SV support matrix — what eidolon can reproduce, and from where

Measured 2026-08-02 on the H1N1 fixture (8 contigs), 60× diploid, ploidy: 2, heterozygous unless noted. Every row is an observation, not a design intent. Cells marked ⚠ or ✗ are known gaps, not omissions.

Two separate questions, and they are not required to agree:

• Input — you supply the record via input_vcf. The contract is fidelity: what you put in comes out, in the truth VCF and in the reads.
• De novo — eidolon samples the record from a model. The contract is realism: the distribution matches the source corpus.

Input fidelity is the higher priority. A researcher modelling a specific variant needs to know it reached the output; a mismatched distribution is a modelling argument, but a variant that silently fails to appear is a broken tool.

2026-08-16 characterization addendum

The focused Gate 2b checks and the first Delta performance/BAM measurements are now complete. These are baselines for the current develop build, not pooled recall estimates.

Post-#537 subclonal SV smoke (develop 4a3ea4a)

Delta jobs 21281985 and 21282371 exercised the merged subclone-SV implementation on multi-contig S. cerevisiae. The higher-rate run produced 12 SV records (7 at CCF 0.2, 1 at CCF 0.5, and 4 clonal at CCF 1.0); all 12 carried EIDOLON_CCF and EIDOLON_VAF. Three reciprocal translocation pairs shared CCFs of 0.2, 1.0, and 0.2. After bwa-mem2 alignment, 199 chimeric alignments were retained, 100% of 2,426,389 reads mapped, 69 were supplementary, and 99.99% were properly paired. This validates CCF stamping, reciprocal-BND pairing, and read-level junction survival; it is not a caller recall estimate.

The full-GRCh38 post-merge stress run (job 21282504, 30×, purity 0.6, nominal SV_RATE_SCALE=1.0) produced 140 tagged SV records: 31 at CCF 0.2, 43 at CCF 0.5, and 66 at CCF 1.0. Its merged BAM contained 588,995,182 reads, all mapped, with 2,837 chimeric alignments, 2,216 supplementary records, 99.99% proper pairing, and 71 GB compressed size. This confirms the subclonal SV path at primary-assembly scale; it is still a simulation/read-level result rather than a pooled caller-recall estimate.

Local performance and BAM baseline

The FASTQ-only benchmark (Delta job 21188169, three replicates per row) remained consistent with the earlier chr22 measurement after the BAM changes:

The yeast thread sweep was 22.85 s (1 thread), 11.15 s (4), 7.18 s (16), and 7.68 s (64). This benchmark does not produce BAMs. A separate chr22 BAM timing smoke produced 7,780,196 records, including 60 chimeric records, in 3:05.39 at 230.5 MB peak RSS; samtools quickcheck passed and the BAM was 843 MB. The result is a BAM-path baseline, not a before/after comparison against an older binary.

A full-primary-assembly BAM-only run (Delta job 21262840, GRCh38 at 30×, 128 requested threads) completed successfully in 23:56.16. It wrote 583,088,206 records to a 62 GB BAM; samtools quickcheck passed. Process-level /usr/bin/time reported 13.6 GiB peak RSS and 924% CPU utilization (about 9.2 cores), showing that this path does not scale to all 128 requested threads. Slurm reported a much larger 111 GiB MaxRSS; that accounting value is retained as a cluster-side note, while the process-level measurement is the comparable RSS figure. This run produced no input SVs, so it characterizes full-genome BAM throughput and resource use rather than BND recovery.

First multi-contig GRCh38 SV smoke

Delta job 21170801 (30×, purity 0.6, SV_RATE_SCALE=1.0, Manta only) produced 137 somatic SV records: 29 DEL, 32 DUP, 15 INV, 2 INS, 52 BND, and 7 CNV. All 52 BND records parsed, and the scorer controls passed (truth-vs-truth recall 1.000; shifted-truth decoy recall 0.000). There were no intra-contig BND spans because this smoke’s BND set was inter-contig, so BNDspan scoring was correctly skipped.

