pearson correlation coefficient matlab corr function  (MathWorks Inc)

Journal: bioRxiv

Article Title: Large-scale deep tissue voltage imaging with targeted illumination confocal microscopy

doi: 10.1101/2023.07.21.548930

Figure Lengend Snippet: (a-c) Example Voltron2 fluorescence images under targeted illumination with confocal slit width set to 4.5, 22.5, and 156 µm. Scale bar 50 µm. (d) Voltron2 fluorescence image over the same FOV but acquired without targeted illumination and with a confocal slit width of 156 µm. TI, targeted illumination. Scale bar 50 µm. (e,h,i) Comparison of spike Δ F / F , spike detection fidelity d ′ , and spike SNR measured with targeted illumination and confocal slit widths of 4.5, 11.3, 22.5, and 156 µm (n = 30 cells from 6 FOVs, 2 mice). Box plots: box, 25th (Q1, bottom line) to 75 th (Q3, top line) percentiles; whiskers, Q 1 − 1.5 × I Q R to Q 3 + 1.5 × I Q R , where I Q R = Q 3 − Q 1 ; middle line, median (m); notch, from m − 1.57 × I Q R / n to m + 1.57 × I Q R / n ; dots, measurement points. p < 0.05, p < 0.01, p < 0.001, no label if p ≥ 0.05, pairwise Wilcoxon signed-rank test, see for statistics. (f,g,j) Comparison of spike Δ F / F , photobleaching rate, and spike SNR measured with and without targeted illumination when using a 14 µm confocal slit. For (f,j), n = 19 cells from 5 FOVs, 2 mice. For (g), n = 92 cells from 5 FOVs, 2 mice. (l,m,n) Example images (scale bar, 20 µm) and corresponding fluorescence traces from two neighboring neurons with targeted illumination and confocal slit widths of 4.5, 22.5, and 156 µm (from top to bottom). Gray line, fluorescence traces; red line, extracted subthreshold Vm traces; r, Pearson cross-correlation coefficient between the subthreshold Vm traces from the 2 neurons.

Article Snippet: To analyze Vm-Vm correlations, we calculated Pearson cross-correlation coefficients (Matlab function corrcoef ) for the extracted subthreshold traces F s u b t from pairs of neurons.

Techniques: Fluorescence, Comparison, IF-P

Journal: Nature Communications

Article Title: Deconvolution of subcellular protrusion heterogeneity and the underlying actin regulator dynamics from live cell imaging

doi: 10.1038/s41467-018-04030-0

Figure Lengend Snippet: Correlation and classification analyses between protrusion velocity and actin regulator dynamics. a – d Time-lag correlation analysis based on Pearson’s cross-correlation of edge velocity and actin ( a ), Arp3 ( b ), VASP ( c ), and HaloTag ( d ). Solid lines indicate population averages. Shaded error bands indicate 95% confidence intervals of the mean computed by bootstrap sampling. The number of samples used for the analysis is identical from Fig. . e Comparison and statistical testing of maximum correlation coefficients from a – d in each cluster. The error bar indicates 95% confidence interval of the mean by bootstrapping. ** p < 0.01, *** p < 0.001 and **** p < 0.0001 indicate the statistical significance by two-tailed two-sample Kolmogorov–Smirnov (KS) test. The p -values are listed in Supplementary Table . f – h Time-specific correlation analysis based on pairwise Pearson’s correlation coefficients of protrusion velocity and fluorescence intensity time series registered relative to protrusion onset. The regions surrounded by the black lines are statistically significant correlation by Benjamini-Hochberg multiple hypothesis testing. i Pearson’s correlation coefficients between early Arp3 intensities and late protrusion velocities in each cluster. The error bar indicates 95% confidence interval of the mean by bootstrapping. The numbers of samples in this analysis are 204 (Cluster I), 112 (Cluster II-1), 161 (Cluster II-2), 178 (Cluster II-3) and 102 (Cluster III) respectively. j – k Classification analysis of Cluster III against Clusters I/II based on fluorescent intensity time series. Boxplots of the accuracy ( j ) and Matthews correlation coefficients ( k ) represent multiple classification results. RF stands for Random Forest, DNN for Deep Neural Network, and SVM for Support Vector Machine. The central line indicates median, and both edges of the box each represent 25 th and 75 th percentiles. The numbers of samples used in these analyses are 934 (actin), 757 (Arp3) and 682 (VASP) respectively

Article Snippet: After the protrusion velocity and fluorescence intensities were registered with respect to protrusion onset at t = 0 , Pearson’s correlation coefficients (Matlab function corrcoef()) between the fluorescence intensity at t 1 and protrusion velocity at t 2 across the samples were calculated across the time points, where t 1 and t 2 were measured relative to the protrusion onset.

Techniques: Sampling, Comparison, Two Tailed Test, Fluorescence, Plasmid Preparation