Cancer Report for Sample SEQC-II-50pc__SEQC-II_Tumor_50pc

Summary

QC_Status	PASS
Purity	0.43 (0.41-0.79)
Ploidy	2.911 (2.851-4.917)
Gender	MALE
Top MutSigs	Old: Sig3 (11082), Sig13 (6441) - New: SBS13 (6369), SBS39 (4511)
CNVs (Somatic)	Min: -0.52; Max: 11.52; N: 1497
SVs (unmelted)	Sum: 807, INS: 19, DUP: 205, DEL: 375, BND: 208
SVs (melted)	Sum: 15879, INS: 21, DUP: 6788, DEL: 8819, BND: 251
Genome	hg38

AF Summary Stats

set	n	mean	median	mode
Global	32264	0.28	0.24	0.25
Key genes CDS	67	0.32	0.25	0.25

Somatic Mutation Profiles

Allelic Frequencies

Summarised below are the allele frequencies (AFs) for somatic variants detected genome-wide (Global) vs. within the coding sequence of ~1,100 UMCCR cancer genes (Key Genes CDS). AFs range from 0 to 1, or 0%-100% (we filter out all novel variants with AF < 10%).

Details

Variants are typically called in bcbio by 3 different callers, with calls supported by at least 2 of them used (“ensemble” approach). In some cases only a single caller is used due to technical reasons (e.g. highly mutated FFPE sample).

The following post-processing steps occur:

1. somatic_vcf_annotate: annotate VCF against databases of known hotspots, germline variants, low mappability regions, UMCCR panel of normals
2. somatic_vcf_filter: filter VCF to remove germline variants and artefacts, but keep known hotspots
3. As preparation for the allelic frequencies plots:
   • subset_to_giab: keep variants in ‘high confidence’ regions as determined by the Genome in a Bottle consortium
   • keep only variants with AF above 10%
4. Allele frequencies for global and keygenes:
   • afs: grab only the INFO/TUMOR_AF field and output to final txt file
   • afs_keygenes: grab the CHROM, POS, ID, REF, ALT and INFO/TUMOR_AF for variants in the UMCCR cancer gene BED file, and output to final txt file

Mutational Signatures

Deciphering the mutational signature of a tumor sample can provide insight into the mutational processes involved in carcinogenesis and help in cancer treatment and prevention. The MutationalPatterns R package is used to generate a mutation signature for the sample. We use the final filtered somatic calls as input.

Context signature

Point mutation spectrum

Description

We can count the mutation type occurrences for the input VCF. For C>T mutations, a distinction is made between C>T at CpG sites and other sites, as deamination of methylated cytosine at CpG sites is a common mutational process. This is the reason the reference genome is needed.

A mutation spectrum shows the relative contribution of each mutation type in the base substitution catalogs. We can plot the mean relative contribution of each of the 6 base substitution types over all samples. Error bars indicate standard deviation over all samples. The total number of mutations is indicated. We can also distinguish between C>T at CpG sites and other sites.

Transcriptional strand bias

Description

We can determine if a gene mutation is on the transcribed or non-transcribed strand, which can be used to evaluate the involvement of transcription-coupled repair. By convention base substitutions are regarded as C>X or T>X, so we try to determine whether the C or T base is on the same strand as the gene definition. Base substitutions on the same strand as the gene definition are considered ‘untranscribed’, and on the opposite strand ‘transcribed’, since the gene definitions report the coding or sense strand, which is untranscribed. No strand information is reported for base substitutions that overlap with more than one gene on different strands.

Replicative strand bias

Description

The involvement of replication-associated mechanisms can be evaluated by testing for a mutational bias between the leading and lagging strand. The replication strand is dependent on the locations of replication origins from which DNA replication is fired. However, replication timing is dynamic and cell-type specific, which makes replication strand determination less straightforward than transcriptional strand bias analysis. Replication timing profiles can be generated with Repli-Seq experiments. Once the replication direction is defined, a strand asymmetry analysis can be performed similarly as the transcription strand bias analysis.

Signature Contribution

Description

The contribution of any set of signatures to the mutational profile of a sample can be quantified. This unique feature is specifically useful for mutational signature analyses of small cohorts or individual samples, but also to relate own findings to known signatures and published findings. The fit_to_signatures function finds the optimal linear combination of mutational signatures that most closely reconstructs the mutation matrix by solving a non-negative least-squares constraints problem.

Shown are signatures with positive Contribution values, along with summarised descriptions and reference signature plots from https://cancer.sanger.ac.uk/cosmic/signatures.

