# Multivariate Analysis as a Tool for Quantification of Conformational Transitions in DNA Thin Films
## 3 Results
### Classification by SVM
Such high success rates, regardless of the spectral region, for the models in which validation was performed on newly introduced spectra, provide an excellent basis not only for the classification of spectra but also for the estimation of %B-form. This is particularly interesting for the model (a) where, utilizing the SVM classification, an unknown %B-form for the 15-25 min spectra was determined as \(\approx\)75% with 100% success rate based on the spectral signatures in the 1800-935 cm\({}^{-1}\) region. In order to challenge the classification ability, the SVM2 calibration dataset was deliberately reduced until it crashed and then expanded with the fewest number of spectra possible to regain correct classification (SVM3 and SVM4). In the SVM3 model, 10 min films were removed from the training and included into the validation. The calibration dataset included 279 spectra of the 3-, 5-, and 40-min films (all three classes), while the validation set included 90 spectra of the 10-, 15-, 20-, and 25-min films (only class 3) and was performed in the 1800-935 cm\({}^{-1}\) region. Without the 10-, 15-, 20-, and 25-min films in the calibration dataset, the success rate fell to less than 25% (22 out of 90 spectra were classified correctly) indicating that the 3-, 5-, and 40-min films are not sufficient to train a good model. In other words, the extent of spectral differences between the 5- and 40-min films is big enough for the model to fall apart. In order to improve the SVM3 model, we expanded the calibration set with 18 spectra of 15 min film so that the calibration set of SVM4 included 297 spectra of the 3-, 5-, 15-, and 40-min films (all three classes), while the validation set included 72 spectra of the 10-, 20-, and 25-min films (only class 3) and was performed in the 1800-935 cm\({}^{-1}\) region. This significantly improved the success rate to over 80% (only 13 misclassified spectra out of 72), which suggests that the 40 min films in the 1800-935 cm\({}^{-1}\) region (compared to the 10- and 15-min films) also contain certain spectral features not entirely related to conformation, as discussed in our previous work. Two final SVM classification models, SVM5 and SVM6, were based on the idea of the minimization of the calibration dataset still capable of resolving different levels of B-form in the spectra. In the SVM5 model, the calibration dataset included 288 spectra of the 3-, 5-, and 10-min films (all three classes), while the validation dataset included 81 spectra of 15-, 20-, 25-, and 40-min films (only class 3) and was performed in the 1800-935 cm\({}^{-1}\) region. The model yielded 100% success rate with none misclassified spectra in 15-40 min films, suggesting two things: there is no significant conformational difference between the 10 and 15-40 min films, as argued in our previous work, and that the sample group of 10 min films is diverse enough to provide a strong model for classification based on %B-form. On the other hand, the SVM3 and SVM4 models, that based the prediction of %B-form on the 40 min spectra, proved to be inferior. This can be easily understood looking at the sample group of 40 min films, which contains less spectra, has less spectral variability and has certain aspects unrelated to conformation present in the spectra (mostly phosphate groups). The final step of the SVM model evaluation (by introducing unseen spectra to the validation dataset) was to include previously obtained DNA thin film spectra from our spectral library and test it against the calibration dataset of SVM5 model. Three spectra of DNA thin films obtained several years ago in our lab were processed in the same manner and used as the validation dataset. Note that the library spectra chosen for validation were obtained from DNA solutions of the same concentration, deposited on the same substrate (Si windows) and recorded on the same instrument, but in a setup with a different vacuum pump (a rotary vacuum pump of the same class but different manufacturer).