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

By: Korpelainen, Eija
Contributor(s): Tuimala, Jarno [author.] | Somervuo, Panu [author.] | Huss, Mikael [author.] | Wong, Garry [author.]
Material type: TextTextSeries: Chapman & Hall/CRC Mathematical and computational biology seriesPublisher: Boca Raton : CRC Press, Taylor & Francis Group, [2015]Edition: 1st edDescription: xxiv, 298 pages : illustrations ; 24 cmContent type: text Media type: unmediated Carrier type: volumeISBN: 9781466595002 (hardcover : alk. paper); 1466595000 (hardcover : alk. paper)Subject(s): Sequence Analysis, RNA -- methods | Transcriptome | Statistics as TopicDDC classification: 572.88 LOC classification: QP623 | .K67 2015Summary: "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"--
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572.88 K.E.R 2015 (Browse shelf) Available 23734

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"--

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