These are PASS-only caller measurements from one replicate, not simulator correctness verdicts. Most importantly, the independent INS probe found 2/2 planted insertions in the reads even though Manta emitted no PASS INS calls. Five de novo insertions longer than the 151 bp read length were dropped as expected under #516. The run retained 30 GB normal and 70 GB tumor BAMs with PRUNE_BAM=0 for follow-up inspection.

Follow-up characterization is complete. The initial smoke is retained above as a historical single-run baseline; the follow-up observations below provide the caller comparison and the nominal-rate Manta repeatability check. These are still separate from the larger pooled campaign reported in the whole-genome tier below.

Follow-up multi-contig GRCh38 observations

Delta job 21226562 reran the same 30×/0.6/SV_RATE_SCALE=1.0 design with both Manta and Delly on one simulated tumor/normal pair. The truth again contained 137 somatic records (including 52 BNDs), all 52 BNDs parsed with zero unpaired or mispaired junctions, and all scorer controls passed. Manta recovered 42/52 BNDs (recall 0.808, precision 0.457); Delly recovered 20/52 (recall 0.385, precision 1.000). Overall scoreable recall/precision were 0.795/0.747 for Manta and 0.821/0.660 for Delly. The independent insertion probe found both planted insertions in the reads (2/2); the zero manta_INS score is therefore a PASS-filter limitation, not evidence that the simulator omitted the insertions.

Delta job 21249416 supplied the third nominal-rate Manta observation. It reproduced the same truth counts and clean BND geometry (52/52 parsed; 0 unpaired or mispaired), with scorer self-tests and decoys passing. Manta scored 67 TP, 11 FN, and 20 FP overall (recall 0.859, precision 0.770), and 42 TP, 10 FN, and 50 FP for BND (recall 0.808, precision 0.457). Across the three Manta observations, BND recall was approximately 0.77–0.81 while aggregate recall remained about 0.86. The consistent truth-side checks and the caller-to-caller difference in BND recovery support a caller/representation limitation rather than a simulator defect.

Input VCF → output

Untested cells: none remain

Every row above is measured. Read-level evidence is depth against a separate no-variant control run, or BAM CIGAR I/D counts against that control’s sequencing-error background (15 I, 20 D in the probed window), or chimeric-read counts.

The “~8% high” figure is size-dependent, and the size it was measured at is not realistic. #499 measured a 1.2 kb event on the 13.5 kb H1N1 fixture, a window where depth noise alone is ~13% sigma. Re-measured on a 10 kb event over a 1 Mb reference, depth reads 0.98 +/- 1.9% — accurate. The three rows above therefore report a bias that does not survive at realistic event size, and are kept only because they are what H1N1 actually shows.

The residual mechanism is real and tracked as #584: junction reads are emitted on top of coverage-multiplied reads rather than as part of them (+0.52 at multiplier 1.0 on a 300 bp DUP). Their count does not vary with event length, so the excess as a fraction of the event scales roughly as 1/length — negligible at 10 kb, dominant at 1 kb. Anything calibrating against eidolon depth needs this number at its own event size, not this table’s.

The confirmed failures

[#498] BND with inserted sequence — FIXED. VCF 4.2 allows a breakend ALT to carry novel bases inserted at the junction, common in real rearrangements since NHEJ frequently leaves sequence at the breakpoint. parse_bnd_alt accepted it while get_bnd_pieces rebuilt the read from reference pieces only, so the insert never reached the output while the truth VCF kept it — a benchmark asserting an insertion the reads did not contain.

parse_bnd_alt now returns the inserted bases and get_stitched_sequence splices them between the two reference pieces. Two details are load-bearing and each has its own test:

• Which end of the replacement sequence holds the reference base flips with the form — t[p[ and t]p] start with it, [p[t and ]p]t end with it. Getting it backwards splices the anchor into the read and drops one inserted base.
• The insert comes OUT of the fragment budget (L1 + insert + L2 == frag_len), it does not extend it. The inserted bases consume READ bases but no REFERENCE bases, so a correct pair spans less reference than the library mean — a reduced insert size is one of the signatures a caller uses to detect an insertion at a junction. Letting the fragment grow keeps the span at the library mean, erases that signature, and puts the mate further into the second piece than the fragment distribution allows: systematically discordant pairs at every inserted junction, and an inferred event size that does not match what was planted. It does not change depth — R1 and R2 are read_len each however long the fragment is. Invisible to every read-content check, since the insert is present, adjacent and correctly oriented; caught only by mutating the arithmetic.

