Article

BayesFM: a software program to fine-map multiple causative variants in GWAS identified risk loci

2016-08-04

Abstract excerpt

<h4>Absract</h4> We herein describe a new method to fine-map GWAS-identified risk loci based on the Bayesian Least Absolute Shrinkage Selection Operator (LASSO) combined with a Monte Carlo Markov Chain (MCMC) approach, and corresponding software package (BayesFM). We characterize the performances of BayesFM using simulated data, showing that it outperforms standard forward selection both in terms of sensitivity a...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 749dadd3-9049-5ee5-835b-509050f0039e
DOI: 10.1101/067801

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

BayesFM: a software program to fine-map multiple causative variants in GWAS identified risk lociDOI 10.1101/067801Read

A fast algorithm for Bayesian multi-locus model in genome-wide association studies.Semantic proximity Read

Genome-wide association analysis by lasso penalized logistic regression.Semantic proximity Read

The Bayesian lasso for genome-wide association studies.Semantic proximity Read

Combining least absolute shrinkage and selection operator (LASSO) and principal-components analysis for detection of gene-gene interactions in genome-wide association studiesSemantic proximity Read

Multivariate genome-wide association study models to improve prediction of Crohn's disease risk and identification of potential novel variants.Semantic proximity Read

Bayesian statistical methods for genetic association studies.Semantic proximity Read

Simultaneous analysis of all SNPs in genome-wide and re-sequencing association studies.Semantic proximity Read

Bayesian multiple logistic regression for case-control GWASSemantic proximity Read

Mining gold dust under the genome wide significance level: a two-stage approach to analysis of GWAS.Semantic proximity Read

CIT-Lasso: a scalable approach beyond guilty by association for identifying causal variants from genome-wide summary statistics.Semantic proximity Read

BayesRB: a markov chain Monte Carlo-based polygenic genetic risk score algorithm for dichotomous traitsSemantic proximity Read

Large sample size, wide variant spectrum, and advanced machine-learning technique boost risk prediction for inflammatory bowel disease.Semantic proximity Read