A fast-growing variety of analytical instruments produce enormous amounts of spectral data (mostly mass-spec). R and Python libraries provide probably the most rich and versatile set of tools for mass-spec processing and especially – classification. It seems natural to have some universal intermediator, between the proprietary mass-spec acquisition software and your script. That intermediator imports the spectral data, organizes it in a structure appropriate for classification, performs pre-processing and finally allows the data to be read from within your script. The purpose of such a universal intermediator is to provide script functions to manipulate and extract data, but at the same time offer a visual interactive control over the spectral data as needed. The ability for visual control (QC) and comparison of spectra, as well as adjusting the pre-processing options are critical for the efficiency of the data preparation. As almost all analytical instruments are running under Windows, so having Spectrino under the same OS is an expected extension of an established practice.
What is it...
The name Spectrino is allusion from neutron -> neutrino, so spectrum -> Spectrino (a tiny spectrum).
You may read an article about Spectrino in "Journal of Statistical Software" https://www.jstatsoft.org/article/view/v018i10 .
R project statistical software or Python offer powerful facilities for quantitative and qualitative analysis for different types of spectral data - variation analysis, linear and non-linear models, etc. From other side, all sorts of spectral instruments generate data, which must be formatted and organized for further analysis. Spectrino interposes between these two sides, serving as spectra organizer for the spectroscopists and as a visualization / data-extraction tool for the statisticians/data analysts.
Here is a typical situation: mass-spectrometrist measured samples from different classes of compounds (e.g. types of oils), after visual check some of the measured mass-spectra are exported to Spectrino (as X-Y pair flat files) in the appropriate group. When the whole data collection is ready for analysis, the data (being in Spectrino) are ready for analysis. So if the mass-spectrometrist has some ready-to-use tools in R to analyze the data, he does it, otherwise the data collection (list of groups in Spectrino) is going to the statistics guys to deal with.
Version 2.0 of Spectrino adds new features to the
spectral part of the application (multi-tab spec-trees) and a new part -
blocks of properties. The latter provides user interface to a list of
properties (accessible from your script) as well as log, chart and
snippet (small pieces of code) support. See the manual.