The DOI matches its Crossref record; 40 of the 40 references it cites were found in a registry or an index.
Computational deconvolution: extracting cell type-specific information from heterogeneous samples
Open accessAbstract
The quanta unit of the immune system is the cell; yet analyzed samples are often heterogeneous with respect to cell subsets which can mislead result interpretation. Experimentally, researchers face a difficult choice whether to profile heterogeneous samples with the ensuing confounding effects, or a priori focus on a few cell subsets of interest, potentially limiting new discoveries. An attractive alternative solution is to extract cell subset-specific information directly from heterogeneous samples via computational deconvolution techniques, thereby capturing both cell-centered and whole system level context. Such approaches are capable of unraveling novel biology, undetectable otherwise. Here we review the present state of available deconvolution techniques, their advantages and limitations, with a focus on blood expression data and immunological studies in general.
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Cited by
Robust enumeration of cell subsets from tissue expression profiles
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Determining cell type abundance and expression from bulk tissues with digital cytometry
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Baron, M., Veres, A., Wolock, S. L., Faust, A. L., Gaujoux, R., Vetere, A., Ryu, J. H., Wagner, B. K., Shen-Orr, S. S., Klein, A. M., et al. (2016) · Cell Systems · doi:10.1016/j.cels.2016.08.011 · Cited by 1,508
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Metadata
- Authors
- Shen-Orr, S. S., & Gaujoux, R.
- Venue
- Current Opinion in Immunology
- Publisher
- Elsevier BV
- Published
- 2013-10
- Volume
- 25
- Issue
- 5
- Pages
- 571-578
- ISSN
- 0952-7915 (ISSN-L)
- OpenAlex
- W1967937330
- Cited by
- 277
- References
- 40
- FWCI
- 0.88
- Type
- journal article
- Language
- en
- Open access
- green
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