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diversity-tables

diversity-tables

Compute scikit-bio community diversity metrics and prepare BIOM-style table-like inputs for count workflows.

Independent GitHub snapshot · Automated classification · Original documentation governs

Documentation de la Skill

GitHub

name: diversity-tables description: "Compute scikit-bio community diversity metrics and prepare BIOM-style table-like inputs for count workflows." disable-model-invocation: true metadata: disco-role: operating license: BSD 3-Clause

Diversity Tables

Use this sub-skill when a task asks for alpha diversity, beta diversity, phylogenetic diversity, UniFrac, large beta-distance computation, BIOM-style tables, table-like count matrices, or table augmentation for biological community data.

Read First

  • references/api-reference.md for callable signatures, return types, metric discovery, table orientation, and augmentation APIs.
  • references/workflows.md for input preparation, alpha/beta runs, Faith PD/UniFrac setup, block decomposition, and dense/table conversions.
  • references/troubleshooting.md for invalid counts, sample/taxon length errors, callable-vs-string metrics, tree/taxa mismatch, table axis confusion, optional backend limits, and validate=False risks.
  • scripts/diversity_table_smoke.py for a deterministic smoke check covering sobs, Bray-Curtis, Faith PD, UniFrac, and Table dense conversion.

Typical Routing

  • Compute richness, evenness, observed features, Chao1, Faith PD, or any per-sample metric with skbio.diversity.alpha_diversity.
  • Compute Bray-Curtis, Jaccard, Euclidean, weighted UniFrac, unweighted UniFrac, or SciPy pairwise distances with skbio.diversity.beta_diversity.
  • Use skbio.diversity.block_beta_diversity when many samples or features make full beta diversity expensive and block/map-reduce execution is appropriate.
  • Use skbio.diversity.partial_beta_diversity only for explicit ID pairs and with caution because uncomputed distances are represented as zeros.
  • Use skbio.table.Table, skbio.table.example_table, pandas DataFrames, NumPy arrays, or other supported table-like inputs when rows are samples and columns are features/taxa.
  • Use skbio.table.mixup, aitchison_mixup, compos_cutmix, or phylomix only as table augmentation helpers for synthetic biological count/composition workflows.

Boundaries

  • Route tree construction, rooting, branch-length repair, and detailed TreeNode validation to ../trees-phylogeny/SKILL.md.
  • Route statistical testing, ordination, PERMANOVA/ANOSIM, and visualization of resulting DistanceMatrix objects to ../statistics-ordination/SKILL.md.
  • Route BIOM/TSV/FASTA/Newick file reading and metadata parsing to ../io-metadata/SKILL.md.
  • Keep this sub-skill focused on count/table preparation, diversity drivers, metrics, outputs, and table augmentation.
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