frapprocess: Process FRAP data

In frapplot: Automatic Data Processing and Visualization for FRAP

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))

frapplot documentation built on May 1, 2019, 11:16 p.m.