1Understand flux versus time analysis overview--:--
2Create info.txt file with treatment data00:14
3Save info file as tab-delimited text01:08
4Load and source fluxvstime.r script01:40
5Enter number of time points02:04
6Review generated summary graph output02:26
7Examine organized data and perform statistics02:52
BotanyBio-protocol VideoCitable · DOI
Flux vs. time
DOI: 10.21769/BioProtoc.v268
Protocol
Difficulty
intermediate
Steps
1
Understand flux versus time analysis overview
The video introduces the flux-versus-time R script used to estimate dose and time-dependent responses based on red to green fluorescent protein ratios. This script will analyze experimental data and generate visualizations of the results.
▶ --:--
2
Create info.txt file with treatment data
Create a two-column tab-delimited text file in Excel with treatment names and start times. The file must be named info.txt and saved in the correct format, as the data must match the experimental file names exactly.
▶ 00:14
3
Save info file as tab-delimited text
Use File > Save As to save the Excel spreadsheet as a tab-delimited .txt file named info. Ensure proper formatting to avoid auto-formatting issues by converting to text format if needed.
▶ 01:08
4
Load and source fluxvstime.r script
In RStudio, select the fluxvstime.r script from the R scripts folder and use Code > Source to load the file. This will initiate the analysis workflow.
▶ 01:40
5
Enter number of time points
When prompted by the script, enter the number of time points from the experiment. In this example, three time points were scanned, so enter 3 and press Enter.
▶ 02:04
6
Review generated summary graph output
The script generates a summary graph showing normalized fluorescent protein ratios over time in hours, normalized to the vehicle control. The output includes both overall and per-seedling data summaries.
▶ 02:26
7
Examine organized data and perform statistics
Review the organized data in the generated summary file. Perform appropriate statistical tests using R or other software like Origin, JMP, or GraphPad Prism based on your specific experimental design.
▶ 02:52
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