5. Transcriptomic Data
Analysis: RNA-Seq
Analysis Using Galaxy
Chia-Lang Hsu∗,‡and Chantal Hoi Yin Cheung†
∗Department of Life Sciences, National Taiwan University,
Taipei, Taiwan
†Institute of Molecular and Cellular Biology,
National Taiwan University, Taipei, Taiwan
‡[email protected]Introduction
The global characterization and profiling of transcriptome are critical steps
for unveiling RNA which plays a multifaceted role in numerous biological
processes. In cancer research, transcriptome analyses have been utilized to
identify aberrant transcripts associated with specific pathogenetic mecha-
nisms and a group of genes, namely the gene signature for distinguishing
cancer subtypes or predicting prognosis of cancer patients. With the evolu-
tion of next-generation sequencing (NGS) technologies, traditional methods,
such as expressed sequence tag (EST) and gene expression microarray,
have been complemented by massively parallel RNA sequencing (RNA-
seq). RNA-seq offers excellent ability to unbiasedly quantify transcript
expression in a single assay. In addition, RNA-seq has the potential ability
to detect new genes and transcript isoforms, genetic variants (e.g., single
nucleotide variants, insertions, and deletions), and gene fusions. RNA-
seq opens up an entirely new age of transcriptome analysis in cancer
research.
RNA-seq is being increasingly used, in part driven by the decreasing cost
of sequencing. Nevertheless, the manipulation and analysis of the massive
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