Association screening of common and rare genetic variants by penalized regression

MOTIVATION This article extends our recent research on penalized estimation methods in genome-wide association studies to the realm of rare variants. RESULTS The new strategy is tested on both simulated and real data. Our findings on breast cancer data replicate previous results and shed light on variant effects within genes. AVAILABILITY Rare variant discovery by group penalized regression is now implemented in the free program Mendel at http://www.genetics.ucla.edu/software/.

[1]  M. Yuan,et al.  Model selection and estimation in regression with grouped variables , 2006 .

[2]  Mee Young Park,et al.  L1‐regularization path algorithm for generalized linear models , 2007 .

[3]  R. Eeles,et al.  Genome-wide association studies in cancer. , 2008, Human molecular genetics.

[4]  K. Frazer,et al.  Human genetic variation and its contribution to complex traits , 2009, Nature Reviews Genetics.

[5]  S. Leal,et al.  Methods for detecting associations with rare variants for common diseases: application to analysis of sequence data. , 2008, American journal of human genetics.

[6]  Kenneth Lange,et al.  Numerical analysis for statisticians , 1999 .

[7]  Jeanette C Papp,et al.  Associations between Single Nucleotide Polymorphisms in Double-Stranded DNA Repair Pathway Genes and Familial Breast Cancer , 2009, Clinical Cancer Research.

[8]  Simon C. Potter,et al.  Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls , 2007, Nature.

[9]  Z. Xuan,et al.  Genome-wide in situ exon capture for selective resequencing , 2007, Nature Genetics.

[10]  Andrew G. Clark,et al.  Darwinian and demographic forces affecting human protein coding genes. , 2009, Genome research.

[11]  Jonathan C. Cohen,et al.  Multiple Rare Alleles Contribute to Low Plasma Levels of HDL Cholesterol , 2004, Science.

[12]  J. Rioux,et al.  Autoimmune diseases: insights from genome-wide association studies. , 2008, Human molecular genetics.

[13]  H. Hameister,et al.  Demethylation, reactivation, and destabilization of human fragile X full-mutation alleles in mouse embryocarcinoma cells. , 2001, American journal of human genetics.

[14]  P. Bühlmann,et al.  The group lasso for logistic regression , 2008 .

[15]  D. Easton,et al.  Risks of cancer in BRCA1-mutation carriers , 1994, The Lancet.

[16]  A. Ashworth,et al.  Counting potentially functional variants in BRCA1, BRCA2 and ATM predicts breast cancer susceptibility. , 2007, Human molecular genetics.

[17]  Wenjiang J. Fu.  Penalized Regressions: The Bridge versus the Lasso , 1998 .

[18]  K. Kinzler,et al.  The Genetic Basis of Human Cancer , 1997 .

[19]  R. Tibshirani,et al.  A note on the group lasso and a sparse group lasso , 2010, 1001.0736.

[20]  A. Clark,et al.  Recent and ongoing selection in the human genome , 2007, Nature Reviews Genetics.

[21]  S. Gabriel,et al.  The Structure of Haplotype Blocks in the Human Genome , 2002, Science.

[22]  R. Tibshirani.  Regression Shrinkage and Selection via the Lasso , 1996 .

[23]  D. Bentley,et al.  Identification of the breast cancer susceptibility gene BRCA2 , 1995, Nature.

[24]  Trevor J. Hastie,et al.  Genome-wide association analysis by lasso penalized logistic regression , 2009, Bioinform..

[25]  S. Browning,et al.  A Groupwise Association Test for Rare Mutations Using a Weighted Sum Statistic , 2009, PLoS genetics.

[26]  Kristilyn Eliason,et al.  Multiple rare nonsynonymous variants in the adenomatous polyposis coli gene predispose to colorectal adenomas. , 2008, Cancer research.

[27]  Pascal Croiseau,et al.  Analysis of North American Rheumatoid Arthritis Consortium data using a penalized logistic regression approach , 2009, BMC proceedings.

[28]  K. Lange,et al.  Coordinate descent algorithms for lasso penalized regression , 2008, 0803.3876.

[29]  K. Mossman.  The Wellcome Trust Case Control Consortium, U.K. , 2008 .

[30]  A. Singleton,et al.  Rare Structural Variants Disrupt Multiple Genes in Neurodevelopmental Pathways in Schizophrenia , 2008, Science.

[31]  I. Johnstone,et al.  Ideal spatial adaptation by wavelet shrinkage , 1994 .

[32]  R. Tibshirani,et al.  PATHWISE COORDINATE OPTIMIZATION , 2007, 0708.1485.

[33]  Michael Dean,et al.  Heterogeneity in the severity of cystic fibrosis and the role of CFTR gene mutations , 1994, Human Genetics.

[34]  Mee Young Park,et al.  L 1-regularization path algorithm for generalized linear models , 2006 .

[35]  W. Thompson,et al.  The genetic attributable risk of breast and ovarian cancer , 1996, Cancer.