The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
SPICE: Exploration and analysis of post‐cytometric complex multivariate datasets
Open accessAbstract
Polychromatic flow cytometry results in complex, multivariate datasets. To date, tools for the aggregate analysis of these datasets across multiple specimens grouped by different categorical variables, such as demographic information, have not been optimized. Often, the exploration of such datasets is accomplished by visualization of patterns with pie charts or bar charts, without easy access to statistical comparisons of measurements that comprise multiple components. Here we report on algorithms and a graphical interface we developed for these purposes. In particular, we discuss thresholding necessary for accurate representation of data in pie charts, the implications for display and comparison of normalized versus unnormalized data, and the effects of averaging when samples with significant background noise are present. Finally, we define a statistic for the nonparametric comparison of complex distributions to test for difference between groups of samples based on multi‐component measurements. While originally developed to support the analysis of T cell functional profiles, these techniques are amenable to a broad range of datatypes. Published 2011 Wiley‐Liss, Inc.
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Cites
Seventeen-colour flow cytometry: unravelling the immune system
Perfetto, S. P., Chattopadhyay, P. K., & Roederer, M. (2004) · Nature Reviews Immunology · doi:10.1038/nri1416 · Cited by 1,019
Self-citationPhenotype and function of human T lymphocyte subsets: Consensus and issues
Appay, V., van Lier, R. A. W., Sallusto, F., & Roederer, M. (2008) · Cytometry Part A · doi:10.1002/cyto.a.20643 · Cited by 729 · cited 1×
“The complexity of this analysis (and size of the measurement vector) grows geometrically with each additional measurement, such as CD4 vs. CD8, restriction to particular differentiation stages (14), or inclusion of additional functional outcomes.”
BackgroundSelf-citationQuantum dot semiconductor nanocrystals for immunophenotyping by polychromatic flow cytometry
Chattopadhyay, P. K., Price, D. A., Harper, T. F., Betts, M. R., Yu, J., Gostick, E., Perfetto, S. P., Goepfert, P., Koup, R. A., De Rosa, S. C., et al. (2006) · Nature Medicine · doi:10.1038/nm1371 · Cited by 372
Self-citation
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A human memory T cell subset with stem cell–like properties
Gattinoni, L., Lugli, E., Ji, Y., Pos, Z., Paulos, C. M., Quigley, M. F., Almeida, J. R., Gostick, E., Yu, Z., Carpenito, C., et al. (2011) · Nature Medicine · doi:10.1038/nm.2446 · Cited by 1,974
Self-citationLong, A. H., Haso, W. M., Shern, J. F., Wanhainen, K. M., Murgai, M., Ingaramo, M., Smith, J. P., Walker, A. J., Kohler, M. E., Venkateshwara, V. R., et al. (2015) · Nature Medicine · doi:10.1038/nm.3838 · Cited by 1,815
mRNA vaccines induce durable immune memory to SARS-CoV-2 and variants of concern
Goel, R. R., Painter, M. M., Apostolidis, S. A., Mathew, D., Meng, W., Rosenfeld, A. M., Lundgreen, K. A., Reynaldi, A., Khoury, D. S., Pattekar, A., et al. (2021) · Science · doi:10.1126/science.abm0829 · Cited by 873
Exhaustion of tumor-specific CD8+ T cells in metastases from melanoma patients
Baitsch, L., Baumgaertner, P., Devêvre, E., Raghav, S. K., Legat, A., Barba, L., Wieckowski, S., Bouzourene, H., Deplancke, B., Romero, P., et al. (2011) · Journal of Clinical Investigation · doi:10.1172/jci46102 · Cited by 845
De Biasi, S., Meschiari, M., Gibellini, L., Bellinazzi, C., Borella, R., Fidanza, L., Gozzi, L., Iannone, A., Lo Tartaro, D., Mattioli, M., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-17292-4 · Cited by 789
Metadata
- Authors
- Roederer, M., Nozzi, J. L., & Nason, M. C.
- Venue
- Cytometry Part A
- Publisher
- Wiley
- Published
- 2011-01-07
- Volume
- 79A
- Issue
- 2
- Pages
- 167-174
- ISSN
- 1552-4922 (ISSN-L)
- 1552-4930
- OpenAlex
- W1965031244
- Cited by
- 831
- References
- 3
- FWCI
- 71.77
- Type
- journal article
- Language
- en
- Open access
- hybrid
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