''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, trans
RNA-seq data analysis a practical approach
โ Scribed by Huss, Mikael; Korpelainen, Eija; Somervuo, Panu; Tuimala, Jarno; Wong, Garry
- Year
- 2017
- Tongue
- English
- Leaves
- 322
- Series
- Chapman & Hall/CRC Mathematical and computational biology series
- Category
- Library
No coin nor oath required. For personal study only.
โฆ Table of Contents
Content: IntroductionIntroduction to RNA-seq data analysisQuality control and preprocessingAligning reads to reference and visualizing them in genomic contextTranscriptome assemblyAnnotation-based quality control and quantitation of gene expressionRNA-seq analysis framework in R and BioconductorDifferential expression analysisAnalysis of differential exon usageAnnotating the resultsVisualizationSmall non-coding RNAsComputational analysis of small noncoding RNA sequencing data
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