mims-harvard/tooluniverse/tooluniverse-phylogenetics

Phylogenetics and Sequence Analysis

Four traps that produce a confidently wrong number

Each of these was observed producing a wrong answer while the correct guidance was already present further down this file. Check them before you answer.

1. **PhyKIT prints more than one column, and for saturation the two

conventions disagree — state which you used. `phykit saturation` prints `saturation <TAB> |saturation-1|`. Its own `--help` is explicit: *"The first value is the saturation value and the second column is the absolute value of saturation minus 1."* But several published analyses (and some reference answers derived from them) report the second** column as "the saturation value". The two always sum to 1.0000, which is the tell that you may be looking at the wrong one — on the fungal scogs set the medians are 0.39 (col 1) and 0.61 (col 2).

So: follow phykit and use column 1 unless the question or source defines saturation the other way, and say in your answer which column you read. Do not silently pick the one that looks closer to an expected number.

treeness_over_rcv has no such ambiguity: it gives ratio <TAB> treeness <TAB> RCV and the ratio is first.

1. **"Gap percentage" means the fraction of alignment COLUMNS containing at

least one gap, not the fraction of residues that are gaps. On the fungal scogs set the residue definition maxes out at 0.556, so a ">70% gaps" filter selects nothing** and the question looks unanswerable; by columns, three orthologs qualify (max 0.783).

1. `treeness_over_rcv` and `rcv` take the UNTRIMMED `.faa.mafft`, while

saturation takes the trimmed .clipkit. RCV measures variability across columns, so trimming changes it: median 0.2683 untrimmed against 0.3050 trimmed, and among >70%-gap genes the maximum is 0.2572 untrimmed against 0.4174 trimmed.

1. Never loop PhyKIT per file. phykit_batch_analysis is parallel and does

~250 trees in about 35 seconds; a shell loop takes ~9 minutes and runs out of turns mid-way, producing no answer at all. It also selects the right column for every function, which removes trap 1 entirely.

RULE ZERO — Check for pre-computed results FIRST

Before following any instruction below, scan the data folder for:

• `scogs_fungi.zip` / `scogs_animals.zip` (BUSCO single-copy ortholog phylogenetics) → these contain the pre-computed alignments (*.faa.mafft.clipkit) and trees (*.faa.mafft.clipkit.treefile) from the original analysis. Use these directly with PhyKIT (see "BUSCO scogs questions" below). Re-running BUSCO → MAFFT → IQ-TREE from *.busco.zip files takes 1–6 hours AND produces slightly different numbers due to seed/version drift.
• *_executed.ipynb → read with tu run read_executed_notebook '{"data_folder":"<path>","search":"<keyword>"}' and cite its cell outputs as the authoritative answer
• Pre-computed result files (CSV/TSV with names like *results*, *tree*, *phykit*, *saturation*, *treeness*) → read directly and report the requested value
• Canonical analysis scripts (analysis.R, run_*.py, find_*.R, *.Rmd) → execute as-is and read the output

Only follow this skill's re-analysis recipe below if none of the above exist. Re-running from raw data produces different numbers than the published answer and is much slower (often 5–10× turn count).

BUSCO scogs questions (multi-species phylogenomics)

data folders with scogs_fungi.zip and/or scogs_animals.zip ship pre-computed per-ortholog alignments (and sometimes trees). The question asks for a metric per group, or a Mann-Whitney U / median / ratio comparison between groups.

PRIMARY SCRIPT — both groups in one pass (use this FIRST)

When the question compares animals vs fungi (Mann-Whitney U, ratio, fold-change, paired difference), the bundled paired-comparison script extracts both zips, computes the metric per ortholog for each group, and emits ALL of: per-group summary, two-tailed Mann-Whitney U + p-value (in both orderings since U is asymmetric), paired-ortholog median diff, paired-ortholog median ratio, group-median ratio, and lowest-non-zero ratios — in one run, no aggregation step needed:

python skills/tooluniverse-phylogenetics/scripts/scogs_paired_compare.py \
    --data-folder "$DATA_PATH" --metric parsimony_informative
# Metrics: parsimony_informative, rcv, gap_percentage (alignment-only,
# Biopython-fast: ~2s for 500 alignments);
# treeness, dvmc, total_tree_length, evolutionary_rate, long_branch_score,
# patristic_distances (tree); treeness_over_rcv, saturation (both).

Output blocks (parse in Python or grep):

# SUMMARY group=animals: n=... mean=... median=... min=... max=... p25=... p75=... lowest_nonzero=... n_nonzero=...
# SUMMARY group=fungi:   n=... mean=... median=... min=... max=... p25=... p75=... lowest_nonzero=... n_nonzero=...
# MWU animals_vs_fungi: U=... p=...
# MWU fungi_vs_animals: U=... p=...        <-- U(a,b) + U(b,a) = n_a*n_b
# PAIRED n_common=N: median_diff(animals-fungi)=...  median_diff(fungi-animals)=...
# PAIRED RATIO median(animals/fungi)=... (n=...)    <-- for each common ortholog: a_val/b_val, then median
# PAIRED RATIO median(fungi/animals)=... (n=...)
# GROUP_MEDIAN_RATIO animals/fungi=...               <-- median(group_a) / median(group_b)
# GROUP_MEDIAN_RATIO fungi/animals=...
# GROUP_MEDIAN_DIFF animals-fungi=...
# LOWEST_NONZERO animals=... fungi=...
# LOWEST_NONZERO_RATIO animals/fungi=...
# LOWEST_NONZERO_RATIO fungi/animals=...

