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Khan et al. (2012) generalized structure response analysis to multivariate correlations with CCA on the CMap.
After imputing SNP values, we produced the two corresponding SD plots (Supplementary Figure), which were remarkably similar, demonstrating that SD plots provide robust and reliable visual 'signatures' depicting aspects of multivariate correlations with respect to particular phenotypes.
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The present study has established several optics-based parameters to be used in a multivariate correlation with breast cancer patient outcome.
To study information redundancy we applied cluster analysis on multivariate correlations between estimates obtained with different methods.
Summary:We present a visualization tool applied on genome-wide association data, revealing disease-associated haplotypes, epistatically interacting loci, as well as providing visual signatures of multivariate correlations of genetic markers with respect to a phenotype.
Multivariate correlations of biochar yields were established using reduced quadratic models with R2 = 0.9949, 0.9801 and 0.9876 for cobs, husks and leaves, respectively.
For multivariate correlation analysis, women with a CD4 count <350 cells/μL had a significant correlation with ASCUS+ (P = 0.043).
Analysis of the data with multivariate correlation analysis, Granger causality, and sparse partial least square (sPLS) provided a functional network perspective of the molecular processes.
Statistical analysis was performed and empirical models with non-linear multivariate correlation equations describing the drying rate, and the benefit-cost ratio were developed.
We used Pearson's linear correlation with CI 95% and a multivariate correlation.
§ Pearsons correlation used for univariate correlation estimations and §§ partial rho correlations used for multivariate correlation estimations.
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