The insert is never reverse-complemented: it is written in the orientation of the record declaring it, while the rev flags describe only how each reference piece is read.

[#500] Symbolic <INS> — FIXED. SVTYPE=INS;SVLEN=60 used to be preserved in the truth VCF while the reads came out behaviourally identical to the no-variant control — same I count, same D count, same depth. A 60 bp insertion was requested and nothing was inserted, so a benchmark built from that truth scored a caller as having missed an insertion that was never in the data.

A symbolic <INS> from input_vcf is now realized: SVLEN novel bases are drawn by the same sample_novel_insertion_bases the de novo path uses — one model must not plant two different kinds of insertion depending on which door the record came through — and the record becomes a literal ALT, which is what routes the bases through the insertion machinery. The truth VCF then states what was actually planted rather than a size and a promise. #580 tracks making that sampler mobile-element-aware; both paths inherit it at once. A <INS> with no usable SVLEN has no length to synthesise and is dropped with a warning rather than kept as an unachievable truth record.

The de novo path did synthesise novel sequence for INS all along, so the capability existed; it was simply not reached from input_vcf. That last sentence was an assertion when first written and is now measured: jobs 20885875/20892075 planted 4 insertions of 296–2500 bp whose novel bases are present in the truth VCF, at a rate consistent with the model’s Ins = 0.0279 (4 observed against ~5.2 expected-visible). It was nearly retracted as false in 2026-08 on the strength of truth INS: 0 in the SV harness — which turned out to be measuring the harness’s own selector, not the generator. See §“De novo generation” below and docs/claude_engineering_audit.md §5.3.

[#516] Large insertions were only PARTIALLY realized — FIXED. Kept here because the defect’s shape is the most instructive one in this repo: the head was always present while the interior collapsed to zero, so any probe near the insertion’s start said it worked, which is where a casual check looks. The truth VCF meanwhile declared the full SVLEN.

Measured on the H1N1 fixture at read_len=100, fragment_mean=250, GT 0/1, counting reads containing a 30-mer from the head / middle / far end of the inserted sequence. Identical fixture and config before and after, so the columns are directly comparable:

The fix samples fragments in altered-haplotype coordinates, where an insertion has real width, so fragments begin inside it. eidolon/tests/long_insertion_rework.rs pins eight criteria on eidolon’s own FASTQ, and eidolon/tests/gate2_realigned_ins.rs pins the same insertion through bwa-mem2: a homozygous 600 bp insertion at 60x yields 5/5 interior probes against 0/5 in a same-seed no-variant control, 96 breakpoint clips against 0, and 51 reads unmapped-with-mapped-mate against 0.

At genome scale, de novo on a 5 Mb chr22 window (default germline model, sv_rate_scale=8): 427 of 440 insertions ≥200 bp have their middle sequence in the reads, with zero fallbacks. The remaining 13 are thinly covered rather than absent — mean interior depth 3.96 against 6.77 for the rest, still 68% of their length covered. Interior coverage of a heterozygous insertion runs at ~half the flanking reference (7.0 vs 13.0 reads per 30-mer), which is the correct ratio, not a shortfall.

What is NOT yet established: Delta job 21378484 (chr22, SV_RATE_SCALE=30, COSMIC pancancer somatic) verified 4 of 4 planted insertions at 5/5 interior probes including one of 2127 bp — real evidence, but a denominator of four. verify_planted_ins now refuses to let a run that small read as validation. A larger-denominator campaign is outstanding.

