Package: susieR 0.12.42

Peter Carbonetto

susieR: Sum of Single Effects Linear Regression

Implements methods for variable selection in linear regression based on the "Sum of Single Effects" (SuSiE) model, as described in Wang et al (2020) <doi:10.1101/501114> and Zou et al (2021) <doi:10.1101/2021.11.03.467167>. These methods provide simple summaries, called "Credible Sets", for accurately quantifying uncertainty in which variables should be selected. The methods are motivated by genetic fine-mapping applications, and are particularly well-suited to settings where variables are highly correlated and detectable effects are sparse. The fitting algorithm, a Bayesian analogue of stepwise selection methods called "Iterative Bayesian Stepwise Selection" (IBSS), is simple and fast, allowing the SuSiE model be fit to large data sets (thousands of samples and hundreds of thousands of variables).

Authors:Gao Wang [aut], Yuxin Zou [aut], Kaiqian Zhang [aut], Peter Carbonetto [aut, cre], Matthew Stephens [aut]

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susieR.pdf |susieR.html✨
susieR/json (API)

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

Peer review:

Bug tracker:https://github.com/stephenslab/susier/issues

Datasets:

On CRAN:

29 exports 174 stars 5.49 score 36 dependencies 6 dependents 2 mentions 504 scripts 1.8k downloads

Last updated 2 months agofrom:ced6a9c83a. Checks:ERROR: 1 WARNING: 6. Indexed: yes.

TargetResultDate
Doc / VignettesFAILAug 31 2024
R-4.5-winWARNINGAug 31 2024
R-4.5-linuxWARNINGAug 31 2024
R-4.4-winWARNINGAug 31 2024
R-4.4-macWARNINGAug 31 2024
R-4.3-winWARNINGAug 31 2024
R-4.3-macWARNINGAug 31 2024

Exports:coef.susiecompute_sscompute_suff_statestimate_s_rssget_cs_correlationkriging_rsspredict.susieprint.summary.susiesummary.susiesusiesusie_autosusie_get_cssusie_get_lfsrsusie_get_nitersusie_get_objectivesusie_get_pipsusie_get_posterior_meansusie_get_posterior_samplessusie_get_posterior_sdsusie_get_prior_variancesusie_get_residual_variancesusie_init_coefsusie_plotsusie_plot_changepointsusie_plot_iterationsusie_rsssusie_suff_statsusie_trendfilterunivariate_regression

Dependencies:clicolorspacecrayonfansifarverggplot2gluegtableirlbaisobandlabelinglatticelifecyclemagrittrMASSMatrixmatrixStatsmgcvmixsqpmunsellnlmepillarpkgconfigplyrR6RColorBrewerRcppRcppArmadilloreshaperlangscalestibbleutf8vctrsviridisLitewithr

Readme and manuals

Help Manual

Help pageTopics
Extract regression coefficients from susie fitcoef.susie
Compute sufficient statistics for input to 'susie_suff_stat'compute_ss
Compute sufficient statistics for input to 'susie_suff_stat'compute_suff_stat
Estimate s in 'susie_rss' Model Using Regularized LDestimate_s_rss
Simulated Fine-mapping Data with Convergence Problem.FinemappingConvergence
Get Correlations Between CSs, using Variable with Maximum PIP From Each CSget_cs_correlation
Compute Distribution of z-scores of Variant j Given Other z-scores, and Detect Possible Allele Switch Issuekriging_rss
Simulated Fine-mapping Data with Two Effect VariablesN2finemapping
Simulated Fine-mapping Data with Three Effect Variables.N3finemapping
Predict outcomes or extract coefficients from susie fit.predict.susie
Summarize Susie Fit.print.summary.susie summary.susie
Simulated Fine-mapping Data with LD matrix From Reference Panel.SummaryConsistency
Sum of Single Effects (SuSiE) Regressionsusie susie_suff_stat
Attempt at Automating SuSiE for Hard Problemssusie_auto
Inferences From Fitted SuSiE Modelsusie_get_cs susie_get_lfsr susie_get_niter susie_get_objective susie_get_pip susie_get_posterior_mean susie_get_posterior_samples susie_get_posterior_sd susie_get_prior_variance susie_get_residual_variance
Initialize a susie object using regression coefficientssusie_init_coef
SuSiE Plots.susie_plot susie_plot_iteration
Plot changepoint data and susie fit using ggplot2susie_plot_changepoint
Sum of Single Effects (SuSiE) Regression using Summary Statisticssusie_rss
Apply susie to trend filtering (especially changepoint problems), a type of non-parametric regression.susie_trendfilter
Perform Univariate Linear Regression Separately for Columns of Xunivariate_regression