 

OLD

Rank	Signature	Contribution	Description	Plot
1	Sig3	11082	Breast, ovarian, pancreatic; germline + somatic BRCA1/BRCA2 mut; failure of DNA ds break-repair; many large indels.
2	Sig13	6441	In 22 cancers; mostly cervical, bladder, breast; AID/APOBEC; C>G mut; similar to sig2; maybe viral infection, retrotransposon jumping or tissue inflammation; kataegis.
3	Sig2	4072	In 22 cancers; mostly cervical + bladder; AID/APOBEC; similar to sig13; maybe viral infection, retrotransposon jumping or tissue inflammation; exon TSB.
4	Sig8	3270	Breast cancer, medulloblastoma; many CC>AA subs; weak strand bias for C>A subs.
5	Sig19	2220	Only in pilocytic astrocytoma.
6	Sig7	1985	Skin, lip, head, neck or oral squamous cancers; ultraviolet light exposure; many CC>TT subs; strong TSB with many C>T mut.
7	Sig16	1246	Liver; strong TSB for T>C at ATN context.
8	Sig12	1093	Liver; TSB for T>C.
9	Sig1	1082	All cancers; correlates with age of diagnosis; few small indels
10	Sig9	996	Chronic lymphocytic leukaemias, malignant B-cell lymphomas; mut pattern associated with polymerase H (implicated with AID during som hypermutation).
11	Sig11	644	Melanoma, glioblastoma; alkylating agents; TSB for C>T.
12	Sig27	66	Subset of kidney clear cell carcinomas; strong TSB for T>A; many small indels.
13	Sig28	38	Subset of stomach cancers.
14	Sig10	6	In 6 cancers; mostly colorectal and uterine; hypermutated samples due to altered POLE activity; TSB for C>A at TCT context, T>G at TTT context.

NEW

Rank	Signature	Contribution	Description	Plot
1	SBS13	6369	https://cancer.sanger.ac.uk/cosmic/signatures/SBS/SBS13.tt
2	SBS39	4511	https://cancer.sanger.ac.uk/cosmic/signatures/SBS/SBS39.tt
3	SBS2	3866	https://cancer.sanger.ac.uk/cosmic/signatures/SBS/SBS2.tt
4	SBS8	3412	https://cancer.sanger.ac.uk/cosmic/signatures/SBS/SBS8.tt
5	SBS3	2803	https://cancer.sanger.ac.uk/cosmic/signatures/SBS/SBS3.tt
6	SBS19	1922	https://cancer.sanger.ac.uk/cosmic/signatures/SBS/SBS19.tt
7	SBS5	1833	https://cancer.sanger.ac.uk/cosmic/signatures/SBS/SBS5.tt
8	SBS7a	1749	https://cancer.sanger.ac.uk/cosmic/signatures/SBS/SBS7a.tt
9	SBS41	1222	https://cancer.sanger.ac.uk/cosmic/signatures/SBS/SBS41.tt
10	SBS37	921	https://cancer.sanger.ac.uk/cosmic/signatures/SBS/SBS37.tt
11	SBS1	733	https://cancer.sanger.ac.uk/cosmic/signatures/SBS/SBS1.tt
12	SBS32	715	https://cancer.sanger.ac.uk/cosmic/signatures/SBS/SBS32.tt
13	SBS31	473	https://cancer.sanger.ac.uk/cosmic/signatures/SBS/SBS31.tt
14	SBS46 (SA)	468	https://cancer.sanger.ac.uk/cosmic/signatures/SBS/SBS46.tt
15	SBS58 (SA)	424	https://cancer.sanger.ac.uk/cosmic/signatures/SBS/SBS58.tt
16	SBS14	370	https://cancer.sanger.ac.uk/cosmic/signatures/SBS/SBS14.tt
17	SBS30	351	https://cancer.sanger.ac.uk/cosmic/signatures/SBS/SBS30.tt
18	SBS12	332	https://cancer.sanger.ac.uk/cosmic/signatures/SBS/SBS12.tt
19	SBS50 (SA)	284	https://cancer.sanger.ac.uk/cosmic/signatures/SBS/SBS50.tt
20	SBS10b	264	https://cancer.sanger.ac.uk/cosmic/signatures/SBS/SBS10b.tt
21	SBS7b	246	https://cancer.sanger.ac.uk/cosmic/signatures/SBS/SBS7b.tt
22	SBS7c	245	https://cancer.sanger.ac.uk/cosmic/signatures/SBS/SBS7c.tt
23	SBS54 (SA)	183	https://cancer.sanger.ac.uk/cosmic/signatures/SBS/SBS54.tt
24	SBS85	151	https://cancer.sanger.ac.uk/cosmic/signatures/SBS/SBS85.tt
25	SBS16	149	https://cancer.sanger.ac.uk/cosmic/signatures/SBS/SBS16.tt
26	SBS17b	125	https://cancer.sanger.ac.uk/cosmic/signatures/SBS/SBS17b.tt
27	SBS53 (SA)	105	https://cancer.sanger.ac.uk/cosmic/signatures/SBS/SBS53.tt
28	SBS43 (SA)	86	https://cancer.sanger.ac.uk/cosmic/signatures/SBS/SBS43.tt
29	SBS27 (SA)	74	https://cancer.sanger.ac.uk/cosmic/signatures/SBS/SBS27.tt
30	SBS55 (SA)	50	https://cancer.sanger.ac.uk/cosmic/signatures/SBS/SBS55.tt
31	SBS35	20	https://cancer.sanger.ac.uk/cosmic/signatures/SBS/SBS35.tt
32	SBS38	17	https://cancer.sanger.ac.uk/cosmic/signatures/SBS/SBS38.tt
32	SBS59 (SA)	17	https://cancer.sanger.ac.uk/cosmic/signatures/SBS/SBS59.tt

 

Rainfall Plot

Rainfall plots show the distribution of mutations along the genome, with mutation types indicated with different colors. The y-axis corresponds to the distance of a mutation from the previous mutation, and is log10 transformed. Drop-downs from the plots indicate clusters or “hotspots” of mutations.

