Simulating pedigrees ascertained for multiple disease-affected relatives

BackgroundStudies that ascertain families containing multiple relatives affected by disease can be useful for identification of causal, rare variants from next-generation sequencing data.ResultsWe present the R package SimRVPedigree, which allows researchers to simulate pedigrees ascertained on the basis of multiple, affected relatives. By incorporating the ascertainment process in the simulation, SimRVPedigree allows researchers to better understand the within-family patterns of relationship amongst affected individuals and ages of disease onset.ConclusionsThrough simulation, we show that affected members of a family segregating a rare disease variant tend to be more numerous and cluster in relationships more closely than those for sporadic disease. We also show that the family ascertainment process can lead to apparent anticipation in the age of onset. Finally, we use simulation to gain insight into the limit on the proportion of ascertained families segregating a causal variant. SimRVPedigree should be useful to investigators seeking insight into the family-based study design through simulation.

[1]  E. Minikel,et al.  Ascertainment bias causes false signal of anticipation in genetic prion disease. , 2014, American journal of human genetics.

[2]  K. Kojima,et al.  Survival of Mutant Genes , 1962, The American Naturalist.

[3]  X. Puente,et al.  Exome sequencing in multiplex autism families suggests a major role for heterozygous truncating mutations , 2014, Molecular Psychiatry.

[4]  Elizabeth A. Thompson,et al.  Statistical inference from genetic data on pedigrees , 2003 .

[5]  T. Beaty,et al.  Whole Exome Sequencing of Distant Relatives in Multiplex Families Implicates Rare Variants in Candidate Genes for Oral Clefts , 2014, Genetics.

[6]  Ingo Ruczinski,et al.  Inferring rare disease risk variants based on exact probabilities of sharing by multiple affected relatives , 2014, Bioinform..

[7]  Lawrence Carin,et al.  Negative Binomial Process Count and Mixture Modeling , 2012, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[8]  Felicitie C. Bell,et al.  Life Tables for the United States Social Security Area 1900-2100 , 2002 .

[9]  L. Cannon-Albright,et al.  A population-based analysis of clustering identifies a strong genetic contribution to lethal prostate cancer , 2013, Front. Genet..

[10]  M. Alda,et al.  Family-based exome-sequencing approach identifies rare susceptibility variants for lithium-responsive bipolar disorder. , 2013, Genome.

[11]  D. Thomas,et al.  Some Surprising Twists on the Road to Discovering the Contribution of Rare Variants to Complex Diseases , 2013, Human Heredity.

[12]  CruceanuCristiana,et al.  Family-based exome-sequencing approach identifies rare susceptibility variants for lithium-responsive bipolar disorder1 , 2013 .

[13]  S. Gruber,et al.  A review of statistical methods for testing genetic anticipation: looking for an answer in Lynch syndrome , 2010, Genetic epidemiology.

[14]  E. Wijsman The role of large pedigrees in an era of high-throughput sequencing , 2012, Human Genetics.

[15]  R. Nussbaum,et al.  Patterns of Single-Gene Inheritance , 2007 .

[16]  P M Conneally,et al.  Anticipation in Huntington's disease is inherited through the male line but may originate in the female. , 1988, Journal of medical genetics.