Hron. Correlation analysis for compositional data. Mathematical Geosciences, to appear, 2009.Filzmoser, P., and Hron, K. (2009), “Correlation Analysis of Compositional Data,” Mathematical Geosciences , 41, 905
In this article, we present Correlation and Consensus-based Cross-taxonomy Network Analysis (C3NA), a user-friendly R package for investigating compositional microbial sequencing data to identify and compare co-occurrence patterns across different taxonomic levels. C3NA contains two interactive graphic us...
Watts, S. C., Ritchie, S. C., Inouye, M., & Holt, K. E. (2018). FastSpar: rapid and scalable correlation estimation for compositional data. Bioinformatics. doi: 10.1093/bioinformatics/bty734 Friedman, J. & Alm, E.J. (2017). Inferring correlation networks from genomic survey data. PL...
A set of data tools in Python pythondatacorrelationanalysismodelingplotroc UpdatedJan 6, 2025 Python Inject an ID into every log message from a Django request. ASGI compatible, integrates with Sentry, and works with Celery djangocorrelationsentryloggingdjango-rest-frameworktracingceleryguidrequest-idasgi...
Because our study design was limited in that each participant provided one fecal sample for analysis, we lacked longitudinal data to fully determine the dynamic variation in each pregnant woman throughout gestation. In addition, the current study does not provide any mechanistic explanation for the...
GPU-accelerated local DIC method at the integer-pixel level for correlation analysis has been proposed by Gembris et al. [34], and in applications such as cracking analysis by Marciniak et al. [35], biomechanics by Singh and Omkar [36], and OCT by Kapinchev et al. [37]. While [37...
Continuous variables are expressed as (mean ± standard deviation), and the independent samples t-test was employed for comparisons between two groups, while one-way analysis of variance (ANOVA) was used for comparisons among multiple groups. Non-normally distributed data were analyzed using ...
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Compositional and semi-quantitative assessment are not covered here. Results The selected articles are presented in historical order as well as by content. We review progress in the technical aspects of image acquisition, segmentation and analysis, advances in understanding tissue growth, physiology, ...
--- # Function parameter description: # function: cclasso # Input: # x --- n x p data matrix (row/column is sample/variable) # n samples & p compositional variables # counts --- Is the compositional data matrix a count matrix? # Default: FALSE # pseudo --- pseudo count if counts...