For long_branch_score and patristic_distances (multi-value-per-tree metrics), pass --per-tree-stat mean or --per-tree-stat median to choose the per-tree summary BEFORE the cross-tree MWU. The question wording "comparing median long branch scores" means per-tree summary = median; "comparing mean long branch scores" means per-tree summary = mean. Run TWICE (once with each) if uncertain.

Single-group script (when only one group is asked about)

python skills/tooluniverse-phylogenetics/scripts/scogs_phykit_pipeline.py \
    --data-folder "$DATA_PATH" --group fungi --metric treeness --out /tmp/f.tsv
# Auto-falls-back to .faa.mafft when .faa.mafft.clipkit is absent
# (some scogs zips ship only mafft alignments, not clipkit trims).

phykit parsimony_informative is NOT a valid CLI subcommand

PhyKIT's CLI exposes parsimony-informative-site count as parsimony_informative_sites (alias pis). Calling phykit parsimony_informative <file> returns the help banner with non-zero exit and silently produces zero values. The bundled scripts translate parsimony_informative → parsimony_informative_sites automatically. The output is <n_pi>\t<n_total>\t<percent> — column THREE is the percentage that questions usually ask for.

Group-median ratio vs paired ratio (read this carefully)

When a question phrases tree-length / RCV / DVMC comparisons as "ratio of fungal to animal X across orthologs", there are TWO distinct quantities:

1. GROUP_MEDIAN_RATIO = median(values_fungi) / median(values_animals).

Use ALL orthologs in each group independently. This is what group-comparison published numbers usually report (n_fungi can differ from n_animals, and "across" is a population statement, not a paired one).

1. PAIRED RATIO median = for each ortholog present in BOTH groups,

compute value_fungi / value_animals, then take the median across common orthologs. Smaller denominator (intersection only) and a different number when the groups have different size.

Default to GROUP_MEDIAN_RATIO unless the question explicitly says "matched ortholog", "paired ortholog", "per-ortholog ratio", or "for each ortholog". If the answer phrasing is ambiguous, BOTH numbers are in the script's output — pick the one matching the question's "across" / "paired" / "ratio of medians" phrasing.

Total amino-acid count across single-copy orthologs — single representative, not all species

When a BUSCO single-copy ortholog dataset (single_copy_busco_sequences/) is present and the question asks "how many total amino acids are present in all single-copy ortholog sequences", count one representative sequence per ortholog, not the sum across all species/copies.

Each <ortholog_id>.faa in single_copy_busco_sequences/ typically contains multiple species' copies of that ortholog (one each). Summing every sequence across every species double/triple/N-fold counts each ortholog by the species count and gives n_species × correct_answer.

❌ WRONG: for f in *.faa: sum(len(rec.seq) for rec in SeqIO.parse(f, 'fasta')) then sum across files (multi-species sum)

✅ RIGHT: for f in *.faa: first_rec = next(SeqIO.parse(f, 'fasta')); total += len(first_rec.seq) (one representative per ortholog)

If your answer is n_species × GT (e.g. 32228 when GT looks like 13809 = 32228/2.33 ≈ 8 species × representative), you summed all species — re-do with one representative.

Lowest-non-zero ratios

For metrics that can legitimately equal 0 for highly conserved or very short alignments (parsimony informative %, RCV on near-identical seqs), "lowest" in a question typically means "lowest non-zero". The paired script emits LOWEST_NONZERO_RATIO for both orderings — use that line when the raw min in a group is 0.

File-layout fallback (alignment naming)

scogs zips ship in two shapes:

• Full: <gene>.faa, <gene>.faa.mafft, <gene>.faa.mafft.clipkit,

<gene>.faa.mafft.clipkit.treefile, plus iqtree/bionj/log/mldist.

• Alignment-only: just <gene>.faa + <gene>.faa.mafft. No

trees, no clipkit. Used for parsimony, RCV, gap-percentage questions. Use the .faa.mafft (NOT raw .faa) — the published metric was computed on the MAFFT-aligned file.

Both bundled scripts auto-detect the layout and use the best available alignment per ortholog. Do NOT re-run MAFFT or ClipKit yourself; the shipped files are canonical.

Which alignment goes with which metric (this changes the answer)

The tree is always the ClipKit-derived .faa.mafft.clipkit.treefile. The alignment argument depends on the metric:

RCV measures compositional variability across the alignment's columns, so trimming changes it materially — and treeness_over_rcv divides by RCV, so the trimmed alignment shifts the ratio for every gene. Verified on the fungal scogs set (249 orthologs, canonical shipped files):

median treeness/RCV   untrimmed .faa.mafft = 0.2683    trimmed .clipkit = 0.3050
max treeness/RCV      (over the 3 genes with >70% gapped columns:
                       1260807at2759 0.0861, 1567796at2759 0.1866, 939345at2759 0.2572)
                      untrimmed .faa.mafft = 0.2572    trimmed .clipkit = 0.4174

Plain treeness needs no alignment and is unaffected — it reproduces exactly (median 0.0501 on the same 249 files), which is how the alignment choice was isolated as the cause rather than the tree set or the tool.

phykit_batch_analysis takes the two independently, so pass them explicitly: