leylabmpi
by Dept of Microbiome Science (Organization)
https://leylab.com
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Packages
| Name | Latest Version | Summary | Updated | License |
|---|
| genometools | 1.5.9 | The GenomeTools genome analysis system is a free collection of bioinformatics tools (in the realm of genome informatics) combined into a single binary named gt. It is based on a C library named “libgenometools” which consists of several modules. | Mar 25, 2025 | BSD |
| qiime_2_ll_quick_viewer | 0.2.8 | Ley Lab Quick Viewer for Qiime 2 artifacts. | Mar 25, 2025 | MIT License |
| pythoncyc | 1.0.3 | A Python interface to Pathway Tools | Mar 25, 2025 | LICENSE |
| comparem | 0.0.23 | — | Mar 25, 2025 | — |
| biolib | 0.0.46 | — | Mar 25, 2025 | — |
| r-tax4fun | 0.3.1 | — | Mar 25, 2025 | — |
| merf | 0.2 | Mixed Effects Random Forest | Mar 25, 2025 | MIT License |
| newick_utils | 1.6.0 | — | Mar 25, 2025 | — |
| pplacer | 1.1.18 | — | Mar 25, 2025 | — |
| r-boruta | 5.3.0 | An all relevant feature selection wrapper algorithm. It finds relevant features by comparing original attributes' importance with importance achievable at random, estimated using their permuted copies (shadows). | Mar 25, 2025 | GPL (>= 2) |
| r-fd | 1.0_13 | — | Mar 25, 2025 | — |
| r-aptreeshape | 1.5_0 | — | Mar 25, 2025 | — |
| r-pez | 1.1_1 | — | Mar 25, 2025 | — |
| drep | 2.0.5 | — | Mar 25, 2025 | — |
| r-caper | 1.0.1 | — | Mar 25, 2025 | — |
| halla | 0.7.18 | HAllA: Hierarchically All-against-All Association Testing | Mar 25, 2025 | MIT |
| r-picante | 1.6_2 | — | Mar 25, 2025 | — |
| ipyrmd | 0.4.3 | — | Mar 25, 2025 | — |
| r-base64url | 1.3 | — | Mar 25, 2025 | — |
| r-cooccur | 1.3 | — | Mar 25, 2025 | — |
| r-indicspecies | 1.7.6 | — | Mar 25, 2025 | — |
| r-bbmisc | 1.11 | Miscellaneous helper functions for and from B. Bischl and some other guys, mainly for package development. | Mar 25, 2025 | BSD_2_clause + file LICENSE |
| r-mlr | 2.12.1 | Interface to a large number of classification and regression techniques, including machine-readable parameter descriptions. There is also an experimental extension for survival analysis, clustering and general, example-specific cost-sensitive learning. Generic resampling, including cross-validation, bootstrapping and subsampling. Hyperparameter tuning with modern optimization techniques, for single- and multi-objective problems. Filter and wrapper methods for feature selection. Extension of basic learners with additional operations common in machine learning, also allowing for easy nested resampling. Most operations can be parallelized. | Mar 25, 2025 | BSD_2_clause + file LICENSE |
| r-randomforest | 4.6_14 | Classification and regression based on a forest of trees using random inputs, based on Breiman (2001) <DOI:10.1023/A:1010933404324>. | Mar 25, 2025 | GPL (>= 2) |
| r-ade4 | 1.7_10 | — | Mar 25, 2025 | — |