Abstract
To efficiently manipulate large amounts of genotype data generated with fluorescently labeled dinucleotide markers, we developed a Microsoft Access database management system, named GenoDB. GenoDB offers several advantages. First, it accommodates the dynamic nature of the accumulations of genotype data during the genotyping process; some data need to be confirmed or replaced 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, including autocomparison of the raw data read by different technicians from the same gel, autoadjustment among the allele fragment-size data from cross-runs or cross-platforms, autobinning of alleles, and autocompilation of genotype data for suitable programs to perform inheritance check in pedigrees. Third, GenoDB provides functions to track electrophoresis gel files to locate gel or sample sources for any resultant genotype data, which is extremely helpful for double-checking consistency of raw and final data and for directing repeat experiments. In addition, the user-friendly graphic interface of GenoDB renders processing of large amounts of data much less labor-intensive. Furthermore, GenoDB has built-in mechanisms to detect some genotyping errors and to assess the quality of genotype data that then are summarized in the statistic reports automatically generated by GenoDB. The GenoDB can easily handle >500,000 genotype data entries, a number more than sufficient for typical whole-genome linkage studies. The modules and programs we developed for the GenoDB can be extended to other database platforms, such as Microsoft SQL server, if the capability to handle still greater quantities of genotype data simultaneously is desired.
| Original language | English |
|---|---|
| Pages (from-to) | 1304-1314 |
| Number of pages | 11 |
| Journal | Genome Research |
| Volume | 11 |
| Issue number | 7 |
| DOIs | |
| State | Published - 2001 |
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All Science Journal Classification (ASJC) codes
- Genetics
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Toward high-throughput genotyping : Dynamic and automatic software for manipulating large-scale genotype data using fluorescently labeled dinucleotide markers. / Li, Jin Long; Deng, Hongyi; Lai, Dong Bing; Xu, Fuhua; Chen, Jian; Gao, Guimin; Recker, Robert R.; Deng, Hong Wen.
In: Genome Research, Vol. 11, No. 7, 2001, p. 1304-1314.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Toward high-throughput genotyping
T2 - Dynamic and automatic software for manipulating large-scale genotype data using fluorescently labeled dinucleotide markers
AU - Li, Jin Long
AU - Deng, Hongyi
AU - Lai, Dong Bing
AU - Xu, Fuhua
AU - Chen, Jian
AU - Gao, Guimin
AU - Recker, Robert R.
AU - Deng, Hong Wen
PY - 2001
Y1 - 2001
N2 - To efficiently manipulate large amounts of genotype data generated with fluorescently labeled dinucleotide markers, we developed a Microsoft Access database management system, named GenoDB. GenoDB offers several advantages. First, it accommodates the dynamic nature of the accumulations of genotype data during the genotyping process; some data need to be confirmed or replaced 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, including autocomparison of the raw data read by different technicians from the same gel, autoadjustment among the allele fragment-size data from cross-runs or cross-platforms, autobinning of alleles, and autocompilation of genotype data for suitable programs to perform inheritance check in pedigrees. Third, GenoDB provides functions to track electrophoresis gel files to locate gel or sample sources for any resultant genotype data, which is extremely helpful for double-checking consistency of raw and final data and for directing repeat experiments. In addition, the user-friendly graphic interface of GenoDB renders processing of large amounts of data much less labor-intensive. Furthermore, GenoDB has built-in mechanisms to detect some genotyping errors and to assess the quality of genotype data that then are summarized in the statistic reports automatically generated by GenoDB. The GenoDB can easily handle >500,000 genotype data entries, a number more than sufficient for typical whole-genome linkage studies. The modules and programs we developed for the GenoDB can be extended to other database platforms, such as Microsoft SQL server, if the capability to handle still greater quantities of genotype data simultaneously is desired.
AB - To efficiently manipulate large amounts of genotype data generated with fluorescently labeled dinucleotide markers, we developed a Microsoft Access database management system, named GenoDB. GenoDB offers several advantages. First, it accommodates the dynamic nature of the accumulations of genotype data during the genotyping process; some data need to be confirmed or replaced 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, including autocomparison of the raw data read by different technicians from the same gel, autoadjustment among the allele fragment-size data from cross-runs or cross-platforms, autobinning of alleles, and autocompilation of genotype data for suitable programs to perform inheritance check in pedigrees. Third, GenoDB provides functions to track electrophoresis gel files to locate gel or sample sources for any resultant genotype data, which is extremely helpful for double-checking consistency of raw and final data and for directing repeat experiments. In addition, the user-friendly graphic interface of GenoDB renders processing of large amounts of data much less labor-intensive. Furthermore, GenoDB has built-in mechanisms to detect some genotyping errors and to assess the quality of genotype data that then are summarized in the statistic reports automatically generated by GenoDB. The GenoDB can easily handle >500,000 genotype data entries, a number more than sufficient for typical whole-genome linkage studies. The modules and programs we developed for the GenoDB can be extended to other database platforms, such as Microsoft SQL server, if the capability to handle still greater quantities of genotype data simultaneously is desired.
UR - http://www.scopus.com/inward/record.url?scp=0034925238&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=0034925238&partnerID=8YFLogxK
U2 - 10.1101/gr.159701
DO - 10.1101/gr.159701
M3 - Article
C2 - 11435414
AN - SCOPUS:0034925238
VL - 11
SP - 1304
EP - 1314
JO - Genome Research
JF - Genome Research
SN - 1088-9051
IS - 7
ER -