Package: repfdr 1.2.3

Ruth Heller

repfdr: Replicability Analysis for Multiple Studies of High Dimension

Estimation of Bayes and local Bayes false discovery rates for replicability analysis (Heller & Yekutieli, 2014 <doi:10.1214/13-AOAS697> ; Heller at al., 2015 <doi:10.1093/bioinformatics/btu434>).

Authors:Ruth Heller [cre, aut], Shachar Kaufman [aut], Shay Yaacoby [aut], David Israeli [aut], Barak Brill [aut], Daniel Yekutieli [aut]

# Install 'repfdr' in R:

install.packages('repfdr', repos = c('https://barakbri.r-universe.dev', 'https://cloud.r-project.org'))

Uses libs:

Datasets:

On CRAN:

Last updated 7 years agofrom:7976283403. Checks:OK: 4 NOTE: 5. Indexed: yes.

Dependencies:Rcpp

Last update: 2017-07-24
Started: 2017-07-24

Help page	Topics
Three GWAS studies - input objects to main function	binned_zmat bz pbz
Simulated data set - input objects to main function	binned_zmat_sim bz_sim pbz_sim
Control Parameters for the EM algorithm	em.control
Enumeration of all possible vectors of association status.	hconfigs
Simulated data set - indicators of association status matrix	hmat_sim
Estimation of posterior probabilities for the vectors of association status	ldr
Estimation of the prior probabilities for each association status vector.	Pi piem
Bayes and local Bayes false discovery rate estimation for replicability analysis	manhattan repfdr
Three GWAS studies SNPs locations and data	SNPlocations
Binning of two sided P-Values and estimation of the probabilities in each bin for the null and non-null states.	twosided.PValues.tobins
Simulated data set	zmat_sim
Binning of z-scores and estimation of the probabilities in each bin for the null and non-null states.	ztobins