flowCore: a Bioconductor package for high throughput flow cytometry
Top Cited Papers
Open Access
- 9 April 2009
- journal article
- research article
- Published by Springer Nature in BMC Bioinformatics
- Vol. 10 (1) , 106
- https://doi.org/10.1186/1471-2105-10-106
Abstract
Recent advances in automation technologies have enabled the use of flow cytometry for high throughput screening, generating large complex data sets often in clinical trials or drug discovery settings. However, data management and data analysis methods have not advanced sufficiently far from the initial small-scale studies to support modeling in the presence of multiple covariates.This publication has 14 references indexed in Scilit:
- Phenotype and function of human T lymphocyte subsets: Consensus and issuesCytometry Part A, 2008
- Gating‐ML: XML‐based gating descriptions in flow cytometryCytometry Part A, 2008
- Automated gating of flow cytometry data via robust model‐based clusteringCytometry Part A, 2008
- Flow cytometry analyses and bioinformatics: Interest in new softwares to optimize novel technologies and to favor the emergence of innovative concepts in cell researchCytometry Part A, 2007
- Optimizing a Multicolor Immunophenotyping AssayPublished by Elsevier ,2007
- High-Content Flow Cytometry and Temporal Data Analysis for Defining a Cellular Signature of Graft-Versus-Host DiseaseTransplantation and Cellular Therapy, 2007
- Standardization of cytokine flow cytometry assaysBMC Immunology, 2005
- Identification of compounds that enhance the anti-lymphoma activity of rituximab using flow cytometric high-content screeningJournal of Immunological Methods, 2004
- Bioconductor: open software development for computational biology and bioinformaticsGenome Biology, 2004
- Proposed new data file standard for flow cytometry, version FCS 3.0Cytometry, 1997