Installation

Install using BiocManager

We are preparing to submit PhyloProfile to Bioconductor. Once the package is accepted, you can easily install it using BiocManager:

if (!requireNamespace("BiocManager"))
    install.packages("BiocManager")

BiocManager::install("PhyloProfile")

Until then please install the dev version of PhyloProfile from our github repository using devtools.

Install using devtools

To install the dev version from github:

if (!requireNamespace("devtools"))
    install.packages("devtools", repos = "http://cran.us.r-project.org")

devtools::install_github(
    "bionf/PhyloProfile",
    INSTALL_opts = c('--no-lock'),
    build_opts = c('--no-resave-data')
)

Since PhyloProfile comes together with a data packages called PhyloProfileData that contains two demo data sets to illustrate running and analysing phylogenetic profiles using the PhyloProfile tool, you will need to install this data package if you want to use those demo data. (NOTE: PhyloProfileData will be automatically installed together with PhyloProfile whenever PhyloProfile is available in Bioconductor. From then this step will not be needed)

if (!requireNamespace("BiocManager"))
    install.packages("BiocManager")
BiocManager::install(version = '3.10', ask = FALSE)
devtools::install_github(
    "bionf/PhyloProfileData",
    INSTALL_opts = c('--no-lock'),
    build_opts = c('--no-resave-data')
)

For Windows Users:

Please run R as administrator in order to install the libraries into R library path.

In some cases, you need to install bindrcpp before installing PhyloProfile.

install.packages("bindrcpp", repos = "http://cran.us.r-project.org")

devtools::install_github(
    "bionf/PhyloProfile",
    INSTALL_opts = c('--no-lock'),
    build_opts = c('--no-resave-data')
)

Start PhyloProfile GUI tool

library(PhyloProfile)
runPhyloProfile()

Check your web browser, PhyloProfile will be displayed there ;-)

Run PhyloProfile Docker image

A Docker image containing a ready-to-run PhyloProfile GUI tool is available at Docker Hub. If you already have Docker, or if you don't want to install PhyloProfile by yourself, you can retrieve and use this Docker image by following these steps:

Install Docker
Run Docker
Open the terminal and use this command to pull and run the latest version of PhyloProfile image

docker run -p 8080:80 trvinh/phyloprofile

Open a web browser and start PhyloProfile by using this address

localhost:8080

Troubleshooting

Independent packages cannot be installed

If for any reasons some packages cannot be installed automatically, please do the installation by yourself using the instruction:

# Get list of missing packages
packages <- c("ape", "bioDist", "BiocStyle", "Biostrings", "Cairo", "colourpicker", "data.table", "dendextend", "devtools", "dplyr", "DT", "energy", "GenomeInfoDbData", "ggplot2", "gplots", "GO.db", "grDevices", "gridExtra", "gtable", "knitr", "RColorBrewer", "RCurl", "reshape2", "rmarkdown", "scales", "shiny", "shinyBS", "shinycssloaders", "shinyjs", "stats", "stringr", "svMisc", "tidyr", "taxize", "utils", "OmaDB", "plyr", "zoo")
missingPkg <- packages[!packages %in% rownames(installed.packages())]
missingPkg

# Then install the missing packages
install.packages(missingPkg, dependencies = TRUE, repos="http://cran.us.r-project.org")

Vignettes cannot be installed

The installation of PhyloProfile can be terminated due to the unsuccessful generation of the vignettes (e.g. due to missing X11 fonts). In this case, you can turn off the option to create the vignettes while installing the tool by removing build_opts = c('--no-resave-data'). For example:

devtools::install_github("bionf/phyloprofile", INSTALL_opts = c('--no-lock'))

The startup takes ages

For the first time running, the tool will download and process the complete NCBI taxonomy database into a readable format for PhyloProfile. Please be patient until you see a message for uploading input files. It will take normally less than 2 minutes.

If it takes more than 5 minutes (depend on how fast your internet connection is), or you just don't want to wait, you can manually do this task by following these commands:

# Download and preprocess NCBI taxonomy information
library(PhyloProfile)
preProcessedTaxonomy <- processNcbiTaxonomy()
# Find the library path, where PhyloProfile has been installed and identify an output file there
path <- find.package("PhyloProfile")
outFile <- paste0(path, "/PhyloProfile/data/preProcessedTaxonomy.txt")
# Write the preprocessed taxonomy file into PhyloProfile data folder
write.table(
	preProcessedTaxonomy,
	file = outFile,
	col.names = TRUE,
	row.names = FALSE,
	quote = FALSE,
	sep = "\t"
)

Python dependencies for OMA parsing scripts

Converting OrthoXML files to an input that works with PhyloProfile or manually downloading OMA data is right now done with Python scripts (data/convert_oma_standalone_orthoxml.pl or data/get_oma_browser.py), which come with their own dependencies.

These can be installed with pip install bs4 and pip install lxml.

Additionally, if you want to use scripts/get_oma_browser.py to get OMA Orthologous Proteins from OMA Browser, you need to install the Core API Library with pip install coreapi.