The PCGR software comes with a range of options to configure the analyses performed and to customize the output report.
Key settings
Below, we will outline key settings that are important with respect to the sequencing assay that has been conducted.
Whole-genome, whole-exome or targeted sequencing assay
By default, PCGR expects that the input VCF comes from whole-exome
sequencing. This can be adjusted with the assay option,
which takes three alternative values:
--assay <WGS|WES|TARGETED>
If the input VCF comes from a targeted sequencing assay/panel
(i.e. --assay TARGETED), the target size of the assay/panel
should be adjusted accordingly, which is critical for tumor mutational
burden estimation. Assay target size, reflecting the protein-coding
portion of the assayed genomic region in megabases, can be
configured through the following option:
--effective_target_size_mb <value>
Ideally, this should reflect the callable target size of the assay, i.e. the size of the target regions for which coding variants is sufficiently covered (i.e. with a certain sequencing depth) by the sequencing assay. This can be estimated by the user based on the design of the sequencing assay, or by using tools such as mosdepth.
Tumor-control vs. tumor-only
The sequencing mode determines the theme color used throughout the HTML report — in the top banner and all value boxes:
| Tumor-control |
Default mode — matched tumor/normal sequencing (#9B3297)
|
| Tumor-only |
Enabled with –tumor_only (#0073C2)
|
By default, PCGR expects that the input VCF contains somatic variants identified from a tumor-control sequencing setup. This implies that the VCF contains information with respect to variant allelic depth/support both for the tumor sample and the corresponding control sample.
If the input VCF comes from a tumor-only assay, turn
on the --tumor_only option. In this mode, PCGR conducts a
set of successive filtering steps on the raw input set of variants,
aiming to exclude the majority of germline variants from the tumor-only
input set. In addition to default filtering applied against variants
found in the gnomAD database (population-specific minor allele frequency
thresholds can be configured, see below), additional filtering
procedures can be explicitly set, i.e.:
--exclude_dbsnp_nonsomatic--exclude_likely_het_germline--exclude_likely_hom_germline--exclude_clinvar_germline--exclude_nonexonic
Users should note that these filters may occasionally remove true somatic variants, and should thus be used with caution.
If the user has provided a panel-of-normals VCF file as
input(--pon_vcf), one may also opt to remove variants found
in that variant collection using a dedicated option:
--exclude_pon
IMPORTANT NOTE 1: A number of the analyses available in PCGR are not particularly well-suited for tumor-only input, e.g. mutational signature analysis and MSI status prediction.
IMPORTANT NOTE 2: If you run PCGR on tumor-only WGS assays, we strongly recommend that you pre-filter/reduce the size of your input VCF somewhat, since we have encountered that a huge unfiltered variant set from such assays may slow down PCGR considerably and potentially make it crash. See also this issue.
Sample properties
A few selected properties of the tumor sample that should be determined prior to PCGR analysis can be provided
--tumor_ploidy <value>--tumor_purity <value>
If not user-provided, PCGR will attempt to estimate ploidy from the
copy number segments (if provided) using a weighted median approach. If
copy number segments are not provided, these properties will be set to
NA in the report.
Tumor site
The primary tissue/site of the tumor sample that is analyzed can and should be be provided, through the following option:
--tumor_site <value>
This option takes a value between 0 and 30, reflecting the main primary sites/tissues for human cancers. This information is used e.g. to discriminate between on and off-label targeted therapies from the actionable biomarkers detected in the sample. Note that the default value is 0 (implies Any tissue/site) - only pan-cancer biomarkers will be considered for Tier I assignment, and all tumor-specific biomarkers will be considered as non-matching site evidence for Tier II/III assignment.
The following lists the possible encodings, and the corresponding primary tissues/sites:
0 = Any
1 = Adrenal Gland
2 = Ampulla of Vater
3 = Biliary Tract
4 = Bladder/Urinary Tract
5 = Bone
6 = Breast
7 = Cervix
8 = CNS/Brain
9 = Colon/Rectum
10 = Esophagus/Stomach
11 = Eye
12 = Head and Neck
13 = Kidney
14 = Liver
15 = Lung
16 = Lymphoid
17 = Myeloid
18 = Ovary/Fallopian Tube
19 = Pancreas
20 = Peripheral Nervous System
21 = Peritoneum
22 = Pleura
23 = Prostate
24 = Skin
25 = Soft Tissue
26 = Testis
27 = Thymus
28 = Thyroid
29 = Uterus
30 = Vulva/Vagina
(default: 0 - any tumor type)If you want to check the nature of cancer subtypes attributed to each of the primary tissue/sites, take a look at the table with phenotype terms and associated primary sites.
