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This book examines a wide range of techniques on RNA extraction, detection, quantification, visualization, and genome-wide profiling, from conventional methods to state-of-the-art high throughput approaches.
RNA abundance analysis is one of the most important approaches for gene expression studies in the field of molecular biology. In RNA Abundance Analysis: Methods and Protocols, expert researchers cover a wide range of techniques on RNA extraction, detection, quantification, visualization, and genome-wide profiling, from conventional methods to state-of-the-art high throughput approaches. This volume includes detailed techniques to examine mRNAs, small non-coding RNAs, protein-associated small RNAs, sulfur-containing RNAs, viral and satellite RNAs, RNA isoforms, and alternatively spliced RNA variants from various organisms, as well as key discussions of computational data processing for genome-wide datasets.
It is difficult to imagine that the statistical analysis of compositional data has been a major issue of concern for more than 100 years. It is even more difficult to realize that so many statisticians and users of statistics are unaware of the particular problems affecting compositional data, as well as their solutions. The issue of ``spurious correlation'', as the situation was phrased by Karl Pearson back in 1897, affects all data that measures parts of some whole, such as percentages, proportions, ppm and ppb. Such measurements are present in all fields of science, ranging from geology, biology, environmental sciences, forensic sciences, medicine and hydrology. This book presents the history and development of compositional data analysis along with Aitchison's log-ratio approach. Compositional Data Analysis describes the state of the art both in theoretical fields as well as applications in the different fields of science. Key Features: Reflects the state-of-the-art in compositional data analysis. Gives an overview of the historical development of compositional data analysis, as well as basic concepts and procedures. Looks at advances in algebra and calculus on the simplex. Presents applications in different fields of science, including, genomics, ecology, biology, geochemistry, planetology, chemistry and economics. Explores connections to correspondence analysis and the Dirichlet distribution. Presents a summary of three available software packages for compositional data analysis. Supported by an accompanying website featuring R code. Applied scientists working on compositional data analysis in any field of science, both in academia and professionals will benefit from this book, along with graduate students in any field of science working with compositional data.
The State of the Art in Transcriptome AnalysisRNA sequencing (RNA-seq) data offers unprecedented information about the transcriptome, but harnessing this information with bioinformatics tools is typically a bottleneck. RNA-seq Data Analysis: A Practical Approach enables researchers to examine differential expression at gene, exon, and transcript le
RNA Methodologies: A Laboratory Guide for Isolation and Characterization, Sixth Edition provides the most up-to-date ribonucleic acid lab techniques for seasoned scientists and graduate students alike. This edition features new material on RNA sequencing, RNA in Situ Hybridization, non-coding RNAs, computational RNA biology, transcriptomes and bioinformatics, along with the latest advances in methods and protocols across the field of RNA investigation. As a leader in the field, Dr. Farrell provides a wealth of knowledge on the topic of RNA biology while also giving readers helpful hints and troubleshooting techniques from his own personal experience in this subject area. This book presents the essential knowledge and techniques to use when working with RNA for the experienced practitioner, while also aiding the beginner in fully understanding this important branch of molecular biology. Presents the latest information covering all aspects of working with RNA, delivering a holistic understanding of this leading field in molecular biology Builds from basic information on RNA techniques to in-depth protocols for specific applications Features new chapters on RNA sequencing and RNA in situ hybridization Includes new material on RNA clinical applications and innovations, including RNA therapeutics and RNA vaccines, with particular relevance to coronavirus Comprises the latest developments in transcriptomes and bioinformatics, with new material on computational RNA biology, RNA CHiP analysis, aptamer biology and RNA epigenetics
This is the fourth edition of the successful laboratory guide which has translated the rich story of riboneucleic acid for over fifteen years. RNA Methodologies 4e presents the latest collection of tested laboratory protocols for the isolation and characterization of eukaryotic and prokaryotic RNA with greater emphasis on transcript profiling, including quantification issues and elucidation of alternative transcription start sites. Collectively the chapters work together providing analysis with clear take-home lessons to assist researchers to understand RNA and to optimize time at the bench. The abundant use of flow charts, tables and graphs are especially helpful in the planning and implementation phases of a project and facilitate learning. 30% new material in this edition includes the addition of RNA isolation protocols including RNA isolation from tissue, expansion of PCR optimization analysis and RNA interference sections, the introduction of a new chapter dealing with the molecular biology of plants, and an expanded glossary. 30% new material with the addition of RNA isolation protocols including RNA isolation from tissue, expansion of PCR optimization analysis and RNA interference sections, the introduction of a new chapter dealing with the molecular biology of plants, and an expanded glossary Author is a well-recognized expert in the field of RNA experimentation and founded Exon-Intron, a well-known biotechnology educational workshop center Includes classic and contemporary techniques useful for all labs
