COMUS: Clinician-Oriented locus-specific mutation detection and deposition system

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COMUS: Clinician-Oriented locus-specific mutation detection and deposition system
Sung Woong Cho; B C Kim; Hoyoung Ghang; J H Kim; D Park; Hak Min Kim; S Y Jung; K Y Yoo; H J Kim; S Lee; Jong Hwa Park
Bibliographic Citation
BMC Genomics, vol. 10, no. Sup 3, pp. S35-S35
Publication Year
Background: A disease-causing mutation refers to a heritable genetic change that is associated with a specific phenotype (disease). The detection of a mutation from a patient's sample is critical for the diagnosis, treatment, and prognosis of the disease. There are numerous databases and applications with which to archive mutation data. However, none of them have been implemented with any automated bioinformatics tools for mutation detection and analysis starting from raw data materials from patients. We present a Locus Specific mutation DB (LSDB) construction system that supports both mutation detection and deposition in one package. Results: COMUS (Clinician-Oriented locus specific MUtation detection and deposition System) is a mutation detection and deposition system for developing specific LSDBs. COMUS contains 1) a DNA sequence mutation analysis method for clinicians' mutation data identification and deposition and 2) a curation system for variation detection from clinicians' input data. To embody the COMUS system and to validate its clinical utility, we have chosen the disease hemophilia as a test database. A set of data files from bench experiments and clinical information from hemophilia patients were tested on the LSDB, KoHemGene, which has proven to be a clinician-friendly interface for mutation detection and deposition. Conclusion: COMUS is a bioinformatics system for detecting and depositing new mutations from patient DNA with a clinician-friendly interface. LSDBs made using COMUS will promote the clinical utility of LSDBs. COMUS is available at
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Ochang Branch Institute > Division of National Bio-Infrastructure > Laboratory Animal Resource & Research Center > 1. Journal Articles
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