The
increasing popularity of high-resolution mass spectrometry
has led to many custom software solutions to process, interpret, and
reveal information from high-resolution mass spectra. Although there
are numerous software packages for peak-picking, calibration, and
formula-finding, there are additional layers of information available
when it comes to detecting repeated motifs from polymers or molecules
with repeating structures or products of chemical or biochemical transformations
that exhibit systematic, serial chemical changes of mass. Constellation
is an open-source, Python-based web application that allows the user
first to expand their high-resolution mass data into the mass defect
space, after which a trend finding algorithm is used for supervised
or unsupervised detection of repeating motifs. Many adjustable parameters
allow the user to tailor their trend-search to target particular chemical
moieties or repeating units, or search for all potential motifs within
certain limits. The algorithm has a built-in optimization routine
to provide a good starting point for the main trend finding parameters
before user customization. Visualization tools allow interrogation
of the data and any trends/patterns to a highly specific degree and
save publication-quality images directly from the interface. As Constellation
is deployed as a web application, it is easily used by anyone with
a web browser; no software download or high-powered computer is required,
as computations are performed on a remote high-powered data server
run by our group.