Skip to contents

Get multiomics integration results

Source: R/slot_accessors.R
get_multiomics.Rd

Get a multiomics integration result from a Giotto object

Usage

get_multiomics(
  gobject,
  spat_unit = NULL,
  feat_type = NULL,
  integration_method = "WNN",
  result_name = "theta_weighted_matrix"
)

Arguments

gobject

A Giotto object

spat_unit

spatial unit (e.g. 'cell')

feat_type

integrated feature type (e.g. 'rna_protein')

integration_method

multiomics integration method used. Default = 'WNN'

result_name

Default = 'theta_weighted_matrix'

Value

A multiomics integration result (e.g. theta_weighted_matrix from WNN)

See also

Other multiomics accessor functions: getMultiomics(), setMultiomics(), set_multiomics()

Other functions to get data from giotto object: getCellMetadata(), getDimReduction(), getExpression(), getFeatureInfo(), getFeatureMetadata(), getGiottoImage(), getMultiomics(), getNearestNetwork(), getPolygonInfo(), getSpatialEnrichment(), getSpatialGrid(), getSpatialLocations(), getSpatialNetwork()

Examples

g <- GiottoData::loadGiottoMini("visium")
#> 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
g <- setMultiomics(
    gobject = g, result = matrix(rnorm(100), nrow = 10),
    spat_unit = "cell", feat_type = "rna_protein"
)

get_multiomics(gobject = g, spat_unit = "cell", feat_type = "rna_protein")
#>              [,1]        [,2]        [,3]       [,4]       [,5]        [,6]
#>  [1,]  2.35584224  0.60109578  0.21107021 -0.1929415 -0.4518673 -0.29697270
#>  [2,] -0.07829679  0.09118194 -1.10175805  1.2685203  0.2796521  0.13122693
#>  [3,] -2.48334004 -0.32197855  0.39341368  1.6365113 -0.9323407 -1.56495310
#>  [4,]  0.40703514 -2.12245121  1.82474216 -0.7338841  0.4217614 -0.82422792
#>  [5,] -2.09087675 -0.34599898  1.26347435 -1.1241179  0.8055708  1.73397408
#>  [6,] -0.92110647 -0.48001955  1.68331051 -0.4216800 -0.7100369 -1.63798556
#>  [7,]  0.59907492 -0.42998550  0.95805295  0.4735953  0.3198127  0.40419912
#>  [8,] -0.43413197 -2.07498956  1.60617521  0.9768600  0.9921510  0.08658439
#>  [9,]  0.83620429  0.11144165  0.07428736 -0.3543777 -0.4675122 -0.45354911
#> [10,] -0.72578170 -1.15421265  1.97654017 -0.6908579 -0.2283285 -0.54641552
#>              [,7]        [,8]        [,9]       [,10]
#>  [1,] -0.01955325 -1.84926159  0.89130758 -2.70348138
#>  [2,] -0.46762272  0.56145707  1.62758122  0.29038123
#>  [3,] -0.16431026 -0.34883770 -1.23260939 -0.68073576
#>  [4,]  1.69912784 -0.13678616  0.68610440  0.31861027
#>  [5,] -1.14369864 -1.19301887 -2.45123127 -0.69780454
#>  [6,] -0.12154774  0.03095702 -1.89533742  1.26014919
#>  [7,] -0.29105927  0.23291895  0.09237754  1.27863214
#>  [8,] -0.24844333 -1.33143153 -0.39016194  1.36949166
#>  [9,] -0.11181289 -0.46128145  1.60620252  0.01060681
#> [10,]  0.23792348  0.08372638 -0.60965213 -0.67390639