title: RNA-seq mixology: designing realistic control experiments to compare protocols and analysis methods.
abstract: Carefully designed control experiments provide a gold standard for benchmarking different genomics research tools. A shortcoming of many gene expression control studies is that replication involves profiling the same reference RNA sample multiple times. This leads to low, pure technical noise that is atypical of regular studies. To achieve a more realistic noise structure, we generated a RNA-sequencing mixture experiment using two cell lines of the same cancer type. Variability was added by extracting RNA from independent cell cultures and degrading particular samples. The systematic gene expression changes induced by this design allowed benchmarking of different library preparation kits (standard poly-A versus total RNA with Ribozero depletion) and analysis pipelines. Data generated using the total RNA kit had more signal for introns and various RNA classes (ncRNA, snRNA, snoRNA) and less variability after degradation. For differential expression analysis, voom with quality weights marginally outperformed other popular methods, while for differential splicing, DEXSeq was simultaneously the most sensitive and the most inconsistent method. For sample deconvolution analysis, DeMix outperformed IsoPure convincingly. Our RNA-sequencing data set provides a valuable resource for benchmarking different protocols and data pre-processing workflows. The extra noise mimics routine lab experiments more closely, ensuring any conclusions are widely applicable.
authors.affiliation: ACRF Stem Cells and Cancer Division, The Walter and Eliza Hall Institute of Medical Research, 1G Royal Parade, Parkville, Victoria 3052, Australia.|Department of Medical Biology, The University of Melbourne, Parkville, Victoria 3010, Australia.
authors.forename: Aliaksei Z
authors.initials: AZ
authors.lastname: Holik
authors.affiliation: Department of Medical Biology, The University of Melbourne, Parkville, Victoria 3010, Australia.|Molecular Medicine Division, The Walter and Eliza Hall Institute of Medical Research, 1G Royal Parade, Parkville, Victoria 3052, Australia.
authors.forename: Charity W
authors.initials: CW
authors.lastname: Law
authors.affiliation: Molecular Medicine Division, The Walter and Eliza Hall Institute of Medical Research, 1G Royal Parade, Parkville, Victoria 3052, Australia.
authors.forename: Ruijie
authors.initials: R
authors.lastname: Liu
authors.affiliation: Statistics Department, George R. Brown School of Engineering, Rice University, 6100 Main Street, Duncan Hall 2124, Houston, TX 77005, USA.|Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, TX 77030, USA.
authors.forename: Zeya
authors.initials: Z
authors.lastname: Wang
authors.affiliation: Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, TX 77030, USA.
authors.forename: Wenyi
authors.initials: W
authors.lastname: Wang
authors.affiliation: Department of Biostatistics, Bioinformatics and Biomathematics, Georgetown University School of Medicine, 4000 Reservoir Road NW, Washington, DC 20057, USA.
authors.forename: Jaeil
authors.initials: J
authors.lastname: Ahn
authors.affiliation: ACRF Stem Cells and Cancer Division, The Walter and Eliza Hall Institute of Medical Research, 1G Royal Parade, Parkville, Victoria 3052, Australia.|Department of Medical Biology, The University of Melbourne, Parkville, Victoria 3010, Australia.
authors.forename: Marie-Liesse
authors.initials: ML
authors.lastname: Asselin-Labat
authors.affiliation: Bioinformatics Division, The Walter and Eliza Hall Institute of Medical Research, 1G Royal Parade, Parkville, Victoria 3052, Australia.|School of Mathematics and Statistics, The University of Melbourne, Parkville, Victoria 3010, Australia.
authors.forename: Gordon K
authors.initials: GK
authors.lastname: Smyth
authors.affiliation: Department of Medical Biology, The University of Melbourne, Parkville, Victoria 3010, Australia.|Molecular Medicine Division, The Walter and Eliza Hall Institute of Medical Research, 1G Royal Parade, Parkville, Victoria 3052, Australia.|School of Mathematics and Statistics, The University of Melbourne, Parkville, Victoria 3010, Australia.
authors.forename: Matthew E
authors.initials: ME
authors.lastname: Ritchie
mesh_terms: D019985:Benchmarking; D045744:Cell Line, Tumor; D004847:Epithelial Cells / Q000166:cytology / Q000378:metabolism; D015723:Gene Library; D023281:Genomics / Q000295:instrumentation / Q000379:methods; D006801:Humans; D012313:RNA / Q000032:analysis* / Q000145:classification / Q000235:genetics; D059367:RNA Cleavage; D011933:Reagent Kits, Diagnostic / Q000592:standards; D012015:Reference Standards; D017423:Sequence Analysis, RNA / Q000379:methods / Q000592:standards* / Q000706:statistics & numerical data
chemical_list: D011933:Reagent Kits, Diagnostic; D012313:RNA