A practical Guide to Next Generation Sequencing Data Analysis
- Available for pre-order on March 23, 2023. Item will ship after April 13, 2023
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Bioinformatics: A Practical Guide to Next Generation Sequencing Data Analysis contains the latest material in the subject, covering NGS applications and meeting the requirements of a complete semester course. This book digs deep into analysis, providing both concept and practice to satisfy the exact need of researchers seeking to understand and use NGS data reprocessing, genome assembly, variant discovery, gene profiling, epigenetics, and metagenomics. The book does not introduce the analysis pipelines in a black box, but with detailed analysis steps to provide readers with the scientific and technical backgrounds required to enable them to conduct analysis with confidence and understanding. The book is primarily designed as a companion for researchers and graduate students using sequencing data analysis, but will also serve as a textbook for teachers and students in biology and bioscience.
Table of Contents
Sequencing and Raw Sequence Data Quality Control, Nucleic acids, Sequencing, Sequencing depth and read quality, FASTQ files, FASTQ read quality assessment, Preprocessing of the FASTQ reads, Mapping of sequence reads to the reference genomes, Introduction to sequence mapping, Read mapping, Read sequence alignment and aligners, Manipulating alignments in SAM/BAM files, Reference-guided genome assembly, De novo Genome Assembly, Introduction to De Novo genome assembly, Examples of De Novo assemblers, Genome Assembly Quality Assessment, Variant Discovery, Introduction to genetic variations, Variant calling programs, Visualizing variants, Variant annotation and prioritization, RNA-seq data analysis, Introduction to RNA-seq, RNA-seq data applications, RNA-seq data analysis workflow, Chromatin Immunoprecipitation sequencing, Introduction to chromatin immunoprecipitation, ChIP sequencing, ChIP-seq analysis workflow, Targeted Gene Metagenomic Data Analysis, Introduction to metagenomics, Analysis workflow, Data Analysis with QIIME2, Shotgun metagenomic data analysis, Introduction, Shotgun metagenomic analysis workflow
Hamid D. Ismail received his M.Sc. and Ph.D. in computational science from North Carolina Agricultural and Technical State University (NC A&T), USA, and DVM and B.Sc. from the University of Khartoum, Sudan. He earned several professional certifications including SAS Advanced Programmer and SQL Expert Programmer. Currently he works as a post-doc scholar at Michigan Technological University and adjunct professor of Data Science and Bioinformatics at NC A&T State University. Hamid is a bioinformatician, biologist, data scientist, statistician, and machine learning specialist. He contributed widely to the field of bioinformatics by developing bioinformatics tools and methods for applications of machine learning on genomic data.