Circos Plots

Circos plots are generated by PURPLE. The first BAF plot is based on PURPLE data and configuration files.

BAF, Total/Minor CN, SVs

Description

• Track1: Chromosomes. Darker shaded areas: gaps in reference genome (centromeres, heterochromatin & missing short arms)
• Track2: Beta Allele Frequency. Given that the BAF points correspond to allele frequencies of heterozygous SNPs that are common in germline samples, there shouldn’t be any in chromosome Y (and chromosome X when male).
• Track3: Total copy number changes adjusted for tumor purity, including focal and chromosomal somatic events. Red = Loss; Green = Gain. Scaled from 0 (complete loss) to 6 (high level gains). If > 6, shown as 6 with a green dot on the outermost green gridline.
• Track4: Minor allele copy numbers. Range from 0 to 3. Expected normal minor allele copy number is 1, and anything below 1 is shown as a loss (Orange), representing an LOH event. Minor allele copy numbers above 1 (Blue) indicate gains of both A and B alleles.
• Track5 (Inner circle): Observed structural variants within or between the chromosomes.
  • Blue = Translocations
  • Red = Deletions
  • Yellow = Insertions
  • Green = Tandem duplications
  • Black = Inversions

SNVs/Indels, Total/Minor CN, SVs

Description

• Track1: Chromosomes. Darker shaded areas: gaps in reference genome (centromeres, heterochromatin & missing short arms)
• Track2: Somatic variants (incl. exon, intron and intergenic regions).
  • outer ring: SNP allele frequencies, corrected for tumor purity and scaled from 0 to 100%. Each dot represents a single somatic variant, coloured according to the type of base change (e.g. C>T/G>A in red).
  • inner ring: short insertion (yellow) and deletion (red) locations.
• Track3: Observed total copy number changes adjusted for tumor purity, including focal and chromosomal somatic events. Red = Loss; Green = Gain. Scaled from 0 (complete loss) to 6 (high level gains). If > 6, shown as 6 with a green dot on the outermost green gridline.
• Track4: Observed minor allele copy numbers. Range from 0 to 3. Expected normal minor allele copy number is 1, and anything below 1 is shown as a loss (Orange), representing an LOH event. Minor allele copy numbers above 1 (Blue) indicate gains of both A and B alleles.
• Track5 (Inner circle): Observed structural variants within or between the chromosomes.
  • Blue = Translocations
  • Red = Deletions
  • Yellow = Insertions
  • Green = Tandem duplications
  • Black = Inversions

Allele Ratios, BAF

Description

• Track1: Chromosomes. Darker shaded areas: gaps in reference genome (centromeres, heterochromatin & missing short arms)
• Track2: Tumor and Normal Allele Ratios
• Track3: Beta Allele Frequency Given that the BAF points correspond to allele frequencies of heterozygous SNPs that are common in germline samples, there shouldn’t be any in chromosome Y (and chromosome X when male).

Structural Variants

Structural variants are inferred with Manta, adjusted using PURPLE, and prioritised using simple_sv_annotation. Allele frequencies, copy number changes and ploidy are purity-adjusted.

Details

The input file corresponds to umccrised/<batch>/structural/<batch>-manta.tsv.

It’s generated through the following steps:

Step 1: Processing

• Input: Manta structural variant calls from bcbio (final/<tumor-name>/<batch-name>-sv-prioritize-manta.vcf.gz (or <batch-name>-manta.vcf.gz if not prioritised))
• Remove following annotations from Manta VCF: ‘INFO/SIMPLE_ANN’, ‘INFO/SV_HIGHEST_TIER’, ‘FILTER/Intergenic’, ‘FILTER/MissingAnn’, ‘FILTER/REJECT’
• Prioritise variants with simple_sv_annotation`
• Output: work/{batch}/structural/prioritize/{batch}-manta.vcf.gz
• Keep PASS variants
• If more than 100,000 variants, keep only variants where INFO/SV_TOP_TIER <= 3
• Output: work/{batch}/structural/keep_pass/{batch}-manta.vcf
• Deal with chromosome capitalisation occurring from SnpEff
• Run BreakPointInspector (BPI) if it was disabled in bcbio
• Output: work/{batch}/structural/maybe_bpi/{batch}-manta.vcf

Step 2: Filtering

• Keep PASS variants (since BPI updates the FILTER column)
• For BND variants require paired reads support (PR) to be higher than split read support (SR)
• Keep all INFO/SV_TOP_TIER <= 2 variants
• For INFO/SV_TOP_TIER > 2 variants require split or paired reads support of at least 5x
• For INFO/SV_TOP_TIER > 2 variants with low allele frequency at any breakpoint (BPI_AF[0 or 1] < 0.1), require SR or PR support of at least 10x
• Output: work/{batch}/structural/filt/{batch}-manta.vcf

