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