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MetaboShiny - interactive processing, analysis and identification of untargeted metabolomics data

Wolthuis, J. C.; Magnusdottir, S.; Pras-Raves, M.; Jans, J. J. M.; Burgering, B. M. T.; van Mil, S.; de Ridder, J.

2019-08-15 bioinformatics
10.1101/734236 bioRxiv
Show abstract

Direct infusion untargeted metabolomics, as mass-over-charge values and intensity of ions, allows for rapid insight into a samples metabolic activity. However, analysis is often complicated by the large array of detected m/z values and the difficulty to prioritize important m/z and simultaneously annotate their putative identities. To address this challenge, we developed MetaboShiny, a novel R/RShiny-based metabolomics package featuring data analysis, database- and formula-prediction-based annotation and visualization. To demonstrate this, we reproduce and further explore a MetaboLights metabolomics bioinformatics study on lung cancer patient urine samples. MetaboShiny enables rapid and rigorous analysis and interpretation of direct infusion untargeted metabolomics data.

Matching journals

The top 4 journals account for 50% of the predicted probability mass.

1
Analytical Chemistry
● 218 papers in training set
Top 0.1%
22.7%
Similar papers in this journal
2
Metabolites
○ 53 papers in training set
Top 0.1%
12.9%
Similar papers in this journal
3
Journal of the American Society for Mass Spectrometry
● 37 papers in training set
Top 0.1%
12.1%
Similar papers in this journal
4
Bioinformatics
◐ 1204 papers in training set
Top 4%
6.4%
Similar papers in this journal
50% of probability mass above
5
Journal of Proteome Research
● 234 papers in training set
Top 0.5%
6.4%
Similar papers in this journal
6
Nature Protocols
○ 33 papers in training set
Top 0.1%
5.6%
7
Nature Communications
○ 5641 papers in training set
Top 26%
5.6%
8
Nature Methods
○ 385 papers in training set
Top 3%
3.3%
9
Scientific Data
○ 209 papers in training set
Top 1%
2.2%
10
Briefings in Bioinformatics
◐ 354 papers in training set
Top 4%
1.9%
11
Scientific Reports
○ 3612 papers in training set
Top 51%
1.8%
12
BMC Bioinformatics
○ 457 papers in training set
Top 5%
1.1%
13
Analytica Chimica Acta
○ 17 papers in training set
Top 0.3%
1.1%
14
Bioinformatics Advances
◐ 203 papers in training set
Top 4%
1.1%
15
Communications Chemistry
○ 48 papers in training set
Top 1.0%
1.1%
16
Computational and Structural Biotechnology Journal
● 242 papers in training set
Top 5%
1.1%
17
PLOS ONE
● 5266 papers in training set
Top 58%
0.9%
18
Communications Biology
○ 993 papers in training set
Top 33%
0.6%
19
Cell Reports Methods
○ 165 papers in training set
Top 4%
0.6%
20
Chemical Science
● 73 papers in training set
Top 2%
0.6%

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.