Step 3: PURPLE and FFPE conditional

• If the sample is not FFPE:
  • Feed above filtered SVs to PURPLE, which outputs purple.sv.vcf.gz that contains rescued SVs
  • Prioritise variants (again)
  • Remove ‘INFO/ANN’ annotation
  • Output: {batch}/structural/{batch}-manta.vcf.gz
• If the sample is FFPE:
  • Just copy filtered variants and don’t do anything (i.e. we don’t want the rescued SVs from PURPLE since they’ll likely be heaps) (note that PURPLE will still get fed with the filtered SVs)
  • Output: {batch}/structural/{batch}-manta.vcf.gz

Step 4: TSV final output

• Input: {batch}/structural/{batch}-manta.vcf.gz VCF
• Output: {batch}/structural/{batch}-manta.tsv TSV

Description of Manta TSV columns

Column	Description
AF_BPI	INFO/BPI_AF: AF at each breakpoint (so AF_BPI1,AF_BPI2)
AF_PURPLE	INFO/PURPLE_AF: AF at each breakend (purity adjusted) (so AF_PURPLE1,AF_PURPLE2)
annotation	INFO/SIMPLE_ANN: Simplified structural variant annotation: ‘SVTYPE | EFFECT | GENE(s) | TRANSCRIPT | PRIORITY (1-4)’
caller	Manta SV caller
chrom	CHROM column in VCF
CN_change_PURPLE	INFO/PURPLE_CN_CHANGE: change in CN at each breakend (purity adjusted) (so CN_change_PURPLE1,CN_change_PURPLE2)
CN_PURPLE	INFO/PURPLE_CN: CN at each breakend (purity adjusted) (so CN_PURPLE1,CN_PURPLE2)
end	INFO/END: End position of the variant described in this record
END_BPI	INFO/BPI_END: BPI adjusted breakend location
ID	ID column in VCF
MATEID	INFO/MATEID: ID of mate breakend
paired_support_PE	FORMAT/PE of tumor sample: ??
paired_support_PR	FORMAT/PR of tumor sample: Spanning paired-read support for the ref and alt alleles in the order listed, for reads where P(allele|read)>0.999
Ploidy_PURPLE	INFO/PURPLE_PLOIDY: Ploidy of variant (purity adjusted)
PURPLE_status	INFERRED if FILTER=INFERRED, or RECOVERED if has INFO/RECOVERED, else blank. INFERRED: Breakend inferred from copy number transition
sample	Tumor sample name
somaticscore	INFO/SOMATICSCORE: Somatic variant quality score
split_read_support	FORMAT/SR of tumor sample: Split reads for the ref and alt alleles in the order listed, for reads where P(allele|read)>0.999
start	POS column in VCF
START_BPI	INFO/BPI_START: BPI adjusted breakend location
svtype	INFO/SVTYPE: Type of structural variant
tier	INFO/SV_TOP_TIER (or 4 if missing): Highest priority tier for the effects of a variant entry

 

Prioritisation process

1. Annotate with SnpEff based on Ensembl gene model
2. Subset annotations to APPRIS principal transcripts
3. Prioritize variants with simple_sv_annotation 1(high)-2(moderate)-3(low)-4(no interest):

• exon loss

  • on prioritisation gene list (1)
  • other (2)

• gene_fusion

  • paired (hits two genes)
    • on list of known pairs (1) (curated by HMF)
    • one gene is a known promiscuous fusion gene (1) (curated by HMF)
    • on list of FusionCatcher known pairs (2)
    • other:
      • one or two genes on prioritisation gene list (2)
      • neither gene on prioritisation gene list (3)
  • unpaired (hits one gene)
    • on prioritisation gene list (2)
    • others (3)

• upstream or downstream

  • on prioritisation gene list genes (2) - e.g. one gene is got into control of another gene’s promoter and get overexpressed (oncogene) or underexpressed (tsgene)

• LoF or HIGH impact in a tumor suppressor

  • on prioritisation gene list (2)
  • other TS gene (3)

• other (4)

• Use PURPLE copy number caller to infer more SV calls from copy number transitions (marked as ‘PURPLE Inferred’)

name	abbreviation
3_prime_UTR_truncation	3UTRtrunc
3_prime_UTR_variant	3UTRvar
5_prime_UTR_truncation	5UTRtrunc
5_prime_UTR_variant	5UTRvar
bidirectional_gene_fusion	BidFusG
chromosome_number_variation	ChromNumV
conservative_inframe_deletion	ConsInframeDel
feature_ablation	DelG
transcript_ablation	DelTx
downstream_gene_variant	DnstreamGV
duplication	Dup
exon_loss_variant	ExonLossV
frameshift_variant	FrameshiftV
feature_fusion	Fus
gene_fusion	FusG
intergenic_region	IntergenReg
intragenic_variant	IntragenV
intron_variant	IntronV
no_func_effect	NoFuncEff
non_coding_transcript_variant	NoncodTxV
no_prio_effect	NoPrioEff
splice_acceptor_variant	SpliceAccV
splice_donor_variant	SpliceDonV
splice_region_variant	SpliceRegV
start_lost	StartLoss
stop_gained	StopGain
stop_lost	StopLoss
TFBS_ablation	TFBSDel
TF_binding_site_variant	TFBSVar
upstream_gene_variant	UpstreamGV

