All functions

FinemappingConvergence

Simulated Fine-mapping Data with Convergence Problem.

N2finemapping

Simulated Fine-mapping Data with Two Effect Variables

N3finemapping

Simulated Fine-mapping Data with Three Effect Variables.

SummaryConsistency

Simulated Fine-mapping Data with LD matrix From Reference Panel.

coef(<susie>)

Extract regression coefficients from susie fit

compute_ss()

Compute sufficient statistics for input to susie_suff_stat

compute_suff_stat()

Compute sufficient statistics for input to susie_suff_stat

estimate_s_rss()

Estimate s in susie_rss Model Using Regularized LD

get_cs_correlation()

Get Correlations Between CSs, using Variable with Maximum PIP From Each CS

kriging_rss()

Compute Distribution of z-scores of Variant j Given Other z-scores, and Detect Possible Allele Switch Issue

predict(<susie>)

Predict outcomes or extract coefficients from susie fit.

summary(<susie>) print(<summary.susie>)

Summarize Susie Fit.

susie() susie_suff_stat()

Sum of Single Effects (SuSiE) Regression

susie_auto()

Attempt at Automating SuSiE for Hard Problems

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

susie_init_coef()

Initialize a susie object using regression coefficients

susie_plot_changepoint()

Plot changepoint data and susie fit using ggplot2

susie_plot() susie_plot_iteration()

SuSiE Plots.

susie_rss()

Sum of Single Effects (SuSiE) Regression using summary statistics

susie_trendfilter()

Apply susie to trend filtering (especially changepoint problems), a type of non-parametric regression.

univariate_regression()

Perform Univariate Linear Regression Separately for Columns of X