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Update paper.md #687

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Expand Up @@ -57,8 +57,8 @@ commonly used platforms are based on mass-spectrometry (MS) and nuclear magnetic
resonance (NMR). Investigators are increasingly using both methods to
increase the metabolite coverage. The challenge for this type of multi-platform
approach is that the data structure may be very different in these two
platforms. For example, NMR data may be reported as a list of spectral features
e.g. bins or peaks with arbitrary intensity units or more directly with named
platforms. For example, NMR data may be reported as a list of spectral features,
e.g., bins or peaks with arbitrary intensity units or more directly with named
metabolites reported in concentration units ranging from micromolar to
millimolar. Some MS approaches can also provide data in the form of identified
metabolite concentrations, but given the superior sensitivity of MS, the
Expand All @@ -67,9 +67,9 @@ approaches yield data in the form of arbitrary response units where the dynamic
range can be more than 6 orders of magnitude.
Importantly, the variability and reproducibility of the data may differ across platforms.
Given the diversity of data
structures (i.e. magnitude and dynamic range) integrating the data from multiple
structures (i.e., magnitude and dynamic range) integrating the data from multiple
platforms can be challenging. This often leads investigators to analyze the
datasets separately which prevents the observation of potentially interesting
datasets separately, which prevents the observation of potentially interesting
relationships and
correlations between metabolites detected on different platforms. Viime
(VIsualization and Integration of Metabolomics Experiments)
Expand Down Expand Up @@ -378,12 +378,12 @@ visualization tools that are generally similar to Viime.
An exhaustive feature comparison with these other platforms is beyond the scope
of this paper, but a major distinguishing feature of Viime is its emphasis on
ease of use and interactivity. Only XCMS and MetaboAnalyst are simple, readily
accessible web applications that require no existing package (e.g. R), downloads
accessible web applications that require no existing package (e.g., R), downloads
or connection to the Galaxy platform. The unique user interactivity in Viime
starts with the ability to simply drag and drop CSV or Excel files and
interactively assign the sample identifiers, comparison groups, metadata, and
metabolites. Dynamic visualization of the PCA scores and loadings plots with
different types of data (e.g. NMR, LC-MS, and GC-MS) and data treatments (e.g.
different types of data (e.g., NMR, LC-MS, and GC-MS) and data treatments (e.g.,
normalization, scaling and transformation) aids in selecting the optimal data
treatment. Viime also enables integration between different data modalities,
offering simple (i.e., concatenative), mid-level, and multi-block data fusion
Expand Down