 

Summary

SV type by top tier before breaking down by annotation BND DEL DUP INS Sum 1 0 0 1 0 1 2 20 27 35 0 82 3 4 27 11 1 43 4 184 321 158 18 681 Sum 208 375 205 19 807

SV type by individual tier after breaking down by annotation BND DEL DUP INS Sum 1 0 0 1 0 1 2 26 117 43 0 186 3 6 257 222 1 486 4 219 8445 6522 20 15206 Sum 251 8819 6788 21 15879

Unmelted Variants

Description

Column	Description
varnum	Original event row number that connects variants to events
TierTop	Top priority of the event (from ‘simple_sv_annotation’: 1 highest, 4 lowest)
Chr	Chromosome
Start	Start position as inferred by BPI (for PURPLE-inferred SVs we use POS)
End	End position. For BNDs this has been assigned to the Chr:Start of the BND’s mate for convenience. Values are inferred by BPI (PURPLE-inferred SVs don’t have an End).
Type	Type of structural variant
ID	ID of BND from Manta (or PURPLE for PURPLE-inferred SVs))
MATEID	ID of BND mate from Manta
BND_ID	ID of BND pair simplified. BNDs with the same BND_ID belong to the same translocation event
BND_mate	‘A’ or ‘B’ depending on if it’s the first or second mate in the BND pair
SR_PR_alt	Number of Split Reads and Paired Reads supporting the alt allele, for reads where P(allele|read)>0.999
SR_PR_ref	Number of Split Reads and Paired Reads supporting the ref allele, for reads where P(allele|read)>0.999
Ploidy	Ploidy of variant from PURPLE (purity adjusted)
AF_PURPLE	PURPLE AF at each breakend preceded by their average
AF_BPI	BPI AF at each breakend preceded by their average
CNC	Copy Number Change at each breakend preceded by their average
CN	Copy Number at each breakend preceded by their average
SScore	Somatic variant quality score
nann	Number of annotations for given event

Translocations (BNDs)

Main Columns

Description

Column	Description
nrow	Row number that connects variants between tables in same tab set
varnum	Original event row number that connects variants to events
Tier	Priority of the specific event (from ‘simple_sv_annotation’: 1 highest, 4 lowest)
Chr	Chromosome
Start	Start position as inferred by BPI (for PURPLE-inferred SVs we use POS)
End	End position. For BNDs this has been assigned to the Chr:Start of the BND’s mate for convenience. Values are inferred by BPI (PURPLE-inferred SVs don’t have an End).
ID	ID of BND from Manta (or PURPLE for PURPLE-inferred SVs))
BND_ID	ID of BND pair simplified. BNDs with the same BND_ID belong to the same translocation event
BND_mate	‘A’ or ‘B’ depending on if it’s the first or second mate in the BND pair
Genes	Genes involved in the event. DEL/DUP/INS events involving more than 2 genes are shown in separate table.
Effect	SV effect (based on SnpEff Effect Sequence Ontology - abbreviations are shown under Details in the Effects table
Detail	Prioritisation detail (from ‘simple_sv_annotation’)
SR_PR_alt	Number of Split Reads and Paired Reads supporting the alt allele, for reads where P(allele|read)>0.999
Ploidy	Ploidy of variant from PURPLE (purity adjusted)
AF_PURPLE	PURPLE AF at each breakend preceded by their average

Other Columns

Description

Column	Description
nrow	Row number that connects variants between tables in same tab set
AF_BPI	BPI AF at each breakend preceded by their average
CNC	Copy Number Change at each breakend preceded by their average
CN	Copy Number at each breakend preceded by their average
SR_PR_ref	Number of Split Reads and Paired Reads supporting the ref allele, for reads where P(allele|read)>0.999
SScore	Somatic variant quality score
ntrx	Number of transcripts for given event
Transcript	Transcripts involved in the event. DEL/DUP/INS events involving more than 2 transcripts are shown in separate table.

PURPLE Inferred

Description

Column	Description
Tier	Priority of the specific event (from ‘simple_sv_annotation’: 1 highest, 4 lowest)
Chr	Chromosome
Start	Start position as inferred by BPI (for PURPLE-inferred SVs we use POS)
Effect	SV effect (based on SnpEff Effect Sequence Ontology - abbreviations are shown under Details in the Effects table
Detail	Prioritisation detail (from ‘simple_sv_annotation’)
Ploidy	Ploidy of variant from PURPLE (purity adjusted)
CN	Copy Number at each breakend preceded by their average
CNC	Copy Number Change at each breakend preceded by their average
ID	ID of BND from Manta (or PURPLE for PURPLE-inferred SVs))

