Package: coloc 6.0.1

coloc: Colocalisation Tests of Two Genetic Traits

Performs the colocalisation tests described in Giambartolomei et al (2013) <doi:10.1371/journal.pgen.1004383>, Wallace (2020) <doi:10.1371/journal.pgen.1008720>, Wallace (2021) <doi:10.1371/journal.pgen.1009440>, Pullin and Wallace (2025) <doi:10.1101/2024.08.21.608957>.

Authors:Chris Wallace [aut, cre], Claudia Giambartolomei [aut], Vincent Plagnol [ctb], Tom Willis [aut], Jeffrey Pullin [aut]

coloc_6.0.1.tar.gz
coloc_6.0.1.zip(r-4.7)coloc_6.0.1.zip(r-4.6)coloc_6.0.1.zip(r-4.5)
coloc_6.0.1.tgz(r-4.6-any)coloc_6.0.1.tgz(r-4.5-any)
coloc_6.0.1.tar.gz(r-4.7-any)coloc_6.0.1.tar.gz(r-4.6-any)
coloc_6.0.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
coloc/json (API)

# Install 'coloc' in R:

install.packages('coloc', repos = c('https://chr1swallace.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/chr1swallace/coloc/issues

Pkgdown/docs site:https://chr1swallace.github.io

Datasets:

coloc_test_data - Simulated data to use in testing and vignettes in the coloc package
eqtlgen_density_data - EQTLGen estimated distance density

On CRAN:

12.86 score 201 stars 3 packages 1.5k scripts 3.5k downloads 49 mentions 22 exports 31 dependencies

Last updated from:50fe5291fe. Checks:7 WARNING, 2 OK. Indexed: yes.

Target	Result	Time
linux-devel-x86_64	WARNING	284
source / vignettes	OK	362
linux-release-x86_64	WARNING	328
macos-release-arm64	WARNING	199
macos-oldrel-arm64	WARNING	154
windows-devel	WARNING	186
windows-release	WARNING	235
windows-oldrel	WARNING	200
wasm-release	OK	310

Exports:annotate_susie check_alignment check_dataset check.alignment check.dataset coloc.abf coloc.bf_bf coloc.signals coloc.susie coloc.susie_bf credible.sets findends finemap.abf finemap.bf finemap.signals plot_dataset plot_datasets plot_extended_datasets process.dataset runsusie sensitivity subset_dataset

Dependencies:cli cpp11 crayon data.table farver ggplot2 glue gridExtra gtable irlba isoband labeling lattice lifecycle Matrix matrixStats mixsqp plyr R6 RColorBrewer Rcpp RcppArmadillo reshape rlang S7 scales susieR vctrs viridis viridisLite withr

Coloc: data structures

Rendered froma02_data.Rmdusingknitr::rmarkdown

Last update: 2025-11-19
Started: 2021-03-23

Coloc: using variant-specific priros in coloc

Variant-specific priors in coloc | Using general variant-specific information | An example of variant-specific information

Rendered froma07_variant-specific-priors.Rmdusingknitr::rmarkdown

Last update: 2025-03-27
Started: 2025-03-27

Coloc: a package for colocalisation analyses

A brief outline of colocalisation analysis | A single causal variant assumption | Sensitivity analysis | Deprecated: relaxing the single causal variant assumption through conditioning | An improved approach to relaxing the single causal variant assumption: SuSiE | Footnotes

Rendered froma01_intro.Rmdusingknitr::rmarkdown

Last update: 2023-05-12
Started: 2019-07-08

Coloc: using SuSiE to relax the single causal variant assumption

Multiple causal variants, using SuSiE to separate the signals | Important notes on running SuSiE

Rendered froma06_SuSiE.Rmdusingknitr::rmarkdown

Last update: 2022-05-05
Started: 2021-03-22

DEPRECATED Coloc: relaxing the single causal variant assumption

Multiple causal variants

Rendered froma05_conditioning.Rmdusingknitr::rmarkdown

Last update: 2022-03-21
Started: 2019-07-08

Coloc: sensitivity to prior values

Sensitivity analysis

Rendered froma04_sensitivity.Rmdusingknitr::rmarkdown

Last update: 2021-06-08
Started: 2019-07-08

Coloc: under a single causal variant assumption

Fine mapping under a single causal variant assumption | (Approximate) Bayes Factor colocalisation analyses | Introduction | The basic coloc.abf function

Rendered froma03_enumeration.Rmdusingknitr::rmarkdown

Last update: 2021-06-08
Started: 2019-07-08

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Colocalisation tests of two genetic traits	-package coloc-package
annotate susie_rss output for use with coloc_susie	annotate_susie
Internal function, approx.bf.estimates	approx.bf.estimates
Internal function, approx.bf.p	approx.bf.p
binomial to linear regression conversion	bin2lin
check alignment	check.alignment check_alignment
check_dataset	check.dataset check_dataset
Simulated data to use in testing and vignettes in the coloc package	coloc_test_data
Fully Bayesian colocalisation analysis using Bayes Factors	coloc.abf
Coloc data through Bayes factors	coloc.bf_bf
Bayesian colocalisation analysis with detailed output	coloc.detail
Post process a coloc.details result using masking	coloc.process
Coloc with multiple signals per trait	coloc.signals
run coloc using susie to detect separate signals	coloc.susie
run coloc using susie to detect separate signals	coloc.susie_bf
combine.abf	combine.abf
credible.sets	credible.sets
eQTLGen estimated distance density	eqtlgen_density_data
generate conditional summary stats	est_cond
estgeno1	estgeno.1.cse estgeno.1.ctl
Pick out snp with most extreme Z score	find.best.signal
trim a dataset to central peak(s)	findends
trim a dataset to only peak(s)	findpeaks
Bayesian finemapping analysis	finemap.abf
Finemap data through Bayes factors	finemap.bf
Finemap multiple signals in a single dataset	finemap.signals
logbf 2 pp	logbf_to_pp
logdiff	logdiff
logsum	logsum
find the next most significant SNP, conditioning on a list of sigsnps	map_cond
find the next most significant SNP, masking a list of sigsnps	map_mask
plot a coloc dataset	plot_dataset
plot a pair of coloc datasets, highlighting the snps that are common between them	plot_datasets
Draw extended plot of summary statistics for two coloc datasets	plot_extended_datasets
plot a coloc_abf object	plot.coloc_abf
print.coloc_abf	print.coloc_abf
process.dataset	process.dataset
Run susie on a single coloc-structured dataset	runsusie
Estimate trait variance, internal function	sdY.est
Prior sensitivity for coloc	sensitivity
subset_dataset	subset_dataset
Var.data	Var.data
Var.data	Var.data.cc