In ErikEnsminger/FastRPA: Analysis tool for root length measurements
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-",
out.width = "100%"
)
FastRPA
Description
The goal of FastRPA is to speed up the interpretation time of root length measurement data.
Manually selecting, organizing and analysing data of potentially thousands of root measurements are time consuming. FastRPA enables a semi-automatic solution, enabling the user to select root length measurements from the multiple output file of FastIDR imageJ tool, thereby centralizing data from numerous data files. This package was developed using R version 4.1.1 (2021-08-10, Platform: x86_64-apple-darwin17.0 (64-bit) and Running under: macOS Big Sur 11.4
Installation
You can install the development version of FastRPA like so:
require("devtools")
devtools::install_github("ErikEnsminger/FastRPA", build_vignettes = TRUE)
library("FastRPA")
Shiny app:
FastRPA::runFastRPA()
Overview
ls("package:FastRPA")
data(package = "FastRPA")
Look into the vignettes for a specific example process flow:
browseVignettes("FastRPA")
An overview of the pacakge is illustrated below.
FastRPA contains 3 functions: filterData, analyseRootData, and createRootBarG.
\n
filterData is the first function in the process. As input for filterData the user must specify a column index of the root measurements to be extracted, the .csv input file (Fig.1 A.i. and Fig.1 A.ii.) , an output file, and the Treatment type used on the roots.It will allow the user to select different Root length measurements and the corresponding Gene Lines from a user defined .csv files.
analyseRootData takes in an input file (prefferably the output file from filterData Fig. 1B), the control Treatment, and an output file. analyseRootData will then based on the indciated controlTreatment normalize each of the treatment data and output the data to the desired output file (Fig. 1C).
createRootBarG takes in an input file (the output file from analyseRootData (Fig.1C)). createRootBarG_ creates a bar plot of the specified treatments and their corresponding gene lines (Fig. 1.D).
An overview of the package R functions illustrated below in Figure 1.:
## Contributions
The author of this package is Erik Ensminger. The _*filterData*_ function makes use of split function of the `plyr` R package for binding data frames.
The _*createRootBarG*_ function makes use of the `reshape2` R package for the melting dataframes. In addition, _*createRootBarG*_ function makes use of the `ggplot` R package for plotting the Bar graph of the root length data.
## References
Steipe B., ABC project (.utility 4.07) A Bioinformatics Course: Applied Bioinformatics http://steipe.biochemistry.utoronto.ca/abc/index.php/Bioinformatics_Main_Page
R Core Team (2021). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/
Wickham H (2007). “Reshaping Data with the reshape Package.” *Journal of Statistical Software*, 21(12), 1–20. http://www.jstatsoft.org/v21/i12/.
Wickham H (2011). “The Split-Apply-Combine Strategy for Data Analysis.” *Journal of Statistical Software*, 40(1), 1–29. http://www.jstatsoft.org/v40/i01/.
Wickham H (2016). ggplot2: Elegant Graphics for Data Analysis. *Springer-Verlag* New York. ISBN 978-3-319-24277-4, https://ggplot2.tidyverse.org.
Wickham, H. and Bryan, J. (2019). *R Packages* (2nd edition). Newton, Massachusetts: O’Reilly Media. https://r-pkgs.org/
## Acknowledgements
This package was developed as part of an assessment for 2021 BCB410H: Applied Bioinfor- matics, University of Toronto, Toronto, CANADA.
## Citation for Package
[Ensminger, E. (2021) FastRPA (Root length measurement analysis tool): an R package for organizing, analysing and visualization of plant root length measurement data)
](https://github.com/ErikEnsminger/FastRPA)
ErikEnsminger/FastRPA documentation built on Sept. 29, 2023, 12:35 a.m.
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knitr::opts_chunk$set( collapse = TRUE, comment = "#>", fig.path = "man/figures/README-", out.width = "100%" )
FastRPA
Description
The goal of FastRPA is to speed up the interpretation time of root length measurement data.
Manually selecting, organizing and analysing data of potentially thousands of root measurements are time consuming. FastRPA enables a semi-automatic solution, enabling the user to select root length measurements from the multiple output file of FastIDR imageJ tool, thereby centralizing data from numerous data files. This package was developed using R version 4.1.1 (2021-08-10, Platform: x86_64-apple-darwin17.0 (64-bit) and Running under: macOS Big Sur 11.4
Installation
You can install the development version of FastRPA like so:
require("devtools") devtools::install_github("ErikEnsminger/FastRPA", build_vignettes = TRUE) library("FastRPA")
Shiny app:
FastRPA::runFastRPA()
Overview
ls("package:FastRPA") data(package = "FastRPA")
Look into the vignettes for a specific example process flow:
browseVignettes("FastRPA")
An overview of the pacakge is illustrated below.
FastRPA contains 3 functions: filterData, analyseRootData, and createRootBarG. \n filterData is the first function in the process. As input for filterData the user must specify a column index of the root measurements to be extracted, the .csv input file (Fig.1 A.i. and Fig.1 A.ii.) , an output file, and the Treatment type used on the roots.It will allow the user to select different Root length measurements and the corresponding Gene Lines from a user defined .csv files. analyseRootData takes in an input file (prefferably the output file from filterData Fig. 1B), the control Treatment, and an output file. analyseRootData will then based on the indciated controlTreatment normalize each of the treatment data and output the data to the desired output file (Fig. 1C).
createRootBarG takes in an input file (the output file from analyseRootData (Fig.1C)). createRootBarG_ creates a bar plot of the specified treatments and their corresponding gene lines (Fig. 1.D).
An overview of the package R functions illustrated below in Figure 1.:
## Contributions
The author of this package is Erik Ensminger. The _*filterData*_ function makes use of split function of the `plyr` R package for binding data frames.
The _*createRootBarG*_ function makes use of the `reshape2` R package for the melting dataframes. In addition, _*createRootBarG*_ function makes use of the `ggplot` R package for plotting the Bar graph of the root length data.
## References
Steipe B., ABC project (.utility 4.07) A Bioinformatics Course: Applied Bioinformatics http://steipe.biochemistry.utoronto.ca/abc/index.php/Bioinformatics_Main_Page
R Core Team (2021). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/
Wickham H (2007). “Reshaping Data with the reshape Package.” *Journal of Statistical Software*, 21(12), 1–20. http://www.jstatsoft.org/v21/i12/.
Wickham H (2011). “The Split-Apply-Combine Strategy for Data Analysis.” *Journal of Statistical Software*, 40(1), 1–29. http://www.jstatsoft.org/v40/i01/.
Wickham H (2016). ggplot2: Elegant Graphics for Data Analysis. *Springer-Verlag* New York. ISBN 978-3-319-24277-4, https://ggplot2.tidyverse.org.
Wickham, H. and Bryan, J. (2019). *R Packages* (2nd edition). Newton, Massachusetts: O’Reilly Media. https://r-pkgs.org/
## Acknowledgements
This package was developed as part of an assessment for 2021 BCB410H: Applied Bioinfor- matics, University of Toronto, Toronto, CANADA.
## Citation for Package
[Ensminger, E. (2021) FastRPA (Root length measurement analysis tool): an R package for organizing, analysing and visualization of plant root length measurement data)
](https://github.com/ErikEnsminger/FastRPA)
ErikEnsminger/FastRPA documentation built on Sept. 29, 2023, 12:35 a.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.