DEL/DUP/INS

Main Columns

Description

Column	Description
nrow	Row number that connects variants between tables in same tab set
varnum	Original event row number that connects variants to events
TierTop	Top priority of the event (from ‘simple_sv_annotation’: 1 highest, 4 lowest)
Tier	Priority of the specific event (from ‘simple_sv_annotation’: 1 highest, 4 lowest)
Type	Type of structural variant
Chr	Chromosome
Start	Start position as inferred by BPI (for PURPLE-inferred SVs we use POS)
End	End position. For BNDs this has been assigned to the Chr:Start of the BND’s mate for convenience. Values are inferred by BPI (PURPLE-inferred SVs don’t have an End).
Effect	SV effect (based on SnpEff Effect Sequence Ontology - abbreviations are shown under Details in the Effects table
Genes	Genes involved in the event. DEL/DUP/INS events involving more than 2 genes are shown in separate table.
Transcript	Transcripts involved in the event. DEL/DUP/INS events involving more than 2 transcripts are shown in separate table.
Detail	Prioritisation detail (from ‘simple_sv_annotation’)
SR_PR_alt	Number of Split Reads and Paired Reads supporting the alt allele, for reads where P(allele|read)>0.999
AF_PURPLE	PURPLE AF at each breakend preceded by their average

Other Columns

Description

Column	Description
varnum	Original event row number that connects variants to events
Ploidy	Ploidy of variant from PURPLE (purity adjusted)
AF_BPI	BPI AF at each breakend preceded by their average
CNC	Copy Number Change at each breakend preceded by their average
CN	Copy Number at each breakend preceded by their average
SR_PR_ref	Number of Split Reads and Paired Reads supporting the ref allele, for reads where P(allele|read)>0.999
SScore	Somatic variant quality score

Many Genes

Description

Column	Description
nrow	Row number that connects variants between tables in same tab set
varnum	Original event row number that connects variants to events
Tier	Priority of the specific event (from ‘simple_sv_annotation’: 1 highest, 4 lowest)
Type	Type of structural variant
Chr	Chromosome
Start	Start position as inferred by BPI (for PURPLE-inferred SVs we use POS)
End	End position. For BNDs this has been assigned to the Chr:Start of the BND’s mate for convenience. Values are inferred by BPI (PURPLE-inferred SVs don’t have an End).
Effect	SV effect (based on SnpEff Effect Sequence Ontology - abbreviations are shown under Details in the Effects table
ngen	Number of genes for given event
Genes	Genes involved in the event. DEL/DUP/INS events involving more than 2 genes are shown in separate table.

Many Transcripts

Description

Column	Description
nrow	Row number that connects variants between tables in same tab set
varnum	Original event row number that connects variants to events
Tier	Priority of the specific event (from ‘simple_sv_annotation’: 1 highest, 4 lowest)
Type	Type of structural variant
Chr	Chromosome
Start	Start position as inferred by BPI (for PURPLE-inferred SVs we use POS)
End	End position. For BNDs this has been assigned to the Chr:Start of the BND’s mate for convenience. Values are inferred by BPI (PURPLE-inferred SVs don’t have an End).
Effect	SV effect (based on SnpEff Effect Sequence Ontology - abbreviations are shown under Details in the Effects table
ntrx	Number of transcripts for given event
Transcript	Transcripts involved in the event. DEL/DUP/INS events involving more than 2 transcripts are shown in separate table.

Copy Number Variants

The purity and ploidy estimator PURPLE is used to generate a copy number profile for the somatic sample.

QC, Purity and Ploidy Summary

PURPLE outputs a QC status along with a summary for the inferred purity and ploidy of the somatic sample. A failed QC status can be attributed to several factors (see Description below).

Description

QC Status

The QC Status field reflects how we have determined the purity of the sample:

• NORMAL - PURPLE fit the purity using COBALT and AMBER output.
• HIGHLY_DIPLOID - The fitted purity solution is highly diploid (> 95%) with a large range of potential solutions, but somatic variants are unable to help either because they were not supplied or because their implied purity was too low.
• SOMATIC - Somatic variants have improved the otherwise highly diploid solution.
• NO_TUMOR - PURPLE failed to find any aneuploidy and somatic variants were supplied but there were fewer than 300 with observed VAF > 0.1.

QC Failure

There are several reasons PURPLE may classify a sample as failed:

• FAIL_SEGMENT: more than 220 copy number segments not supported at either end by SV breakpoints. Indicates samples with extreme GC bias, with differences in depth of >= 10x between high and low GC regions. GC normalisation is unreliable when the corrections are so extreme so it is recommended to fail the sample (concerns with miscalled deletions or amplifications or have poor sensitivity in high GC regions.
• NO_TUMOR: no aneuploidy found and the number of somatic SNVs found is less than 1,000
• MIN_PURITY: fitted purity < 20%
• FAIL_DELETED_GENES: more than 280 deleted genes. This QC step was added after observing that in a handful of samples with high MB scale positive GC bias we sometimes systematically underestimate the copy number in high GC regions. This can lead us to incorrectly infer homozygous loss of entire chromosomes, particularly on chromosomes 17 and 19.
• FAIL_GENDER: if the AMBER and COBALT inferred genders are inconsistent then the COBALT one is used but the sample is failed.

