FINEMAP: efficient variable selection using summary data from genome-wide association studies

Clicks: 2
ID: 305570
2016
Free PDF
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal
Steady

Ranked #792 of 835 articles by views in BMC Bioinformatics

Most read Least read

Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 835 in total.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Sign in to mint
Abstract
The goal of fine-mapping in genomic regions associated with complex diseases and traits is to identify causal variants that point to molecular mechanisms behind the associations. Recent fine-mapping methods using summary data from genome-wide association studies rely on exhaustive search through all possible causal configurations, which is computationally expensive.We introduce FINEMAP, a software package to efficiently explore a set of the most important causal configurations of the region via a shotgun stochastic search algorithm. We show that FINEMAP produces accurate results in a fraction of processing time of existing approaches and is therefore a promising tool for analyzing growing amounts of data produced in genome-wide association studies and emerging sequencing projects.FINEMAP v1.0 is freely available for Mac OS X and Linux at http://www.christianbenner.com: christian.benner@helsinki.fi or matti.pirinen@helsinki.fi.
Reference Key
openalex_W2297334215 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Christian Benner, Chris C. A. Spencer, Aki S. Havulinna, Veikko Salomaa, Samuli Ripatti, Matti Pirinen
Journal BMC Bioinformatics
Year 2016
DOI
10.1093/bioinformatics/btw018
URL
https://academic.oup.com/bioinformatics/article-pdf/32/10/1493/6687224/btw018.pdf
Keywords Keywords not found

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

Comments

No comments yet. Be the first to comment on this article.