Evidence map›Paper›PMID 29109515›Full record

ArticleScientific reports2017

Chemical Similarity Enrichment Analysis (ChemRICH) as alternative to biochemical pathway mapping for metabolomic datasets.

Dinesh Kumar Barupal, Oliver Fiehn

Abstract read
In one paragraph

Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 204 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
204citing 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

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

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144 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

2 authors.

Dinesh Kumar BarupalNIH-West Coast Metabolomics Center, Genome Center University of California, Davis, USA.
Oliver FiehnNIH-West Coast Metabolomics Center, Genome Center University of California, Davis, USA. ofiehn@ucdavis.edu.ORCID 0000-0002-6261-8928

Funding

West Coast Central Comprehensive Metabolomics Resource Core (WC3MRC)U24DK097154 · NIDDK · UNIVERSITY OF CALIFORNIA AT DAVIS · PI FIEHN, OLIVER · 2012 to 2017
$9.9M
NIDDK NIH HHS U24 DK097154
6 · The paper itself

Abstract

Metabolomics answers a fundamental question in biology: How does metabolism respond to genetic, environmental or phenotypic perturbations? Combining several metabolomics assays can yield datasets for more than 800 structurally identified metabolites. However, biological interpretations of metabolic regulation in these datasets are hindered by inherent limits of pathway enrichment statistics. We have developed ChemRICH, a statistical enrichment approach that is based on chemical similarity rather than sparse biochemical knowledge annotations. ChemRICH utilizes structure similarity and chemical ontologies to map all known metabolites and name metabolic modules. Unlike pathway mapping, this strategy yields study-specific, non-overlapping sets of all identified metabolites. Subsequent enrichment statistics is superior to pathway enrichments because ChemRICH sets have a self-contained size where p-values do not rely on the size of a background database. We demonstrate ChemRICH's efficiency on a public metabolomics data set discerning the development of type 1 diabetes in a non-obese diabetic mouse model. ChemRICH is available at www.chemrich.fiehnlab.ucdavis.edu.

Indexed as

Data Interpretation, StatisticalMetabolic Networks and PathwaysMetabolomicsAnimalsBiological OntologiesDatasets as TopicDiabetes Mellitus, ExperimentalDisease Models, AnimalHumansMice

Identifiers

PMID29109515
PMCPMC5673929

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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.