Introduction

Detecting temporal signals of a phylogenetic tree is crucial for estimating divergence times and ccan also serve as a data quality control measure before applying molecular clock models. The shinyTempSignal package implemntes temporal signal analysis under both strict and relaxed molecular clock assumptions and allows exploring temporal signals across the entire tree as well as within different lineages.

ShinyTempSignal allows regression analysis of various types of data, including measurable biological traits and statistical values obtained from evolutionary analysis. Such a versatile regression analysis is highly beneficial for discovering potential evolutionary patterns and addressing biological questions.

Implementing using R shiny, shinyTempSignal provides an interactive interface that allows users to visualize analysis results in real-time and explore data easily.

If you use shinyTempSignal in published research, please cite the following paper:

Installation

shinyTempSignal is available in CRAN and user can use the following command to install it:

install.packages("shinyTempSignal")

Run the shiny application

After loading the package, users can use the run_shinyTempSignal() command to launch the shiny application.

library(shinyTempSignal)
run_shinyTempSignal()

Interactive Web Interface

Tree structure exploration panel

Exploring tree structure. Users need to upload a tree file and a corresponding regular expression to extract sampling dates from tip labels through steps (1-6); users can modify the tree plot appearance (7-9) and select using temporal or phylogenetic signals for detecting outliers (10) which will be shown in a different color of tip points; different panels (11-14) can be selected to present different analysis results.
Exploring tree structure. Users need to upload a tree file and a corresponding regular expression to extract sampling dates from tip labels through steps (1-6); users can modify the tree plot appearance (7-9) and select using temporal or phylogenetic signals for detecting outliers (10) which will be shown in a different color of tip points; different panels (11-14) can be selected to present different analysis results.

Sample date panel

Exploring sampling dates. This panel is used to present the sampling dates extracted from the tip labels of the tree and the divergence from the tip to the root will also be calculated.
Exploring sampling dates. This panel is used to present the sampling dates extracted from the tip labels of the tree and the divergence from the tip to the root will also be calculated.

Temporal signal panel

Exploring temporal signal. This panel displays the root-to-tip regression.It is divided into two sections. For the upper portion(1), users can interact with the following functionalities: Clicking the autodel button will delete outliers automatically, and clicking the Reset button will restore the original tree. Users can choose an interesting clade by entering a selected node number in the node text box. The regression equation is displayed in the regression plot, and the corresponding statistics including the intercept, slope, and R-squared will be presented in a table next to the plot. As for the lower portion(2), users can simultaneously explore temporal signals by inputting multiple node numbers separated by commas.
Exploring temporal signal. This panel displays the root-to-tip regression.It is divided into two sections. For the upper portion(1), users can interact with the following functionalities: Clicking the autodel button will delete outliers automatically, and clicking the Reset button will restore the original tree. Users can choose an interesting clade by entering a selected node number in the node text box. The regression equation is displayed in the regression plot, and the corresponding statistics including the intercept, slope, and R-squared will be presented in a table next to the plot. As for the lower portion(2), users can simultaneously explore temporal signals by inputting multiple node numbers separated by commas.

Phylogenetic signal panel

Exploring phylogenetic signal. This panel works if users upload corresponding external data. It is also divided into two parts. For the upper section (1), it conducts phylogenetic signal analysis similar to temporal signal analysis. Users can select variables for regression analysis. With the chosen phylogenetic signals, users can infer relationships between them (3), while controlling for phylogenetic signals using methods such as Phylogenetic Independent Contrast (PIC) or Phylogenetic Generalized Least Squares (PGLS). As for the lower section (3), users can similarly input multiple nodes to simultaneously analyze multiple subtrees for phylogenetic signal exploration.
Exploring phylogenetic signal. This panel works if users upload corresponding external data. It is also divided into two parts. For the upper section (1), it conducts phylogenetic signal analysis similar to temporal signal analysis. Users can select variables for regression analysis. With the chosen phylogenetic signals, users can infer relationships between them (3), while controlling for phylogenetic signals using methods such as Phylogenetic Independent Contrast (PIC) or Phylogenetic Generalized Least Squares (PGLS). As for the lower section (3), users can similarly input multiple nodes to simultaneously analyze multiple subtrees for phylogenetic signal exploration.