title: How many biological replicates are needed in an RNA-seq experiment and which differential expression tool should you use?
abstract: RNA-seq is now the technology of choice for genome-wide differential gene expression experiments, but it is not clear how many biological replicates are needed to ensure valid biological interpretation of the results or which statistical tools are best for analyzing the data. An RNA-seq experiment with 48 biological replicates in each of two conditions was performed to answer these questions and provide guidelines for experimental design. With three biological replicates, nine of the 11 tools evaluated found only 20%-40% of the significantly differentially expressed (SDE) genes identified with the full set of 42 clean replicates. This rises to >85% for the subset of SDE genes changing in expression by more than fourfold. To achieve >85% for all SDE genes regardless of fold change requires more than 20 biological replicates. The same nine tools successfully control their false discovery rate at ≲5% for all numbers of replicates, while the remaining two tools fail to control their FDR adequately, particularly for low numbers of replicates. For future RNA-seq experiments, these results suggest that at least six biological replicates should be used, rising to at least 12 when it is important to identify SDE genes for all fold changes. If fewer than 12 replicates are used, a superior combination of true positive and false positive performances makes edgeR and DESeq2 the leading tools. For higher replicate numbers, minimizing false positives is more important and DESeq marginally outperforms the other tools.
authors.affiliation: Division of Computational Biology, College of Life Sciences, University of Dundee, Dundee DD1 5EH, United Kingdom.
authors.forename: Nicholas J
authors.identifier: 0000-0001-9068-9654
authors.initials: NJ
authors.lastname: Schurch
authors.affiliation: Division of Computational Biology, College of Life Sciences, University of Dundee, Dundee DD1 5EH, United Kingdom Division of Gene Regulation and Expression, College of Life Sciences, University of Dundee, Dundee DD1 5EH, United Kingdom.
authors.forename: Pietá
authors.identifier: 0000-0002-6398-2537
authors.initials: P
authors.lastname: Schofield
authors.affiliation: Division of Computational Biology, College of Life Sciences, University of Dundee, Dundee DD1 5EH, United Kingdom Division of Gene Regulation and Expression, College of Life Sciences, University of Dundee, Dundee DD1 5EH, United Kingdom.
authors.forename: Marek
authors.initials: M
authors.lastname: Gierliński
authors.affiliation: Division of Computational Biology, College of Life Sciences, University of Dundee, Dundee DD1 5EH, United Kingdom.
authors.forename: Christian
authors.identifier: 0000-0002-2560-2484
authors.initials: C
authors.lastname: Cole
authors.affiliation: Division of Computational Biology, College of Life Sciences, University of Dundee, Dundee DD1 5EH, United Kingdom.
authors.forename: Alexander
authors.initials: A
authors.lastname: Sherstnev
authors.affiliation: Division of Gene Regulation and Expression, College of Life Sciences, University of Dundee, Dundee DD1 5EH, United Kingdom.
authors.forename: Vijender
authors.initials: V
authors.lastname: Singh
authors.affiliation: Edinburgh Genomics, University of Edinburgh, Edinburgh EH9 3JT, United Kingdom.
authors.forename: Nicola
authors.initials: N
authors.lastname: Wrobel
authors.affiliation: Edinburgh Genomics, University of Edinburgh, Edinburgh EH9 3JT, United Kingdom.
authors.forename: Karim
authors.initials: K
authors.lastname: Gharbi
authors.affiliation: Division of Plant Sciences, College of Life Sciences, University of Dundee, Dundee DD1 5EH, United Kingdom.
authors.forename: Gordon G
authors.initials: GG
authors.lastname: Simpson
authors.affiliation: Division of Gene Regulation and Expression, College of Life Sciences, University of Dundee, Dundee DD1 5EH, United Kingdom.
authors.forename: Tom
authors.initials: T
authors.lastname: Owen-Hughes
authors.affiliation: Edinburgh Genomics, University of Edinburgh, Edinburgh EH9 3JT, United Kingdom.
authors.forename: Mark
authors.initials: M
authors.lastname: Blaxter
authors.affiliation: Division of Computational Biology, College of Life Sciences, University of Dundee, Dundee DD1 5EH, United Kingdom Division of Gene Regulation and Expression, College of Life Sciences, University of Dundee, Dundee DD1 5EH, United Kingdom Division of Biological Chemistry and Drug Discovery, College of Life Sciences, University of Dundee, Dundee DD1 5EH, United Kingdom.
authors.forename: Geoffrey J
authors.identifier: 0000-0002-9014-5355
authors.initials: GJ
authors.lastname: Barton
mesh_terms: D020869:Gene Expression Profiling; D012331:RNA, Fungal / Q000235:genetics; D015203:Reproducibility of Results; D012441:Saccharomyces cerevisiae / Q000235:genetics; D017423:Sequence Analysis, RNA / Q000379:methods*
chemical_list: D012331:RNA, Fungal
keywords: RNA-seq; benchmarking; differential expression; experimental design; replication; statistical power; yeast