Run scrublet doublet detection for raw expression. Intended for single cell data
doScrubletDetect(
gobject,
feat_type = NULL,
spat_unit = "cell",
expression_values = "raw",
expected_doublet_rate = 0.06,
min_counts = 1,
min_cells = 1,
min_gene_variability_pctl = 85,
n_prin_comps = 30,
return_gobject = TRUE,
seed = 1234
)giotto object containing expression data
feature type
spatial unit
expression values to use
expected transcriptomes that are doublets. 0.06 is from 10x Chromium guide.
scrublet internal data filtering, min counts found to be considered a cell
scrublet internal data filtering. min cells expressed to be considered a feat
scrublet internal PCA generation. highly variable gene percentile cutoff
number of PCs to use in PCA for detection
return as gobject if TRUE, data.frame with cell_ID if FALSE
If a numeric is provided, then it will be used as a seed. If NULL, no seed will be set.
if return_gobject = FALSE, a data.table cell_ID, doublet scores,
and classifications are returned. If TRUE, that information is appended
into the input giotto object's metadata and the giotto object is
returned.
This function wraps the python package scrublet doi:10.1016/j.cels.2018.11.005
# Should only be done with single cell data, but this is just a
# convenient example.
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 : '/usr/bin/python3'
#> python version : 3.10
#> checking default envname 'giotto_env'
#> a system default python environment was found
#> Using python path:
#> "/usr/bin/python3"
g <- doScrubletDetect(g)
#> Error: package 'scrublet' is not yet installed
#>
#> To install:
#> ## active python env: '/usr/bin/python3'
#> ## python version: 3.10
#> ## restart session then use GiottoClass::set_giotto_python_path() if this is incorrect
#> reticulate::conda_install(envname = '/usr/bin/python3', packages = c('scrublet'), pip = TRUE)
pDataDT(g) # doublet_scores and doublet cols are added
#> cell_ID in_tissue nr_feats perc_feats total_expr leiden_clus
#> <char> <int> <int> <num> <num> <num>
#> 1: AACTCGATGGCGCAGT-1 1 265 41.79811 1057.9308 2
#> 2: GGCTGGCTAGCTTAAA-1 1 279 44.00631 1064.7493 5
#> 3: GACGCCTGTTGCAGGG-1 1 219 34.54259 964.9294 2
#> 4: GAGGGCATCGCGTATC-1 1 294 46.37224 1142.7664 2
#> 5: TCAACACATTGGGTAA-1 1 261 41.16719 1063.3517 2
#> ---
#> 620: GGTAGTGCTCGCACCA-1 1 179 28.23344 768.4749 5
#> 621: AAGCTCGTGCCAAGTC-1 1 195 30.75710 756.0675 5
#> 622: TATTCAATTCTAATCC-1 1 247 38.95899 921.8264 5
#> 623: TTCAAAGTCTCTAGCC-1 1 384 60.56782 916.5929 6
#> 624: TTGAATATGGACTTTC-1 1 380 59.93691 912.3051 6
#> custom_leiden
#> <num>
#> 1: 4
#> 2: 3
#> 3: 3
#> 4: 3
#> 5: 3
#> ---
#> 620: 4
#> 621: 4
#> 622: 4
#> 623: 7
#> 624: 4
dimPlot2D(g, cell_color = "doublet_scores", color_as_factor = FALSE)
#> Error in plot_point_layer_ggplot(ggobject = pl, instrs = instructions(gobject), annotated_DT_selected = annotated_DT_selected, annotated_DT_other = annotated_DT_other, cell_color = cell_color, color_as_factor = color_as_factor, cell_color_code = cell_color_code, cell_color_gradient = cell_color_gradient, gradient_midpoint = gradient_midpoint, gradient_style = gradient_style, gradient_limits = gradient_limits, select_cell_groups = select_cell_groups, select_cells = select_cells, show_other_cells = show_other_cells, other_cell_color = other_cell_color, other_point_size = other_point_size, show_cluster_center = show_cluster_center, show_center_label = show_center_label, center_point_size = center_point_size, center_point_border_col = center_point_border_col, center_point_border_stroke = center_point_border_stroke, label_size = label_size, label_fontface = label_fontface, edge_alpha = edge_alpha, point_size = point_size, point_alpha = point_alpha, point_border_col = point_border_col, point_border_stroke = point_border_stroke, show_legend = show_legend): doublet_scores is not a color or a column name