metamicrobiomeR
Microbiome Data Analysis & Meta-Analysis with GAMLSS-BEZI & Random Effects
Generalized Additive Model for Location, Scale and Shape (GAMLSS) with zero inflated beta (BEZI) family for analysis of microbiome relative abundance data (with various options for data transformation/normalization to address compositional effects) and random effects meta-analysis models for meta-analysis pooling estimates across microbiome studies are implemented. Random Forest model to predict microbiome age based on relative abundances of shared bacterial genera with the Bangladesh data (Subramanian et al 2014), comparison of multiple diversity indexes using linear/linear mixed effect models and some data display/visualization are also implemented. The reference paper is published by Ho NT, Li F, Wang S, Kuhn L (2019) doi:10.1186/s12859-019-2744-2.
- Version1.2
- R version≥ 4.0.0
- LicenseGPL-2
- Needs compilation?No
- Ho NT, Li F, Wang S, Kuhn L (2019) doi:10.1186/s12859-019-2744-2
- Last release11/09/2020
Documentation
Team
Nhan Ho
Insights
Last 30 days
This package has been downloaded 156 times in the last 30 days. More than a random curiosity, but not quite a blockbuster. Still, it's gaining traction! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 3 times.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Last 365 days
This package has been downloaded 2,429 times in the last 365 days. That's enough downloads to impress a room full of undergrads. A commendable achievement indeed. The day with the most downloads was Jul 21, 2024 with 70 downloads.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
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Dependencies
- Depends1 package
- Imports12 packages
- Suggests16 packages