Wrapper for the different Giotto object processing functions
giotto object
additional parameters to filterGiotto
additional parameters to normalizeGiotto
additional parameters to addStatistics
additional parameters to adjustGiottoMatrix; set to NULL if not required
be verbose (default is TRUE)
giotto object
See filterGiotto
, normalizeGiotto
,
addStatistics
, and adjustGiottoMatrix
. For more
information about the different parameters in each step. If you do not
provide them it will use the default values. If no adjustment is required,
adjust_params must be set to NULL
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
#> cell_spatInfo_spatVector.shp
#> cell
#>
#> 3.2 read Giotto spatial centroid information
#> cell
#>
#> 3.3 read Giotto spatial overlap information
#> No overlaps were found, overlap loading will be
#> skipped
#>
#> 4. read Giotto image information
#> a giotto python environment was found
#> Using python path:
#> "/Users/yuanlab/Library/r-miniconda/envs/giotto_env/bin/pythonw"
processGiotto(gobject = g,
adjust_params = list(covariate_columns = "leiden_clus"))
#> 1. start filter step
#> completed 1: preparation
#> completed 2: subset expression data
#> completed 3: subset spatial locations
#> completed 4: subset cell metadata
#> completed 5: subset feature metadata
#> completed 6: subset spatial network(s)
#> completed 7: subsetted dimension reductions
#> completed 8: subsetted nearest network(s)
#> completed 9: subsetted spatial enrichment results
#> for cell
#> --> cell found back in polygon layer: cell
#> completed 10: subsetted spatial information data
#>
#> Feature type: rna
#> Number of cells removed: 2 out of 624
#> Number of feats removed: 93 out of 634
#> 2. start normalization step
#>
#> first scale feats and then cells
#> > normalized already exists and will be replaced with new values
#> > scaled already exists and will be replaced with new values
#> 3. start cell and gene statistics step
#> feat statistics has already been applied once; overwriting
#> cells statistics has already been applied once; overwriting
#> 4. start adjusted matrix step
#> An object of class giotto
#> >Active spat_unit: cell
#> >Active feat_type: rna
#> [SUBCELLULAR INFO]
#> polygons : cell
#> [AGGREGATE INFO]
#> expression -----------------------
#> [cell][rna] raw normalized scaled custom
#> spatial locations ----------------
#> [cell] raw
#> spatial networks -----------------
#> [cell] Delaunay_network spatial_network
#> spatial enrichments --------------
#> [cell][rna] cluster_metagene DWLS
#> dim reduction --------------------
#> [cell][rna] pca custom_pca umap custom_umap tsne
#> nearest neighbor networks --------
#> [cell][rna] sNN.pca custom_NN
#> attached images ------------------
#> images : alignment image
#>
#>
#> Use objHistory() to see steps and params used