Subset a giotto object with [[ to disassemble it into a list of Giotto
S4 subobjects. If drop is FALSE, the selected subobjects
will be reassembled into a new giotto object. Note that indexing within
the [[ filters for only those subobjects that have those attributes.
This may remove some unexpected information. For specifically splitting the
giotto object by spatial unit and/or feature type while keeping all
expected information, use sliceGiotto()
Usage
# S4 method for class 'giotto,missing,missing'
x[[spat_unit = NULL, feat_type = NULL, drop = TRUE, ...]]
# S4 method for class 'giotto,character,missing'
x[[i, spat_unit = NULL, feat_type = NULL, drop = TRUE, ...]]
# S4 method for class 'giotto,missing,character'
x[[j, spat_unit = NULL, feat_type = NULL, drop = TRUE, ...]]
# S4 method for class 'giotto,character,character'
x[[i, j, spat_unit = NULL, feat_type = NULL, drop = TRUE, ...]]Examples
g <- GiottoData::loadGiottoMini("vizgen")
#> 1. read Giotto object
#> 2. read Giotto feature information
#> 3. read Giotto spatial information
#> 3.1 read Giotto spatial shape information
#> 3.2 read Giotto spatial centroid information
#> 3.3 read Giotto spatial overlap information
#> 4. read Giotto image information
#> python already initialized in this session
#> active environment : 'giotto_env'
#> python version : 3.10
force(g)
#> An object of class giotto
#> >Active spat_unit: z0
#> >Active feat_type: rna
#> dimensions : 337, 498 (features, cells)
#> [SUBCELLULAR INFO]
#> polygons : z0 z1 aggregate
#> features : rna
#> [AGGREGATE INFO]
#> expression -----------------------
#> [z0][rna] raw
#> [z1][rna] raw
#> [aggregate][rna] raw normalized scaled pearson
#> spatial locations ----------------
#> [z0] raw
#> [z1] raw
#> [aggregate] raw
#> spatial networks -----------------
#> [aggregate] Delaunay_network kNN_network
#> spatial enrichments --------------
#> [aggregate][rna] cluster_metagene
#> dim reduction --------------------
#> [aggregate][rna] pca umap tsne
#> nearest neighbor networks --------
#> [aggregate][rna] sNN.pca
#> attached images ------------------
#> images : 4 items...
#>
#>
#> Use objHistory() to see steps and params used
# return as lists of subobjects with drop = TRUE (default)
g[[, "raw"]]
#> [[1]]
#> An object of class spatLocsObj : "raw"
#> spat_unit : "z0"
#> provenance: z0
#> dimensions: 498 3
#> preview :
#> sdimx sdimy cell_ID
#> <num> <num> <char>
#> 1: 6405.067 -4780.499 40951783403982682273285375368232495429
#> 2: 6426.020 -4972.519 240649020551054330404932383065726870513
#> 3: 6428.456 -4799.158 274176126496863898679934791272921588227
#>
#> ranges:
#> sdimx sdimy
#> [1,] 6402.438 -5146.726
#> [2,] 6899.203 -4700.157
#>
#>
#> [[2]]
#> An object of class spatLocsObj : "raw"
#> spat_unit : "z1"
#> provenance: z1
#> dimensions: 504 3
#> preview :
#> sdimx sdimy cell_ID
#> <num> <num> <char>
#> 1: 6404.014 -4779.625 40951783403982682273285375368232495429
#> 2: 6408.296 -4970.794 17685062374745280598492217386845129350
#> 3: 6401.148 -4991.061 223553142498364321238189328942498473503
#>
#> ranges:
#> sdimx sdimy
#> [1,] 6401.148 -5147.193
#> [2,] 6899.323 -4700.410
#>
#>
#> [[3]]
#> An object of class spatLocsObj : "raw"
#> spat_unit : "aggregate"
#> provenance: z0 z1
#> dimensions: 462 3
#> preview :
#> sdimx sdimy cell_ID
#> <num> <num> <char>
#> 1: 6637.881 -5140.465 100210519278873141813371229408401071444
#> 2: 6471.978 -4883.541 101161259912191124732236989250178928032
#> 3: 6801.610 -4968.685 101488859781016188084173008420811094152
#>
#> ranges:
#> sdimx sdimy
#> [1,] 6401.412 -5146.747
#> [2,] 6899.108 -4700.326
#>
#>
#> [[4]]
#> An object of class exprObj : "raw"
#> spat_unit : "z0"
#> feat_type : "rna"
#> provenance: z0
#>
#> contains:
#> 337 x 498 sparse Matrix of class "dgCMatrix"
#>
#> Mlc1 . . . . . . . . . . . . . ......
#> Gprc5b . . 1 . 1 . . . 1 . 2 . . ......
