RNA-seq

Technical variability and sampling

Lauren M. McIntyre, Kenneth K. Lopiano, Alison M. Morse, Victor Amin, Ann L Oberg, Linda J. Young, Sergey V. Nuzhdin

Research output: Contribution to journalArticle

149 Citations (Scopus)

Abstract

Background: RNA-seq is revolutionizing the way we study transcriptomes. mRNA can be surveyed without prior knowledge of gene transcripts. Alternative splicing of transcript isoforms and the identification of previously unknown exons are being reported. Initial reports of differences in exon usage, and splicing between samples as well as quantitative differences among samples are beginning to surface. Biological variation has been reported to be larger than technical variation. In addition, technical variation has been reported to be in line with expectations due to random sampling. However, strategies for dealing with technical variation will differ depending on the magnitude. The size of technical variance, and the role of sampling are examined in this manuscript.Results: In this study three independent Solexa/Illumina experiments containing technical replicates are analyzed. When coverage is low, large disagreements between technical replicates are apparent. Exon detection between technical replicates is highly variable when the coverage is less than 5 reads per nucleotide and estimates of gene expression are more likely to disagree when coverage is low. Although large disagreements in the estimates of expression are observed at all levels of coverage.Conclusions: Technical variability is too high to ignore. Technical variability results in inconsistent detection of exons at low levels of coverage. Further, the estimate of the relative abundance of a transcript can substantially disagree, even when coverage levels are high. This may be due to the low sampling fraction and if so, it will persist as an issue needing to be addressed in experimental design even as the next wave of technology produces larger numbers of reads. We provide practical recommendations for dealing with the technical variability, without dramatic cost increases.

Original languageEnglish (US)
Article number293
JournalBMC Genomics
Volume12
DOIs
StatePublished - Jun 6 2011

Fingerprint

Exons
RNA
Alternative Splicing
Transcriptome
Protein Isoforms
Research Design
Nucleotides
Technology
Gene Expression
Costs and Cost Analysis
Messenger RNA
Genes

ASJC Scopus subject areas

  • Biotechnology
  • Genetics

Cite this

McIntyre, L. M., Lopiano, K. K., Morse, A. M., Amin, V., Oberg, A. L., Young, L. J., & Nuzhdin, S. V. (2011). RNA-seq: Technical variability and sampling. BMC Genomics, 12, [293]. https://doi.org/10.1186/1471-2164-12-293

RNA-seq : Technical variability and sampling. / McIntyre, Lauren M.; Lopiano, Kenneth K.; Morse, Alison M.; Amin, Victor; Oberg, Ann L; Young, Linda J.; Nuzhdin, Sergey V.

In: BMC Genomics, Vol. 12, 293, 06.06.2011.

Research output: Contribution to journalArticle

McIntyre, LM, Lopiano, KK, Morse, AM, Amin, V, Oberg, AL, Young, LJ & Nuzhdin, SV 2011, 'RNA-seq: Technical variability and sampling', BMC Genomics, vol. 12, 293. https://doi.org/10.1186/1471-2164-12-293
McIntyre LM, Lopiano KK, Morse AM, Amin V, Oberg AL, Young LJ et al. RNA-seq: Technical variability and sampling. BMC Genomics. 2011 Jun 6;12. 293. https://doi.org/10.1186/1471-2164-12-293
McIntyre, Lauren M. ; Lopiano, Kenneth K. ; Morse, Alison M. ; Amin, Victor ; Oberg, Ann L ; Young, Linda J. ; Nuzhdin, Sergey V. / RNA-seq : Technical variability and sampling. In: BMC Genomics. 2011 ; Vol. 12.
@article{c6108f62c8304a42acd11dedb6ab3b71,
title = "RNA-seq: Technical variability and sampling",
abstract = "Background: RNA-seq is revolutionizing the way we study transcriptomes. mRNA can be surveyed without prior knowledge of gene transcripts. Alternative splicing of transcript isoforms and the identification of previously unknown exons are being reported. Initial reports of differences in exon usage, and splicing between samples as well as quantitative differences among samples are beginning to surface. Biological variation has been reported to be larger than technical variation. In addition, technical variation has been reported to be in line with expectations due to random sampling. However, strategies for dealing with technical variation will differ depending on the magnitude. The size of technical variance, and the role of sampling are examined in this manuscript.Results: In this study three independent Solexa/Illumina experiments containing technical replicates are analyzed. When coverage is low, large disagreements between technical replicates are apparent. Exon detection between technical replicates is highly variable when the coverage is less than 5 reads per nucleotide and estimates of gene expression are more likely to disagree when coverage is low. Although large disagreements in the estimates of expression are observed at all levels of coverage.Conclusions: Technical variability is too high to ignore. Technical variability results in inconsistent detection of exons at low levels of coverage. Further, the estimate of the relative abundance of a transcript can substantially disagree, even when coverage levels are high. This may be due to the low sampling fraction and if so, it will persist as an issue needing to be addressed in experimental design even as the next wave of technology produces larger numbers of reads. We provide practical recommendations for dealing with the technical variability, without dramatic cost increases.",
author = "McIntyre, {Lauren M.} and Lopiano, {Kenneth K.} and Morse, {Alison M.} and Victor Amin and Oberg, {Ann L} and Young, {Linda J.} and Nuzhdin, {Sergey V.}",
year = "2011",
month = "6",
day = "6",
doi = "10.1186/1471-2164-12-293",
language = "English (US)",
volume = "12",
journal = "BMC Genomics",
issn = "1471-2164",
publisher = "BioMed Central",

