Buch, Englisch, 324 Seiten, Format (B × H): 156 mm x 241 mm, Gewicht: 586 g
A Practical Approach
Buch, Englisch, 324 Seiten, Format (B × H): 156 mm x 241 mm, Gewicht: 586 g
Reihe: Chapman & Hall/CRC Computational Biology Series
ISBN: 978-1-4665-9500-2
Verlag: Taylor & Francis Inc
The State of the Art in Transcriptome Analysis RNA 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 levels and to discover novel genes, transcripts, and whole transcriptomes.
Balanced Coverage of Theory and Practice.Each chapter starts with theoretical background, followed by descriptions of relevant analysis tools and practical examples. Accessible to both bioinformaticians and nonprogramming wet lab scientists, the examples illustrate the use of command-line tools, R, and other open source tools, such as the graphical Chipster software.
The Tools and Methods to Get Started in Your Lab. Taking readers through the whole data analysis workflow, this self-contained guide provides a detailed overview of the main RNA-seq data analysis methods and explains how to use them in practice. It is suitable for researchers from a wide variety of backgrounds, including biology, medicine, genetics, and computer science. The book can also be used in a graduate or advanced undergraduate course.
Korpelainen / Wong / Tuimala
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Balanced Coverage of Theory and Practice.Each chapter starts with theoretical background, followed by descriptions of relevant analysis tools and practical examples. Accessible to both bioinformaticians and nonprogramming wet lab scientists, the examples illustrate the use of command-line tools, R, and other open source tools, such as the graphical Chipster software.
The Tools and Methods to Get Started in Your Lab. Taking readers through the whole data analysis workflow, this self-contained guide provides a detailed overview of the main RNA-seq data analysis methods and explains how to use them in practice. It is suitable for researchers from a wide variety of backgrounds, including biology, medicine, genetics, and computer science. The book can also be used in a graduate or advanced undergraduate course.
Zielgruppe
Academic and Professional Practice & Development
Autoren/Hrsg.
Fachgebiete
Weitere Infos & Material
Introduction. Quality Control. Mapping, and Assembly. Differential Expression. Analysis of Small Non-Coding RNAs.
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