Allelic support
Proper designation of INFO tags in the input VCF that denote variant depth/allelic fraction is critical to make the report as comprehensive as possible. See the input section on how to accomplish this.
Several options are used to inform PCGR about tags in the VCF INFO field that encodes this information:
--tumor_dp_tag <value>--tumor_af_tag <value>--control_dp_tag <value>--control_af_tag <value>
If these tags are set correctly, one may set thresholds (sequencing depth and/or allelic depth/fraction) on the variants to be included in the report, i.e. through:
--tumor_dp_min <value>--tumor_af_min <value>--tumor_ad_min <value>--control_dp_min <value>--control_af_max <value>--control_ad_max <value>
The allelic depth thresholds refer to the minimum number of
reads supporting the alternate allele in the tumor sample
(--tumor_ad_min), and the maximum number of reads
supporting the alternate allele in the control sample
(--control_ad_max).
Tumor mutational burden (TMB)
If tags for allelic support is provided in the VCF and configured by the user, users can configure the TMB calculation by setting minimum requirements for sequencing coverage and allelic fraction, i.e.:
--tmb_dp_min <value>--tmb_af_min <value>
Large input sets (VCF)
For input VCF files with > 500,000 variants, note that these will be subject to filtering prior to the final step in PCGR (step 4: reporting). For such scenarios, raw input sets will be filtered according to consequence type, in the sense that intergenic/intronic/upstream/downstream gene variants will be excluded prior to reporting. This is a necessary step to avoid memory issues etc. during processing with the PCGR R package.
If you have a large input VCF, and have sufficient memory capacity on
your compute platform, we also recommend to increase the VEP
buffer size (option --vep_buffer_size), as this will
speed up the VEP processing significantly.
Somatic copy number variant class thresholds
When copy number segments are provided (--input_cna),
PCGR classifies each segment as an amplification, gain, heterozygous
deletion, or homozygous deletion based on configurable thresholds. The
thresholding strategy is controlled by:
-
--cna_threshold_mode <absolute|relative|combined>(default:absolute)
Three modes are supported:
-
absolute — thresholds are expressed as total copy
numbers (integer values). A segment is classified based on its total
copy number (
nMajor + nMinor), irrespective of tumor ploidy. -
relative — thresholds are expressed as fold-change
over the estimated tumor ploidy. If
--tumor_ploidyis not provided explicitly by the user, PCGR will auto-estimate the ploidy from the copy number segments using a genome-wide weighted median approach. - combined — a segment must satisfy both the absolute and relative threshold criteria to be assigned a given class. This is the most conservative mode.
The per-class thresholds that can be configured are:
| Class | Absolute option | Default | Relative option | Default |
|---|---|---|---|---|
| Amplification | --cna_amp_threshold_absolute |
Total CN ≥ 5 | --cna_amp_threshold_relative |
≥ 2.5× ploidy |
| Gain | --cna_gain_threshold_absolute |
Total CN ≥ 3 | --cna_gain_threshold_relative |
≥ 1.5× ploidy |
| Heterozygous deletion | --cna_del_threshold_absolute |
Total CN ≤ 1 | --cna_del_threshold_relative |
≤ 0.5× ploidy |
Segments with total copy number of zero are always classified as homozygous deletions, regardless of the threshold mode.
An additional option controls which genes are considered affected by a CNA event:
-
--cna_transcript_overlap_pct <value>— minimum mean percent overlap between the copy number segment and gene transcripts required to report a gene as affected (default: 50)
OncoKB biomarker integration
PCGR can optionally query the OncoKB precision oncology knowledge base to annotate SNVs/InDels, copy number alterations and fusions with functional annotations and clinical actionability evidence. To enable this, provide a valid OncoKB API token:
--oncokb_api_token <ONCOKB_API_TOKEN>
OncoKB annotation requires that you run PCGR in an open environment - with access to the internet.
To specify the tumor type for OncoKB queries, provide the relevant OncoTree code:
-
--oncokb_oncotree_code <CODE>(e.g.COADfor colon adenocarcinoma)
If no OncoTree code is provided, PCGR will map the primary tumor site to its corresponding OncoTree code based on a predefined mapping. If the tumor site is set to “Any” (code 0), OncoKB queries will be performed without specifying a tumor type.
