Package: coloc 5.2.3

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>.

Authors:Chris Wallace [aut, cre], Claudia Giambartolomei [aut], Vincent Plagnol [ctb]

coloc_5.2.3.tar.gz
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coloc_5.2.3.tgz(r-4.4-any)coloc_5.2.3.tgz(r-4.3-any)
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coloc.pdf |coloc.html
coloc/json (API)
NEWS

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

Peer review:

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

Datasets:
  • coloc_test_data - Simulated data to use in testing and vignettes in the coloc package

On CRAN:

12.25 score 148 stars 3 packages 896 scripts 1.4k downloads 49 mentions 19 exports 40 dependencies

Last updated 9 days agofrom:fd1c035118. Checks:OK: 1 WARNING: 6. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 13 2024
R-4.5-winWARNINGNov 13 2024
R-4.5-linuxWARNINGNov 13 2024
R-4.4-winWARNINGNov 13 2024
R-4.4-macWARNINGNov 13 2024
R-4.3-winWARNINGNov 13 2024
R-4.3-macWARNINGNov 13 2024

Exports:annotate_susiecheck_alignmentcheck_datasetcheck.alignmentcheck.datasetcoloc.abfcoloc.bf_bfcoloc.signalscoloc.susiecoloc.susie_bffindendsfinemap.abffinemap.bffinemap.signalsplot_datasetprocess.datasetrunsusiesensitivitysubset_dataset

Dependencies:clicolorspacecrayondata.tablefansifarverggplot2gluegridExtragtableirlbaisobandlabelinglatticelifecyclemagrittrMASSMatrixmatrixStatsmgcvmixsqpmunsellnlmepillarpkgconfigplyrR6RColorBrewerRcppRcppArmadilloreshaperlangscalessusieRtibbleutf8vctrsviridisviridisLitewithr

Coloc: a package for colocalisation analyses

Rendered froma01_intro.Rmdusingknitr::rmarkdownon Nov 13 2024.

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

Coloc: data structures

Rendered froma02_data.Rmdusingknitr::rmarkdownon Nov 13 2024.

Last update: 2023-05-12
Started: 2021-03-23

Coloc: sensitivity to prior values

Rendered froma04_sensitivity.Rmdusingknitr::rmarkdownon Nov 13 2024.

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

Coloc: under a single causal variant assumption

Rendered froma03_enumeration.Rmdusingknitr::rmarkdownon Nov 13 2024.

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

Coloc: using SuSiE to relax the single causal variant assumption

Rendered froma06_SuSiE.Rmdusingknitr::rmarkdownon Nov 13 2024.

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

DEPRECATED Coloc: relaxing the single causal variant assumption

Rendered froma05_conditioning.Rmdusingknitr::rmarkdownon Nov 13 2024.

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

Readme and manuals

Help Manual

Help pageTopics
Colocalisation tests of two genetic traitscoloc-package
annotate susie_rss output for use with coloc_susieannotate_susie
Internal function, approx.bf.estimatesapprox.bf.estimates
Internal function, approx.bf.papprox.bf.p
binomial to linear regression conversionbin2lin
check alignmentcheck.alignment check_alignment
check_datasetcheck.dataset check_dataset
Simulated data to use in testing and vignettes in the coloc packagecoloc_test_data
Fully Bayesian colocalisation analysis using Bayes Factorscoloc.abf
Coloc data through Bayes factorscoloc.bf_bf
Bayesian colocalisation analysis with detailed outputcoloc.detail
Post process a coloc.details result using maskingcoloc.process
Coloc with multiple signals per traitcoloc.signals
run coloc using susie to detect separate signalscoloc.susie
run coloc using susie to detect separate signalscoloc.susie_bf
combine.abfcombine.abf
generate conditional summary statsest_cond
estgeno1estgeno.1.cse estgeno.1.ctl
Pick out snp with most extreme Z scorefind.best.signal
trim a dataset to central peak(s)findends
trim a dataset to only peak(s)findpeaks
Bayesian finemapping analysisfinemap.abf
Finemap data through Bayes factorsfinemap.bf
Finemap multiple signals in a single datasetfinemap.signals
logbf 2 pplogbf_to_pp
logdifflogdiff
logsumlogsum
find the next most significant SNP, conditioning on a list of sigsnpsmap_cond
find the next most significant SNP, masking a list of sigsnpsmap_mask
plot a coloc datasetplot_dataset
plot a coloc_abf objectplot.coloc_abf
print.coloc_abfprint.coloc_abf
process.datasetprocess.dataset
Run susie on a single coloc-structured datasetrunsusie
Estimate trait variance, internal functionsdY.est
Prior sensitivity for colocsensitivity
subset_datasetsubset_dataset
Var.dataVar.data
Var.dataVar.data.cc