Description Usage Arguments Value Examples
Extract the distance to each nearest neighbor for specified cell-types, normalized by downsampling each cell-type to the same size (the smallest population from among the specified markers), calculates for a single specified sample
| 1 2 3 4 5 6 7 8 | normal_nearest_neighbor_sample(sample_name, data, markers, n_resamples = 500,
  minimum_cells = 50, quantiles = c(0.05, 0.25, 0.5, 0.75, 0.95),
  grouped_sample = TRUE)
## S4 method for signature 'character,ImageSet'
normal_nearest_neighbor_sample(sample_name, data,
  markers, n_resamples = 500, minimum_cells = 50, quantiles = c(0.05,
  0.25, 0.5, 0.75, 0.95), grouped_sample = TRUE)
 | 
| sample_name | string name of the sample | 
| data | IrisSpatialFeatures ImageSet object | 
| markers | vector of marker names to use | 
| n_resamples | number of times to resample each frame (default:500) | 
| minimum_cells | smallest number of cells to consider a frame (default:50) | 
| quantiles | vector of numeric fractions to include in vector to show the mean distance calculated across resamplings (default:c(0.05,0.25,0.5,0.75,0.95)) | 
| grouped_sample | TRUE/FALSE group samples together (default:TRUE) | 
data.frame
| 1 2 3 | #loading pre-read dataset
dataset <- IrisSpatialFeatures_data
normal_nearest_neighbor_sample("MEL2",dataset,c("SOX10+ PDL1+","SOX10+ PDL1-"),10)
 | 
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