Evidence map›Paper›PMID 19358741›Full record

ArticleBMC bioinformatics2009

flowCore: a Bioconductor package for high throughput flow cytometry.

Florian Hahne, Nolwenn LeMeur, Ryan R Brinkman, Byron Ellis, Perry Haaland, Deepayan Sarkar, Josef Spidlen, Errol Strain, Robert Gentleman

Open access · goldAbstract read
In one paragraph

Article in BMC bioinformatics, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 355 papers.

0numbers the graph read from it
0cells of the map it votes in
355citing papers in PubMed
5.4field-weighted citation impact, top 3% of its field
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

355 citing papers in PubMed, 645 citations in OpenAlex.

  1. Trial
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  10. Reproducible Data Analysis With R in Laboratory Hematology.International journal of laboratory hematology · 2026
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  13. DNA damage-associated vesicle production inJournal of bacteriology · 2026
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  15. Opsonization Improves Dual Proteomic Analysis ofJournal of proteome research · 2026
    Article
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  19. Review
  20. bioRxiv : the preprint server for biology · 2026
    Article

295 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 6 institutions in 3 countries.

Florian HahneLife Sciences Department, Computational Biology Program, Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington 98109-1024, USA. fhahne@fhcrc.org
Nolwenn LeMeur
Ryan R Brinkman
Byron Ellis
Perry Haaland
Deepayan Sarkar
Josef Spidlen
Errol Strain
Robert Gentleman
Fred Hutch Cancer Center · USResearch Triangle Park Foundation · USBC Cancer Agency · CACBRITE (United States) · USTerry Fox Research Institute · CAUniversité de Rennes · FR

Funding

The Statistical and Computational Analysis of Flow Cytometry DataR01EB008400 · NIBIB · FRED HUTCHINSON CANCER RESEARCH CENTER · PI GOTTARDO, RAPHAEL · 2008 to 2015
$2.9M
Bioinformatics Standards for Flow CytometryR01EB005034 · NIBIB · BRITISH COLUMBIA CANCER AGENCY · PI BRINKMAN, RYAN REMY · 2005 to 2008
$912k
NIBIB NIH HHS EB005034NIBIB NIH HHS R01 EB005034NIBIB NIH HHS R01 EB008400
6 · The paper itself

Abstract

backgroundRecent 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.

resultsWe developed a set of flexible open source computational tools in the R package flowCore to facilitate the analysis of these complex data. A key component of which is having suitable data structures that support the application of similar operations to a collection of samples or a clinical cohort. In addition, our software constitutes a shared and extensible research platform that enables collaboration between bioinformaticians, computer scientists, statisticians, biologists and clinicians. This platform will foster the development of novel analytic methods for flow cytometry.

conclusionThe software has been applied in the analysis of various data sets and its data structures have proven to be highly efficient in capturing and organizing the analytic work flow. Finally, a number of additional Bioconductor packages successfully build on the infrastructure provided by flowCore, open new avenues for flow data analysis.

Indexed as

Flow CytometrySoftwareComputational BiologyDatabase Management SystemsDrug DiscoveryInformation Storage and RetrievalUser-Computer Interface

Identifiers

PMID19358741
PMCPMC2684747
OpenAlexW2150756255

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.