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Bindng
NextGeneration Sequencing Data Analysis
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A Practical Guide to the Highly Dynamic Area of Massively Parallel SequencingThe development of genome and transcriptome sequencing technologies has led to a paradigm shift in life science research and disease diagnosis and prevention. Scientists are now able to see how human diseases and phenotypic changes are connected to DNA mutation, polymorphism, genome structure, and epigenomic abnormality. NextGeneration Sequencing Data Analysis shows how nextgeneration sequencing (NGS) technologies are applied to transform nearly all aspects of biological research.The book walks readers through the multiple stages of NGS data generation and analysis in an easytofollow fashion. It covers every step in each stage, from the planning stage of experimental design, sample processing, sequencing strategy formulation, the early stage of base calling, reads quality check and data preprocessing to the intermediate stage of mapping reads to a reference genome and normalization to more advanced stages specific to each application. All major applications of NGS are covered, including: RNAseq: mRNAseq and small RNAseq Genotyping and variant discovery through genome resequencing De novo genome assembly ChIPseq to study DNAprotein interaction Methylated DNA sequencing on epigenetic regulation Metagenome analysis through community genome shotgun sequencingBefore detailing the analytic steps for each of these applications, the book presents the ins and outs of the most widely used NGS platforms, with sidebyside comparisons of key technical aspects. This helps practitioners decide which platform to use for a particular project. The book also offers a perspective on the development of DNA sequencing technologies, from Sanger to futuregeneration sequencing technologies.The book discusses concepts and principles that underlie each analytic step, along with software tools for implementation. It highlights key features of the tools while omitting tedious details to provide an easytofollow guide for practitioners in life sciences, bioinformatics, and biostatistics. In addition, references to detailed descriptions of the tools are given for further reading if needed. The accompanying website for the book provides stepbystep, realworld examples of how to apply the tools covered in the text to research projects. All the tools are freely available to academic users.
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