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locuszoomr

This is a pure R implementation of locuszoom for plotting genetic data at genomic loci accompanied by gene annotations. Plots can be produced in base graphics, ggplot2 or plotly. Plots can be stacked or laid out with multiple plots per page, or the gene track can be plotted separately and added to your own plots.

The LDlink API can be queried to obtain linkage disequilibrium data from 1000 Genomes. Recombination rate can also be shown by querying UCSC genome browser.

See the detailed vignette for code examples.

Installation

Bioconductor package ensembldb and an Ensembl database installed either as a package or accessed through Bioconductor package AnnotationHub are required before installation.

if (!requireNamespace("BiocManager", quietly = TRUE))
  install.packages("BiocManager")
BiocManager::install("ensembldb")
BiocManager::install("EnsDb.Hsapiens.v75")

Install from CRAN

install.packages("locuszoomr")

Install from Github

devtools::install_github("myles-lewis/locuszoomr")

locuszoomr can leverage the LDlinkR package to query the 1000 Genomes Project for linkage disequilibrium (LD) across SNPs. In order to make use of this API function you will need a personal access token, available from the LDlink website.

We recommend that users who want to add recombination rate lines to multiple plots download the recombination rate track from UCSC and use it as described in the 'Add recombination rate' section in the vignette.

Example locus plot

# Locus plot using SLE GWAS data from Bentham et al 2015
# Using subset of data embedded in the package
library(locuszoomr)
data(SLE_gwas_sub)

library(EnsDb.Hsapiens.v75)
loc <- locus(gene = 'UBE2L3', SLE_gwas_sub, flank = 1e5,
             ens_db = "EnsDb.Hsapiens.v75")
summary(loc)
locus_plot(loc)

# Or FTP download the full summary statistics from
# https://www.ebi.ac.uk/gwas/studies/GCST003156
library(data.table)
SLE_gwas <- fread('../bentham_2015_26502338_sle_efo0002690_1_gwas.sumstats.tsv')

loc <- locus(gene = 'UBE2L3', SLE_gwas, flank = 1e5,
             ens_db = "EnsDb.Hsapiens.v75")
locus_plot(loc)

Example layered plot shown in the paper

library(locuszoomr)
library(EnsDb.Hsapiens.v75)

data(SLE_gwas_sub)
loc <- locus(data = SLE_gwas_sub, gene = 'IRF5', flank = c(1e5, 2e5),
             ens_db = "EnsDb.Hsapiens.v75")

# add recombination rate
loc <- link_recomb(loc, genome = "hg19")

# add LD and eQTL data
# users must obtain an API token from https://ldlink.nih.gov/?tab=apiaccess
loc <- link_LD(loc, token = "your_API_token")
loc <- link_eqtl(loc, token = "your_API_token")

# set up layered plot with 2 plots & a gene track
pdf("locuszoomr_demo.pdf", width = 4.5, height = 7)
oldpar <- set_layers(2)
scatter_plot(loc, xticks = FALSE, labels = c("index", "rs113708239"),
             label_x = c(-4, 4))
eqtl_plot(loc, xlab = "")
genetracks(loc, highlight = "IRF5")
par(oldpar)
dev.off()

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Install

install.packages('locuszoomr')

Monthly Downloads

655

Version

0.3.6

License

GPL (>= 3)

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Maintainer

Myles Lewis

Last Published

January 26th, 2025

Functions in locuszoomr (0.3.6)

locus

Create locus object for plotting
link_eqtl

Obtain GTEx eQTL data via LDlinkR
scatter_plot

Locus scatter plot
locus_plotly

Locus plotly
quick_peak

Fast peak finder in GWAS data
locus_ggplot

Locus plot using ggplot2
locus_plot

Locus plot
multi_layout

Layout multiple locus plots
link_recomb

Query UCSC for Recombination data
overlay_plot

Plot overlaying eQTL and GWAS data
scatter_plotly

Locus scatter plotly
set_layers

Set up a column of multiple plots
line_plot

Locus line plot
genetracks_grob

Create gene tracks grob
gg_genetracks

Plot gene tracks
SLE_gwas_sub

SLE GWAS data subset
genetrack_ly

Gene tracks using 'plotly'
gg_scatter

Locus scatter plot using ggplot2
link_LD

Obtain LD at a locus from LDlink
genetracks

Plot gene tracks
eqtl_plot

Locus eQTL plot
gg_addgenes

Add gene tracks to a ggplot2 plot