By default, PCGR integrates biomarker evidence from multiple knowledge sources (CIViC, CGI, OncoKB). If you want to limit biomarker reporting to OncoKB only and skip CIViC and CGI, use:
--oncokb_exclusive
Licensing notice — OncoKB terms of use: OncoKB is freely accessible for non-commercial research use. However, use of OncoKB data for commercial purposes or for patient care in a hospital or clinical setting — including the generation of PCGR reports used to inform diagnostic or therapeutic decisions — requires a separate commercial license from Memorial Sloan Kettering Cancer Center. Users are solely responsible for ensuring that their use of OncoKB through PCGR complies with the OncoKB Terms of Use. If in doubt, contact the OncoKB team at contact@oncokb.org before use.
RNA fusions
If RNA fusion data is available for the tumor sample, it can be provided via:
--input_rna_fusion <FILE>
PCGR will cross-reference the detected fusions against curated cancer gene databases and known fusion events. A minimum split-read support threshold can be configured to filter low-confidence fusions:
-
--fusion_min_split_reads <value>(default: 3, minimum: 2)
See the input section for details on the required file format.
Configuration of output files
If you only want the Excel/TSV output (with all variant
classifications and auxiliary analyses (e.g. MSI classifications, TMB
estimates, mutational signatures predictions) of PCGR, you may turn off
the HTML output by using the --no_html option. This will
speed up the analysis, and could be a useful option if you foresee that
the sample input datasets are too large for the HTML report generation
to work properly.
If you only want the annotated VCF (also converted to TSV), use the
option --no_reporting. This will skip the final steps of
the PCGR workflow, and only generate the annotated VCF and TSV
files.
All options
A tumor sample report is generated by running the pcgr command, which takes the following arguments and options:
usage:
pcgr -h [options]
[--input_vcf <INPUT_VCF>]
[--input_cna <INPUT_CNA>]
[--input_rna_fusion <INPUT_RNA_FUSION>]
[--input_rna_expression <INPUT_RNA_EXPRESSION>]
[--vep_dir <VEP_DIR>]
--refdata_dir <REFDATA_DIR>
--output_dir <OUTPUT_DIR>
--genome_assembly <GENOME_ASSEMBLY>
--sample_id <SAMPLE_ID>
Personal Cancer Genome Reporter (PCGR) workflow for clinical translation of tumor omics data
(SNVs/InDels, CNA, RNA expression, RNA fusions)
Required arguments:
--refdata_dir REFDATA_DIR
Directory where PCGR reference data bundle was downloaded and unpacked
--output_dir OUTPUT_DIR
Output directory
--genome_assembly {grch37,grch38}
Human genome assembly build: grch37 or grch38
--sample_id SAMPLE_ID
Tumor sample/cancer genome identifier - prefix for output files
Input file options:
--input_vcf INPUT_VCF
VCF input file with somatic variants in tumor sample, SNVs/InDels
--input_cna INPUT_CNA
Somatic copy number alteration segments (tab-separated values)
--input_rna_fusion INPUT_RNA_FUSION
File with RNA fusion transcripts detected in tumor (tab-separated values)
--input_rna_expression INPUT_RNA_EXP
File with bulk RNA expression counts (TPM) of transcripts in tumor (tab-separated values)
SNV/InDel analysis options:
--vep_dir VEP_DIR Directory of VEP cache, e.g. $HOME/.vep (required when --input_vcf is provided)
--assay {WGS,WES,TARGETED}
Type of DNA sequencing assay performed for input data (VCF), default: WES
--effective_target_size_mb EFFECTIVE_TARGET_SIZE_MB
Effective target size in Mb (potentially limited by read depth) of sequencing
assay (for TMB analysis) (default: 34 (WES/WGS))
--tumor_only Input VCF comes from tumor-only sequencing, calls will be filtered for variants
of germline origin (default: False)
--vcfanno_n_proc VCFANNO_N_PROC
Number of vcfanno processes (option '-p' in vcfanno), default: 4
--retained_info_tags RETAINED_INFO_TAGS
Comma-separated string of VCF INFO tags from query VCF to keep in PCGR output TSV
