Package 'frapplot'

Title: Automatic Data Processing and Visualization for FRAP
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>.
Authors: Guanqiao Ding <[email protected]>
Maintainer: Guanqiao Ding <[email protected]>
License: MIT + file LICENSE
Version: 0.1.3
Built: 2024-10-31 20:26:52 UTC
Source: https://github.com/guanqiaoding/frapplot

Help Index


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 frapprocess().

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))