#> Gfap . . . 1 1 . . . 27 . . . . ......
#>
#> ........suppressing 485 columns and 331 rows
#>
#> Adgrf4 . . . . . . . . . . . . . ......
#> Epha2 . . . . . . . . . . . . . ......
#> Blank-139 . . . . . . . . . . . . . ......
#>
#> First four colnames:
#> 40951783403982682273285375368232495429
#> 240649020551054330404932383065726870513
#> 274176126496863898679934791272921588227
#> 323754550002953984063006506310071917306
#>
#> [[5]]
#> An object of class exprObj : "raw"
#> spat_unit : "z1"
#> feat_type : "rna"
#> provenance: z1
#>
#> contains:
#> 337 x 504 sparse Matrix of class "dgCMatrix"
#>
#> Mlc1 . . . . . . . . . . . 1 . ......
#> Gprc5b . . . . . . . 2 . . . 1 . ......
#> Gfap . 3 . 2 . 1 4 . . . . 18 . ......
#>
#> ........suppressing 491 columns and 331 rows
#>
#> Adgrf4 . . . . . . . . . . . . . ......
#> Epha2 . . . . . . . . . . . . . ......
#> Blank-139 . . . . . . . . . . . . . ......
#>
#> First four colnames:
#> 40951783403982682273285375368232495429
#> 17685062374745280598492217386845129350
#> 223553142498364321238189328942498473503
#> 240649020551054330404932383065726870513
#>
#> [[6]]
#> An object of class exprObj : "raw"
#> spat_unit : "aggregate"
#> feat_type : "rna"
#> provenance: z0 z1
#>
#> contains:
#> 337 x 462 sparse Matrix of class "dgCMatrix"
#>
#> Mlc1 . . . . . . 1 . . 1 . . . ......
#> Gprc5b . 1 . 3 . . 2 . 4 2 . 1 . ......
#> Gfap 2 . 2 1 . . 45 . 1 1 . . . ......
#>
#> ........suppressing 449 columns and 331 rows
#>
#> Adgrf4 . . . . . . . . . . . . . ......
#> Epha2 . . . . . . . . . . . . . ......
#> Blank-139 . . . . . . . . . . . . . ......
#>
#> First four colnames:
#> 240649020551054330404932383065726870513
#> 274176126496863898679934791272921588227
#> 323754550002953984063006506310071917306
#> 87260224659312905497866017323180367450
#>
g[["expression", spat_unit = "aggregate"]]
#> [[1]]
#> An object of class exprObj : "raw"
#> spat_unit : "aggregate"
#> feat_type : "rna"
#> provenance: z0 z1
#>
#> contains:
#> 337 x 462 sparse Matrix of class "dgCMatrix"
#>
#> Mlc1 . . . . . . 1 . . 1 . . . ......
#> Gprc5b . 1 . 3 . . 2 . 4 2 . 1 . ......
#> Gfap 2 . 2 1 . . 45 . 1 1 . . . ......
#>
#> ........suppressing 449 columns and 331 rows
#>
#> Adgrf4 . . . . . . . . . . . . . ......
#> Epha2 . . . . . . . . . . . . . ......
#> Blank-139 . . . . . . . . . . . . . ......
#>
#> First four colnames:
#> 240649020551054330404932383065726870513
#> 274176126496863898679934791272921588227
#> 323754550002953984063006506310071917306
#> 87260224659312905497866017323180367450
#>
#> [[2]]
#> An object of class exprObj : "normalized"
#> spat_unit : "aggregate"
#> feat_type : "rna"
#> provenance: z0 z1
#>
#> contains:
#> 337 x 462 sparse Matrix of class "dgCMatrix"
#>
#> Mlc1 . . . . . . 5.291601 . . 5.821597 . . .
#> Gprc5b . 6.398031 . 7.454658 . . 6.273066 . 7.680054 6.808785 . 5.082989 .
#> Gfap 10.48137 . 7.901442 5.886051 . . 10.746982 . 5.701006 5.821597 . . .
#>
#> Mlc1 ......
#> Gprc5b ......
#> Gfap ......
#>
#> ........suppressing 449 columns and 331 rows
#>
#> Adgrf4 . . . . . . . . . . . . . ......
#> Epha2 . . . . . . . . . . . . . ......
#> Blank-139 . . . . . . . . . . . . . ......
#>
#> First four colnames:
#> 240649020551054330404932383065726870513
#> 274176126496863898679934791272921588227
#> 323754550002953984063006506310071917306
#> 87260224659312905497866017323180367450
#>
#> [[3]]
#> An object of class exprObj : "scaled"
#> spat_unit : "aggregate"
#> feat_type : "rna"
#> provenance: z0 z1
#>
#> contains:
#>
#> 337 x 462 dense matrix of class "dgeMatrix"
#>
#> Mlc1 -0.51096453 -0.4718074 -0.3859440 -0.4383384 -0.3827836 -0.3152653 ......
