Gaining comprehensive biological insight into the transcriptome by performing a broad-spectrum RNA-seq analysis. Sahraeian, S. M. E., Mohiyuddin, M., Sebra, R., Tilgner, H., Afshar, P. T., Au, K. F., Bani Asadi, N., Gerstein, M. B., Wong, W. H., Snyder, M. P., Schadt, E., & Lam, H. Y. K. Nature Communications, 8(1):59, July, 2017. Number: 1 Publisher: Nature Publishing Group![Gaining comprehensive biological insight into the transcriptome by performing a broad-spectrum RNA-seq analysis [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex 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 \textasciitilde120 combinations, and \textasciitilde490 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.
@article{sahraeian_gaining_2017,
title = {Gaining comprehensive biological insight into the transcriptome by performing a broad-spectrum {RNA}-seq analysis},
volume = {8},
copyright = {2017 The Author(s)},
issn = {2041-1723},
url = {https://www.nature.com/articles/s41467-017-00050-4},
doi = {10.1038/s41467-017-00050-4},
abstract = {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 {\textasciitilde}120 combinations, and {\textasciitilde}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.},
language = {en},
number = {1},
urldate = {2020-08-21},
journal = {Nature Communications},
author = {Sahraeian, Sayed Mohammad Ebrahim and Mohiyuddin, Marghoob and Sebra, Robert and Tilgner, Hagen and Afshar, Pegah T. and Au, Kin Fai and Bani Asadi, Narges and Gerstein, Mark B. and Wong, Wing Hung and Snyder, Michael P. and Schadt, Eric and Lam, Hugo Y. K.},
month = jul,
year = {2017},
note = {Number: 1
Publisher: Nature Publishing Group},
keywords = {zotero\_ex\_vancouver},
pages = {59}
}
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