v2 CN: real-data validation vs NYGC 30x SVs (interim), noise gate on normalised LRR (K-027)
GSE165845 360 arrays: constitutional DEL/DUP calls 77/74 % in the NYGC SV truth, LOH reproduced across replicates 74 %; mosaic calls are mostly false positives (12-23 %), sensitivity for 25 kb-1 Mb events 7-13 % at QUAL >= 20. All samples had been flagged SampleQuality by the summary logr_dev (cluster-file mismatch); the gate now uses the SD of the LRR after the batch reference. Validation script: --ignore-filter.
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# v2 module validation — genome-wide CNV / LOH / mosaicism (`simurg cn`) — interim
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Date: 2026-09-29. Status: **not accepted yet** — constitutional calling works, mosaic calling produces mostly false
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positives on the real-data set; see "Next steps". Spec: CYTO-001 … CYTO-040.
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## Delivered
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`simurg cn build-model` (GC 1 kb / 100 kb / 1 Mb, PFB from the cluster file, sex-aware batch reference from normal
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GTCs), `simurg cn call` (GC-wave correction, smoothing, HMM with constitutional, gain-LOH, mosaic and haploid
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states, events, post-filters, thresholds, centromere mask, CNV VCF + tabix, segments, summary, sidecar),
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`simurg cn annotate` (JSON report, ISCN 2020, cytobands, RefSeq genes), `scripts/build_annotation_bundle.sh`.
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Unit tests: `tests/unit/test_cn.py` (11).
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## Synthetic implants (CYTO-022), GSA v4 demo, 22 synthetic samples, 216 events
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Reference model from 30 samples, events implanted into the other 6 (`scripts/v2/cn_synthetic_eval.py`,
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`V2_cn_synthetic_gsa36.json`), 4 replicates per cell:
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| Event | 1 Mb | 5 Mb | 20 Mb |
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|---|---|---|---|
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| constitutional DEL / DUP | 4/4 · 2/4 | 4/4 · 4/4 | 4/4 · 4/4 |
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| constitutional LOH (threshold 3 Mb) | 0/4 | 3/4 | 4/4 |
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| mosaic loss / gain / CN-LOH, 15 % | 3/4 · 1/4 · 0/4 | **4/4 · 4/4 · 4/4** | 4/4 · 4/4 · 4/4 |
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| mosaic, 5–10 % | mostly missed | mostly missed | 0–3/4 |
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The CYTO-022 gate (≥ 90 % at 15 % / 5 Mb) is met on implanted data (12/12, small n).
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## Real data: GSE165845 (360 GSA-MD arrays, 120 individuals × 3) vs NYGC 30x SV callset (freeze V3)
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Cloud run 2026-09-29 (m7g.4xlarge, `cn call` 360 samples in 7 min 40 s; reference from 120 arrays of the same set).
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Truth: non-reference DEL/DUP ≥ 25 kb of the same individual, ≥ 10 array probes; match = reciprocal overlap ≥ 50 %.
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* Every sample was flagged `SampleQuality` (summary `logr_dev` median 0.246 — the GSA v1 C1 cluster file does not
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match the GSA-MD chips, P8) and 46 fell into whole-chromosome-only mode, although the LRR used for calling has a
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robust SD of 0.099 after the batch reference. The gate now uses the SD of the normalised LRR (K-027). The numbers
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below ignore `SampleQuality` (`--ignore-filter`), evaluated from the run's sidecar.
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| QUAL ≥ 20 | DEL | DUP |
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|---|---|---|
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| sensitivity 25–50 / 50–100 / 100–500 / 500–1000 kb | 7 / 8 / 8 / 7 % | 1 / 3 / 11 / 13 % |
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| precision (all calls of the class) | 39 % | 34 % |
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| Call type (QUAL ≥ 20) | calls | in NYGC truth | seen in another replicate |
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|---|---|---|---|
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| constitutional DEL | 227 | **77 %** | 50 % |
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| constitutional DUP | 23 | **74 %** | 30 % |
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| LOH | — | — | 74 % |
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| mosaic loss | 399 | 12 % | 12 % |
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| mosaic gain | 567 | 23 % | 23 % |
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Constitutional calls are mostly true; the mosaic states generate most calls and most false positives (large
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BAF-supported "mosaic" events are 0–2 % in truth and rarely reproduced: shifted heterozygous BAF bands of the
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mismatched cluster file mimic allelic imbalance). Small BAF-supported mosaic gains are often real germline
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duplications labelled mosaic (43 % in truth).
