Revisiting Global Gene Expression Analysis
Open accessAbstract
Gene expression analysis is a widely used and powerful method for investigating the transcriptional behavior of biological systems, for classifying cell states in disease, and for many other purposes. Recent studies indicate that common assumptions currently embedded in experimental and analytical practices can lead to misinterpretation of global gene expression data. We discuss these assumptions and describe solutions that should minimize erroneous interpretation of gene expression data from multiple analysis platforms.
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Calibration techniques such as spike-in normalization in RNA-seq and ChIP-seq have made absolute quantification of genomics experiments possible.
“This is an intrinsic limitation of all genomics methods, in which the signal is quantified from sequencing read counts, but calibration techniques such as spike-in normalization in RNA-seq52 and ChIP-seq53–55 have made absolute quantification of genomics experiments possible.”
From Genome-wide absolute quantification of chromatin looping (2026) · cites this paper as [53]
The Experimental Approach and Implications sections (pages unavailable) show that RNA spike-ins let the authors normalize RNA-seq data to cell number and detect changes in transcript levels more accurately. This supports the RNA-seq calibration point, but the paper does not establish absolute quantification of genomics experiments generally; the ChIP-seq portion is attributed to other citations. (LLM, conf=0.83)
Experimental — accuracy not yet measuredNormalization of technical library-to-library differences is a prerequisite for further analysis in scRNA-seq.
“As in bulk RNA-seq51, normalization of technical library-to-library differences is a prerequisite for further analysis.”
From Revealing the vectors of cellular identity with single-cell genomics (2016) · cites this paper as [51]
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- Authors
- Lovén, J., Orlando, D. A., Sigova, A. A., Lin, C. Y., Rahl, P. B., Burge, C. B., Levens, D. L., Lee, T. I., & Young, R. A.
- Affiliations
- Whitehead Institute for Biomedical Research (US)
- Massachusetts Institute of Technology (US)
- National Cancer Institute (US)
- Corresponding author
- Lee, Tong Ihn
- Young, Richard A.
- ORCID
- Venue
- Cell
- Publisher
- Elsevier BV
- Published
- 2012-10
- Volume
- 151
- Issue
- 3
- Pages
- 476-482
- ISSN
- 0092-8674 (ISSN-L)
- PMC
- PMC3505597
- OpenAlex
- W2147109452
- Cited by
- 616
- References
- 45
- Citations by year
- 2026: 16 · 2025: 21 · 2024: 32 · 2023: 54 · 2022: 35 · 2021: 62 · 2020: 42 · 2019: 38 · 2018: 33 · 2017: 51 · 2016: 62 · 2015: 54 · 2014: 69 · 2013: 45 · 2012: 1
- FWCI
- 4.93
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Cell (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- DSpace@MIT (Massachusetts Institute of Technology) (submittedVersion)
- Elsevier eBooks
- Funders
- American Cancer Society
- Vetenskapsrådet (VR-B0086301)
- National Institutes of Health
- National Human Genome Research Institute (HG002668, R01HG002439, R01HG002668)
- National Cancer Institute (CA146445, R01CA146445)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene expression and cancer classification
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Keywords
- gene expression data interpretation, cell state classification
- MeSH terms
- Humans, Transcription, Genetic, Proto-Oncogene Proteins c-myc, Sequence Analysis, RNA, Oligonucleotide Array Sequence Analysis, Gene Expression Profiling, Genome-Wide Association Study
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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