The historical mechanism, kept because it explains why the defect was invisible:

Fragments and read windows were chosen purely in reference offsets (cover_dataset, generate_fragments.rs:323), and an insertion has zero reference width, so no read window could ever begin inside one. Reads are assembled per-read by walking a reference slice and expanding variants inline, bounded by bases_written < read_length (fastq_tools.rs:429) with a break 'outer at :555 that discards the rest of the insert silently — no log, no counter. Hence:

novel bases visible in one read = min(L, read_length − anchor_offset − 1)

At most read_length − 1 inserted bases are ever realized, at any declared SVLEN. Probe visibility follows exactly: head needs anchor_offset ≤ 69 (no L term), middle needs anchor_offset ≤ 84 − L/2 (impossible for L ≥ 170), tail needs ≤ 99 − L (impossible for L ≥ 100) — which reproduces all fifteen measured cells.

The head count is size-independent: with the heterozygous coin removed (GT 1/1) it is 42/41/50/50/50 across the five sizes. An earlier version of this note claimed it “rises with size” and read meaning into 16 → 27; that was RNG drift, since a larger insert fires break 'outer sooner and consumes fewer sequencing-error draws.

Consequence, measured: SV validation campaign 20925151 planted 22 de novo somatic insertions of 61–2155 bp and Manta detected exactly one — the 61 bp event, and only at MinSomaticScore. That is not primarily a caller limitation. Manta documents a fully assembled ceiling of “approximately twice the read-pair fragment size” and states it also reports very large insertions from a breakend signature alone, as IMPRECISE <INS> with LEFT_SVINSSEQ/RIGHT_SVINSSEQ. Most of the planted set was inside that range, and Manta reported nothing within 2 kb of any of them — because the evidence for the declared length was not in the reads. INS recall figures from campaigns before the fix are invalid above ~a read length and must not be re-quoted; DEL/DUP/INV/BND/CNV from those runs are unaffected. Job 21378484 is the first post-fix counter-example: Manta’s single INS call was an exact position-and-size match to a planted 93 bp insertion, dropped only by --passonly as MinSomaticScore, while the three larger insertions it did not call were all confirmed present in the reads at 5/5 interior probes. Evidence present, caller declined — which is a different finding from evidence absent, and the read-level probe is what separates them.

The interim read_len - 1 cap on de novo insertions has been REMOVED. While #516 was open, gen-reads refused to plant a de novo insertion whose novel sequence exceeded what a read could carry, rather than emit a truth record the reads could not support. That truncated the model’s own distribution — the bundled default puts Ins at log-normal (5.7, 1.0), median ~299 bp, so at read_len=150 roughly three quarters of INS draws were refused.

With insertions sampled in altered-haplotype coordinates the cap is unnecessary, and its removal is pinned by eidolon/tests/multi_sv_integration.rs, which now asserts the opposite of what it once did: a de novo insertion MAY declare more novel bases than read_len - 1. Reinstating the cap, or unwiring the sampler, fails that assertion while every other assertion in the file stays green — which is the specific regression it exists to catch. De novo insertion sizes now follow the model rather than the read length; measured largest realized on a 5 Mb chr22 window is 9,093 bp.

Pinned by runner.rs’s unrealizable_insertions_are_dropped_at_exactly_the_boundary and the_insertion_cap_does_not_touch_other_variant_types (a must-not-fire: dropping large DELs/DUPs/INVs would be far worse than the bug being worked around), plus an end-to-end assertion in multi_sv_integration.rs that no de novo INS in the truth VCF exceeds read_len - 1. Removing the call site makes that fail with eleven oversized records.

This is an interim measure. It removes the false-truth problem, not the capability gap: eidolon still cannot simulate insertions longer than a read.

[#500] A single breakend (A.) — FIXED by rejecting it. VCF 4.2 allows an unresolved partner. parse_bnd_alt returns no mate, and accepting the record anyway was worse than ignoring it: depth fell 72.0 → 42.4 (−41%) with zero chimeric reads. The truth declared a breakend, the reads contained no junction, and a depth caller saw a partial deletion no record described.

It is now rejected during input_vcf filtering, with a warning naming the record. That keeps it out of the truth VCF and leaves coverage alone — the regression test asserts both, and the depth ratio it checks is the old failing threshold inverted (0.59 measured then, > 0.85 required now). Rejection rather than realization because eidolon has no way to build a junction read without a partner; revisit if junction generation ever represents one.

