Background: Bioinformatic tools for the enrichment of 'omics' datasets facilitate interpretation and understanding of data. To date few are suitable for metabolomics datasets. The main objective of this work is to give a critical overview, for the first time, of the performance of these tools. To that aim, datasets from metabolomic repositories were selected and enriched data were created. Both types of data were analysed with these tools and outputs were thoroughly examined.
Results: An exploratory multivariate analysis of the most used tools for the enrichment of metabolite sets, based on a non-metric multidimensional scaling (NMDS) of Jaccard's distances, was performed and mirrored their diversity. Codes (identifiers) of the metabolites of the datasets were searched in different metabolite databases (HMDB, KEGG, PubChem, ChEBI, BioCyc/HumanCyc, LipidMAPS, ChemSpider, METLIN and Recon2). The databases that presented more identifiers of the metabolites of the dataset were PubChem, followed by METLIN and ChEBI. However, these databases had duplicated entries and might present false positives. The performance of over-representation analysis (ORA) tools, including BioCyc/HumanCyc, ConsensusPathDB, IMPaLA, MBRole, MetaboAnalyst, Metabox, MetExplore, MPEA, PathVisio and Reactome and the mapping tool KEGGREST, was examined. Results were mostly consistent among tools and between real and enriched data despite the variability of the tools. Nevertheless, a few controversial results such as differences in the total number of metabolites were also found. Disease-based enrichment analyses were also assessed, but they were not found to be accurate probably due to the fact that metabolite disease sets are not up-to-date and the difficulty of predicting diseases from a list of metabolites.
Conclusions: We have extensively reviewed the state-of-the-art of the available range of tools for metabolomic datasets, the completeness of metabolite databases, the performance of ORA methods and disease-based analyses. Despite the variability of the tools, they provided consistent results independent of their analytic approach. However, more work on the completeness of metabolite and pathway databases is required, which strongly affects the accuracy of enrichment analyses. Improvements will be translated into more accurate and global insights of the metabolome.
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http://dx.doi.org/10.1186/s12859-017-2006-0 | DOI Listing |
J Chromatogr A
December 2024
Electroanalytical Chemistry Research Laboratory, Department of Analytical Chemistry, Faculty of Chemistry, University of Mazandaran, Babolsar, Iran.
A new thin film was fabricated using FeO@SiO-polyoxometalate (POM) as the coating and it was coupled with a HPLC-UV to develop a method for the selective determination of ibuprofen, paracetamol and diclofenac (as the model analytes) from human plasma and urine samples. The prepared magnetic POM was coated on the pores and surface of cotton yarn to prepare the extracting device. The prepared sorbent was characterized by several techniques including: FT-IR, XRD, BET, SEM, and VSM analysis.
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December 2024
Division of Pediatric Surgery, Department of Surgery, Max Rady College of Medicine, University of Manitoba, and Children's Hospital Research Institute of Manitoba, AE402-820 Sherbrook Street, Winnipeg, MB, R3A 1S1, Canada.
Purpose: Circular RNAs (circRNAs) are stable, non-coding RNAs with tissue- and developmental-specific expression making them suitable biomarkers for congenital anomalies. Current circRNA discovery pipelines have focused on human and mouse. We aim to bridge this gap by combining bioinformatics resources and used circtial1 as a model candidate in the nitrofen rat model of congenital diaphragmatic hernia (CDH).
View Article and Find Full Text PDFRes Involv Engagem
December 2024
HEARTS Study Team, Mental Health Accessibility and Policy Solutions Lab, Mississauga, Ontario, Canada.
Background: This commentary article critically assesses the inclusion and recognition of young adults with lived and living experiences (YALLE) in academic publishing. Stemming from our involvement in a health research study, this analysis interrogates the disparity between the stated importance of YALLE contributions in health research and their actual recognition, specifically in academic publications, which serve as the principal "currency" in research. This tokenism limits the potential for their unique insights to substantially enrich the discourse and dissemination of knowledge.
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December 2024
Key Laboratory of Molecular Biophysics of the Ministry of Education, Hubei Key Laboratory of Bioinformatics and Molecular Imaging, Department of Bioinformatics and Systems Biology, Center for Artificial Intelligence Biology, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei, 430074, China.
Background: Metagenome-assembled viral genomes have significantly advanced the discovery and characterization of the human gut virome. However, we lack a comparative assessment of assembly tools on the efficacy of viral genome identification, particularly across next-generation sequencing (NGS) and third-generation sequencing (TGS) data.
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NAR Genom Bioinform
December 2024
Precision Health, The Kids Research Institute Australia, 15 Hospital Ave, Nedlands, 6009, WA, Australia.
A robust understanding of the cellular mechanisms underlying diseases sets the foundation for the effective design of drugs and other interventions. The wealth of existing single-cell atlases offers the opportunity to uncover high-resolution information on expression patterns across various cell types and time points. To better understand the associations between cell types and diseases, we leveraged previously developed tools to construct a standardized analysis pipeline and systematically explored associations across four single-cell datasets, spanning a range of tissue types, cell types and developmental time periods.
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