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RNA-seq data analysis : a practical approach / Eija Korpelainen, Jarno Tuimala, Panu Somervuo, Mikael Huss, Garry Wong.

By: Contributor(s): Material type: TextLanguage: English Series: Chapman & Hall/CRC mathematical and computational biology seriesPublisher: Boca Raton : Taylor & Francis, 2015Description: xxiv, 298 pages illustrationsContent type:
  • text
Media type:
  • unmediated
Carrier type:
  • volume
ISBN:
  • 9781466595002
Subject(s): DDC classification:
  • 572.88 23/swe
NLM classification:
  • 2014 M-484
  • QU 58.7
Summary: "RNA-seq offers unprecedented information about transcriptome, but harnessing this information with bioinformatics tools is typically a bottleneck. This self-contained guide enables researchers to examine differential expression at gene, exon, and transcript level and to discover novel genes, transcripts, and whole transcriptomes. Each chapter starts with theoretical background, followed by descriptions of relevant analysis tools. The book also provides examples using command line tools and the R statistical environment. For non-programming scientists, the same examples are covered using open source software with a graphical user interface"--Provided by publisher.
Holdings
Cover image Item type Current library Home library Collection Shelving location Call number Materials specified Vol info URL Copy number Status Notes Date due Barcode Item holds Item hold queue priority Course reserves
Books from NU Högskolan Väst Övre plan / Upper floor NU-biblioteket 572 Korpelainen Available 6004300049490
Total holds: 0

Includes bibliographical references and index.

"RNA-seq offers unprecedented information about transcriptome, but harnessing this information with bioinformatics tools is typically a bottleneck. This self-contained guide enables researchers to examine differential expression at gene, exon, and transcript level and to discover novel genes, transcripts, and whole transcriptomes. Each chapter starts with theoretical background, followed by descriptions of relevant analysis tools. The book also provides examples using command line tools and the R statistical environment. For non-programming scientists, the same examples are covered using open source software with a graphical user interface"--Provided by publisher.

Imported from: ilsz3950.nlm.nih.gov:7091/voyager (Do not remove)