Journal article
Sequential Dirichlet process mixtures of multivariate skew t-distributions for model-based clustering of flow cytometry data
- Abstract:
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Flow cytometry is a high-throughput technology used to quantify multiple surface and intracellular markers at the level of a single cell. This enables us to identify cell subtypes and to determine their relative proportions. Improvements of this technology allow us to describe millions of individual cells from a blood sample using multiple markers. This results in high-dimensional datasets, whose manual analysis is highly time-consuming and poorly reproducible. While several methods have been...
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- Publication status:
- Published
- Peer review status:
- Peer reviewed
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(Version of record, pdf, 1.5MB)
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- Publisher copy:
- 10.1214/18-AOAS1209
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Authors
Funding
+ Agence nationale de la recherche
More from this funder
Grant:
BayesianNonparametricMethodsforSignal
ImageProcessingANR-13-BS-03-0006-0
Bibliographic Details
- Publisher:
- Institute of Mathematical Statistics Publisher's website
- Journal:
- Annals of Applied Statistics Journal website
- Volume:
- 13
- Issue:
- 1
- Pages:
- 638-660
- Publication date:
- 2019-04-10
- Acceptance date:
- 2018-09-05
- DOI:
- EISSN:
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1941-7330
- ISSN:
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1932-6157
- Source identifiers:
-
930504
Item Description
- Keywords:
- Pubs id:
-
pubs:930504
- UUID:
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uuid:c71b8430-b62f-4270-b31d-53108b2dde18
- Local pid:
- pubs:930504
- Deposit date:
- 2018-10-23
Terms of use
- Copyright holder:
- Institute of Mathematical Statistics
- Copyright date:
- 2019
- Notes:
- Copyright © 2019 Institute of Mathematical Statistics.
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