}

TY - JOUR

T1 - RNA-seq

T2 - Technical variability and sampling

AU - McIntyre, Lauren M.

AU - Lopiano, Kenneth K.

AU - Morse, Alison M.

AU - Amin, Victor

AU - Oberg, Ann L

AU - Young, Linda J.

AU - Nuzhdin, Sergey V.

PY - 2011/6/6

Y1 - 2011/6/6

N2 - Background: RNA-seq is revolutionizing the way we study transcriptomes. mRNA can be surveyed without prior knowledge of gene transcripts. Alternative splicing of transcript isoforms and the identification of previously unknown exons are being reported. Initial reports of differences in exon usage, and splicing between samples as well as quantitative differences among samples are beginning to surface. Biological variation has been reported to be larger than technical variation. In addition, technical variation has been reported to be in line with expectations due to random sampling. However, strategies for dealing with technical variation will differ depending on the magnitude. The size of technical variance, and the role of sampling are examined in this manuscript.Results: In this study three independent Solexa/Illumina experiments containing technical replicates are analyzed. When coverage is low, large disagreements between technical replicates are apparent. Exon detection between technical replicates is highly variable when the coverage is less than 5 reads per nucleotide and estimates of gene expression are more likely to disagree when coverage is low. Although large disagreements in the estimates of expression are observed at all levels of coverage.Conclusions: Technical variability is too high to ignore. Technical variability results in inconsistent detection of exons at low levels of coverage. Further, the estimate of the relative abundance of a transcript can substantially disagree, even when coverage levels are high. This may be due to the low sampling fraction and if so, it will persist as an issue needing to be addressed in experimental design even as the next wave of technology produces larger numbers of reads. We provide practical recommendations for dealing with the technical variability, without dramatic cost increases.

AB - Background: RNA-seq is revolutionizing the way we study transcriptomes. mRNA can be surveyed without prior knowledge of gene transcripts. Alternative splicing of transcript isoforms and the identification of previously unknown exons are being reported. Initial reports of differences in exon usage, and splicing between samples as well as quantitative differences among samples are beginning to surface. Biological variation has been reported to be larger than technical variation. In addition, technical variation has been reported to be in line with expectations due to random sampling. However, strategies for dealing with technical variation will differ depending on the magnitude. The size of technical variance, and the role of sampling are examined in this manuscript.Results: In this study three independent Solexa/Illumina experiments containing technical replicates are analyzed. When coverage is low, large disagreements between technical replicates are apparent. Exon detection between technical replicates is highly variable when the coverage is less than 5 reads per nucleotide and estimates of gene expression are more likely to disagree when coverage is low. Although large disagreements in the estimates of expression are observed at all levels of coverage.Conclusions: Technical variability is too high to ignore. Technical variability results in inconsistent detection of exons at low levels of coverage. Further, the estimate of the relative abundance of a transcript can substantially disagree, even when coverage levels are high. This may be due to the low sampling fraction and if so, it will persist as an issue needing to be addressed in experimental design even as the next wave of technology produces larger numbers of reads. We provide practical recommendations for dealing with the technical variability, without dramatic cost increases.

UR - http://www.scopus.com/inward/record.url?scp=79957882567&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=79957882567&partnerID=8YFLogxK

U2 - 10.1186/1471-2164-12-293

DO - 10.1186/1471-2164-12-293

M3 - Article

VL - 12

JO - BMC Genomics

JF - BMC Genomics

SN - 1471-2164

M1 - 293

ER -