Fragment spanning a whole DUP — retracted, it was never broken. This cell previously read ❌, citing a three-piece stitch (left + block + right) that get_dup_pieces cannot express, and “4 of 30 reads match no haplotype”. All three parts are withdrawn:

• Measured false. short_dup_spanned_by_a_fragment_still_matches_the_derived_haplotype sweeps DUP blocks of 60/100/150/200/400/800 bp against a ~200 bp fragment — every one spannable by a fragment — and all match the derived haplotype at the ≥90% threshold used throughout that file.
• The 13% was the error model. matches_with_one_small_indel exists because a purely positional comparison frameshifts on sequencing-error indels; its own note says that without it “a correct implementation looks ~9% broken”. 4 of 30 = 13% sits inside that band, so the original measurement almost certainly predates that tolerance.
• The issue reference was wrong. #474 is closed and concerns INV/DUP anchor-base conventions, not stitching — it never covered this.

Residual, and why this is ✅ rather than settled: the test asserts the reads that exist are correct, not that none are missing. Fragments needing three pieces being silently dropped would dip coverage across a short DUP and leave the test green. A depth comparison against a no-variant control would close that.

<INV> — investigated, and the test was wrong, not the code

The first measurement of this cell read 0.63, which looked like a balanced inversion losing a third of its coverage. It was flagged rather than filed, and that was the right call: diagnosis showed the fixture was at fault.

Against a no-variant control run of the identical config:

300bp inversion, 250bp fragments (H1N1_NA:300-600)
  inside inversion      0.62
  flank left            0.81
  flank right           0.76
  far away              1.00     <- coverage is fine elsewhere, so the loss is real

1200bp inversion, 250bp fragments (H1N1_PB2:500-1700)
  deep interior         1.00     <- NO loss
  near left junction    0.82
  near right junction   0.74
  outside               0.99

The inverted sequence is covered at full depth. The depletion is junction-proximal, extending roughly one fragment length around each breakpoint. A 300 bp inversion is smaller than a 250 bp fragment, so nearly every fragment overlapping it touches a junction and the entire event sits inside the dip zone — which is what produced 0.63.

The remaining junction dip (0.74–0.82 over ~180 bp) is consistent with the mechanism: a fragment spanning a junction becomes a chimeric read placed at one locus, so its coverage contribution to the other side is not counted. Real aligners soft-clip and place such reads at one side too, so some dip is expected. How much dip is realistic has not been compared against real data — that is unquantified, not verified.

Practical consequence for anyone writing SV tests: an inversion shorter than the fragment length is not a clean fixture. Its coverage behaviour is dominated by junction effects, not by the inversion.

<CNV> — semantics confirmed, but a systematic ~8% bias found (#499)

The first reading of this cell (1.67 for CN=4) matched no sensible interpretation. It was measured against an in-run control span on a 300 bp event — the same flawed method that produced the bogus <INV> result. Re-measured properly (1200 bp event, deep interior only, against a separate no-variant run):

CN   multiplier  expected  observed  obs/exp
 0      0.00       0.00      0.00     exact
 1      0.50       0.50      0.54     1.08
 2      1.00       1.00      1.00     exact
 3      1.50       1.50      1.61     1.07
 4      2.00       2.00      2.17     1.09
 6      3.00       3.00      3.28     1.09

Semantics answered: CN is the total copy number, multiplier CN/ploidy, and genotype is ignored when CN is present. That is consistent and defensible.

But the delivery is ~8% high whenever the multiplier is neither 0 nor 1 — and it is not CNV-specific. The same bias appears in DEL and DUP, both genotypes:

DEL het  0.54 vs 0.50   (1.079)      DUP het  1.61 vs 1.50   (1.073)
DEL hom  0.00 vs 0.00   exact        DUP hom  2.17 vs 2.00   (1.084)

coverage_multiplier_for returns the correct values; the gap is between the requested multiplier and the depth actually delivered. Mechanism not diagnosed — see #499.

Update 2026-08-23 — mechanism diagnosed, and it is size-dependent. #499 is closed. Two effects contribute, both boundary effects, both shrinking as the event grows relative to the fragment length: chimeric junction reads landing outside the coverage-multiplied budget (#499’s own, excess ~1/event_length), and fragments legitimately extending across the event’s coverage-multiplier boundary into its neighbours (introduced with the fragment-placement rewrite, and the thing that removes an artificial dead zone at every such boundary). See the size guidance below.

