Molecular Profiling of RNA Tumors Using High-Throughput RNA Sequencing: From Raw Data to Systems Level Analyses

Willian A da Silveira, E Starr Hazard, Dongjun Chung, Gary Hardiman

Research output: Contribution to journalArticle

2 Citations (Scopus)
114 Downloads (Pure)

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.

Original languageEnglish
Pages (from-to)185-204
Number of pages20
JournalMethods in Molecular Biology
Volume1908
Early online date17 Jan 2019
DOIs
Publication statusEarly online date - 17 Jan 2019

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