A Family-Based Probabilistic Method for Capturing De Novo Mutations from High-Throughput Short-Read Sequencing Data
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Reed A. Cartwright
Recent advances in high-throughput DNA sequencing technologies and associated statistical analyses have enabled in-depth analysis of whole-genome sequences. As this technology is applied to a growing number of individual human genomes, entire families are now being sequenced. Information contained within the pedigree of a sequenced family can be leveraged when inferring the donors' genotypes. The presence of a de novo mutation within the pedigree is indicated by a violation of Mendelian inheritance laws. Here, we present a method for probabilistically inferring genotypes across a pedigree using high-throughput sequencing data and producing the posterior probability of de novo mutation at each genomic site examined. This framework can be used to disentangle the effects of germline and somatic mutational processes and to simultaneously estimate the effect of sequencing error and the initial genetic variation in the population from which the founders of the pedigree arise. This approach is examined in detail through simulations and areas for method improvement are noted. By applying this method to data from members of a well-defined nuclear family with accurate pedigree information, the stage is set to make the most direct estimates of the human mutation rate to date.
©2012 Walter de Gruyter GmbH & Co. KG, Berlin/Boston
Artikel in diesem Heft
- Editorial Introduction
- Special Issue on Computational Statistical Methods for Genomics and Systems Biology
- Article
- A Generalized Hidden Markov Model for Determining Sequence-based Predictors of Nucleosome Positioning
- Gene Filtering in the Analysis of Illumina Microarray Experiments
- Principal Components of Heritability for High Dimension Quantitative Traits and General Pedigrees
- Bayesian Sparsity-Path-Analysis of Genetic Association Signal using Generalized t Priors
- A Family-Based Probabilistic Method for Capturing De Novo Mutations from High-Throughput Short-Read Sequencing Data
- Adjusting for Spurious Gene-by-Environment Interaction Using Case-Parent Triads
- Querying Genomic Databases: Refining the Connectivity Map
- A Model-Based Analysis to Infer the Functional Content of a Gene List
- Candidate Pathway Based Analysis for Cleft Lip with or without Cleft Palate
- Improving Pedigree-based Linkage Analysis by Estimating Coancestry Among Families
Artikel in diesem Heft
- Editorial Introduction
- Special Issue on Computational Statistical Methods for Genomics and Systems Biology
- Article
- A Generalized Hidden Markov Model for Determining Sequence-based Predictors of Nucleosome Positioning
- Gene Filtering in the Analysis of Illumina Microarray Experiments
- Principal Components of Heritability for High Dimension Quantitative Traits and General Pedigrees
- Bayesian Sparsity-Path-Analysis of Genetic Association Signal using Generalized t Priors
- A Family-Based Probabilistic Method for Capturing De Novo Mutations from High-Throughput Short-Read Sequencing Data
- Adjusting for Spurious Gene-by-Environment Interaction Using Case-Parent Triads
- Querying Genomic Databases: Refining the Connectivity Map
- A Model-Based Analysis to Infer the Functional Content of a Gene List
- Candidate Pathway Based Analysis for Cleft Lip with or without Cleft Palate
- Improving Pedigree-based Linkage Analysis by Estimating Coancestry Among Families
