000			01908nam a22001817a 4500
999			_c296486 _d296486
020			_a9781466595002
082			_a572.88 KOR-R
100			_a Eija Korpelainen
245			_aRNA-Seq Data Analysis : A practical approach
260			_a Boca Raton _b CRC Press, Taylor & Francis Group _c2015
300			_a xxiv, 298 p. : ill ; 24 cm.
490			_a Chapman and Hall/CRC mathematical & computational biology series.
505			_a Chapter 1. Introduction to RNA-seq -- chapter 2. Introduction to RNA-seq data analysis -- chapter 3. Quality control and preprocessing -- chapter 4. Aligning reads to reference -- chapter 5. Transcriptome assembly -- chapter 6. Quantitation and annotation-based quality control -- chapter 7. RNA-seq analysis framework in R and bioconductor -- chapter 8. Differential expression analysis -- chapter 9. Analysis of differential exon usage -- chapter 10. Annotating the results -- chapter 11. Visualization -- chapter 12. Small noncoding RNAs -- chapter 13. Computational analysis of small noncoding RNA sequencing data.
520			_a "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"-
650			_a RNA -- Analysis. Sequence Analysis, RNA -- methods. Transcriptome.
700			_aJarno Tuimala; Panu Somervuo; Mikael Huss; Garry Wong
942			_cBK