How big does an SV need to be for its declared depth to be accurate?

Rule of thumb: depth multipliers land within ~1% for events ≳10× the fragment length. Below ~5×, expect several percent of under-delivery. On a small contig it is worse, because the flanking baseline is narrow too.

Measured, het <DUP> (declared 1.50×), read_len: 100, fragment_mean: 250, 3 seeds averaged except where noted:

Read this conservatively: the 1,200 bp (93%) against 1,500 bp (~100%) difference is within seed-to-seed noise at that scale, so the useful signal is the trend, not any single row. What the table does establish is that both ends are real — a fragment-length-scale event genuinely loses several percent, and a realistic event genuinely does not.

Practical guidance:

• Validating depth-multiplier accuracy (DEL/DUP/CNV dosage, copy-ratio callers): use events ≳10× fragment length on a reference with wide flanking sequence. The depth_modulation_is_accurate_at_realistic_scale test does exactly this and is the reference measurement.
• Small references (viral genomes, small scaffolds, the H1N1 fixture) cannot host an event much larger than the fragment length and leave wide flanks — H1N1 is 2,280 bp total. They remain excellent for fast mechanism checks and are used that way throughout this file, but they should not be used to validate depth precision.
• Small SVs on any reference carry the same few-percent under-delivery. If you are simulating sub-kilobase events and depend on their exact dosage, measure it rather than assuming the declared multiplier.

Whole-genome tier — de novo, scored by callers

Everything above is H1N1: 8 contigs of 1–2.3 kb, largest event ~1.2 kb. That fixture cannot say whether an SV behaves at the sizes anyone simulates. This section is the other tier — GRCh38 at 30×, purity 0.6, SV_RATE_SCALE=1.0, scored by Manta 1.6.0 and Delly against truvari.

It answers a different question. The tables above are input fidelity — what you supplied came out. This is de novo generation as an independent tool can recover it. Neither substitutes for the other, and the gap between them is the subject of docs/sv_polish_roadmap.md.

⚠ Four replicates, pooled — against a target of ~8. aggregate_sv_reps.sh pools summed TP/FN/FP (not a mean of per-replicate ratios, which would weight a replicate with 3 events the same as one with 40). At SV_RATE_SCALE=1.0 GRCh38 yields ~25 translocations per run, so ~8 replicates is the design target. Per-replicate truth counts vary widely — BND 50–76, INV 9–20, DUP 18–34 — so single-replicate figures were never going to be stable.

⚠ Every recall below is PASS-only. truvari is run with --passonly, so a truth event whose only matching call was non-PASS is scored FN. Measured instance: chr10:45850637 was called by Manta with identical POS/END/SVLEN and scored a DUP false negative because its FILTER was MinSomaticScore. These recalls are therefore underestimates by an unmeasured amount — see #541.

Array 21072620 (2026-08-13, seeds 9–12, GRCh38 30x, purity 0.6, SV_RATE_SCALE=1.0), pooled over 4 replicates:

The INS rows ran in 1 and 2 of 4 replicates respectively and are not comparable with the rest; the aggregator says so itself rather than pooling them silently.

DUP: both callers miss the identical set, and one of them is ours

manta_DUP and delly_DUP agree to the record — TP=91, FN=14 — differing only in FP. Two independent callers missing the same events points at a property of the events, not the callers. Examined for one replicate (FN = 4):

So it is not a size floor (1.7 Mb is trivially detectable by depth) and not assembly gaps (three are 0.0% N; SV placement already requires a ±200 bp N-free window at both breakpoints, sv_model.rs ALIGNABLE_WINDOW, #224). One of the four is a filter artifact (#541). The remaining three — including a megabase-scale duplication with nothing called anywhere near it — are unexplained, and diagnosing them needs reads, so PRUNE_BAM=0 on a future run.

Calibration controls passed: truth-vs-truth recall 1.000 with all 71 scoreable records scored, decoy (shifted truth) recall 0.000; same for BND across all 50. So the matching configuration is not loose enough to accept anything.

