Titlebook: Genome Data Analysis; Ju Han Kim Textbook 2019 Springer Nature Singapore Pte Ltd. 2019 Genome data analysis.Bioinformatics.Practice in dat

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Next-Generation Sequencing Technology and Personal Genome Data Analysis various annotation and detection methods of SNP/InDel from the obtained sequences. This chapter describes the difference in analytical methods between common variants and rare variants, and an analysis approach using biological pathways, pharmacogenomics, and information of racial differences using

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Personal Genome Data Analysiss approaches for adding SNP annotations and medicinal interpretations, using open sources based on personal genome data and genome variation information. This chapter will cover the following: (1) effective use of SNP data in SNPedia, (2) auto annotations of large volume of SNPs using Promethease ap

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Gene Set Approaches and Prognostic Subgroup Predictionred genes obtained by microarray data clustering analysis and test the statistical significance of different prognoses between clusters. It provides an understanding of the correlation between biological interpretation and GO and pathway analysis of the clustered genes and an interpretation with GSE