» Articles » PMID: 31943015

EpiMetal: an Open-source Graphical Web Browser Tool for Easy Statistical Analyses in Epidemiology and Metabolomics

Abstract

Motivation: An intuitive graphical interface that allows statistical analyses and visualizations of extensive data without any knowledge of dedicated statistical software or programming.

Implementation: EpiMetal is a single-page web application written in JavaScript, to be used via a modern desktop web browser.

General Features: Standard epidemiological analyses and self-organizing maps for data-driven metabolic profiling are included. Multiple extensive datasets with an arbitrary number of continuous and category variables can be integrated with the software. Any snapshot of the analyses can be saved and shared with others via a www-link. We demonstrate the usage of EpiMetal using pilot data with over 500 quantitative molecular measures for each sample as well as in two large-scale epidemiological cohorts (N >10 000).

Availability: The software usage exemplar and the pilot data are open access online at [http://EpiMetal.computationalmedicine.fi]. MIT licensed source code is available at the Github repository at [https://github.com/amergin/epimetal].

Citing Articles

Clinical and biochemical associations of urinary metabolites: quantitative epidemiological approach on renal-cardiometabolic biomarkers.

Li T, Ihanus A, Ohukainen P, Jarvelin M, Kahonen M, Kettunen J Int J Epidemiol. 2023; 53(1).

PMID: 38030573 PMC: 10859141. DOI: 10.1093/ije/dyad162.


New software tools, databases, and resources in metabolomics: updates from 2020.

Misra B Metabolomics. 2021; 17(5):49.

PMID: 33977389 PMC: 8112213. DOI: 10.1007/s11306-021-01796-1.

References
1.
Lithovius R, Toppila I, Harjutsalo V, Forsblom C, Groop P, Makinen V . Data-driven metabolic subtypes predict future adverse events in individuals with type 1 diabetes. Diabetologia. 2017; 60(7):1234-1243. DOI: 10.1007/s00125-017-4273-8. View

2.
Schaefer E, Levy R, Anderson D, Danner R, BREWER Jr H, Blackwelder W . Plasma-triglycerides in regulation of H.D.L.-cholesterol levels. Lancet. 1978; 2(8086):391-3. DOI: 10.1016/s0140-6736(78)91863-9. View

3.
Makinen V, Forsblom C, Thorn L, Waden J, Gordin D, Heikkila O . Metabolic phenotypes, vascular complications, and premature deaths in a population of 4,197 patients with type 1 diabetes. Diabetes. 2008; 57(9):2480-7. PMC: 2518500. DOI: 10.2337/db08-0332. View

4.
Makinen V, Kangas A, Soininen P, Wurtz P, Groop P, Ala-Korpela M . Metabolic phenotyping of diabetic nephropathy. Clin Pharmacol Ther. 2013; 94(5):566-9. DOI: 10.1038/clpt.2013.158. View

5.
Weir J, Wong G, Barlow C, Greeve M, Kowalczyk A, Almasy L . Plasma lipid profiling in a large population-based cohort. J Lipid Res. 2013; 54(10):2898-908. PMC: 3770102. DOI: 10.1194/jlr.P035808. View