Thai CNV

Thai CNV Database


ThaiCNV is the first comprehensive Copy Number Variation (CNV) database in Thai population. CNVs were called from high quality, high-density Illumina SNP array data of the 3.017 Thai individuals that was generated under collaboration between Department of Medical Science, Ministry of Public Health, Thailand Center of Excellence for Life Science (TCELS), and Center for Genomic Medicine, RIKEN, Japan [1-5].

Informed consent forms have been collected and the research protocols have been approved by the Institutional Review Board (IRB) of Faculty of Medicine Ramathibodi Hospital, Mahidol University. This database is a collaborative effort between researchers from Faculty of Medicine Ramathibodi Hospital, Faculty of Medicine Siriraj Hospital, Faculty of Science, Faculty of Information and Communication Technology, and Integrative Computational Bioscience Center (ICBS), Mahidol University. The database contains consensus CNV predicted from PennCNV [6] and CNV [7]. Briefly, PennCNV uses hidden-Markov model and CNV Workshop uses segmentation algorithm to predict the genomic location of CNVs. Identical CNV calls were defined as CNVs with at least 60% overlapping segments accross all algorithms [7]. The database has been designed to facilitate both CNV query and CNV visualization based on a Generic Genome Browser [8]. The data can be exported and visualized through public genome browser, such as UCSC genome browser and Ensembl. For comparison and interpretation purposes, we also provide interactive links from each CNV to other large CNV database.


  1. To discover and determine the frequency if Copy Number Variation (CNVs) in Thai population.
  2. To make CNV genotypic information available for public access through database hosted by ICBS. This database contains CNV frequencies, types of CNV, and genomic locations.
  3. To create a comprehensive database of CNV specific to Thai population that can be used as control for clinical interpretation or in population genetics study.


  1. Mahasirimongkol S. et al., Genome-wide association studies of tuberculosis in Asians identify distinct at-risk locus for young tuberculosis. J Hum Genet. 2012 PMID: 22551897.
  2. Jongjaroenprasert W. et al., A genome-wide association study identifies novel susceptibility genetic variation for thyrotoxic hypokalemic periodic paralysis. J Hum Genet. 2012. PMID: 22399142.
  3. Chantarangsu S. et al., Genome-wide association study identifies variations in 6p21.3 associated with nevirapine-induced rash. Clin Infect Dis. 2011 Aug;53(4):341-8. doi: 10.1093/cid/cir403. PMID: 21810746.
  4. Nuinoon M. et al., A genome-wide association identified the common genetic variants influence disease severity in beta0-thalassemia/hemoglobin E. Hum Genet. 2010 Mar;127(3):303-14. doi: 10.1007/s00439-009-0770-2. PMID: 20183929.
  5. Wangsomboonsiri W. et al., Association between HLA-B*4001 and lipodystrophy among HIV-infected patients from Thailand who received a stavudine-containing antiretroviral regimen. Clin Infect Dis. 2010 Feb 15;50(4):597-604. doi: 10.1086/650003. PMID: 20073992.
  6. Wang K. et al., an integrated hidden Markov model designed for high-resolution copy number variation detection in whole-genome SNP genotyping data. Genome Res. 2007 Nov;17(11):1665-74. Epub 2007 Oct 5. PMID: 17921354.
  7. Gai X. et al., CNV Workshop: an integrated platform for high-throughput copy number variation discovery and clinical diagnostics. BMC Bioinformatics. 2010 Feb 4;11:74. doi: 10.1186/1471-2105-11-74. PMID: 20132550.
  8. Stein L.D. et al., The generic genome browser: a building block for a model organism system database. Genome Res. 2002 Oct;12(10):1599-610. PubMed PMID: 12368253.