plsda models  (Eigenvector Research Inc)

Journal: Cellular and Molecular Bioengineering

Article Title: Inference of Cellular Immune Environments in Sputum and Peripheral Blood Associated with Acute Exacerbations of COPD

doi: 10.1007/s12195-019-00567-2

Figure Lengend Snippet: A one latent variable PLSDA model of VIP-selected proteins from the combined serum and sputum samples combined resulted in clear differentiation between stable and exacerbation measurements across 9 paired stable and AE-COPD events experienced by 7 unique patients. (a) PLSDA and VIP scores identified a signature of 19 proteins that differentiated the stable (purple) from exacerbation (orange) states with 88.89% cross-validation and calibration accuracy. Latent variable 1 accounted for 21.73% of the variance in the data. The scores plot shown is based on a two latent variable model to enable better visualization of group separation. (b) The loadings plot illustrates the protein contributions to the VIP-selected signature, with positive loadings positively associated with the exacerbation measurements, and negative loadings comparatively reduced during exacerbation.

Article Snippet: All PLSDA models, VIP scores, Wilcoxon signed rank tests, hierarchical clusters, heat maps, and Spearman correlation testing were created or calculated using MATLAB (MATLAB, Natick, MA); PLSDA models and VIP scores were specifically generated using the PLS toolbox in MATLAB (Eigenvector, Manson, WA).

Techniques: Biomarker Discovery

Journal: Cellular and Molecular Bioengineering

Article Title: Inference of Cellular Immune Environments in Sputum and Peripheral Blood Associated with Acute Exacerbations of COPD

doi: 10.1007/s12195-019-00567-2

Figure Lengend Snippet: VIP scores and PLSDA identified a signature of 7 serum proteins that differentiated stable from exacerbation measurements in 16 paired stable and AE-COPD events experienced by 11 unique patients. (a) VIP scores identified a 7-protein serum signature that differentiated stable (purple) and exacerbation (orange) events with 81.25% cross-validation accuracy and 84.38% calibration accuracy. Latent variable 1 (LV1) accounted for 25.00% of the variance in the data, and latent variable 2 (LV2) accounted for 16.75% of the variance in the data. (b) The loadings plot shows how much each protein contributes to the signature, with positive loadings associated with exacerbation events, and negative loadings comparatively reduced in exacerbation. (c) Comparison of the differentiation between stable and exacerbated states based on individual factors vs. multivariate signatures. The VIP signature identified by the PLSDA models trended towards higher cross-validation accuracy than individual factors that were most significantly different. A one-way ANOVA determined that this signature was significantly better than IL-15 alone, with ** indicating a p value less than 0.01 after Tukey’s test for multiple comparisons. (d) Comparison of the calibration accuracies for individual factors vs. the VIP signature identified by the PLSDA model.

Article Snippet: All PLSDA models, VIP scores, Wilcoxon signed rank tests, hierarchical clusters, heat maps, and Spearman correlation testing were created or calculated using MATLAB (MATLAB, Natick, MA); PLSDA models and VIP scores were specifically generated using the PLS toolbox in MATLAB (Eigenvector, Manson, WA).

Techniques: Biomarker Discovery, Comparison

Journal: Cellular and Molecular Bioengineering

Article Title: Inference of Cellular Immune Environments in Sputum and Peripheral Blood Associated with Acute Exacerbations of COPD

doi: 10.1007/s12195-019-00567-2

Figure Lengend Snippet: A one latent variable PLSDA model based on two rounds of VIP selection from serum and sputum proteins and blood flow markers shows clear differentiation between stable and exacerbation events across 8 pairs of patient samples, which included 7 paired stable and AE-COPD events experienced by 6 unique patients and one stable and one exacerbation measurement that were not patient matched. (a) PLSDA and two rounds of VIP analysis identified a signature of eleven factors that differentiated the stable (purple) from the exacerbation (orange) events, with 87.5% calibration and cross-validation accuracy. Latent variable 1 (LV1) accounted for 41.51% of the variance in the data. The scores plot shown is based on a two latent variable model to enable better visualization of group separation. (b) The loadings plot highlights factor contributions to the VIP-selected signature, with positive loadings positively associated with AE-COPD, and negative loadings comparatively reduced during an exacerbation event.

Article Snippet: All PLSDA models, VIP scores, Wilcoxon signed rank tests, hierarchical clusters, heat maps, and Spearman correlation testing were created or calculated using MATLAB (MATLAB, Natick, MA); PLSDA models and VIP scores were specifically generated using the PLS toolbox in MATLAB (Eigenvector, Manson, WA).

Techniques: Selection, Biomarker Discovery