ArticleCytometry. Part A : the journal of the International Society for Analytical Cytology2009
Scalable analysis of flow cytometry data using R/Bioconductor.
Article in Cytometry. Part A : the journal of the International Society for Analytical Cytology, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
13 citing papers in PubMed, 25 citations in OpenAlex.
- Cell Communication Network factor 4 promotes tumor-induced immunosuppression in breast cancer.bioRxiv : the preprint server for biology · 2026Article
- Data-driven learning how oncogenic gene expression locally alters heterocellular networks.Nature communications · 2022Article
- A Method for the Interpretation of Flow Cytometry Data Using Genetic Algorithms.Journal of pathology informatics · 2018Article
- Melanoma exosomes deliver a complex biological payload that upregulates PTPN11 to suppress T lymphocyte function.Pigment cell & melanoma research · 2017Article
- Interlocked positive and negative feedback network motifs regulate β-catenin activity in the adherens junction pathway.Molecular biology of the cell · 2015Article
- Exosomes: improved methods to characterize their morphology, RNA content, and surface protein biomarkers.The Analyst · 2015Article
- cGMP-dependent protein kinase I gamma encodes a nuclear localization signal that regulates nuclear compartmentation and function.Cellular signalling · 2014Article
- Induction of Wnt-inducible signaling protein-1 correlates with invasive breast cancer oncogenesis and reduced type 1 cell-mediated cytotoxic immunity: a retrospective study.PLoS computational biology · 2014Article
- A quantitative systems approach to identify paracrine mechanisms that locally suppress immune response to Interleukin-12 in the B16 melanoma model.Integrative biology : quantitative biosciences from nano to macro · 2012Article
- Quantifying crosstalk among interferon-γ, interleukin-12, and tumor necrosis factor signaling pathways within a TH1 cell model.Science signaling · 2012Article
- Inferring relevant control mechanisms for interleukin-12 signaling in naïve CD4+ T cells.Immunology and cell biology · 2011Article
- Data reduction for spectral clustering to analyze high throughput flow cytometry data.BMC bioinformatics · 2010Article
- Anti-Tumor Effect ofIranian journal of parasitologyArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
Flow cytometry is one of the fundamental research tools available to the life scientist. The ability to observe multidimensional changes in protein expression and activity at single-cell resolution for a large number of cells provides a unique perspective on the behavior of cell populations. However, the analysis of complex multidimensional data is one of the obstacles for wider use of polychromatic flow cytometry. Recent enhancements to an open-source platform-R/Bioconductor-enable the graphical and data analysis of flow cytometry data. Prior examples have focused on high-throughput applications. To facilitate wider use of this platform for flow cytometry, the analysis of a dataset, obtained following isolation of CD4(+)CD62L(+) T cells from Balb/c splenocytes using magnetic microbeads, is presented as a form of tutorial. A common workflow for analyzing flow cytometry data was presented using R/Bioconductor. In addition, density function estimation and principal component analysis are provided as examples of more complex analyses. The compendium presented here is intended to help illuminate a path for inquisitive readers to explore their own data using R/Bioconductor (available as Supporting Information).
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.