| Type: | Package |
| Title: | Automatic Data Processing and Visualization for FRAP |
| Version: | 0.1.3 |
| Author: | Guanqiao Ding <gding16@gmail.com> |
| Maintainer: | Guanqiao Ding <gding16@gmail.com> |
| Description: | Automatically process Fluorescence Recovery After Photobleaching (FRAP) data and generate consistent, publishable figures. Note: this package does not replace 'ImageJ' (or its equivalence) in raw image quantification. Some references about the methods: Sprague, Brian L. (2004) <doi:10.1529/biophysj.103.026765>; Day, Charles A. (2012) <doi:10.1002/0471142956.cy0219s62>. |
| Depends: | R (≥ 2.10) |
| Imports: | grDevices, graphics, stats, utils |
| BugReports: | https://github.com/GuanqiaoDing/frapplot/issues |
| URL: | https://github.com/GuanqiaoDing/frapplot |
| License: | MIT + file LICENSE |
| Encoding: | UTF-8 |
| LazyData: | true |
| RoxygenNote: | 6.1.1 |
| NeedsCompilation: | no |
| Packaged: | 2019-01-03 06:32:56 UTC; dinggq |
| Repository: | CRAN |
| Date/Publication: | 2019-01-08 16:30:10 UTC |
Example dataset
Description
Example dataset
Usage
example_dataset
Format
A list of three matrices: each contains FRAP data for a control or experimental group. For each matrix, nrow = time_points + 1, ncol = sample size.
Exclude samples from the dataset
Description
If certain samples are of poor quality, use this function to exclude them from the dataset.
Usage
exclude(ds, group, cols)
Arguments
ds |
Name of the dataset. |
group |
Name of the group from which to exclude certain samples. |
cols |
A vector of numbers specifying the column(s) to exclude. |
Value
Modified dataset in the same format.
Examples
ds <- exclude(example_dataset, group = "mut1", cols = c(1,3))
Plot FRAP data of two selected groups
Description
Plot FRAP data of any two groups (e.g. control and mutant) in a consistent and publishable format.
Usage
frapplot(path, control, mutant, info)
Arguments
path |
Path of the output directory |
control |
Name of the control. |
mutant |
Name of the mutant. |
info |
Returned information from |
Examples
info <- frapprocess(example_dataset, seq(0, 145, 5))
frapplot(tempdir(), "control", "mut2", info)
Process FRAP data
Description
Normalize and analyze FRAP data. Perform non-linear regression and calculate ymax, ymin, k, halftime, tau, total_recovery, total_recovery_sd.
Usage
frapprocess(ds, time_points)
Arguments
ds |
A dataset that contains FRAP data for multiple experiment groups |
time_points |
A vector of time points (in second) that the experiment uses, e.g. 0, 5, 10, .... |
Value
A list of results:
$time_points: a vector of time points
$summary: summary of the regression
$sample_means: a matrix of sample means, nrow = num of time points, ncol = sample size
$sample_sd: a matrix of standard deviations, nrow = num of time points, ncol = sample size
$model: a list of models for each group from the non-linear regression
$details: details of the regression for each group
Examples
info <- frapprocess(example_dataset, seq(0, 145, 5))