Advances in RNA-sequencing (RNA-seq) technologies have provided an unprecedented opportunity to explore the gene expression landscape across individuals, tissues, and environments by efficiently profiling the RNA sequences present in the samples. When a reference genome sequence or a transcriptome of the sample is available, mapping-based RNA-seq analysis protocols align the RNA-seq reads to the reference sequences, identify novel transcripts, and quantify the abundance of expressed transcripts.The reads that fail to map to the human reference, known as unmapped reads, are a large and often overlooked output of standard RNA-seq analyses. Even in carefully executed experiments, the unmapped reads can comprise a considerable fraction of the complete set of reads produced, and can arise due to technical sequencing produced by low-quality and error-prone copies of the nascent RNA sequence being sampled. Reads can also remain unmapped due to unknown transcripts, recombined B and T cell receptor sequences, A-to-G mismatches from A-to-I RNA editing, trans-splicing, gene fusion, circular RNAs, and the presence of non-host RNA sequences (e.g. bacterial, fungal, and viral organisms). Unmapped reads represent a rich resource for the study of B and T cell receptor repertoires and the human microbiome system—without incurring the expense of additional targeted sequencing.This book introduces and describes the Read Origin Protocol (ROP), a tool that identifies the origin of both mapped and unmapped reads. The protocol first identifies human reads using a standard high-throughput algorithm to map them onto a reference genome and transcriptome. After alignment, reads are grouped into genomic (e.g. CDS, UTRs, introns) and repetitive (e.g. SINEs, LINEs, LTRs) categories. The rest of the ROP protocol characterizes the remaining unmapped reads, which failed to map to the human reference sequences.
A timely update of a highly popular handbook on statistical genomics This new, two-volume edition of a classic text provides a thorough introduction to statistical genomics, a vital resource for advanced graduate students, early-career researchers and new entrants to the field. It introduces new and updated information on developments that have occurred since the 3rd edition. Widely regarded as the reference work in the field, it features new chapters focusing on statistical aspects of data generated by new sequencing technologies, including sequence-based functional assays. It expands on previous coverage of the many processes between genotype and phenotype, including gene expression and epigenetics, as well as metabolomics. It also examines population genetics and evolutionary models and inference, with new chapters on the multi-species coalescent, admixture and ancient DNA, as well as genetic association studies including causal analyses and variant interpretation. The Handbook of Statistical Genomics focuses on explaining the main ideas, analysis methods and algorithms, citing key recent and historic literature for further details and references. It also includes a glossary of terms, acronyms and abbreviations, and features extensive cross-referencing between chapters, tying the different areas together. With heavy use of up-to-date examples and references to web-based resources, this continues to be a must-have reference in a vital area of research. Provides much-needed, timely coverage of new developments in this expanding area of study Numerous, brand new chapters, for example covering bacterial genomics, microbiome and metagenomics Detailed coverage of application areas, with chapters on plant breeding, conservation and forensic genetics Extensive coverage of human genetic epidemiology, including ethical aspects Edited by one of the leading experts in the field along with rising stars as his co-editors Chapter authors are world-renowned experts in the field, and newly emerging leaders. The Handbook of Statistical Genomics is an excellent introductory text for advanced graduate students and early-career researchers involved in statistical genetics.
This laboratory guide represents a growing collection of tried, tested and optimized laboratory protocols for the isolation and characterization of eukaryotic RNA, with lesser emphasis on the characterization of prokaryotic transcripts. Collectively the chapters work together to embellish the RNA story, each presenting clear take-home lessons, liberally incorporating flow charts, tables and graphs to facilitate learning and assist in the planning and implementation phases of a project. RNA Methodologies, 3rd edition includes approximately 30% new material, including chapters on the more recent technologies of RNA interference including: RNAi; Microarrays; Bioinformatics. It also includes new sections on: new and improved RT-PCR techniques; innovative 5’ and 3’ RACE techniques; subtractive PCR methods; methods for improving cDNA synthesis. * Author is a well-recognized expert in the field of RNA experimentation and founded Exon-Intron, a well-known biotechnology educational workshop center * Includes classic and contemporary techniques * Incorporates flow charts, tables, and graphs to facilitate learning and assist in the planning phases of projects