Infer integer allele-specific copy number, tumor purity, and ploidy from tumor sequencing by jointly modeling read depth (logR) and B-allele frequency (BAF) with ASCAT, Sequenza, FACETS, PURPLE, and PureCN (tumor-only). Covers the purity-ploidy identifiability problem, the diploid-baseline (dipLogR) anchor, major/minor copy number, loss of heterozygosity, sunrise/contour fit diagnostics, and reconciliation of conflicting fits. Use when tumor analysis needs absolute copy number rather than relative log2, when estimating purity and ploidy, calling LOH or copy-neutral LOH, resolving whole-genome doubling, running tumor-only allele-specific calling, or choosing among ASCAT, Sequenza, FACETS, and PureCN.
Instrucciones de origen · Vista previa de solo lectura
name
bio-copy-number-allele-specific-copy-number
description
Infer integer allele-specific copy number, tumor purity, and ploidy from tumor sequencing by jointly modeling read depth (logR) and B-allele frequency (BAF) with ASCAT, Sequenza, FACETS, PURPLE, and PureCN (tumor-only). Covers the purity-ploidy identifiability problem, the diploid-baseline (dipLogR) anchor, major/minor copy number, loss of heterozygosity, sunrise/contour fit diagnostics, and reconciliation of conflicting fits. Use when tumor analysis needs absolute copy number rather than relative log2, when estimating purity and ploidy, calling LOH or copy-neutral LOH, resolving whole-genome doubling, running tumor-only allele-specific calling, or choosing among ASCAT, Sequenza, FACETS, and PureCN.
Before using code patterns, verify installed versions match. If versions differ:
R: packageVersion('ASCAT') / 'sequenza' / 'facets' / 'PureCN', then ?function
CLI: sequenza-utils --version, snp-pileup --help
Sequenza 3.0 depends on the copynumber Bioconductor package, REMOVED from Bioconductor 3.18+ (2023). Install a maintained fork (ShixiangWang/copynumber or ) before Sequenza will load. ASCAT's GC-correction function was renamed across 2.x->3.x ( -> ) — verify against the installed version.
igordot/copynumber
ascat.GCcorrect
ascat.correctLogR
Allele-Specific Copy Number
"How many copies of each allele, in what fraction of cells, at what tumor purity" -> Jointly model read depth and B-allele frequency to fit tumor purity, ploidy, and integer major/minor copy number per segment. Depth alone gives only relative copy ratio; depth + BAF gives absolute allele-specific copy number. This skill is required whenever the question involves LOH, absolute copy number, purity, ploidy, or whole-genome doubling — CNVkit and GATK somatic CNV cannot answer those.
CLI: purple (Hartwig WGS pipeline, with AMBER + COBALT)
The Identifiability Problem — Why This Is Hard
Purity and ploidy are not identifiable from depth alone. The same log-ratio profile is explained equally well by many (purity, ploidy) pairs: a homozygous deletion at 30% purity looks identical to a heterozygous deletion at 60% purity; an entire profile can be reinterpreted at 2x ploidy with halved purity. Every allele-specific caller breaks this degeneracy by adding BAF — allelic imbalance constrains which solution is real. The consequence: the likelihood surface is multimodal, the fit can lock onto an integer-multiple of the true ploidy, and a single point estimate must never be trusted without inspecting the fit diagnostic (ASCAT sunrise plot, Sequenza cellularity/ploidy contour, FACETS dipLogR). A documented example: the same tumor scored ploidy 4.27 by FACETS (WGS) and 2.42 by ASCAT (SNP array).
