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susieR
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Download and install susieR package within the R console
Install from CRAN:
install.packages("susieR")
Install from Github:
library("remotes")
install_github("cran/susieR")
Install by package version:
library("remotes")
install_version("susieR", "0.12.35")
Attach the package and use:
library("susieR")
Maintained by
Peter Carbonetto
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[Scholar Profile | Author Map]
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First Published: 2021-06-02
Latest Update: 2023-02-17
Description:
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).
How to cite:
Peter Carbonetto (2021). susieR: Sum of Single Effects Linear Regression. R package version 0.12.35, https://cran.r-project.org/web/packages/susieR. Accessed 03 Dec. 2024.
Previous versions and publish date:
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Complete documentation for susieR
Functions, R codes and Examples using
the susieR R package
Some associated functions: FinemappingConvergence . N2finemapping . N3finemapping . SummaryConsistency . coef.susie . compute_ss . compute_suff_stat . estimate_s_rss . get_cs_correlation . kriging_rss . predict.susie . single_effect_regression . summary.susie . susie . susieR-package . susie_auto . susie_get_methods . susie_init_coef . susie_plot_changepoint . susie_plots . susie_rss . susie_trendfilter . univariate_regression .
Some associated R codes: compute_ss.R . data.R . elbo.R . elbo_rss.R . elbo_ss.R . estimate_residual_variance.R . initialize.R . initialize_rss.R . predict.susie.R . remove_null_effects.R . set_R_attributes.R . single_effect_regression.R . single_effect_regression_rss.R . single_effect_regression_ss.R . sparse_multiplication.R . summary.susie.R . susie.R . susieR-package.R . susie_plot_changepoint.R . susie_plots.R . susie_rss.R . susie_rss_lambda.R . susie_ss.R . susie_trendfilter.R . susie_utils.R . susie_zzz_auto.R . trend_filtering_multiplication.R . univariate_regression.R . update_each_effect.R . update_each_effect_rss.R . update_each_effect_ss.R . zzz.R . Full susieR package functions and examples
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