Literature DB >> 27085080

Software Application Profile: RVPedigree: a suite of family-based rare variant association tests for normally and non-normally distributed quantitative traits.

Karim Oualkacha1, Lajmi Lakhal-Chaieb2, Celia Mt Greenwood3.   

Abstract

MOTIVATION: RVPedigree (Rare Variant association tests in Pedigrees) implements a suite of programs facilitating genome-wide analysis of association between a quantitative trait and autosomal region-based genetic variation. The main features here are the ability to appropriately test for association of rare variants with non-normally distributed quantitative traits, and also to appropriately adjust for related individuals, either from families or from population structure and cryptic relatedness. IMPLEMENTATION: RVPedigree is available as an R package. GENERAL FEATURES: The package includes calculation of kinship matrices, various options for coping with non-normality, three different ways of estimating statistical significance incorporating triaging to enable efficient use of the most computationally-intensive calculations, and a parallelization option for genome-wide analysis. AVAILABILITY: The software is available from the Comprehensive R Archive Network [CRAN.R-project.org] under the name 'RVPedigree' and at [https://github.com/GreenwoodLab]. It has been published under General Public License (GPL) version 3 or newer.
© The Author 2016; all rights reserved. Published by Oxford University Press on behalf of the International Epidemiological Association.

Keywords:  kernel tests; kinship; kurtosis; mixed models; pedigrees; region-based tests

Mesh:

Year:  2016        PMID: 27085080      PMCID: PMC5841637          DOI: 10.1093/ije/dyw047

Source DB:  PubMed          Journal:  Int J Epidemiol        ISSN: 0300-5771            Impact factor:   7.196


  10 in total

1.  A rare variant association test in family-based designs and non-normal quantitative traits.

Authors:  Lajmi Lakhal-Chaieb; Karim Oualkacha; Brent J Richards; Celia M T Greenwood
Journal:  Stat Med       Date:  2015-09-29       Impact factor: 2.373

2.  Genomewide rapid association using mixed model and regression: a fast and simple method for genomewide pedigree-based quantitative trait loci association analysis.

Authors:  Yurii S Aulchenko; Dirk-Jan de Koning; Chris Haley
Journal:  Genetics       Date:  2007-07-29       Impact factor: 4.562

3.  Rare-variant association testing for sequencing data with the sequence kernel association test.

Authors:  Michael C Wu; Seunggeun Lee; Tianxi Cai; Yun Li; Michael Boehnke; Xihong Lin
Journal:  Am J Hum Genet       Date:  2011-07-07       Impact factor: 11.025

4.  Asymptotic tests of association with multiple SNPs in linkage disequilibrium.

Authors:  Wei Pan
Journal:  Genet Epidemiol       Date:  2009-09       Impact factor: 2.135

5.  SNP set association analysis for familial data.

Authors:  Elizabeth D Schifano; Michael P Epstein; Lawrence F Bielak; Min A Jhun; Sharon L R Kardia; Patricia A Peyser; Xihong Lin
Journal:  Genet Epidemiol       Date:  2012-09-11       Impact factor: 2.135

6.  Sequence kernel association test for quantitative traits in family samples.

Authors:  Han Chen; James B Meigs; Josée Dupuis
Journal:  Genet Epidemiol       Date:  2012-12-26       Impact factor: 2.135

7.  Adjusted sequence kernel association test for rare variants controlling for cryptic and family relatedness.

Authors:  Karim Oualkacha; Zari Dastani; Rui Li; Pablo E Cingolani; Timothy D Spector; Christopher J Hammond; J Brent Richards; Antonio Ciampi; Celia M T Greenwood
Journal:  Genet Epidemiol       Date:  2013-03-25       Impact factor: 2.135

8.  A method to predict the impact of regulatory variants from DNA sequence.

Authors:  Dongwon Lee; David U Gorkin; Maggie Baker; Benjamin J Strober; Alessandro L Asoni; Andrew S McCallion; Michael A Beer
Journal:  Nat Genet       Date:  2015-06-15       Impact factor: 38.330

9.  Integrating sequence and array data to create an improved 1000 Genomes Project haplotype reference panel.

Authors:  Olivier Delaneau; Jonathan Marchini
Journal:  Nat Commun       Date:  2014-06-13       Impact factor: 14.919

10.  Functional annotation of noncoding sequence variants.

Authors:  Graham R S Ritchie; Ian Dunham; Eleftheria Zeggini; Paul Flicek
Journal:  Nat Methods       Date:  2014-02-02       Impact factor: 28.547

  10 in total

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