Caller Taxonomy
Tool
Input
Segmentation
Best for
Fails when
ASCAT
SNP array or WGS logR+BAF
ASPCF (allele-specific PCF)
WGS, SNP6, large cohorts
Near-diploid genome with few aberrations cannot anchor purity -> defaults toward purity ~100%
Sequenza
Tumor-normal WES/WGS (seqz)
copynumber PCF
Exome, accessible install
Picks a near-diploid local optimum; needs manual review of alternative solutions
FACETS
Tumor-normal, snp-pileup
Joint logR+BAF CBS
Targeted panels, WES, clinical NGS
cval too low -> hyperfragmentation; EM locks onto an integer-multiple ploidy
PURPLE
WGS, AMBER+COBALT+SVs
Integrates SV breakpoints
WGS with matched SV calls
Targeted/WES (designed for WGS); needs the Hartwig tool stack
PureCN
Tumor-only WES/panel + PoN
Coverage + VCF, normal DB
No matched normal
Sparse hets; small panels; needs a well-built normal database
Battenberg
WGS logR+BAF, phased
ASCAT-based clonal + subclonal
Subclonal CN, clonal evolution
Heavy; needs phasing reference — see subclonal-copy-number
Decision Tree by Data Type
Scenario
Recommended caller
Rationale
Tumor-normal WGS
ASCAT or PURPLE
PURPLE if SV calls available (resolves breakpoints); ASCAT otherwise
Tumor-normal WES
Sequenza or FACETS
Both joint logR+BAF; FACETS faster, Sequenza reports alternative solutions
Targeted panel (tumor-normal)
FACETS
Designed for panel het density; clinical-NGS standard
Tumor-only panel / WES
PureCN
Models a normal database; the standard tumor-only solution
SNP array (legacy)
ASCAT
ASCAT was built for SNP arrays
Subclonal CN / clonal evolution
Battenberg / TITAN
See subclonal-copy-number
Only relative gain/loss needed
CNVkit / GATK
Allele-specific machinery is unnecessary
FACETS — Tumor-Normal Allele-Specific CN
Goal: Fit purity, ploidy, and integer allele-specific CN for a panel or WES pair.
Approach: Pile up read counts at common SNPs with snp-pileup, then run the two-pass FACETS workflow — a high-cval purity run whose dipLogR seeds a low-cval sensitivity run for focal events.
# Step 1: pileup at dbSNP common sites (normal first, then tumor)
snp-pileup -g -q15 -Q20 -P100 -r25,0 dbsnp_common.vcf.gz \
sample.snp_pileup.csv.gz normal.bam tumor.bam
library(facets)
set.seed(1234)# FACETS uses random initialization
rcmat <- readSnpMatrix('sample.snp_pileup.csv.gz')
xx <- preProcSample(rcmat)# gbuild default 'hg19'; pass gbuild='hg38' for GRCh38# Pass 1: purity/ploidy at a coarse cval (panels ~150-300; WGS ~25-100)
oo1 <- procSample(xx, cval =300)
fit1 <- emcncf(oo1)# Pass 2: focal sensitivity, seeded by the diploid baseline from pass 1
oo2 <- procSample(xx, cval =150, dipLogR = oo1$dipLogR)
fit2 <- emcncf(oo2)
cat('purity', fit2$purity,'ploidy', fit2$ploidy,'dipLogR', oo2$dipLogR,'\n')# fit2$cncf has per-segment tcn.em (total CN) and lcn.em (minor CN); lcn.em == 0 -> LOH
plotSample(x = oo2, emfit = fit2)# ALWAYS inspect this diagnostic plot
Sequenza — Exome Tumor-Normal
Goal: Estimate cellularity/ploidy and allele-specific CN from a WES pair, with explicit alternative solutions.
Approach: Build a seqz file from the BAMs, bin it, then run the extract/fit/results chain; inspect the cellularity/ploidy contour and the reported alternative solutions.
library(sequenza)
seqz <- sequenza.extract('sample.bin.seqz.gz')
CP <- sequenza.fit(seqz)# grid search over cellularity x ploidy
sequenza.results(seqz, CP,'sampleID', out.dir ='sequenza_out')# Inspect *_CP_contours.pdf and *_alternative_solutions.txt before accepting the fit.
ASCAT — WGS / SNP Array
Goal: Fit purity (rho), ploidy (psi), and allele-specific CN genome-wide.
Approach: Load logR/BAF, correct for GC (and optionally replication timing), segment with ASPCF, run the ASCAT fit, and read the sunrise plot.
library(ASCAT)
ascat.bc <- ascat.loadData('Tumor_LogR.txt','Tumor_BAF.txt','Germline_LogR.txt','Germline_BAF.txt')
ascat.bc <- ascat.correctLogR(ascat.bc, GCcontentfile ='GC_G1000.txt',
replictimingfile ='RT_G1000.txt')# RT optional
ascat.bc <- ascat.aspcf(ascat.bc)
ascat.output <- ascat.runAscat(ascat.bc,gamma=1)# gamma=1 for NGS; ~0.55 for arrays# ascat.output$purity, $ploidy, $goodnessOfFit; $nA / $nB are major/minor CN per segment# Inspect the sunrise plot: banding at multiples of ploidy signals an ambiguous fit.
PureCN — Tumor-Only
Goal: Recover purity, ploidy, allele-specific CN, and LOH without a matched normal.
