Toward high-throughput genotyping: Dynamic and automatic software for manipulating large-scale genotype data using fluorescently labeled dinucleotidemarkers

Citation
Jl. Li et al., Toward high-throughput genotyping: Dynamic and automatic software for manipulating large-scale genotype data using fluorescently labeled dinucleotidemarkers, GENOME RES, 11(7), 2001, pp. 1304-1314
Citations number
26
Categorie Soggetti
Molecular Biology & Genetics
Journal title
GENOME RESEARCH
ISSN journal
10889051 → ACNP
Volume
11
Issue
7
Year of publication
2001
Pages
1304 - 1314
Database
ISI
SICI code
1088-9051(200107)11:7<1304:THGDAA>2.0.ZU;2-9
Abstract
To efficiently manipulate large amounts of genotype data generated with flu orescently labeled dinucleotide markers, we developed a Microsoft Access da tabase management system, named GenoDB. GenoDB offers several advantages. F irst, it accommodates the dynamic nature of the accumulations of genotype d ata during the genotyping process; some data need to be confirmed or replac ed by repeat lab procedures. By using GenoDB, the raw genotype data can be imported easily and continuously and incorporated into the database during the genotyping process that may continue over an extended period of time in large projects. Second, almost all of the procedures are automatic, includ ing autocomparison of the raw data read by different technicians from the s ame gel, autoadjustment among the allele fragment-size data from cross-runs or cross-platforms, autobinning of alleles, and autocompilation of genotyp e data for suitable programs to perform inheritance check in pedigrees. Thi rd, GenoDB provides functions to track electrophoresis gel files to locate gel or sample sources for any resultant genotype data, which is extremely h elpful for double-checking consistency of raw and final data and for direct ing repeat experiments. In addition, the user-friendly graphic interface of GenoDB renders processing of large amounts of data much less labor-intensi ve. Furthermore, GenoDB has built-in mechanisms to detect some genotyping e rrors and to assess the quality of genotype data that then are summarized i n the statistic reports automatically generated by GenoDB. The GenoDB can e asily handle >500,000 genotype data entries, a number more than sufficient for typical whole-genome linkage studies. The modules and programs we devel oped for the GenoDB can be extended to other database platforms, such as Mi crosoft SQL server, if the capability to handle still greater quantities of genotype data simultaneously is desired.