Practical Bioinformatics for Beginners: From Raw Sequence Analysis to Machine Learning Applications

Description

Next-Generation Sequencing (NGS) is increasingly common and has applications in various fields such as clinical diagnosis, animal and plant breeding, and conservation of species. This incredible tool has become cost-effective. However, it generates a deluge of sequence data that requires efficient analysis. The highly sought-after skills in computational and statistical analyses include machine learning and, are essential for successful research within a wide range of specializations, such as identifying causes of cancer, vaccine design, new antibiotics, drug development, personalized medicine, and increased crop yields in agriculture. This invaluable book provides step-by-step guides to complex topics that make it easy for readers to perform specific analyses, from raw sequenced data to answer important biological questions using machine learning methods. It is an excellent hands-on material for lecturers who conduct courses in bioinformatics and as reference material for professionals. The chapters are standalone recipes making them suitable for readers who wish to self-learn selected topics. Readers gain the essential skills necessary to work on sequenced data from NGS platforms; hence, making themselves more attractive to employers who need skilled bioinformaticians. Contents Foreword from the First Edition Foreword from the First Edition Preface Acknowledgements Chapter 1 Introduction to Next Generation Sequencing Technologies A Brief History of DNA Sequencing Next Generation Sequencing Technologies 454 ABI SOLiD Illumina Ion Torrent Pacific Biosciences Oxford Nanopore Technologies Informatics Challenges References Chapter 2 Primer on Linux Introduction Listing the Contents of a Directory Create Directory Print Working Directory Change Directory Download Data File Compression Display the Contents of a File Count the Number of Lines Search a Pattern Combine Multiple Commands Together Converting a FASTQ File into a Tabular Format Pattern Matching Using Awk Sort and Extract Unique Sequences Convert Reads into FASTA Format Sequences Write a Shell Script to Split Sequences into Individual Files Changing File Permissions Run the Bash Script Summary Chapter 3 Inspection of Sequence Quality Introduction FastQC Installation Step in Linux Environment Download Datasets Fastx-toolkit & FASTQ Processing Utilities Installation Step in Linux Environment Conclusion References Chapter 4 Alignment of Sequenced Reads Introduction Practical Short Reads Alignment Dataset Software Requirements Alignment Process SAM to BAM conversion Sort BAM alignments Alternative: novoAlign & novoSort View BAM alignment with IGV References Chapter 5 Establish a Research Workflow Introduction Materials Shell Scripts Galaxy Conclusion References Chapter 6 De novo Assembly of a Genome Introduction Overall Steps Download Sequences Filter Out Bad Reads Assemble the Genome(s) Hybrid assembly with PacBio reads Long SE read assembly (PacBio) Long SE read assembly (Oxford Nanopore) Check the Quality of the Genome Discussion and Conclusion References Chapter 7 Exome Sequencing Introduction General Workflow of WES Background Information on the Practical Software Datasets Download Datasets Creating a New Folder Mapping of Raw Data to the Reference Genome Variants Calling Prediction of SNVs and Indels Effects Visualization Conclusion References Chapter 8 Transcriptomics Introduction Practical Datasets & Software Dataset Software Required Reads Pre-processing & Quality Control (QC) Prepare Files Perform Initial QC Trimming for Bad Quality and Adapters Run FastQC on Trimmed Reads HISAT2: Reads Alignment Prepare Files Generate Genome Index Reads Alignment Single Sample Expression Gene Expression Count Using HTSEQ Gene Expression Count Using featureCounts Gene Expression Count StringTie Differential Expression edgeR & Limma for Counts Data Perform edgeR and limma and linear model References Chapter 9 Metagenomics Introduction Introduction to MG-RAST Server Workflow Registration to MG-RAST Submission of Dataset Job Status Monitor Data Analysis and Result Viewing Analysis of Shotgun Metagenomic Sequence Datasets Getting Started Uploading and Submission Results Analysis of 16S rRNA-targeted Metagenomic Sequence Datasets Getting Started Visualization Conclusion References Chapter 10 Applications of NGS Data Introduction Classical Linkage Map OneMap (2.1.3) Installation Input formatting Linkage mapping analysis From Linkage Map to Physical Map Genome-wide Association Studies (GWAS) PLINK 1.90 Beta Installation Input files and format Download datasets Association analysis Summary References Chapter 11 Predicting Human Enhancers with Machine Learning Introduction Setting up the Software Environment Transforming the Data One-hot encoding with a simple convolutional neural network (CNN) References Index