Approach: Build a normal database (PoN) once, then run runAbsoluteCN with the tumor coverage and a VCF; PureCN uses the normal DB and a mapping-bias model in place of a matched normal.
library(PureCN)
ret <- runAbsoluteCN(
tumor.coverage.file ='tumor_coverage.txt.gz',
vcf.file ='tumor.vcf.gz',
normalDB = readRDS('normalDB.rds'),# built once from >= ~20 process-matched normals
genome ='hg38', sampleid ='tumor',
interval.file ='baits_intervals.txt')# ret$results[[1]]$purity / $ploidy; createCurationFile() flags fits needing manual review
Failure Modes
ASCAT defaults to ~100% purity on a near-diploid genome
Trigger: A tumor with very few copy-number aberrations and overall ploidy near 2.
Mechanism: ASCAT infers purity from the depth/BAF deviation of aberrant segments. With almost no aberrant segments there is nothing to anchor purity against, so the grid search drifts to the boundary.
Symptom: Reported purity ~1.0 (or implausibly high) with an almost flat profile; the sunrise plot is nearly featureless.
Fix: Treat purity as indeterminate, not 100%. Cross-check with an orthogonal estimate (SNV VAF mode for clonal mutations, pathology estimate). A genuinely quiet genome simply does not support a confident purity call.
FACETS hyperfragmentation from too-low cval
Trigger:cval set too low for the data (e.g. panel data run at WGS-scale cval).
Mechanism:cval is the segmentation critical value; low values let the segmenter split on noise, shattering the profile into spurious micro-segments.
Symptom: Hundreds of tiny segments; tcn.em/lcn.em incoherent with cnlr.median; jagged plotSample output.
Fix: Use cval ~150-300 for panels/WES, ~25-100 for WGS. Run the two-pass workflow (coarse purity run -> dipLogR-seeded sensitivity run). If naive tcn and EM tcn.em disagree wildly, the fit is bad — re-tune cval.
Integer-multiple ploidy flip
Trigger: Any allele-specific caller on a genome where the diploid baseline is ambiguous (few hets, low purity, or genuine WGD).
Mechanism: The likelihood surface has near-equal modes at ploidy P and 2P; the optimizer can select the wrong one, halving or doubling all copy numbers.
Symptom: Two callers disagree by a factor of ~2 in ploidy; "balanced" CN states that should be odd come out even (or vice versa); SNV multiplicities inconsistent with the called CN.
Fix: Inspect the fit diagnostic (sunrise/contour). Cross-check ploidy against the fraction of the genome at odd vs even CN and against clonal-SNV VAF. Prefer the solution consistent with known biology; if truly ambiguous, report both.
Sequenza fails to load / picks a near-diploid optimum
Trigger: Fresh Sequenza install on Bioconductor 3.18+; or accepting sequenza.fit's point estimate without review.
Mechanism: Sequenza depends on copynumber, removed from Bioconductor 3.18+. Separately, the LPP grid search can settle on a near-diploid local optimum when a higher-ploidy solution fits comparably.
Symptom:copynumber not available at load; or a ploidy ~2 call that conflicts with visible large-scale imbalance.
Fix: Install a maintained copynumber fork. Always inspect *_CP_contours.pdf and *_alternative_solutions.txt; if a non-diploid alternative fits nearly as well and matches the BAF pattern, prefer it.
Mechanism: Allelic imbalance and depth deviation both shrink with purity; below ~40% the signal approaches the noise floor and segmentation fails.
Symptom: No confident fit; purity estimate unstable across reruns; flat BAF.
Fix: Below ~40% purity, allele-specific calling is unreliable; below ~20% it is not possible with bulk sequencing. Report indeterminate; consider deeper sequencing or microdissection.
Reconciliation: When Callers Disagree
Pattern
Likely cause
Action
Caller A ploidy ~= 2x caller B
Integer-multiple ploidy flip
Check odd/even CN fraction and SNV multiplicity; pick the biology-consistent fit
Purity differs widely, ploidy agrees
One caller hit a boundary on a quiet genome
Trust the caller whose diagnostic plot shows real structure
FACETS vs ASCAT integer CN differ
Different segmentation (CBS vs ASPCF) at boundaries
Compare segment edges; arm-level calls usually agree, focal may not
Tumor-only (PureCN) vs tumor-normal differ
Tumor-only has weaker purity constraint
Prefer the matched-normal fit when available
Operational rule: Report an allele-specific fit as confident only when (1) the fit diagnostic (sunrise/contour/dipLogR) shows clear, non-degenerate structure, (2) purity is above ~40%, (3) ploidy is consistent with the odd/even CN fraction and with clonal-SNV multiplicity, and (4) for ambiguous cases, the alternative solutions have been reviewed. A bare purity/ploidy number with no diagnostic inspection is not a result.
