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Installation

library(devtools)
install_github("ArtemisZhao/INTRIGUE/R_src")

Example dataset

library(INTRIGUE)
data("heterodata")

This is a simulated datasets with n=5000 experimental units (e.g., genes) and m=2 replicates. The true proportions for the null, the reproducible and the irreproducible signal categories are 0.80, 0.18, 0.02, respectively.

CEFN prior

##for convenience, only test on first 100 units 
hetero.out.cefn<-hetero(heterodata[1:100,],fdr.level=0.05)

META prior

hetero.out.meta<-hetero(heterodata[1:100,],use_cefn=FALSE,fdr.level=0.05)

Outcome

names(hetero.out.cefn)

## overall proportion
print(hetero.out$est_prop)

Return a list containing the following,

  1. gridweight: estimated weight on each grid point.

  2. ind_prob: individual probability of falling into three groups.

  3. est_prop: estimated overall proportion for three groups.

  4. lfdr: false discovery rate.

  5. significant: decision based on the fdr.level in the input.

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Version

Install

install.packages('INTRIGUE')

Monthly Downloads

161

Version

0.1.0

License

GPL-2

Maintainer

Michael Kleinsasser

Last Published

November 5th, 2020

Functions in INTRIGUE (0.1.0)

bf.cal.cefn

Bayes Factor Calculation Scheme for CENF prior
bf.em

Bayes Factor EM Updating Scheme
bf.loglik

Bayes Factor Loglikelihood Function
bf.weighted_sum

Bayes Factor Weighted Summation
bf.cal.meta

Bayes Factor Calculation Scheme for META prior
heterodata

Simulation Dataset
bf.approx

Bayes Factor Approximation
hetero.lfdr

Local False Discovery Rate Evaluation
hetero

Heterogeneity Evaluation