Evidence map›Paper›PMID 19187010›Full record

ArticleAssay and drug development technologies2009

WebFlow: a software package for high-throughput analysis of flow cytometry data.

Mark M Hammer, Nikesh Kotecha, Jonathan M Irish, Garry P Nolan, Peter O Krutzik

Abstract read
In one paragraph

Article in Assay and drug development technologies, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
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

4 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Article
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

5 authors.

Mark M HammerBaxter Laboratory in Genetic Pharmacology, Department of Microbiology, Stanford University, Stanford, California 94305, USA.
Nikesh Kotecha
Jonathan M Irish
Garry P Nolan
Peter O Krutzik

Funding

POSTDOCTORAL TRAINING IN MEDICAL INFORMATION SCIENCEST15LM007033 · NLM · STANFORD UNIVERSITY · PI SYLVIA KATINA PLEVRITIS · 1985 to 2026
$25.5M
NF-KB P50 AND BCL-3 AS COREGULATORS OF HIV AND BCL-3R01AI035304 · NIAID · STANFORD UNIVERSITY · PI NOLAN, GARRY P · 1994 to 2004
$1.5M
Targeting the B Cell Receptor Signaling Network in LymphomaK99CA143231 · NCI · STANFORD UNIVERSITY · PI IRISH, JONATHAN MICHAEL · 2009 to 2009
$136k
NHLBI PROTEOMICS INITIATIVE-N01HV28183N01HV028183 · HV · STANFORD UNIVERSITY · PI NOLAN, GARRY P · 2002 to 2006
–
NHLBI NIH HHS N01-HV-28183NIAID NIH HHS AI35304NLM NIH HHS T15 LM007033
6 · The paper itself

Abstract

Flow cytometry has emerged as a powerful tool for quantitative, single-cell analysis of both surface markers and intracellular antigens, including phosphoproteins and kinase signaling cascades, with the flexibility to process hundreds of samples in multiwell plate format. Quantitative flow cytometric analysis is being applied in many areas of biology, from the study of immunology in animal models or human patients to high-content drug screening of pharmacologically active compounds. However, these experiments generate thousands of data points per sample, each with multiple measured parameters, leading to data management and analysis challenges. We developed WebFlow (http://webflow.stanford.edu), a web server-based software package to manage, analyze, and visualize data from flow cytometry experiments. WebFlow is accessible via standard web browsers and does not require users to install software on their personal computers. The software enables plate-based annotation of large data sets, which provides the basis for exploratory data analysis tools and rapid visualization of multiple different parameters. These tools include custom user-defined statistics to normalize data to other wells or other channels, as well as interactive, user-selectable heat maps for viewing the underlying single-cell data. The web-based approach of WebFlow allows for sharing of data with collaborators or the general public. WebFlow provides a novel platform for quantitative analysis of flow cytometric data from high-throughput drug screening or disease profiling experiments.

Indexed as

SoftwareAnimalsData Interpretation, StatisticalDose-Response Relationship, DrugDrug Evaluation, PreclinicalFlow CytometryHumansInternetMembrane ProteinsU937 CellsMembrane Proteins

Identifiers

PMID19187010
PMCPMC2956679

What OpenQuestion holds

Textmetadata
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.