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"
)
See also
Other multiomics accessor functions:
getMultiomics()
,
setMultiomics()
,
set_multiomics()
Other functions to get data from giotto object:
getDimReduction()
,
getExpression()
,
getFeatureInfo()
,
getGiottoImage()
,
getMultiomics()
,
getNearestNetwork()
,
getPolygonInfo()
,
getSpatialEnrichment()
,
getSpatialGrid()
,
getSpatialLocations()
,
getSpatialNetwork()
,
get_NearestNetwork()
,
get_dimReduction()
,
get_feature_info()
,
get_giottoImage()
,
get_polygon_info()
,
get_spatialGrid()
,
get_spatialNetwork()
,
get_spatial_enrichment()
,
get_spatial_locations()
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
#> checking default envname 'giotto_env'
#> a system default python environment was found
#> Using python path:
#> "/usr/share/miniconda/envs/giotto_env/bin/python"
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,] -0.1698655 -1.24095435 -2.7800737 -1.5206390 -2.5197112 0.47131362
#> [2,] 1.1884979 1.47605219 -1.9719497 1.7008620 -1.1675388 -0.05642605
#> [3,] -0.6211862 -0.07589098 -0.4848200 -0.4662269 -0.7923482 1.19142146
#> [4,] -0.4248148 0.62842700 -1.3848879 -0.3168777 -0.3003550 -0.02745457
#> [5,] -1.2693983 0.19674511 -0.1762610 -1.2131392 0.1794639 0.88144485
#> [6,] -0.2533625 0.08158049 0.2596137 0.2466786 -0.9374372 -3.09168198
#> [7,] -0.1116180 -0.89830298 -0.2510197 0.1118254 1.4479660 1.12917805
#> [8,] -0.1315426 -0.61990929 -1.0445444 -1.0078516 1.3361280 1.96047642
#> [9,] 0.8725992 -1.06214909 -2.0920704 1.2416995 0.4995538 0.24592419
#> [10,] -0.1657629 0.78311754 -0.5391583 1.3815616 -2.7557557 -0.43052706
#> [,7] [,8] [,9] [,10]
#> [1,] -0.28259708 -0.9525677 -0.61461492 0.01302273
#> [2,] -0.37221254 -0.4087357 -0.87151065 1.04067074
#> [3,] 0.18263134 -2.2371918 -0.50174591 0.48370651
#> [4,] 0.06055847 1.6845247 0.61345388 -1.38514216
#> [5,] -0.28844587 0.8478142 -2.27293071 -0.98822934
#> [6,] 1.40416927 -1.4393261 -0.02903636 -0.81254630
#> [7,] 1.96437541 0.7074581 -1.31878087 -0.03695966
#> [8,] -1.76916228 2.4144420 -1.59245568 0.12226510
#> [9,] 0.11502054 -0.9043406 -0.15879473 -0.74855108
#> [10,] -0.47298787 0.4745312 0.39397965 0.09353390