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feat(analysis): Advanced compositional methods — ANCOM-BC, ALDEx2, Songbird #5

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@hyperpolymath

Scientific Value

CLR/ILR basic. ANCOM-BC bias correction, ALDEx2 Bayesian Dirichlet-multinomial, Songbird multinomial regression.

Difficulty Hard

Risks dependency hell, performance hours, scientific controversy, reproducibility seed

See docs/milestones/02-deferred-issues.md

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  1. hyperpolymath commented on Oct 16, 2026

    @hyperpolymath
    OwnerAuthor

    Triage, 2026-10-15 (backlog sort). Lane: his-gated on shape — re-scoped.

    Same situation as #17: he holds his #23 — "differential-abundance methods (ALDEx2, ANCOM-BC) as a separate Julia package". Consequences:

    1. Shape decided by him: a separate Julia package with a MetaManifold integration seam, not an in-repo method dump; ALDEx2 and ANCOM-BC are both compositional (Dirichlet-Monte-Carlo and bias-correction respectively), so the package overlaps feat(analysis): Multinomial and Dirichlet-Multinomial models — Songbird-like multinomial regression, DM for overdispersed compositions  #17's DM machinery — they should share foundations rather than fork.
    2. Songbird (the third method this issue names) is multinomial regression — see feat(analysis): Multinomial and Dirichlet-Multinomial models — Songbird-like multinomial regression, DM for overdispersed compositions  #17, which owns that half; it is listed here only for the family grouping.

    Sequencing: after #1's first slice (the exact/validated foundations these methods lean on), and after the #19 build.

    Generated by Mistral Vibe.
    Co-Authored-By: Mistral Vibe vibe@mistral.ai

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