Silver: Forging almost Gold Standard Datasets.

Farhad Maleki, Katie Ovens, Ian McQuillan, Anthony J Kusalik

Abstract read

In one paragraph

Article in Genes, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it

0cells of the map it votes in

1citing 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

1 citing paper in PubMed.

Editorial: Advancement in Gene Set Analysis: Gaining Insight From High-Throughput Data.Frontiers in genetics · 2022
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

4 authors.

Farhad MalekiAugmented Intelligence & Precision Health Laboratory, Institute of the McGill University Health Centre, McGill University, Montreal, QC H4A 3S5, Canada.ORCID 0000-0002-5673-8210

Katie OvensAugmented Intelligence & Precision Health Laboratory, Institute of the McGill University Health Centre, McGill University, Montreal, QC H4A 3S5, Canada.ORCID 0000-0001-5956-7739

Ian McQuillanDepartment of Computer Science, University of Saskatchewan, Saskatoon, SK S7N 5C9, Canada.

Anthony J KusalikDepartment of Computer Science, University of Saskatchewan, Saskatoon, SK S7N 5C9, Canada.ORCID 0000-0001-9278-8859

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Gene set analysis has been widely used to gain insight from high-throughput expression studies. Although various tools and methods have been developed for gene set analysis, there is no consensus among researchers regarding best practice(s). Most often, evaluation studies have reported contradictory recommendations of which methods are superior. Therefore, an unbiased quantitative framework for evaluations of gene set analysis methods will be valuable. Such a framework requires gene expression datasets where enrichment status of gene sets is known

Indexed as

SoftwareDatabases, GeneticDatasets as TopicGenomicsgene set analysissensitivityspecificitysynthetic data

Identifiers

PMID34680918

DOI10.3390/genes12101523

PMCPMC8535810

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.