RiVIERA-MT specifications

Information


Unique identifier OMICS_13965
Name RiVIERA-MT
Alternative name Risk Variant Inference using Epigenomic Reference Annotations to predict Multiple Trait-causing mutations
Software type Framework/Library
Interface Command line interface
Restrictions to use None
Input data GWAS summary association statistics in one or more traits (Z-scores), linkage disequilibrium (LD) either from the GWAS cohort or reference panel from 1000 Genome consortium, functional annotation matrix (binary or continuous) for each SNP
Output data Simulated marginal summary statistics, causal status of each SNP, causal status of each epigenomic annotations
Operating system Unix/Linux, Mac OS
Programming languages R
Computer skills Advanced
Version 0.9.3
Stability No
Requirements
Rcpp, RcppArmadillo
Maintained No

Download


download.png

Versioning


No version available

Documentation


Maintainer


This tool is not available anymore.

Publication for Risk Variant Inference using Epigenomic Reference Annotations to predict Multiple Trait-causing mutations

RiVIERA-MT citation

library_books

Statistical methods to detect pleiotropy in human complex traits

2017
Open Biol
PMCID: 5717338
PMID: 29093210
DOI: 10.1098/rsob.170125

[…] PA, a Bayesian method entitled EPS also accounts for LD, but infers association at the gene- rather than the variant-level, and can incorporate gene expression data from a large number of tissues []. RiVIERA-MT further allows for multiple causal variants within one locus []. […]

RiVIERA-MT institution(s)
Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, Cambridge, MA, USA; The Broad Institute of Harvard and MIT, Cambridge, MA, USA

RiVIERA-MT reviews

star_border star_border star_border star_border star_border
star star star star star

Be the first to review RiVIERA-MT