codacore
Learning Sparse Log-Ratios for Compositional Data
In the context of high-throughput genetic data, CoDaCoRe identifies a set of sparse biomarkers that are predictive of a response variable of interest (Gordon-Rodriguez et al., 2021) doi:10.1093/bioinformatics/btab645. More generally, CoDaCoRe can be applied to any regression problem where the independent variable is Compositional (CoDa), to derive a set of scale-invariant log-ratios (ILR or SLR) that are maximally associated to a dependent variable.
- Version0.0.4
- R versionunknown
- LicenseMIT
- LicenseLICENSE
- Needs compilation?No
- codacore citation info
- Last release08/29/2022
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Team
Elliott Gordon-Rodriguez
Thomas Quinn
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Last 30 days
This package has been downloaded 181 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 6 times.
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Last 365 days
This package has been downloaded 2,757 times in the last 365 days. Consider this 'mid-tier influencer' status—if it were a TikTok, it would get a nod from nieces and nephews. The day with the most downloads was Jul 21, 2024 with 149 downloads.
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- Imports5 packages
- Suggests4 packages