Peptimetric: Quantifying and Visualizing Differences in Peptidomic Data

Finding new sustainable means of diagnosing and treating diseases is one of the most
pressing issues of our time. In recent years, several endogenous peptides have been found
to be both excellent biomarkers for many diseases and to possess important physiological
roles which may be utilized in treatments. The detection of peptides has been facilitated by
the rapid development of biological mass spectrometry and now the combination of fast
and sensitive high resolution MS instruments and stable nano HP-LC equipment
sequences thousands of peptides in one single experiment. In most research
conducted with these advanced systems, proteolytically cleaved proteins are analyzed
and the specific peptides are identified by software dedicated for protein quantification
using different proteomics workflows. Analysis of endogenous peptides with peptidomics
workflows also benefit from the novel sensitive and advanced instrumentation, however,
the generated peptidomic data is vast and subsequently laborious to visualize and
examine, creating a bottleneck in the analysis. Therefore, we have created Peptimetric,
an application designed to allow researchers to investigate and discover differences
between peptidomic samples. Peptimetric allows the user to dynamically and
interactively investigate the proteins, peptides, and some general characteristics of
multiple samples, and is available as a web application at https://peptimetric.
herokuapp.com. To illustrate the utility of Peptimetric, we’ve applied it to a peptidomic
dataset of 15 urine samples from diabetic patients and corresponding data from healthy
subjects.