Evidence map›Paper›PMID 24522610›Full record

ArticleScientific reports2014

Importance of collection in gene set enrichment analysis of drug response in cancer cell lines.

Alain R Bateman, Nehme El-Hachem, Andrew H Beck, Hugo J W L Aerts, Benjamin Haibe-Kains

Abstract read
In one paragraph

Article in Scientific reports, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 citing papers in PubMed.

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  9. Identification of Key circRNAs/lncRNAs/miRNAs/mRNAs and Pathways in Preeclampsia Using Bioinformatics Analysis.Medical science monitor : international medical journal of experimental and clinical research · 2019
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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.

Alain R BatemanBioinformatics and Computational Genomics Laboratory, Institut de Recherches Cliniques de Montréal, University of Montreal, Montreal, Quebec, Canada.
Nehme El-HachemBioinformatics and Computational Genomics Laboratory, Institut de Recherches Cliniques de Montréal, University of Montreal, Montreal, Quebec, Canada.
Andrew H BeckDepartment of Pathology, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA.
Hugo J W L Aerts1] Department of Biostatistics and Computational Biology and Center for Cancer Computational Biology, Dana-Farber Cancer Institute, Boston, MA, USA [2] Department of Radiation Oncology & Radiology, Dana-Farber Cancer Institute, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA [3] Department of Radiation Oncology, Maastricht University, Maastricht, The Netherlands.
Benjamin Haibe-Kains1] Bioinformatics and Computational Genomics Laboratory, Institut de Recherches Cliniques de Montréal, University of Montreal, Montreal, Quebec, Canada [2] Ontario Cancer Institute, Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Gene set enrichment analysis (GSEA) associates gene sets and phenotypes, its use is predicated on the choice of a pre-defined collection of sets. The defacto standard implementation of GSEA provides seven collections yet there are no guidelines for the choice of collections and the impact of such choice, if any, is unknown. Here we compare each of the standard gene set collections in the context of a large dataset of drug response in human cancer cell lines. We define and test a new collection based on gene co-expression in cancer cell lines to compare the performance of the standard collections to an externally derived cell line based collection. The results show that GSEA findings vary significantly depending on the collection chosen for analysis. Henceforth, collections should be carefully selected and reported in studies that leverage GSEA.

Indexed as

AlgorithmsCell Line, TumorComputational BiologyDatabases, GeneticGene Expression ProfilingGene Expression RegulationHumansNeoplasmsPharmaceutical PreparationsPharmaceutical Preparations

Identifiers

PMID24522610
PMCPMC3923229

What OpenQuestion holds

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LicenceCC BY-NC-SA
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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.