<h1> ChromaQuant Pre-alpha is now online (0.3.1)! </h1>
<img width="256" alt="ChromaQuant Logo" src="https://github.com/JnliaH/ChromaQuant/blob/main/images/ChromaQuantIcon.png">
<h2> Pre-Introduction Notes </h2>
This is the ChromaQuant 0.3.1 release. It is the exact same as 0.3.0 but with an updated README, workflow diagram, and (of course) package wheel. This is the first release published on PyPI!
<h2> Introduction </h2>
We're super excited to be releasing v0.3.1 as ChromaQuant's first, public open source release. This version is packaged with all the fundamentals of the software: that is, fully-fledged FID and MS peak matching via retention time- and third-order-based modeling and a robust quantification algorithm.
<h2> Details </h2>
This release assumes that the user is able to obtain integration values, peak compound labels, and spectra via external software. This release also has several points at which personal configuration is hard-coded: right now, TCD data is only used to quantify gas-phase C1-C4 hydrocarbons and nonionizable species (e.g., hydrogen). Gas-phase FID data is used to quantify gas-phase C5+, and liquid-phase FID data is used to quantify all liquid hydrocarbons. There are points at which preferences can be changed in the script to specify which elements are excluded from quantification, which we have used in our case to only to quantify hydrocarbon products.
As for response factor assignment, this is also limited. It is assumed that an external standard along with pre-determined extrapolated response factors is used for Gas FID quantification. It is likewise assumed that an internal standard of CO2 is used for TCD quantification. Finally, it is assumed that an internal standard method is used for liquids analysis.
The degree to which this script is customizable to certain workflows and GC configurations varies by portion. The quantification algorithm as of now is tailored to our specific case, whereas the response factor and peak matching algorithms are more easily generalizable. Future releases will focus on separating functionality and making it easier to apply this project in cases different than ours.
There are further details about the limitations of this project that have been left out here, such as the dependence of the third-order modeling script on some number of manually-assigned peaks in the early retention time region. Keep an eye out for improvements as well as further documentation of these issues and limitations.
<h2> Installation </h2>
This project will be distributed on PyPI and should be able to be installed using pip. This shifts this project's structure from a downloadable, self-standing application to a package with dependencies. Keep an eye out for further installation instructions in the README.md
<h2> Conclusions </h2>
Thank you for being interested in the ChromaQuant project! It is something we are very excited about and we are glad that there are others interested in this work. We hope to eventually grow ChromaQuant from a humble quantification algorithm used in a specific application to a generalizable resource for simplifying chromatographic analysis. To do this, we'll need the support and interest of readers like you, so thank you and happy analyzing!
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<b>Julia Hancock</b><br>
Research Assistant, UW ChemE