euclidean_linker {Bioi}

Return the group number for each localization.

Description

Group PALM/iPALM localizations based on their physical separation distance

Usage

euclidean_linker(
  input,
  critDist,
  use_prog_bar = TRUE,
  run_parallel = FALSE,
  num_cores = NULL,
  partition_req = 5000,
  parallel_call_depth = 3,
  ...
)

Arguments

input

A numeric matrix where each row is a localization and each column is a spatial axis.

critDist

The critical distance for which localizations nearer than this distance are deemed part of the same group.

use_prog_bar

TRUE/FALSE indicating whether a progress bar should be used. This is only available when run_parallel is FALSE.

run_parallel

TRUE/FALSE indicating whether operations should be performed in parallel. This is only valid if partitioning is performed.

num_cores

The number of cores to use if running in parallel.

partition_req

The minimum number of points required to create a new partition.

parallel_call_depth

The number of levels of partitioning that should be performed before terminating calls to run operations in parallel. The number of threads opened when running in parallel is equal to 2^(parallel_call_depth)*num_cores.

...

Additional parameters passed to euclidean_linker (i.e. finding_blobs).

Details

PALM/iPALM data results in a list of spatial coordinates for fluorophore localizations. This function groups nearby localizations if they are within the provided critical distance from each other.

Author(s)

Zach Colburn

Examples

# Generate random data.
#set.seed(10)
#input <- as.matrix(data.frame(x=rnorm(10),y=rnorm(10)))

# Perform linking.
#euclidean_linker(input, 0.4)