Evidence map›Paper›PMID 28994825›Full record

ArticleScientific data2017

Clustergrammer, a web-based heatmap visualization and analysis tool for high-dimensional biological data.

Nicolas F Fernandez, Gregory W Gundersen, Adeeb Rahman, Mark L Grimes, Klarisa Rikova, Peter Hornbeck, Avi Ma'ayan

Abstract readDataset
In one paragraph

Article in Scientific data, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 132 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
132citing papers in PubMed, 1 pooled it
–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

132 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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72 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

7 authors.

Nicolas F FernandezDepartment of Pharmacological Sciences, Mount Sinai Center for Bioinformatics, BD2K-LINCS Data Coordination and Integration Center (DCIC), Icahn School of Medicine at Mount Sinai, New York, New York 10029, USA.
Gregory W GundersenDepartment of Pharmacological Sciences, Mount Sinai Center for Bioinformatics, BD2K-LINCS Data Coordination and Integration Center (DCIC), Icahn School of Medicine at Mount Sinai, New York, New York 10029, USA.
Adeeb RahmanHuman Immune Monitoring Core, Icahn School of Medicine at Mount Sinai, New York, New York 10029, USA.
Mark L GrimesCenter for Structural and Functional Neuroscience, University of Montana, Missoula, Montana 59812, USA.
Klarisa RikovaCell Signaling Technology Inc., Danvers, Massachusetts 01923, USA.
Peter HornbeckCell Signaling Technology Inc., Danvers, Massachusetts 01923, USA.
Avi Ma'ayanDepartment of Pharmacological Sciences, Mount Sinai Center for Bioinformatics, BD2K-LINCS Data Coordination and Integration Center (DCIC), Icahn School of Medicine at Mount Sinai, New York, New York 10029, USA.

Funding

Data Coordination and Integration Center for LINCS-BD2KU54HL127624 · NHLBI · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI MA'AYAN, AVI, SCHURER, STEPHAN C · 2014 to 2019
$23.5M
User Interface PortalU54CA189201 · NCI · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI DUDLEY, JOEL THOMAS, MA'AYAN, AVI · 2014 to 2017
$1.9M
Expression2Kinases: mRNA Profiling Linked to Multiple Upstream Regulatory LayersR01GM098316 · NIGMS · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI MA'AYAN, AVI · 2012 to 2015
$1.3M
NCI NIH HHS U54 CA189201NHLBI NIH HHS U54 HL127624NIGMS NIH HHS R01 GM098316
6 · The paper itself

Abstract

Most tools developed to visualize hierarchically clustered heatmaps generate static images. Clustergrammer is a web-based visualization tool with interactive features such as: zooming, panning, filtering, reordering, sharing, performing enrichment analysis, and providing dynamic gene annotations. Clustergrammer can be used to generate shareable interactive visualizations by uploading a data table to a web-site, or by embedding Clustergrammer in Jupyter Notebooks. The Clustergrammer core libraries can also be used as a toolkit by developers to generate visualizations within their own applications. Clustergrammer is demonstrated using gene expression data from the cancer cell line encyclopedia (CCLE), original post-translational modification data collected from lung cancer cells lines by a mass spectrometry approach, and original cytometry by time of flight (CyTOF) single-cell proteomics data from blood. Clustergrammer enables producing interactive web based visualizations for the analysis of diverse biological data.

Indexed as

SoftwareAnimalsElectronic Data ProcessingGene ExpressionGene Expression ProfilingHumansProteomics

Identifiers

PMID28994825
PMCPMC5634325

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.