 

Variable	value	details
QC_Status	PASS
Purity	0.43 (0.41-0.79)	Purity of tumor in the sample (and min-max with score within 10% of best)
Ploidy	2.911 (2.851-4.917)	Average ploidy of tumor sample after adjusting for purity (and min-max with score within 10% of best)
Gender	MALE
WGD	true	Whole genome duplication
MSI (indels/Mb)	MSS (0.135)	MSI status (MSI, MSS or UNKNOWN if somatic variants not supplied) & MS Indels per Mb
Polyclonal Prop	0.287	Proportion of CN regions that are more than 0.25 from a whole copy number
Diploidy Prop	0.015 (0.001-0.015)	Proportion of CN regions that have 1 (+- 0.2) minor and major allele
Segment_Pass	TRUE	Score: 15; Unsupported: 15
Gender_Pass	TRUE	Amber: MALE; Cobalt: MALE
DelGenes_Pass	TRUE	count: 77
TMB	12.714 (HIGH)	Tumor mutational burden per mega base (Status: ‘HIGH’, ‘LOW’ or ‘UNKNOWN’ if somatic variants not supplied)
TML	0 (LOW)	Tumor mutational load (Status: ‘HIGH’, ‘LOW’ or ‘UNKNOWN’ if somatic variants not supplied)

UMCCR Gene CNV Calls

Description

PURPLE copy number alterations in the UMCCR Cancer Gene panel (~1,200 genes) - description is from https://github.com/hartwigmedical/hmftools/blob/master/purity-ploidy-estimator/README.md#gene-copy-number-file

Column	Description
gene	Name of gene
minCN/maxCN	Min/Max copy number found in gene exons
chrom/start/end	Chromosome/start/end location of gene transcript
chrBand	Chromosome band of the gene
onco_or_ts	oncogene (‘oncogene’), tumor suppressor (‘tsgene’), or both (‘onco+ts’), as reported by Cancermine
transcriptID	Ensembl transcript ID (dot version)
minMinorAllelePloidy	Minimum allele ploidy found over the gene exons - useful for identifying LOH events
somReg (somaticRegions)	Count of somatic copy number regions this gene spans
germDelReg (germlineHomDeletionRegions / germlineHetToHomDeletionRegions)	Number of regions spanned by this gene that are (homozygously deleted in the germline / both heterozygously deleted in the germline and homozygously deleted in the tumor)
minReg (minRegions)	Number of somatic regions inside the gene that share the min copy number
minRegStartEnd	Start/End base of the copy number region overlapping the gene with the minimum copy number
minRegSupportStartEndMethod	Start/end support of the CN region overlapping the gene with the min CN (plus determination method)

 

Genome-wide CNV Segments

Description

PURPLE outputs a file with the copy number profile of all contiguous segments of the tumor sample:

PURPLE copy number profile of all (contiguous) segments of the tumor sample - description is from https://github.com/hartwigmedical/hmftools/blob/master/purity-ploidy-estimator/README.md#copy-number-file

Column	Description
Chr/Start/End	Coordinates of copy number segment
CN	Fitted absolute copy number of segment adjusted for purity and ploidy
Ploidy Min+Maj	Ploidy of minor + major allele adjusted for purity
BAF	Tumor BAF after adjusted for purity and ploidy
BafCount	Count of AMBER baf points covered by this segment
Start/End SegSupport	Type of SV support for the CN breakpoint at start/end of region. Allowed values: CENTROMERE, TELOMERE, INV, DEL, DUP, BND (translocation), SGL (single breakend SV support), NONE (no SV support for CN breakpoint), MULT (multiple SV support at exact breakpoint)
Method	Method used to determine the CN of the region. Allowed values: BAF_WEIGHTED (avg of all depth windows for the region), STRUCTURAL_VARIANT (inferred using ploidy of flanking SVs), LONG_ARM (inferred from the long arm), GERMLINE_AMPLIFICATION (inferred using special logic to handle regions of germline amplification)
windowCount	Count of COBALT windows covered by this segment
GC	Proportion of segment that is G or C

 

PURPLE Charts

PURPLE generates charts for summarising tumor sample characteristics. Description is from the PURPLE docs.

Copy number / Minor allele ploidy

The following figures show the AMBER BAF count weighted distribution of copy number and minor allele ploidy throughout the fitted segments. Copy numbers are broken down by colour into their respective minor allele ploidy (MAP) while the minor allele ploidy figure is broken down by copy number.

Rainfall

If a somatic variant VCF has been supplied, a figure will be produced showing the somatic variant ploidy broken down by copy number as well as a rainfall plot with kataegis clusters highlighted in grey.

Purity/ploidy

The following ‘sunrise’ chart shows the range of scores of all examined solutions of purity and ploidy. Crosshairs identify the best purity / ploidy solution.

Clonality

The following diagram illustrates the clonality model of a typical sample.

The top figure shows the histogram of somatic ploidy for all SNVs and INDELs in blue. Superimposed are peaks in different colours fitted from the sample as described in the docs while the black line shows the overall fitted ploidy distribution. Red filled peaks are below the 0.85 subclonal threshold.

We can determine the likelihood of a variant being subclonal at any given ploidy as shown in the bottom half of the figure.

