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SimReg (version 3.4)

Similarity Regression

Description

Similarity regression, evaluating the probability of association between sets of ontological terms and binary response vector. A no-association model is compared with one in which the log odds of a true response is linked to the semantic similarity between terms and a latent characteristic ontological profile - 'Phenotype Similarity Regression for Identifying the Genetic Determinants of Rare Diseases', Greene et al 2016 .

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Version

Install

install.packages('SimReg')

Monthly Downloads

209

Version

3.4

License

GPL (>= 2)

Maintainer

Daniel Greene

Last Published

February 21st, 2024

Functions in SimReg (3.4)

Similarity Regression Functions

posterior_prediction

Predicted probability of y given x conditional on association and given data.

plot.sim_reg_summary

Plot summary of sim_reg_output object

print.sim_reg_summary

Print sim_reg_summary object

plot_term_marginals

Create ontological plot of marginal probabilities of terms

prob_association

Calculate probability of association between y and x

print.sim_reg_output

Print sim_reg_output object

get_term_marginals

Calculate marginal probability of terms inclusion in phi from sim_reg_out object

Get full set of terms to use in inference procedure based on similarity function arguments

Calculate log Bayes factor for similarity the model, gamma=1 and baseline model, gamma=0.

summary.sim_reg_output

Get summary of sim_reg_output object

Calculate marginal probability of terms inclusion in phi

Calculate sum of log probabilities on log scale without over/under-flow

Similarity regression