1. VarDetect: a nucleotide sequence variation exploratory tool VarDetect Chumpol Ngamphiw 1, Supasak Kulawonganunchai 2, Anunchai Assawamakin 3, Ekachai Jenwitheesuk 1 and Sissades Tongsima 1 1 Genome Institute, National Center for Genetic Engineering and Biotechnology, Thailand 2 Department of Computer Science, School of Engineering and Technology, Asian Institute of Technology, Thailand 3 Division of Medical Genetics, Siriraj Hospital, Mahidol University, Thailand

2. 2Outline  Nucleotide sequence variation  Common sequencing artifacts  VarDetect: algorithms overview  Experimental results  Conclusions

3. 3 http://urgi.versailles.inra.fr/projects/GnpSNP/general_documentation.php Nucleotide sequence variation

4. 4 Common sequencing artifacts http://seqcore.brcf.med.umich.edu/doc/dnaseq/trouble/badseq.html

5. 5 VarDetect: algorithms Reading nucleotide traces Base-Calling Alignment of input sequences to the reference sequence SNPs identification Re-sampling Pre-alignment, Alignment Enhancement CodeMap

6. 6 Chromatogram trace: base-calling Reading nucleotide traces: base-calling Base-calling with BioJava

7. 7 Calculate peak intensity ratio Reading nucleotide traces: intensity ratio Q v – Q o ( δ ) for increasing the confidence of SNP detection

8. 8 Partitioning and Re-sampling (PnR) technique Reading nucleotide traces: partition and re-sampling

9. 9 Pooled DNA: possible biallelic pattern Base-call parameters setting in VarDetect

10. 10 Pre-alignment & alignment enhancement Alignment

11. 11 CodeMap analysis SNPs identification: CodeMap

12. 12 VarDetect: main graphical user interface http://www.biotec.or.th/GI/tools/vardetect

13. 13 Experimental results - Tocharoentanaphol C, et al. : Evaluation of resequencing on number of tag SNPs of 13 atherosclerosis-related genes in Thai population. J Hum Genet 2008, 53:74–86. - Thailand SNP discovery project : http://www.biotec.or.th/thaisnp

14. 14Conclusions We presented novel algorithm to interpret fluorescent-based chromatograms in an automatic fashion and platform independent (Java). Three main heuristic procedures are employed: Turning point (bell shape) detection (PnR algorithm). Increasing the SNP detection confidence by checking the difference between vicinity and observed quality values (Q v - Q o ). Introduction of CodeMap to detect pattern of SNP and Indel. VarDetect offers the most features including the ability to detect SNPs from pooled DNA samples. VarDetect use of XML annotated reference sequence to cross check the SNP discovery results within the tool without using external applications. VarDetect’s heuristics minimize both false positive and negative errors reducing the effort needed to detect and validate SNPs, making it the tool of choice for automatic SNP detection.

15. 15Acknowledgements  Dr. Mazazumi Takahashi, Centre National de Genotypage (CNG), France  Dr. Philip Shaw  Dr. Prasit Palittapolgarnpim  Dr. Chintana Tocharoentanaphol, Chulabhorn Research Institute  Dr. Chanin Limwongse, Siriraj Hospital, Mahidol University  Thailand SNP discovery project  National Center for Genetic Engineering and Biotechnology (BIOTEC)

16. Thank You For Your Attention VarDetect Chumpol Ngamphiw 1, Supasak Kulawonganunchai 2, Anunchai Assawamakin 3, Ekachai Jenwitheesuk 1 and Sissades Tongsima 1 1 Genome Institute, National Center for Genetic Engineering and Biotechnology, Thailand 2 Department of Computer Science, School of Engineering and Technology, Asian Institute of Technology, Thailand 3 Division of Medical Genetics, Siriraj Hospital, Mahidol University, Thailand