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Minor updates to documentation for CRAN #22

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Sep 3, 2024
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Minor updates to documentation for CRAN #22

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10 changes: 5 additions & 5 deletions R/methods-TxpResult-plot.R
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Expand Up @@ -23,13 +23,13 @@
#' when `TRUE`
#' @param ... Passed to [pieGridGrob] when plotting ToxPi and to pointsGrob
#' when plotting ranks
#' @param ncol Number of columns for [ggplot2] ToxPi profiles
#' @param ncol Number of columns for ggplot2 ToxPi profiles
#' @param bgColor,borderColor,sliceBorderColor,sliceValueColor,sliceLineColor
#' Various color options when creating [ggplot2] ToxPi profiles. Set to NULL
#' Various color options when creating ggplot2 ToxPi profiles. Set to NULL
#' for no color
#' @param showMissing Boolean for coloring data missingness in [ggplot2]
#' @param showMissing Boolean for coloring data missingness in ggplot2
#' ToxPi profiles
#' @param showCenter Boolean for showing inner circle in [ggplot2] ToxPi
#' @param showCenter Boolean for showing inner circle in ggplot2 ToxPi
#' profiles. When set to False overrides showMissing
#'
#' @details
Expand All @@ -44,7 +44,7 @@
#' If the labels are running of the device, the top or bottom margins can be
#' increased with the `margins` parameter.
#'
#' ToxPi profiles can also be plotted using the [ggplot2] package.
#' ToxPi profiles can also be plotted using the ggplot2 package.
#'
#' @template roxgn-loadExamples
#' @template roxgn-calcTxpModel
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10 changes: 5 additions & 5 deletions man/TxpResult-plot.Rd
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4 changes: 2 additions & 2 deletions vignettes/introduction.Rmd
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Expand Up @@ -46,7 +46,7 @@ This document introduces ToxPi and describes how to use the `toxpiR` package to

## What is ToxPi?

The Toxicological Prioritization Index (ToxPi) is a statistical modeling framework that allows transparent integration and visualization of data across disparate sources (i.e. multimodal or multiscale information). This framework aggregates related features into scored ‘slices’, rescales individual slice scores to range 0–1, and then develops an overall score for each sample using a weighted model. The slice weights can be interpreted as the "importance" of categorized features when predicting sample scores and associated ranks. The resulting scores for each sample are visualized as ToxPi profiles (see image below). Slice weights are represented as the arc-width, slice scores are represented as the radius, and the overall sample scores are represented by the combination of slice weights and radii. These visualizations allow for quick comparison of overall feature importance, feature impacts driving a specific sample, relative impact ranking of common features between samples, and overall ranking between samples. As a flexible method capable of integrating data from any source, it has been [applied](https://scholar.google.com/scholar?start=5&hl=en&as_sdt=0,34&sciodt=0,34&cites=14315759707117183281,8409987751811922970,6830405381891567320,6660731247750930378,6264826653350493071,6008919238370157052,5228323847718230279,14470107422640831138) to problems in several different fields. Additional information is linked from [toxpi.org](https://toxpi.org).
The Toxicological Prioritization Index (ToxPi) is a statistical modeling framework that allows transparent integration and visualization of data across disparate sources (i.e. multimodal or multiscale information). This framework aggregates related features into scored ‘slices’, rescales individual slice scores to range 0–1, and then develops an overall score for each sample using a weighted model. The slice weights can be interpreted as the "importance" of categorized features when predicting sample scores and associated ranks. The resulting scores for each sample are visualized as ToxPi profiles (see image below). Slice weights are represented as the arc-width, slice scores are represented as the radius, and the overall sample scores are represented by the combination of slice weights and radii. These visualizations allow for quick comparison of overall feature importance, feature impacts driving a specific sample, relative impact ranking of common features between samples, and overall ranking between samples. As a flexible method capable of integrating data from any source, it has been applied to problems in several different fields. Additional information is linked from [toxpi.org](https://toxpi.org).

<center>
![](embeddedFigures/txp_explain1.png){width=700px}
Expand Down Expand Up @@ -230,7 +230,7 @@ Two paths exist for visualization, **ggplot** methods and **grid** methods. The

<div >
<h3>ggPlot</h3>
* Examples shown in this vignette produce a "look-and-feel" that is closer to the graphics output of the familiar [ToxPi GUI](www.toxpi.org)
* Examples shown in this vignette produce a "look-and-feel" that is closer to the graphics output of the familiar [ToxPi GUI](https://toxpi.org)
* Aesthetics are easy to customize
* Includes missing data visuals (center circle à la ToxPi GUI output)
</div>
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