BND geometry is fixed, confirmed at genome scale

This is the first whole-genome confirmation of the v3.1.0 fix. BND recall=0.000 was the symptom of a truth VCF describing a rearrangement the reads did not carry; it now reads:

BND geometry: 50 record(s), 50 parsed into a form, 0 unparsable
  t[p[  direct/deletion-like    9      t]p]  head-to-head            18
  [p[t  tail-to-tail           14      ]p]t  direct/duplication-like  9
  reciprocity: 0 unpaired, 0 mispaired

All four bracket forms present, every record parsed, 0 unpaired and 0 mispaired — the #451-era failure (truth emitted unmatchable by construction) is gone, and Manta independently recovers 46 of the 50 records from the reads alone.

INV precision 0.500 is ours, not the callers’ — and Gate 2 now shows the reads are clean

Both callers report TP=9, FP=9 — identically. The pipeline predicts this in its own pre-flight: 16 of the truth’s junctions are inversion-oriented (t]p] or [p[t), and a caller’s breakends for those convert to <INV> via Manta’s convertInversion.py, landing as INV false positives. Two independent callers arriving at the same number is the evidence that it is a representation artifact. INV recall 1.000 is real; INV precision from this tier is not quotable.

Gate 2 (eidolon/tests/gate2_realigned_inv.rs) closes the remaining inference. Realigning a homozygous 1.2 kb inversion with bwa-mem2 gives 123 breakpoint-clipped reads against 0 in the control, 98 same-orientation (FF/RR) pairs against 0, 0 everted (RF) pairs — so nothing suggests a duplication — and interior depth of 1.026x the flank, i.e. balanced. The reads carry an unambiguous inversion signature, so the false positives are not attributable to them. That was previously an argument from two callers agreeing; it is now a measurement.

INS: one planted, one verified present, zero found

truth INS: 1 (65 bp) was the #516 cap working as designed, and the drop log proved it rather than implying it: 2 insertions dropped (chr2, chr19) + 1 kept = 3 draws, against ~3.5 expected from Ins = 0.0279 over ~130 SVs, of which ~0.9 were expected to survive the 150 bp cap.

That cap no longer exists (#516 fixed, 2026-08-24). Every draw is now realized, so a run’s INS count is the model’s own rate rather than the rate times a survival fraction — which is why the numbers in this section cannot be compared to a post-fix run.

INS read support: 1 of 1 — 7 reads carry a 30-mer from the middle of the inserted sequence. This is the first campaign to check that the reads contained what the truth declared before the BAMs were pruned, which is exactly how #516 survived three campaigns.

⚠ But the check itself is not trustworthy yet. Job 21076622, same array, reports INS read support: 0 of 1 — which turned out to measure nothing. Its probe file is well formed (chr3 92124128 56bp + a valid 30-mer), yet no per-insertion line was emitted on stdout or stderr: count_probe_hits produced no output, the reporting loop ran zero iterations, and the 0 is an untouched initialiser printed against an independently counted n_probes. Worse, unsupported stayed 0, so the failure gate never fired and the replicate archived as a clean result (#540).

The 1 of 1 above came through the same code path. It did print its detail line, so it is probably a true pass, but treated the #516 cap as unverified in production until #540 is fixed and both replicates are re-checked. Moot for the cap itself, which is gone; the #540 concern about a replicate archiving a clean result without printing its detail line stands.

Neither caller found it. Manta’s only INS call was a false positive on another chromosome (chr11:99348945, 58 bp, non-PASS); nothing was called within 2 kb of the planted event. Delly emitted no INS records at all. So the miss is verified rather than inferred — the reads demonstrably carried the insertion. With n=1 this does not constrain a recall rate (95% CI ≈ [0, 0.98]); why it was missed is unresolved, and separating “somatic-score threshold at ~7 supporting reads” from “the reads lack a signature the aligner can present” needs PRUNE_BAM=0 and a look at the CIGARs.

A 30× GRCh38 replicate yields ~3 INS draws and ~1 after the cap. INS cannot be validated at caller level from single replicates at any runtime — it needs pooled replicates or an INS-enriched model. Across the ~8 replicates the aggregator targets that is still only ~8 planted insertions, so an INS-enriched model is likely the only route to a usable denominator.

