pca plots and loading analysis  (GraphPad Software Inc)

Journal: Cytotherapy

Article Title: Characterizing human mesenchymal stromal cells’ immune-modulatory potency using targeted lipidomic profiling of sphingolipids

doi: 10.1016/j.jcyt.2021.12.009

Figure Lengend Snippet: Unstimulated and IFN-γ–stimulated BM-MSC SL profile. (A) Schematic illustrating IDO converting tryptophan to kynurenine (kyn), an immunosuppressive metabolite. (B) SL concentrations of unstimulated and IFN-γ–primed MSCs. (C) PCA of high and low IDO unstimulated (Unstim) MSC groups. (D) PCA variable plot of MSC groups. (E) PCA of high and low IDO IFN-γ–primed groups. (F) PCA variable plot of IFN-γ groups. (G) LDA of high and low MSCs from Unstim and IFN-γ groups. *Statistical significance (P < .05). Mann–Whitney U test was used to determine significance. All groups were measured in triplicates (n = 3).

Article Snippet: Graphical illustrations of PCA variable loading plots were generated in RStudio.

Techniques: MANN-WHITNEY

Journal: Frontiers in Immunology

Article Title: Expression of ACE2, Soluble ACE2, Angiotensin I, Angiotensin II and Angiotensin-(1-7) Is Modulated in COVID-19 Patients

doi: 10.3389/fimmu.2021.625732

Figure Lengend Snippet: (A) Representation of the principal component analysis (PCA) biplot (score plot + loading plot). All patient codes and clinical results were deidentified before being made available to the principal investigator (B) Hierarchical clustering heatmap analysis (each colored cell on the map corresponds to a concentration value) of the different angiotensin metabolites in each group.

Article Snippet: The data were submitted to multivariate principal component analysis (PCA) biplot (score plot + loading plot) (RStudio) and hierarchical clustering heatmap analysis (ClustVis).

Techniques: Concentration Assay

Journal: Experimental hematology

Article Title: CD34 and EPCR coordinately enrich functional murine hematopoietic stem cells under normal and inflammatory conditions

doi: 10.1016/j.exphem.2019.12.003

Figure Lengend Snippet: (A) Experimental design of Fluidigm-based molecular analysis of SLAM cells fractionated by EPCR and CD34 expression from mice treated ± IL-1 for 20d. (B) Heatmap and hierarchical clustering analysis, and (C) principal component analysis (PCA; left) and PCA loading plot (right) of Fluidigm gene expression data (N = 7–8 per group). (D) Expression of HSC-associated genes in SLAM cells fractionated by EPCR and CD34 expression, from mice treated ± IL-1 for 20d. (E) Expression of HSC-associated genes in total SLAM cells and EPCR+/CD34− SLAM cells from mice treated ± IL-1 for 20d. Data in (D-E) are expressed as log10 fold expression vs. -IL-1 EPCR+/CD34− SLAM cells. ○ p < 0.05, ○○ p < 0.01, ○○○ p < 0.001 vs. -IL-1 EPCR+/CD34− SLAM cells; * p < 0.05, ** p < 0.01, *** p < 0.001 vs. -IL-1 condition within each fraction, as determined by two-way ANOVA. Data are representative of two independent experiments.

Article Snippet: PCA and PCA loading plots were generated using Prism 8 (Graphpad) from data generated by ClustVis.

Techniques: Expressing, Gene Expression