Segment

The contribution of each fitted segment to the final score of the best fit is shown in the following figure. Each segment is divided into its major and minor allele ploidy. The area of each circle shows the weight (AMBER baf count) of each segment.

Oncoviruses

Oncoviruses and their integration sites. Viral sequences are obtained from the GDC database. Host genes are reported if the integration site falls on a gene or at least before 100kbp of the gene start.

## No oncoviral content detected in this sample.

Addendum

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Conda Pkgs Main

name	version	build	channel	envs
umccrise	1.0.0	dev_0	<develop>	NA
snakemake	5.17.0	dev_0	<develop>	NA
reference-data	1.0.3	dev_0	<develop>	NA
r-base	3.5.1	hc461eb7_1012	conda-forge	_pcgr, _cancer_report
r-base	3.6.3	h316533a_2	conda-forge	_hmf
python	3.7.3	h357f687_2	conda-forge	NA, _pcgr, _hmf
python	3.8.2	he5300dc_7_cpython	conda-forge	_cancer_report
pcgr	0.8.4.10	py37r35_0	pcgr	_pcgr
pandocfilters	1.4.2	py37_1	NA	NA
pandoc	2.9.2.1	0	conda-forge	NA, _pcgr, _hmf, _cancer_report
ngs-utils	2.6.2	dev_0	<develop>	NA
ngs_utils	2.5.6	py37_0	vladsaveliev	_pcgr
multiqc-bcbio	0.2.8	pypi_0	pypi	NA
multiqc	1.9.dev0	dev_0	<develop>	NA
htslib	1.10.2	h78d89cc_0	bioconda	NA, _hmf
htslib	1.9	h244ad75_9	bioconda	_pcgr
hmftools-sage	1.0	0	bioconda	_hmf
hmftools-purple	2.40	0	bioconda	_hmf
hmftools-linx	1.7	0	bioconda	_hmf
hmftools-cobalt	1.8	0	bioconda	_hmf
hmftools-amber	3.2	0	bioconda	_hmf
gridss	2.8.3	0	bioconda	_hmf
cpsr	0.5.2.6	0	pcgr	_pcgr
conpair	0.2	pypi_0	pypi	NA
cacao	0.2.1.2	0	pcgr	_pcgr

Report Inputs

key	value
title	Cancer Report for Sample
tumor_name	SEQC-II_Tumor_50pc
batch_name	SEQC-II-50pc__SEQC-II_Tumor_50pc
genome_build	hg38
key_genes	/g/data/gx8/extras/vlad/synced/NGS_Utils/ngs_utils/reference_data/key_genes/umccr_cancer_genes.latest.tsv
af_global	/g/data/gx8/extras/vlad/umccrise_tests/Jun14_SEQC2/work/SEQC-II-50pc__SEQC-II_Tumor_50pc/rmd/afs/af_tumor.txt
af_keygenes	/g/data/gx8/extras/vlad/umccrise_tests/Jun14_SEQC2/work/SEQC-II-50pc__SEQC-II_Tumor_50pc/rmd/afs/af_tumor_keygenes.txt
somatic_snv	/g/data/gx8/extras/vlad/umccrise_tests/Jun14_SEQC2/work/SEQC-II-50pc__SEQC-II_Tumor_50pc/rmd/somatic-with_chr_prefix.vcf
somatic_sv	/g/data/gx8/extras/vlad/umccrise_tests/Jun14_SEQC2/SEQC-II-50pc__SEQC-II_Tumor_50pc/structural/SEQC-II-50pc__SEQC-II_Tumor_50pc-manta.tsv
purple_gene_cnv	/g/data/gx8/extras/vlad/umccrise_tests/Jun14_SEQC2/work/SEQC-II-50pc__SEQC-II_Tumor_50pc/purple/SEQC-II-50pc__SEQC-II_Tumor_50pc.purple.cnv.gene.tsv
purple_cnv	/g/data/gx8/extras/vlad/umccrise_tests/Jun14_SEQC2/work/SEQC-II-50pc__SEQC-II_Tumor_50pc/purple/SEQC-II-50pc__SEQC-II_Tumor_50pc.purple.cnv.somatic.tsv
purple_purity	/g/data/gx8/extras/vlad/umccrise_tests/Jun14_SEQC2/work/SEQC-II-50pc__SEQC-II_Tumor_50pc/purple/SEQC-II-50pc__SEQC-II_Tumor_50pc.purple.purity.tsv
purple_qc	/g/data/gx8/extras/vlad/umccrise_tests/Jun14_SEQC2/work/SEQC-II-50pc__SEQC-II_Tumor_50pc/purple/SEQC-II-50pc__SEQC-II_Tumor_50pc.purple.qc
oncoviral_present_viruses	/g/data/gx8/extras/vlad/umccrise_tests/Jun14_SEQC2/work/SEQC-II-50pc__SEQC-II_Tumor_50pc/oncoviruses/present_viruses.txt
oncoviral_breakpoints_tsv
conda_list	/g/data/gx8/extras/vlad/umccrise_tests/Jun14_SEQC2/work/conda_pkg_list.txt

Conda Pkgs All