soma-exp-pbmc-small/ms
#> groups: RNA
To use larger (or smaller) buffer sizes:
diff --git a/articles/soma-objects.html b/articles/soma-objects.html index 054f40fd7c..e045f6e5cb 100644 --- a/articles/soma-objects.html +++ b/articles/soma-objects.html @@ -95,7 +95,7 @@Example data
uri <- extract_dataset("soma-exp-pbmc-small") uri -#> [1] "/tmp/Rtmpg9udEr/soma-exp-pbmc-small"
experiment <- SOMAExperimentOpen(uri)
experiment
#> <SOMAExperiment>
-#> uri: /tmp/Rtmpg9udEr/soma-exp-pbmc-small
+#> uri: /tmp/RtmpXZxQi9/soma-exp-pbmc-small
#> arrays: obs
#> groups: msNote that opening a SOMAExperiment (or any SOMA object) only returns a pointer to the object on disk. No data is actually read into memory until it’s requested. This is important as the full experiment may be too large to fit in memory.
experiment$ms
#> <SOMACollection>
-#> uri: file:///tmp/Rtmpg9udEr/soma-exp-pbmc-small/ms
+#> uri: file:///tmp/RtmpXZxQi9/soma-exp-pbmc-small/ms
#> groups: RNAThis returns the SOMACollection of measurements. We’ll take a closer look at this later.
To access the obs field containing the observation annotations:
experiment$obs
#> <SOMADataFrame>
-#> uri: file:///tmp/Rtmpg9udEr/soma-exp-pbmc-small/obs
+#> uri: file:///tmp/RtmpXZxQi9/soma-exp-pbmc-small/obs
#> dimensions: soma_joinid
#> attributes: orig.ident, nCount_RNA, nFeature_RNA, RNA_snn_res.0.8, letter.idents, groups,...
experiment$ms
#> <SOMACollection>
-#> uri: file:///tmp/Rtmpg9udEr/soma-exp-pbmc-small/ms
+#> uri: file:///tmp/RtmpXZxQi9/soma-exp-pbmc-small/ms
#> groups: RNAIn this case, we have one member: RNA, which is a SOMAMeasurement. A specific measurement can be accessed by name with the get() method:
experiment$ms$get("RNA")
#> <SOMAMeasurement>
-#> uri: file:///tmp/Rtmpg9udEr/soma-exp-pbmc-small/ms/RNA
+#> uri: file:///tmp/RtmpXZxQi9/soma-exp-pbmc-small/ms/RNA
#> arrays: var
#> groups: obsm, obsp, varm, XThis 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():
This returns a SOMASparseNDArray. As we did before, we can inspect the array’s schema:
## <SOMASparseNDArray>
-## uri: file:///tmp/Rtmpaivl1V/soma-exp-pbmc-small/ms/RNA/X/counts
+## uri: file:///tmp/RtmpJuklno/soma-exp-pbmc-small/ms/RNA/X/counts
## dimensions: soma_dim_0, soma_dim_1
## attributes: soma_dataSimilar to SOMADataFrame, we can load the data into memory as an Arrow Table: