Gaining comprehensive biological insight into the transcriptome by performing a broad-spectrum RNA-seq analysis
| Autor: | Narges Bani Asadi, Wing Hung Wong, Pegah Tootoonchi Afshar, Eric E. Schadt, Sayed Mohammad Ebrahim Sahraeian, Michael Snyder, Kin Fai Au, Hugo Y. K. Lam, Hagen Tilgner, Marghoob Mohiyuddin, Mark Gerstein, Robert Sebra |
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| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: |
0301 basic medicine
Science genetic processes General Physics and Astronomy RNA-Seq Computational biology Biology Bioinformatics Article General Biochemistry Genetics and Molecular Biology Cell Line Transcriptome 03 medical and health sciences Broad spectrum Expression analysis Humans natural sciences Embryonic Stem Cells Protocol (science) Multidisciplinary Base Sequence General Chemistry Pipeline (software) 3. Good health 030104 developmental biology Workflow ComputingMethodologies_PATTERNRECOGNITION TheoryofComputation_MATHEMATICALLOGICANDFORMALLANGUAGES RNA editing |
| Zdroj: | Nature Communications, Vol 8, Iss 1, Pp 1-15 (2017) Nature Communications |
| ISSN: | 2041-1723 |
| Popis: | RNA-sequencing (RNA-seq) is an essential technique for transcriptome studies, hundreds of analysis tools have been developed since it was debuted. Although recent efforts have attempted to assess the latest available tools, they have not evaluated the analysis workflows comprehensively to unleash the power within RNA-seq. Here we conduct an extensive study analysing a broad spectrum of RNA-seq workflows. Surpassing the expression analysis scope, our work also includes assessment of RNA variant-calling, RNA editing and RNA fusion detection techniques. Specifically, we examine both short- and long-read RNA-seq technologies, 39 analysis tools resulting in ~120 combinations, and ~490 analyses involving 15 samples with a variety of germline, cancer and stem cell data sets. We report the performance and propose a comprehensive RNA-seq analysis protocol, named RNACocktail, along with a computational pipeline achieving high accuracy. Validation on different samples reveals that our proposed protocol could help researchers extract more biologically relevant predictions by broad analysis of the transcriptome. RNA-seq is widely used for transcriptome analysis. Here, the authors analyse a wide spectrum of RNA-seq workflows and present a comprehensive analysis protocol named RNACocktail as well as a computational pipeline leveraging the widely used tools for accurate RNA-seq analysis. |
| Databáze: | OpenAIRE |
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