--ignore_noncoding Ignore non-coding (i.e. non protein-altering) variants in report, default: False
--vep_n_forks VEP_N_FORKS
Number of forks (VEP option '--fork'), default: 4
--vep_buffer_size VEP_BUFFER_SIZE
Variant buffer size (variants read into memory simultaneously, VEP option
'--buffer_size') - set lower to reduce memory usage, default: 500
--vep_pick_order VEP_PICK_ORDER
Comma-separated string of ordered transcript/variant properties for selection of
primary variant consequence (option '--pick_order' in VEP), default:
mane_select,mane_plus_clinical,canonical,biotype,ccds,rank,tsl,appris,length
--vep_no_intergenic Skip intergenic variants during variant annotation (VEP option '--no_intergenic'),
default: False
--vep_regulatory Add VEP regulatory annotations (VEP option '--regulatory'), default: False
--vep_gencode_basic Consider basic GENCODE transcript set only (VEP option '--gencode_basic')
Tumor sample options:
--sex {FEMALE,MALE,UNKNOWN}
Sex of cancer case/sample (default: UNKNOWN)
--tumor_site TSITE Optional integer code to specify primary tumor type/site of query sample,
choose any of the following identifiers:
0 = Any
1 = Adrenal Gland
2 = Ampulla of Vater
3 = Biliary Tract
4 = Bladder/Urinary Tract
5 = Bone
6 = Breast
7 = Cervix
8 = CNS/Brain
9 = Colon/Rectum
10 = Esophagus/Stomach
11 = Eye
12 = Head and Neck
13 = Kidney
14 = Liver
15 = Lung
16 = Lymphoid
17 = Myeloid
18 = Ovary/Fallopian Tube
19 = Pancreas
20 = Peripheral Nervous System
21 = Peritoneum
22 = Pleura
23 = Prostate
24 = Skin
25 = Soft Tissue
26 = Testis
27 = Thymus
28 = Thyroid
29 = Uterus
30 = Vulva/Vagina
(default: 0 - any tumor type)
--tumor_purity TUMOR_PURITY
Estimated tumor purity (between 0 and 1) (default: None)
--tumor_ploidy TUMOR_PLOIDY
Estimated tumor ploidy (default: None)
Allelic support options:
--tumor_dp_tag TUMOR_DP_TAG
Specify VCF INFO tag for sequencing depth (tumor, must be Type=Integer,
default: _NA_)
--tumor_af_tag TUMOR_AF_TAG
Specify VCF INFO tag for variant allelic fraction (tumor, must be Type=Float,
default: _NA_)
--control_dp_tag CONTROL_DP_TAG
Specify VCF INFO tag for sequencing depth (control, must be Type=Integer,
default: _NA_)
--control_af_tag CONTROL_AF_TAG
Specify VCF INFO tag for variant allelic fraction (control, must be Type=Float,
default: _NA_)
--call_conf_tag CALL_CONF_TAG
Specify VCF INFO tag for somatic variant call confidence (must be categorical,
e.g. Type=String, default: _NA_)
--tumor_dp_min TUMOR_DP_MIN
Minimum sequencing depth (tumor) for inclusion in report (default: None)
--tumor_ad_min TUMOR_AD_MIN
Minimum allelic depth (tumor, reads supporting alternate allele) for inclusion
in report (default: None)
--tumor_af_min TUMOR_AF_MIN
Minimum allelic fraction (tumor) for inclusion in report (default: None)
--control_dp_min CONTROL_DP_MIN
Minimum sequencing depth (control) for inclusion in report (default: None)
--control_ad_max CONTROL_AD_MAX
Maximum allelic depth (control, reads supporting alternate allele) for inclusion
in report (default: None)
--control_af_max CONTROL_AF_MAX
Maximum allelic fraction (control) for inclusion in report (default: None)
Tumor-only filtering options:
--pon_vcf PON_VCF VCF file with germline calls from Panel of Normals (PON) - blacklisted variants
(default: None)
--gnomad_popmax_af_tolerated GNOMAD_POPMAX_AF_TOLERATED
Exclude variants in tumor (SNVs/InDels, tumor-only mode) with gnomAD popmax
MAF greater than this value (default: 0.001)
--exclude_pon Exclude variants occurring in PoN (if --pon_vcf provided), default: False
--exclude_likely_hom_germline
Exclude likely homozygous germline variants (allelic fraction of 1.0 for
alternate allele in tumor), default: False
--exclude_likely_het_germline
Exclude likely heterozygous germline variants (0.4-0.6 allelic fraction, AND
presence in dbSNP + gnomAD, AND not in COSMIC/TCGA), default: False
--exclude_clinvar_germline
Exclude variants found in ClinVar (germline origin only), default: False