#> Gprc5b -0.97549417 1.6804631 -0.5746594 1.2850731 -0.5794505 -0.4583322 ......
#> Gfap 5.46807822 -0.7367558 1.3902670 0.5804327 -0.6152080 -0.4843442 ......
#> Ednrb 9.34063752 3.7384966 2.5412669 1.5736461 2.8570134 -0.2823656 ......
#> Sox9 -0.59906517 -0.5143258 2.4318798 -0.4671338 -0.4200826 -0.3423988 ......
#> Aqp4 -0.64987710 -0.5388482 2.0705344 1.0223253 1.9919249 -0.3580479 ......
#> Gjc3 0.02982685 5.0161718 -0.1662473 -0.2615829 -0.1538300 -0.1487112 ......
#> Sox8 -0.47826316 3.5325216 2.5366322 -0.4276501 -0.3689389 -0.3051939 ......
#> Ntsr2 6.06580557 2.6068464 1.7367543 1.1330202 -0.6019376 -0.4746906 ......
#> Adcyap1r1 -2.17060870 0.8282834 0.8492637 -0.9807865 -1.0854235 -0.8264062 ......
#>
#> First four colnames:
#> 240649020551054330404932383065726870513
#> 274176126496863898679934791272921588227
#> 323754550002953984063006506310071917306
#> 87260224659312905497866017323180367450
#>
#> [[4]]
#> An object of class exprObj : "pearson"
#> spat_unit : "aggregate"
#> feat_type : "rna"
#> provenance: z0 z1
#>
#> contains:
#>
#> 337 x 462 dense matrix of class "dgeMatrix"
#>
#> Mlc1 -0.1671233 -0.4887705 -0.4090814 -0.5848627 -0.3515289 -0.3681237 ......
#> Gprc5b -0.2390668 0.7264405 -0.5847568 2.7313611 -0.5026041 -0.5262978 ......
#> Gfap 4.1820021 -1.2576333 0.8204327 -0.8491028 -0.9074561 -0.9499730 ......
#> Ednrb 6.2681837 8.3133382 2.2399348 1.2854419 2.7238921 -0.3428383 ......
#> Sox9 -0.1862585 -0.5445941 3.9225159 -0.6515799 -0.3917326 -0.4102193 ......
#> Aqp4 -0.2836816 -0.8280158 2.1766489 0.0105117 1.0752709 -0.6242357 ......
#> Gjc3 -0.1409193 4.4308083 -0.3450090 -0.4933833 -0.2964520 -0.3104520 ......
#> Sox8 -0.1577216 6.0278079 2.2000617 -0.5520553 -0.3317706 -0.3474348 ......
#> Ntsr2 5.2211595 12.2321831 2.5314771 1.9147811 -0.7517658 -0.7870865 ......
#> Adcyap1r1 -0.3682081 -0.1508472 0.2046257 -1.2808439 -0.7730688 -0.8093776 ......
#>
#> First four colnames:
#> 240649020551054330404932383065726870513
#> 274176126496863898679934791272921588227
#> 323754550002953984063006506310071917306
#> 87260224659312905497866017323180367450
#>
# return as a subset giotto object with drop = FALSE
g[[, "raw", drop = FALSE]]
#> An object of class giotto
#> >Active spat_unit: z0
#> >Active feat_type: rna
#> dimensions : 337, 498 (features, cells)
#> [SUBCELLULAR INFO]
#> [AGGREGATE INFO]
#> expression -----------------------
#> [z0][rna] raw
#> [z1][rna] raw
#> [aggregate][rna] raw
#> spatial locations ----------------
#> [z0] raw
#> [z1] raw
#> [aggregate] raw
#>
#>
#> Use objHistory() to see steps and params used
g[[spat_unit = "aggregate", drop = FALSE]]
#> An object of class giotto
#> >Active spat_unit: aggregate
#> >Active feat_type: rna
#> dimensions : 337, 462 (features, cells)
#> [SUBCELLULAR INFO]
#> polygons : aggregate
#> [AGGREGATE INFO]
#> expression -----------------------
#> [aggregate][rna] raw normalized scaled pearson
#> spatial locations ----------------
#> [aggregate] raw
#> spatial networks -----------------
#> [aggregate] Delaunay_network kNN_network
#> spatial enrichments --------------
#> [aggregate][rna] cluster_metagene
#> dim reduction --------------------
#> [aggregate][rna] pca umap tsne
#> nearest neighbor networks --------
#> [aggregate][rna] sNN.pca
#>
#>
#> Use objHistory() to see steps and params used