What this tier does NOT establish

• Input fidelity at scale. Every cell above this section is still H1N1-only.
• Dosage. Detection is not dosage; the ~8% over-delivery (#499) was measured on a 1.2 kb event and has never been checked at these sizes.
• Subclonal behaviour. Resolved for de-novo SVs in #537. Supported DEL/DUP/INV/INS/CNV records now carry EIDOLON_CCF/EIDOLON_VAF and use CCF-adjusted depth and junction evidence; reciprocal translocation BND mates share one CCF. Delta yeast validation exercised CCF 0.2/0.5/1.0 and retained 199 chimeric alignments. This section’s older nominal-rate campaign predates that fix; the full-GRCh38 post-fix run above is the current release-candidate stress test.
• Small events. The planted set skews very large (DUP 3.4 Mb, DEL 9.1 Mb, INV 2.0 Mb). Multi-megabase events are easy to detect by depth; these recall figures say little about the 1–50 kb range where callers actually struggle.

De novo generation

BND de novo means inter-chromosomal translocation only. PCAWG’s TRA class is 100% inter-chromosomal (68,547/68,547, docs/pcawg_sv_measurement.md M1), and a same-contig junction is a DEL/DUP/INV by its orientation — already sampled at their own rates.

De novo INS is a LITERAL record, and it must carry SVTYPE=INS. Unlike every other sampled type, an insertion is emitted as REF=<anchor>, ALT=<anchor><novel bases> rather than as symbolic <INS> — that routes the novel sequence through gen-reads’ literal-insertion machinery, so reads spanning the locus actually carry the bases, and it matches what Manta emits for a resolved insertion. END equals POS (an insertion consumes no reference span) and SVLEN is positive and equal to ALT.len() - REF.len().

The tag is not cosmetic. Without it the record is indistinguishable from a small-indel-model insertion of the same size, so nothing downstream can attribute it — a length threshold cannot separate them, because the Ins length fit puts ~17% of structural insertions below 100 bp while the indel tail reaches ~93 bp. Measured consequence: SV validation jobs 20885875 and 20892075 planted 4 insertions between them (296, 1057, 1492, 2500 bp) and scored none, both reporting truth INS: 0, because sv_pipeline.sbatch selects SVs on ALT[0]~"<" || INFO/SVTYPE!=".". Every SV validation run before this had the same hole. Pinned by sampled_ins_carry_svtype_and_svlen_so_they_are_separable_from_indels and, across the sampler/writer boundary, sampled_ins_svtype_survives_the_vcf_writer.

De novo SVs are opt-in: sv_rate_scale defaults to 0.0. For human germline they are not recommended at all — constitutional balanced translocations occur in roughly 1 in 500 live births, so a normal genome carries ~zero. The machinery stays for cancer (rates are real and verified) and is expected to matter for plants.

Where input and de novo deliberately differ

These are not inconsistencies to reconcile. Input is “reproduce what I gave you”; de novo is “sample what the corpus says”. A researcher wanting a specific rearrangement should use input_vcf — that path preserves IDs, POS and ALT verbatim and generates junction reads.

How this was measured

# per cell: one variant, input_vcf, sv_rate_scale 0.0, produce_bam
eidolon gen-reads -c cell.yml
samtools index o.bam
samtools depth -a -r CONTIG:START-END o.bam | awk '{s+=$3;n++} END{print s/n}'   # vs a control span
zcat o_r1.fastq.gz | paste - - - - | awk '$1 ~ /EIDOLON_chimeric/' | grep -c PROBE

One methodological trap, hit while producing this table. Do not grep a FASTQ for a sequence probe without separating the sequence from the quality string: paste - - - - puts them on one line, and Phred+33 quality characters overlap the DNA alphabet (G is Q38, so a run of 12 Gs is common in quality). A homopolymer probe reported 71 false matches that way. Filter to the sequence field, and prefer a non-homopolymer probe. This is the same class of error as the FASTA reader accepting a FASTQ because > is Q29.