Scinovex
article Open Access

RNA-seq: An assessment of technical reproducibility and comparison with gene expression arrays

Genome Research · 2008 · Vol. 18(9) · pp. 1509–1517
John C. MarioniChristopher E. MasonShrikant ManeMatthew StephensYoav Gilad

Abstract

Ultra-high-throughput sequencing is emerging as an attractive alternative to microarrays for genotyping, analysis of methylation patterns, and identification of transcription factor binding sites. Here, we describe an application of the Illumina sequencing (formerly Solexa sequencing) platform to study mRNA expression levels. Our goals were to estimate technical variance associated with Illumina sequencing in this context and to compare its ability to identify differentially expressed genes with existing array technologies. To do so, we estimated gene expression differences between liver and kidney RNA samples using multiple sequencing replicates, and compared the sequencing data to results obtained from Affymetrix arrays using the same RNA samples. We find that the Illumina sequencing data are highly replicable, with relatively little technical variation, and thus, for many purposes, it may suffice to sequence each mRNA sample only once (i.e., using one lane). The information in a single lane of Illumina sequencing data appears comparable to that in a single array in enabling identification of differentially expressed genes, while allowing for additional analyses such as detection of low-expressed genes, alternative splice variants, and novel transcripts. Based on our observations, we propose an empirical protocol and a statistical framework for the analysis of gene expression using ultra-high-throughput sequencing technology.

Gene expression and cancer classificationMolecular Biology Techniques and ApplicationsSingle-cell and spatial transcriptomicsBiologyIllumina dye sequencingGeneticsDeep sequencingComputational biologyRNA-SeqSingle cell sequencingDNA sequencingGeneDNA microarray

MeSH terms

HumansMaleModels, BiologicalRNA, MessengerReproducibility of ResultsLikelihood FunctionsSequence Analysis, RNAOligonucleotide Array Sequence AnalysisGene Expression Profiling

Funding

  • Alfred P. Sloan Foundation
  • Yale University
  • University of Chicago
  • National Institutes of Health
Citations
2,821
FWCI
field-weighted impact
References
27
Percentile
vs. same field & year
Citations per year
Cited by
Genome Regulation by Long Noncoding RNAs
Annual Review of Biochemistry · 2012 · 4,065 citations
TopHat: discovering splice junctions with RNA-Seq
Bioinformatics · 2009 · 12,093 citations
Next-Generation Sequencing: From Basic Research to Diagnostics
Clinical Chemistry · 2009 · 819 citations
Waste Not, Want Not: Why Rarefying Microbiome Data Is Inadmissible
PLoS Computational Biology · 2014 · 3,022 citations
The Technology and Biology of Single-Cell RNA Sequencing
Molecular Cell · 2015 · 1,557 citations
References
Statistical significance for genomewide studies
Proceedings of the National Academy of Sciences · 2003 · 10,009 citations
Citation Network

How this paper connects to the literature. Drag to explore, click any node to open that paper.