Cited by 114Gene expression and cancer classificationSingle-cell and spatial transcriptomicsGenomics and Phylogenetic Studies

qSVA framework for RNA quality correction in differential expression analysis

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Jaffe, Andrew E., Tao, Ran, Norris, Alexis L., Kealhofer, Marc, Nellore, Abhinav, Shin, Joo Heon, Kim, Dewey, Jia, Yankai +5 more·2017·Proceedings of the National Academy of Sciences

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Abstract

Significance: Many studies use measurements of gene expression in human postmortem and ex vivo tissues like brain and blood to characterize genomic correlates of illness. However, molecular analyses of these tissues can be susceptible to a wide range of confounders that may be difficult to measure and remove. In this article, we describe an analysis framework for identifying and removing previously uncharacterized quality biases in measurements of RNA. Our paper critically highlights the shortcomings of standard RNA quality correction approaches, such as statistically adjusting for RNA integrity numbers. We show that the our framework removes residual confounding by RNA quality and greatly improves replication of significant differentially expressed genes across independent datasets by more than threefold compared with previous approaches.

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Crossref · 10.1073/pnas.1617384114

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  • Differential expression results did not overlap with RNA degradation metrics, indicating they were not driven by RNA-quality confounds.

    “Differential expression did not overlap with experimentally defined RNA degradation metrics in brain, indicating that results were not driven by RNA-quality confounds (Fig S4) (22).”

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Authors
Jaffe, A. E., Tao, R., Norris, A. L., Kealhofer, M., Nellore, A., Shin, J. H., Kim, D., Jia, Y., Hyde, T. M., Kleinman, J. E., Straub, R. E., Leek, J. T., & Weinberger, D. R.
Affiliations
  • Johns Hopkins University (US)
  • Kennedy Krieger Institute (US)
Corresponding author
Jaffe, Andrew E.
Venue
Proceedings of the National Academy of Sciences
Published
2017-06-20
Volume
114
Issue
27
Pages
7130-7135
ISSN
  • 0027-8424 (ISSN-L)
  • 1091-6490
OpenAlex
W2681631427
Cited by
114
References
35
Citations by year
2026: 9 · 2025: 7 · 2024: 8 · 2023: 13 · 2022: 19 · 2021: 11 · 2020: 12 · 2019: 15 · 2018: 16 · 2017: 4
FWCI
5.25
Type
journal article
Language
en
Open access
Locations
  • Proceedings of the National Academy of Sciences (publishedVersion)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion)
  • Europe PMC (PubMed Central) (publishedVersion)
  • PubMed Central (publishedVersion)
  • PubMed (publishedVersion)
Funders
  • HHS | NIH | National Institute of Mental Health (R21MH109956)
  • HHS | NIH | National Institute of General Medical Sciences (R01GM105705)
  • Lieber Institute for Brain Development (Internal Funds)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene expression and cancer classification
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
Keywords
RNA quality, RNA degradation, confounding adjustment, differential expression analysis, postmortem brain, schizophrenia, replication rate, transcriptomics
MeSH terms
Algorithms, Animals, DNA Replication, Gene Expression Regulation, Genotype, Humans, RNA, Schizophrenia, Sequence Analysis, RNA, Computational Biology, Oligonucleotide Array Sequence Analysis, Gene Expression Profiling, High-Throughput Nucleotide Sequencing, Transcriptome, Gray Matter

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