title: Genome-scale sequencing to identify genes involved in Mendelian disorders.
abstract: The analysis of genome-scale sequence data can be defined as the interrogation of a complete set of genetic instructions in a search for individual loci that produce or contribute to a pathological state. Bioinformatic analysis of sequence data requires sufficient discriminant power to find this needle in a haystack. Current approaches make choices about selectivity and specificity thresholds, and the quality, quantity, and completeness of the data in these analyses. There are many software tools available for individual, analytic component-tasks, including commercial and open-source options. Three major types of techniques have been included in most published exome projects to date: frequency/population genetic analysis, inheritance state consistency, and predictions of deleteriousness. The required infrastructure and use of each technique during analysis of genomic sequence data for clinical and research applications are discussed. Future developments will alter the strategies and sequence of using these tools and are also discussed.
authors: Undiagnosed Diseases Program, National Institutes of Health, Bethesda, Maryland.
authors: Thomas C
authors: TC
authors: Markello
authors: Undiagnosed Diseases Program, National Institutes of Health, Bethesda, Maryland.
authors: David R
authors: DR
authors: Adams
mesh_terms: D001483:Base Sequence; D002874:Chromosome Mapping; D019295:Computational Biology / Q000379:methods*; D059472:Exome; D005787:Gene Frequency; D020022:Genetic Predisposition to Disease; D005820:Genetic Testing / Q000379:methods*; D015894:Genome, Human; D060005:Genotyping Techniques; D059014:High-Throughput Nucleotide Sequencing / Q000379:methods*; D006801:Humans; D016415:Sequence Alignment; D017422:Sequence Analysis, DNA / Q000379:methods*; D012984:Software
keywords: Mendelian inheritance; bioinformatics; clinical sequencing; exome; next generation sequencing