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Updated: Jan 30, 2026

Highly Efficient Ligation of Small RNA Molecules for MicroRNA Quantitation by High-Throughput Sequencing
Published on: November 18, 2014
Molecular Profiling of RNA Tumors Using High-Throughput RNA Sequencing: From Raw Data to Systems Level Analyses
Willian A da Silveira1,2, E Starr Hazard1,3, Dongjun Chung4
1MUSC Bioinformatics, Center for Genomics Medicine, Medical University of South Carolina (MUSC), Charleston, SC, USA.
Abstract:
RNAseq is a powerful technique enabling global profiles of transcriptomes in healthy and diseased states. In this chapter we review pipelines to analyze the data generated by sequencing RNA, from raw data to a system level analysis. We first give an overview of workflow to generate mapped reads from FASTQ files, including quality control of FASTQ, filtering and trimming of reads, and alignment of reads to a genome. Then, we compare and contrast three popular options to determine differentially expressed (DE) transcripts (The Tuxedo Pipeline, DESeq2, and Limma/voom). Finally, we examine four tool sets to extrapolate biological meaning from the list of DE genes (Genecards, The Human Protein Atlas, GSEA, and ToppGene). We emphasize the need to ask a concise scientific question and to clearly under stand the strengths and limitations of the methods.
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