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## Next steps
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1. Mosaic calling: require consistent BAF imbalance with a per-probe reference of heterozygous BAF spread, raise the
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evidence for mosaic states (prior/size), and relabel compressed germline gains/losses as constitutional; tune on
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GSE165845 and re-measure (replicate reproducibility is the cheapest check).
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2. Sensitivity for 25–500 kb events: lower switch cost for short events with strong LRR, per-probe LRR SD from the
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reference.
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3. Re-run the truth comparison; document the final numbers.
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{
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"samples": 360,
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"min_qual": 10.0,
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"ignored_filters": [
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"SampleQuality"
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],
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"sensitivity": {
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"DEL": {
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"100-500kb": {
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"found": 230,
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"truth": 1554,
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"rate": 0.148
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},
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"1000-infkb": {
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"found": 0,
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"truth": 15,
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"rate": 0.0
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},
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"25-50kb": {
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"found": 54,
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"truth": 225,
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"rate": 0.24
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},
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"50-100kb": {
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"found": 132,
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"truth": 894,
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"rate": 0.1477
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},
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"500-1000kb": {
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"found": 51,
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"truth": 180,
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"rate": 0.2833
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}
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},
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"DUP": {
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"100-500kb": {
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"found": 279,
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"truth": 1059,
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"rate": 0.2635
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},
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"1000-infkb": {
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"found": 9,
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"truth": 21,
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"rate": 0.4286
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},
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"25-50kb": {
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"found": 4,
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"truth": 198,
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"rate": 0.0202
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},
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"50-100kb": {
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"found": 55,
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"truth": 462,
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"rate": 0.119
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},
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"500-1000kb": {
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"found": 19,
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"truth": 78,
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"rate": 0.2436
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}
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}
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},
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"precision": {
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"DEL": {
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"in_truth": 473,
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"calls": 1814,
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"rate": 0.2607
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},
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"DUP": {
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"in_truth": 367,
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"calls": 1494,
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"rate": 0.2456
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}
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},
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"replicate_reproducibility": {
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"CNV": {
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"matched": 2132,
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"comparisons": 6616,
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"rate": 0.3222
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},
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"LOH": {
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"matched": 400,
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"comparisons": 532,
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"rate": 0.7519
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}
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},
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"calls_per_sample_median": 6.0,
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"loh_calls_per_sample_median": 0.0
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}
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@@ -0,0 +1,89 @@
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{
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"samples": 360,
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"min_qual": 20.0,
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"ignored_filters": [
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"SampleQuality"
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],
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"sensitivity": {
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"DEL": {
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"100-500kb": {
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"found": 126,
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"truth": 1554,
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"rate": 0.0811
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},
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"1000-infkb": {
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"found": 0,
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"truth": 15,
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"rate": 0.0
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},
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"25-50kb": {
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"found": 16,
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"truth": 225,
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"rate": 0.0711
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},
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"50-100kb": {
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"found": 70,
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"truth": 894,
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"rate": 0.0783
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},
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"500-1000kb": {
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"found": 13,
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"truth": 180,
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"rate": 0.0722
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}
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},
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"DUP": {
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"100-500kb": {
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"found": 117,
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"truth": 1059,
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"rate": 0.1105
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},
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"1000-infkb": {
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"found": 6,
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"truth": 21,
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"rate": 0.2857
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},
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"25-50kb": {
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"found": 1,
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"truth": 198,
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"rate": 0.0051
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},
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"50-100kb": {
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"found": 15,
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"truth": 462,
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"rate": 0.0325
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},
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"500-1000kb": {
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"found": 10,
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"truth": 78,
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"rate": 0.1282
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}
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}
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},
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"precision": {
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"DEL": {
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"in_truth": 222,
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"calls": 571,
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"rate": 0.3888
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},
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"DUP": {
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"in_truth": 149,
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"calls": 436,
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"rate": 0.3417
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}
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},
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"replicate_reproducibility": {
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"CNV": {
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"matched": 554,
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"comparisons": 2014,
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"rate": 0.2751
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},
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"LOH": {
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"matched": 286,
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"comparisons": 394,
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"rate": 0.7259
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}
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},
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"calls_per_sample_median": 2.0,
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"loh_calls_per_sample_median": 0.0
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}
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