Get multiomics integration results

Get a multiomics integration result from a Giotto object

Usage

getMultiomics(
  gobject = NULL,
  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: get_multiomics(), setMultiomics(), set_multiomics()

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

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"
)

getMultiomics(gobject = g, spat_unit = "cell", feat_type = "rna_protein")
#>             [,1]        [,2]        [,3]        [,4]        [,5]        [,6]
#>  [1,]  0.7606355  1.27953045 -0.40336354  0.36599423  1.55204487 -1.54728667
#>  [2,] -0.2548313 -1.06048935 -0.53405902  0.51535775  0.01291856  0.15626219
#>  [3,]  1.4343212 -0.47468303 -0.09874618 -0.07226779 -0.06884171 -1.04072862
#>  [4,]  1.2481823 -1.56499623 -0.88919767 -0.09200505  0.45537367 -0.11467107
#>  [5,]  1.9995063  0.32106942 -0.68903907  0.35919294  0.69329514 -0.09855060
#>  [6,] -1.5652562  0.18177153  0.57772371 -0.14658417  0.13482743  0.58468086
#>  [7,]  0.6744919  0.03621533  0.06415506  0.78382409 -0.59147264  1.81903015
#>  [8,]  1.1597817  1.19094521 -0.08329305  0.43823326  0.43063156  0.02010859
#>  [9,]  0.3360061 -1.21327908 -0.69473991 -0.31838798 -0.64506122 -1.36697635
#> [10,] -0.3694493 -2.75973852  2.10970820 -0.30934519  1.12982851  0.62464581
#>              [,7]       [,8]       [,9]       [,10]
#>  [1,] -0.15323120 -0.2880079  0.1504491  0.15113150
#>  [2,] -0.21303912 -0.9015857 -0.4378595 -0.47971217
#>  [3,]  0.02506200  1.4179229  0.9804014  1.37373240
#>  [4,]  1.96181765 -0.5921200 -0.8170110  0.45401113
#>  [5,] -0.29303855 -0.8486003 -0.2404877  0.66119987
#>  [6,]  0.58223044 -1.5604810  0.7612364 -0.33980112
#>  [7,]  0.29278767  0.3805031  0.7141979  0.46630398
#>  [8,] -0.04028543  0.1234657  0.6746769 -0.06975380
#>  [9,] -0.21435764 -0.6939894 -0.9004623 -0.09697841
#> [10,]  1.54624238  1.3994524 -0.7682120  0.92150179