Using binary decision tree for phasing SNPs from next-generation sequencing data
碩士 === 國立高雄應用科技大學 === 資訊工程系 === 102 === SNPs (Single nucleotide polymorphisms) are the variation of single nucleotides occurred at one position on the chromosomes。It is the most abundant，broad，representative and hereditary genetic variability。SNPs which locate in the DNA coding regions have direct i...
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| Format: | Others |
| Language: | zh-TW |
| Published: |
2013
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| Online Access: | http://ndltd.ncl.edu.tw/handle/85246172815816708613 |
| Summary: | 碩士 === 國立高雄應用科技大學 === 資訊工程系 === 102 === SNPs (Single nucleotide polymorphisms) are the variation of single nucleotides occurred at one position on the chromosomes。It is the most abundant，broad，representative and hereditary genetic variability。SNPs which locate in the DNA coding regions have direct influence and may control the composition of proteins。Therefore, identifying the SNPs in the disease-related genes is of great significance。So far，most studies have focused on discovering a single causative SNP or a statistically significant collection for a certain disease。However, they do not provide the disease haplotype。
Our approach is first using computer algorithms for aligning the SNPs which are located in the coding regions of genes。 Next we use the SAMtools for finding SNP from the sample。Finally we construct a full binary decision tree for selecting the highest possible disease haplotype。Ultimately, we expect this method to be helpful for analysis on personal medicine。
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