Protocol: two-stage hierarchical meta-analysis across diseases

Tier: D (cMD paper) · Type: composite · Category: Statistical Analysis

What

Where a disease is represented by several datasets, pool within the disease first; then pool the resulting per-disease summaries across diseases in a second stage — keeping the two levels of between-study variance distinct rather than throwing every dataset into one flat pool.

Why it matters

Flattening would let the four multi-dataset diseases (colorectal cancer, type 2 diabetes, Crohn's, ulcerative colitis) dominate a 15-disease synthesis. The hierarchy is the correct handling and it is a genuinely non-obvious design that deserves to be written down separately from the pooling arithmetic.

Source material

• waldronlab/curatedMetagenomicDataAnalyses — python_tools/hierarchical_metaanalysis.py, python_tools/hierarchical_binary_test.py, cMD3_paper_analyses/all_command_lines_py.sh (SECTION 2: hierarchical meta-analysis on 12 diseases)
• Paper: 10.1038/s41467-025-66888-1

Scope

In: the rule for which diseases enter stage one; how a single-dataset disease is carried into stage two; propagation of the stage-one standard errors; whether heterogeneity is re-estimated at stage two; multiple testing applied at which stage.

Out: the pooling arithmetic itself (component protocol).

Frontmatter starting point

type: "composite"
category: "Statistical Analysis"
citation: "10.1038/s41467-025-66888-1"
protocols_used:
  - name: "per-dataset-smd-covariate-adjusted"
  - name: "random-effects-meta-analysis-pm"

Acceptance criteria

• Single-dataset diseases have an explicitly defined treatment at stage two
• States at which stage FDR correction is applied, and why
• Note: the paper text says 15 diseases and the analysis scripts say 12 — resolve and document which is right

Cite the method's origin, not its users

PROTOCOL_STANDARD.md is explicit: an atomic protocol carries "strictly 1 citation... corresponding
to the primary literature where the method was originally published." Find the paper that proposed
the method. Do not cite a paper that merely applied it — including the BugSigDB and curatedMetagenomicData
papers, which are the source of the analysis these protocols were extracted from but almost never the
source of the method.

Tracing a method back to its first publication is real work, and it is part of the task, not a
formality. Three things to expect:

• Candidate DOIs in this issue are leads, not answers. Anything marked VERIFY has not been checked.
• Some methods predate modern citation practice or have no single identifiable origin. If that is
  genuinely the case, say so in the pull request rather than reaching for a convenient recent paper.
  Raise it as an issue in waldronlab/agent-protocol-standard — the standard may need a way to express
  "classical method, no primary source".
• If you cannot name one paper that proposed everything the protocol does, it is more than one
  protocol. That test has now split four protocols out of this batch: enrichment into three methods,
  filtering from transformation, LODO from random forest, and PERMANOVA from ANOSIM.

Where the lab's own paper genuinely did propose the method — the oral-to-gut score, and LODO
cross-validation in Pasolli et al. 2016 — citing it is correct. That is the exception, not the pattern.

Before you start

Read CONTRIBUTING.md and
PROTOCOL_STANDARD.md.
The format is defined in the standard repo, not this one. Protocols are prose, not code: they say what to do
and why, precisely enough that two people — or two agents, in two languages — get the same answer. The existing
independent-filtering-variance
protocol is the model to imitate for tone and level of detail.

Validate locally before opening the PR:

git clone https://github.com/waldronlab/agent-protocol-standard.git
Rscript agent-protocol-standard/scripts/validate-protocol.R protocols

Read CONTRIBUTING.md, PROTOCOL_STANDARD.md, and protocols/independent-filtering-variance/protocol.md first. Inspect hierarchical_metaanalysis.py, hierarchical_binary_test.py, and SECTION 2 of cMD3_paper_analyses/all_command_lines_py.sh, then trace the method to its primary paper. Document stage-one and stage-two disease handling, standard-error and FDR rules, and the 15-versus-12 discrepancy; validate with the supplied Rscript command.