SMOLR_FEATURES: Get feature analysis from kernel density estimation...

In ErasmusOIC/SMoLR: Single Molecule Localization Microscopy visualization and analysis in R

Get feature analysis from kernel density estimation (SMoLR_KDE) data

Description

Returns a feature analysis of a kernel density estimation.

Usage

smlmr_features(x, filter = NULL, filter_value = NULL)

Arguments

x	A single molecule kernel density estimation (data type must be smolr_kde)
filter	Name of a feature to filter for. The result will be in the parameters
filter_value	Value to filter, counts features that have a value higher than filter_value

Details

Feature analysis as present in the EBImage package

Value

features	A table of features measured per channel
parameters	number of features per channel and number of filtered features

Note

Features can be applied tot the kernel density estimation images parameters using the apply_filtered_features function from the SMoLR package

Author(s)

Optical Imaging Centre ErasmusMC Rotterdam

References

https://rdrr.io/bioc/EBImage/man/computeFeatures.html

Examples

test_kde <- SMOLR_KDE(c(200,150,400,210),c(200,300,400.5,239),ch=c(2,3,4,3),threshold=0.01)

test_features <- SMOLR_FEATURES(test_kde)
test_features <- SMOLR_FEATURES(test_kde, filter="x.0.s.area", filter_value=1000)

ErasmusOIC/SMoLR documentation built on July 27, 2023, 8:05 p.m.