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LocusExplorer

An interactive graphical illustration of genetic associations and their biological context

Install / Use

/learn @oncogenetics/LocusExplorer
About this skill

Quality Score

0/100

Supported Platforms

Universal

README

An interactive graphical illustration of genetic associations and their biological context.

<p> <img src="www/Figure1_v07.jpeg" height="840px" width="700px"> </p>

Disclaimer

LocusExplorer should be used for illustrative purposes only. Any results provided by LocusExplorer should be used with caution.

Availability

The source code and installation instructions for LocusExplorer are available at https://github.com/oncogenetics/LocusExplorer.

LocusExplorer is made available under the MIT license.

Required Software

LocusExplorer runs in the R environment but is designed to be an easy to use interface that does not require familiarity with R as a prerequisite. LocusExplorer is platform agnostic and able to run on any operating system for which R is available.

LocusExplorer requires R version 3.2.2 to run and can be downloaded by following the instructions at https://www.r-project.org/. Some required packages are not available for earlier versions of R.

After installation of the R software, R packages used by LocusExplorer must be installed prior to use. This may take a few minutes, but is only required on the first occasion. To install packages, open the R program, copy the following code into the R console and hit Return:

#install CRAN packages, if missing
packages <- c("shiny","dplyr","tidyr","lazyeval","data.table","ggplot2","ggrepel","knitr","markdown","DT","lattice","acepack","cluster","DBI","colourpicker","igraph","visNetwork", "devtools")
if (length(setdiff(packages, rownames(installed.packages()))) > 0) {
  install.packages(setdiff(packages, rownames(installed.packages())), dependencies = TRUE)  
} else { print("All required CRAN packages installed")}

#install Bioconductor packages if missing
source("https://bioconductor.org/biocLite.R")
bioc <- c("ggbio","GenomicRanges","TxDb.Hsapiens.UCSC.hg19.knownGene","org.Hs.eg.db","rtracklayer")
if (length(setdiff(bioc, rownames(installed.packages()))) > 0) {
  biocLite(setdiff(bioc, rownames(installed.packages())))  
} else { print("All required Bioconductor packages installed")}

#install GitHub packages:
devtools::install_github("oncogenetics/oncofunco")
  • In cases when user do not have admin rights, pop up window will prompt to set a personal library location for installation of packages, please click yes.
  • If using R GUI then user might get prompted to choose CRAN mirror to use for package downloads, please choose the city nearer to your location.
  • If prompted to "Update packages all/some/none [a/s/n]", type "n" and hit Return.

Launch LocusExplorer

LocusExplorer runs through a web browser and uses an intuitive interface that does not require high level computational skills to operate.

1. Using runGitHub() within RStudio

Open RStudio (start a new R session) copy the following code into the console and hit Return:

library(shiny)  
runGitHub("LocusExplorer", "oncogenetics", launch.browser = TRUE)

2. Using Download as Zip (Recommended)

Click on Download as ZIP button, this will download the repisotory locally as a zip file LocusExplorer-master.zip. Unzip the folder. Open ui.R file in RStudio (start a new R session) and click on Run App (Please ensure Run External option is selected for full functionality) button at top right corner, or run below code.

library(shiny)  
runApp(launch.browser = TRUE)

Cite LocusExplorer

<a href="http://bioinformatics.oxfordjournals.org/content/early/2015/11/19/bioinformatics.btv690.abstract" target="_blank">LocusExplorer: a user-friendly tool for integrated visualisation of genetic association data and biological annotations</a>
Tokhir Dadaev<sup>1</sup>, Daniel A Leongamornlert<sup>1</sup>, Edward J Saunders<sup>1</sup>, Rosalind Eeles<sup>1,2</sup> , Zsofia Kote-Jarai<sup>1</sup>

<sup>1</sup>Department of Genetics and Epidemiology, The Institute of Cancer Research, London, UK
<sup>2</sup>Royal Marsden NHS Foundation Trust, London, UK

Bioinformatics first published online November 20, 2015 doi:10.1093/bioinformatics/btv690

Abstract

Summary: In this article we present LocusExplorer, a data visualisation and exploration tool for genetic association data. LocusExplorer is written in R using the Shiny library, providing access to powerful R-based functions through a simple user interface. LocusExplorer allows users to simultaneously display genetic, statistical and biological data for humans in a single image and allows dynamic zooming and customisation of the plot features. Publication quality plots may then be produced in a variety of file formats.
Availability and implementation: LocusExplorer is open source and runs through R and a web browser. It is available at www.oncogenetics.icr.ac.uk/LocusExplorer/ or can be installed locally and the source code accessed from https://github.com/oncogenetics/LocusExplorer.

Publications: LocusExplorer plots

  • <a href="http://www.ncbi.nlm.nih.gov/pubmed/26025378" target="_blank">Multiple novel prostate cancer susceptibility signals identified by fine-mapping of known risk loci among Europeans.</a> Al Olama AA, et al.

    • <a href="http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4572072/figure/DDV203F1/" target="_blank">Figure 1</a>
  • Accepted, not published yet:

    • Fine-mapping of Prostate Cancer Susceptibility Loci in a Large Meta-Analysis Identifies Candidate Causal Variants. Tokhir Dadaev, et al.
    • Prostate cancer meta-analysis of more than 140,000 men identifies 63 novel prostate cancer susceptibility loci. Fredrick R. Schumacher, et al.
    • Germline Variation at 8q24 and Prostate Cancer Risk in Men of European Ancestry. Marco Matejcic, et al.

Frequently asked questions

See FAQ.

Contact

Questions, suggestions, and bug reports are welcome and appreciated.

To-do List

https://github.com/oncogenetics/LocusExplorer/issues

Issue Stats Issue Stats

Related Skills

View on GitHub
GitHub Stars17
CategoryDevelopment
Updated8mo ago
Forks14

Languages

R

Security Score

87/100

Audited on Jul 23, 2025

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