title: Genome mapping statistics and bioinformatics.
abstract: The unprecedented availability of genome sequences, coupled with user-friendly, web-enabled search and analysis tools allows practitioners to locate interesting genome features or sequence tracts with relative ease. Although many public model organism- and genome-mapping resources offer pre-mapped genome browsing, biologists also still need to perform de novo mapping analyses. Correct interpretation of the results in genome annotation databases or the results of one's individual analyses requires at least a conceptual understanding of the statistics and mechanics of genome searches, the expected results from statistical considerations, as well as the algorithms used by different search tools. This chapter introduces the basic statistical results that underlie mapping of nucleotide sequences to genomes and briefly surveys the common programs and algorithms that are used to perform genome mapping, all available via public hosted web sites. Selection of the appropriate sequence search and mapping tool will often demand tradeoffs in sensitivity and specificity relating to the statistics of the search.
authors.affiliation: Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA.
authors.forename: Josyf C
authors.initials: JC
authors.lastname: Mychaleckyj
mesh_terms: D001483:Base Sequence; D002874:Chromosome Mapping / Q000379:methods*; D019295:Computational Biology / Q000379:methods*; D003627:Data Interpretation, Statistical; D030541:Databases, Genetic; D015894:Genome, Human / Q000235:genetics*; D006801:Humans; D008969:Molecular Sequence Data; D012984:Software