| Version: | 1.4.1 |
| Date: | 2024-05-27 |
| Title: | Shiny Apps for Lateral Flow Assays |
| Author: | Filip Paskali 
[aut, cre],
Weronika Schary
[aut],
Matthias Kohl
[aut] |
| Maintainer: | Filip Paskali <Filip.Paskali@gmail.com> |
| Description: | Shiny apps for the quantitative analysis of images from lateral flow assays (LFAs). The images are segmented and background corrected and color intensities are extracted. The apps can be used to import and export intensity data and to calibrate LFAs by means of linear, loess, or gam models. The calibration models can further be saved and applied to intensity data from new images for determining concentrations. |
| License: | LGPL-3 |
| Depends: | R (≥ 4.0.0) |
| Imports: | stats, utils, graphics, methods, mgcv, shiny, shinyjs, shinythemes, shinyFiles, shinyMobile (≥ 0.9), EBImage, DT, ggplot2, fs |
| Suggests: | knitr, rmarkdown, remotes |
| VignetteBuilder: | knitr |
| Encoding: | UTF-8 |
| URL: | https://github.com/fpaskali/LFApp |
| BugReports: | https://github.com/fpaskali/LFApp/issues |
| NeedsCompilation: | no |
| Packaged: | 2024-05-27 13:48:43 UTC; filip |
| Repository: | CRAN |
| Date/Publication: | 2024-05-27 14:10:02 UTC |
Shiny Apps for Lateral Flow Assays.
Description
Shiny apps for the quantitative analysis of images from lateral flow assays (LFAs). The images are segemented and background corrected and color intensities are extracted. The apps can be used to import and export intensity data and to calibrate LFAs by means of linear, loess, or gam models. The calibration models can further be saved and applied to intensity data from new images for determining concentrations.
Details
library(LFApp)
Author(s)
Filip Paskali, Weronika Schary, Matthias Kohl
Maintainer: Filip Paskali Filip.Paskali@gmail.com
Run Analysis Shiny Apps
Description
Function start the Analysis Shiny App.
Usage
run_analysis()
run_cal()
run_core()
run_quan()
run_mobile_analysis()
run_mobile_cal()
run_mobile_core()
run_mobile_quan()
Details
The functions start the various shiny apps included in the package.
Value
An object that represents the app. Printing the object will run the app.
Author(s)
Filip Paskali F.Paskali@hs-furtwangen.de, Weronika Schary W.Schary@hs-furtwangen.de, Matthias Kohl Matthias.Kohl@stamats.de
Examples
if(interactive()){
## start full analysis app
run_analysis()
## start mobile version of full analysis app
run_mobile_analysis()
}
Li Thresholding Algorithm
Description
The function computes a background theshold of an image by using Li's iterative minimum cross entropy method.
Usage
threshold_li(image, tolerance = NULL, initial_guess = NULL, iter_callback = NULL)
Arguments
image |
object of class |
tolerance |
optional tolerance threshold. |
initial_guess |
optional initial value for the minimization. |
iter_callback |
optional function applied to the minimizsation criterion. |
Details
For more details about the method see Li and Lee (1993) as well as Li and Tam (1998).
Value
numeric vector with the computed threshold.
Author(s)
Filip Paskali Filip.Paskali@gmail.de
References
C.H. Li and C.K. Lee (1993). Minimum cross entropy thresholding. Pattern Recognition 26 (4): 617-25. https://doi.org/10.1016/0031-3203(93)90115-D.
C.H. Li and P.K.S. Tam (1998). An iterative algorithm for minimum cross entropy thresholding. Pattern Recognition Letters 19 (8): 771-76. https://doi.org/10.1016/S0167-8655(98)00057-9.
Examples
library(EBImage)
x <- readImage(system.file("images", "sample.TIF", package="LFApp"))
threshold_li(x)
Triangle Thresholding Algorithm
Description
The function computes a background theshold of an image using the triangle algorithm.
Usage
triangle(image, offset = 0.2, breaks = 256)
Arguments
image |
object of class |
offset |
numeric, additional offset added to the computed threshold. |
breaks |
integer, number of breaks used in the histogram. |
Details
The Triangle method is based on the histogram of the intensities. Based on the range of intensities and the maximum peak a threshold is determined. The method was proposed in Zack et al. (1977).
Value
numeric vector with the computed threshold.
Author(s)
Matthias Kohl Matthias.Kohl@stamats.de
References
G.W. Zack, W. E. Rogers, and S. A. Latt (1977). Automatic measurement of sister chromatid exchange frequency. The journal of histochemistry and cytochemistry: official journal of the Histochemistry Society 25 (7): 741-53. https://doi.org/10.1177/25.7.70454.
Examples
library(EBImage)
x <- readImage(system.file("images", "sample.TIF", package="LFApp"))
triangle(x)