In Norisama/VFtree: visualization of combined Virulence Factors and Phylogenetic Tree

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
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Overview

VFtree is an R-package for visualization of Virulence Factors and Phylogenetic Tree of bacterial pan-genome.The goal of VFtree is to build a phylogenetic Tree based on the tree data and the presence/absence sheet of the gene/factors to plot a circular prepresentation of the matched information. This package provide a pan-genome approach to easily illustrate the data among strains at the species level.

Getting Help

Create an issue on github https://github.com/Norisama/VFtree/issues

Installation

VFtree is currently being hosted on GitHub at https://github.com/Norisama/VFtree The most up-to-date version of VFtree can be easily installed directly within R, using the devtools package.

# install devtools, if necessary:
install.packages("devtools", dep=TRUE)
library(devtools)

# install VFtree from github:
install_github("Norisama/VFtree", build_vignettes = TRUE, force=TRUE)
library(VFtree)

library(VFtree, quietly = TRUE, verbose=FALSE)

To open the vignette from within R, run browseVignettes and click on the HTML hyperlink:

browseVignettes("VFtree")

Getting started with VFtree

VFtree generally works as a stand along package, the only package that closely works with VFtree is ggplot2, please see the ggplot2 package vignette:

> library(ggplot2)
> browseVignettes("ggplot2")

Here we will go over the functions and arguments used within the VFtree package. We will use a simple example dataset available within VFtree to illustrate the code involved.

Require Data

To generate a circular tree + ring plot using VFtree, the following data is required:

A phylogenetic tree : An newick file contains the information of the phylogenetic tree. Tip labels are required and must correspond to both the row labels of the VF presence/absence data matrix and the names of the phenotypic variable.

An Pathogenecity Potentialtable Table (VFtable) : A csv file that have the same number of strains as the input phylogenetic tree, the row named id should contain the same names as the tip.labels of above tree.

Example Data

We will use the data stored within VFtree as an examples throughout this section of the vignette. We load the data using the data function and examine its structure below:

data("VF100")
data("Tree100")

Create plot with combinedPlot()

## Load example data:
data(VF25_2)
data(Tree25)

## Plot tree showing phenotype:
sampleTreePlot <- combinedPlot(VF25_2, Tree25, inputNum = 25)

library(png)
library(grid)
img <- readPNG("vignettes_images/image1.png")
grid.raster(img)

## Load example data:
data(VF150)
data(Tree150)

## Plot tree showing phenotype:
sampleTreePlot <- combinedPlot(VF150, Tree150, inputNum = 150)

library(png)
library(grid)
img <- readPNG("vignettes_images/image2.png")
grid.raster(img)

Shiny app

VFtree is also supported as a shiny app. Find it online at link or execute runVFtreeApp() in the console.

runVFtreeApp()

Liscencing

VFtree is liscenced under the MIT liscence. If you use VFtree published research, please cite:

Zhu, B (2019). VFtree. R. Retrieved from https://github.com/Norisama/VFtree

References

Zhu, B (2019). VFtree. https://github.com/Norisama/VFtree

Silva, A (2019). anjalisilva/TestingPackage https://github.com/anjalisilva/TestingPackage

H. Wickham. ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag New York, 2016. https://ggplot2.tidyverse.org/

Norisama/VFtree documentation built on Dec. 8, 2019, 9:28 a.m.