Data analysis for metabolomics and small
molecule mass spectrometry.
The Problem: Untargeted metabolomics suffers
from incomplete data analysis
Untargeted metabolomics is a powerful tool for biological discoveries.
However, these discoveries are highly dependent on the quality of analysis of
the raw data. Reliable detection of relevant signals in the raw data and the
correct interpretation of the underlying spectral features are critical for both
exploratory research as well as multi-omic data integration. Reanalysis of
published untargeted metabolomics studies shows omissions of numerous relevant
compounds in original results as well as typical interpretation mistakes. These
results show an unexplored potential of current as well as legacy metabolomics
data.
Examples of omissions and mistakes in results from a published
study. (
a) Visualization of a part of one of the raw datafiles. Gray
labels correspond to annotations from original results accompanying the study
data. Magenta labels correspond to omissions or mistakes. (
b-d) Mass
spectra and extracted ion chromatograms for examples of omissions. (
e) A
mass spectrum and extracted ion chromatograms for examples of mistakes. An
in-source fragment ion and an isotopic peak of a multimer of HEPES were
incorrectly identified as different compounds. Peaks of related ions for a given
compound in plots of mass spectra are highlighted in magenta. More examples:
https://doi.org/10.1101/143818
Solution 1: Our data
analysis services
We can analyze your raw data and
deliver lists of peaks with peak areas as well as lists of corresponding
compounds with putative identities, where possible. We use our own computational
tools, but the key aspect of the service is manual curation of the results by
experts. We can help you to correct your existing results, find key differences
among samples, or perform an exhaustive data analysis. Avoid omissions and
mistakes in your results.
Contact us to learn more about
the possibilities and benefits of working with us.
Use high quality expert
curated results for your downstream analysis!
Solution 2:
MassCurator Software
MassCurator is the right tool for rigorous data analysis of your
untargeted metabolomics data. MassCurator provides robust automated tools as
well as a responsive interactive interface for data analysis. Use MassCurator to
correct your existing results or to analyze your raw data from scratch.
Contact:
