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Updated: May 5, 2026

Transcriptomic Analysis of C. elegans RNA Sequencing Data Through the Tuxedo Suite on the Galaxy Project
Published on: April 8, 2017
Key Concepts in Transcriptomics Data Analysis in the Era of Next-Gen Sequencing
Saumya Kumar1,2
1Centre for Individualised Infection Medicine (CiiM), a joint venture between the Helmholtz Centre for Infection Research (HZI) and Hannover Medical School (MHH), Hannover, Germany. saumya.dileepkumar@helmholtz-hzi.de.
Abstract:
With the rise of next-generation sequencing technologies, gaining new insights into the molecular profiles of cells and tissues has become easier than ever. These technologies enable the investigation of the complete transcriptome, encompassing both known and unknown RNA molecules at single-base pair resolution and at much lower costs. Since comprehensive proteome measurements for biological samples remain challenging, transcriptome sequencing offers valuable insights and new avenues for exploring biological samples. These RNA-sequencing (RNA-seq) experiments generate high-throughput data, making them useful for examining unique molecular profiles alongside biological pathways and networks in various tissues and cellular subsets. Moreover, with the increasing ease of conducting single-cell transcriptomics studies, there has been a surge in large datasets, which greatly enhance our understanding of biological systems in human health and disease. In this chapter, fundamental and advanced analysis methods and concepts for both bulk and single-cell transcriptomics are discussed.
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