Package index
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FinemappingConvergence - Simulated Fine-mapping Data with Convergence Problem.
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N2finemapping - Simulated Fine-mapping Data with Two Effect Variables
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N3finemapping - Simulated Fine-mapping Data with Three Effect Variables.
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SummaryConsistency - Simulated Fine-mapping Data with LD matrix From Reference Panel.
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coef(<susie>) - Extract regression coefficients from susie fit
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compute_ss() - Compute sufficient statistics for input to
susie_suff_stat
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compute_suff_stat() - Compute sufficient statistics for input to
susie_suff_stat
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estimate_s_rss() - Estimate s in
susie_rssModel Using Regularized LD
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get_cs_correlation() - Get Correlations Between CSs, using Variable with Maximum PIP From Each CS
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kriging_rss() - Compute Distribution of z-scores of Variant j Given Other z-scores, and Detect Possible Allele Switch Issue
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predict(<susie>) - Predict outcomes or extract coefficients from susie fit.
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summary(<susie>)print(<summary.susie>) - Summarize Susie Fit.
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susie()susie_suff_stat() - Sum of Single Effects (SuSiE) Regression
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susie_auto() - Attempt at Automating SuSiE for Hard Problems
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susie_get_objective()susie_get_posterior_mean()susie_get_posterior_sd()susie_get_niter()susie_get_prior_variance()susie_get_residual_variance()susie_get_lfsr()susie_get_posterior_samples()susie_get_cs()susie_get_pip() - Inferences From Fitted SuSiE Model
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susie_init_coef() - Initialize a susie object using regression coefficients
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susie_plot_changepoint() - Plot changepoint data and susie fit using ggplot2
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susie_plot()susie_plot_iteration() - SuSiE Plots.
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susie_rss() - Sum of Single Effects (SuSiE) Regression using Summary Statistics
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susie_trendfilter() - Apply susie to trend filtering (especially changepoint problems), a type of non-parametric regression.
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univariate_regression() - Perform Univariate Linear Regression Separately for Columns of X