Modeling Information Content Via Dirichlet-Multinomial Regression Analysis
Sign Up to like & getrecommendations! Published in 2017 at "Multivariate Behavioral Research"
DOI: 10.1080/00273171.2017.1279957
Abstract: ABSTRACT Shannon entropy is being increasingly used in biomedical research as an index of complexity and information content in sequences of symbols, e.g. languages, amino acid sequences, DNA methylation patterns and animal vocalizations. Yet, distributional… read more here.
Keywords: information; entropy; multinomial regression; information content ... See more keywords
Mixtures of logistic normal multinomial regression models for microbiome data
Sign Up to like & getrecommendations! Published in 2024 at "Journal of Applied Statistics"
DOI: 10.1080/02664763.2024.2383286
Abstract: In the realm of bioinformatics, we frequently encounter discrete data, particularly microbiome taxa count data obtained through 16S rRNA sequencing. These microbiome datasets are commonly characterized by their high dimensionality and the ability to provide… read more here.
Keywords: mixtures logistic; microbiome data; normal multinomial; multinomial regression ... See more keywords
Batch effects correction for microbiome data with Dirichletâmultinomial regression
Sign Up to like & getrecommendations! Published in 2019 at "Bioinformatics"
DOI: 10.1093/bioinformatics/bty729
Abstract: Motivation: Metagenomic sequencing techniques enable quantitative analyses of the microbiome. However, combining the microbial data from these experiments is challenging due to the variations between experiments. The existing methods for correcting batch effects do not… read more here.
Keywords: bdmma; multinomial regression; microbiome data; batch ... See more keywords