--exclude_dbsnp_nonsomatic
Exclude variants found in dbSNP (except those in ClinVar (somatic), TCGA, or
COSMIC), default: False
--exclude_nonexonic Exclude non-exonic variants, default: False
Tumor mutational burden (TMB) and MSI options:
--estimate_tmb Estimate tumor mutational burden from total somatic mutations and target region
size, default: False
--tmb_display {coding_and_silent,coding_non_silent,missense_only}
Type of TMB measure to show in report, default: coding_and_silent
--tmb_dp_min TMB_DP_MIN
Minimum sequencing depth (tumor) for TMB calculation (default: None)
--tmb_af_min TMB_AF_MIN
Minimum allelic fraction (tumor) for TMB calculation (default: None)
--tmb_ad_min TMB_AD_MIN
Minimum allelic depth (tumor) for TMB calculation (default: None)
--estimate_msi Predict microsatellite instability status from somatic mutation patterns,
default: False
Mutational signature options:
--estimate_signatures
Estimate relative contributions of reference mutational signatures (re-fitting),
default: False
--min_mutations_signatures MIN_MUTATIONS_SIGNATURES
Minimum number of SNVs required for signature re-fitting (SBS)
(default: 200, minimum n = 100)
--all_reference_signatures
Use all reference mutational signatures (SBS) during re-fitting rather than
only those attributed to the tumor type (default: False)
--include_artefact_signatures
Include sequencing artefacts in the reference signature collection
(default: False)
--prevalence_reference_signatures PREVALENCE_REFERENCE_SIGNATURES
Minimum tumor-type prevalence (in percent) of reference signatures to be
included in refitting (default: 0.1)
Somatic CNA analysis options:
--cna_threshold_mode {absolute,relative,combined}
Thresholding mode for CNA tier assignment: 'absolute' (total copy number),
'relative' (fold-change over tumor ploidy), or 'combined' (both criteria must
be met) (default: absolute)
--cna_amp_threshold_absolute CNA_AMP_THRESHOLD_ABSOLUTE
Absolute total copy number threshold for amplifications (default: 5)
--cna_amp_threshold_relative CNA_AMP_THRESHOLD_RELATIVE
Relative fold-change over tumor ploidy for amplifications (default: 2.5)
--cna_gain_threshold_absolute CNA_GAIN_THRESHOLD_ABSOLUTE
Absolute total copy number threshold for gains (default: 3)
--cna_gain_threshold_relative CNA_GAIN_THRESHOLD_RELATIVE
Relative fold-change over tumor ploidy for gains (default: 1.5)
--cna_del_threshold_absolute CNA_DEL_THRESHOLD_ABSOLUTE
Absolute total copy number at or below which (but above zero) a segment is
considered a heterozygous deletion (default: 1)
--cna_del_threshold_relative CNA_DEL_THRESHOLD_RELATIVE
Relative fold-change below tumor ploidy for heterozygous deletions
(default: 0.5)
--cna_transcript_overlap_pct CNA_TRANSCRIPT_OVERLAP_PCT
Minimum mean percent overlap between copy number segment and gene transcripts
for reporting of gains/losses in oncogenes/tumor suppressors (default: 50)
RNA expression and fusion options:
--fusion_min_split_reads FUSION_MIN_SPLIT_READS
Minimum number of split reads supporting a fusion event
(default: 3, minimum: 2)
--expression_sim Compare expression profile of tumor sample to known expression profiles
(default: False)
--expression_sim_db EXPRESSION_SIM_DB
Comma-separated string of databases for RNA expression similarity analysis,
default: tcga,depmap,treehouse
Germline variant options:
--input_cpsr INPUT_CPSR
CPSR-classified germline calls
(file '<cpsr_sample_id>.cpsr.<genome_assembly>.classification.tsv.gz')
--input_cpsr_yaml INPUT_CPSR_YAML
CPSR YAML configuration file
(file '<cpsr_sample_id>.cpsr.<genome_assembly>.conf.yaml')
--cpsr_ignore_vus Do not show variants of uncertain significance (VUS) in the germline section
of the HTML report (default: False)
Biomarker and tiering options:
--oncokb_api_token ONCOKB_API_TOKEN
OncoKB API token for querying the OncoKB precision oncology knowledge base
(default: None)
--oncokb_oncotree_code ONCOKB_ONCOTREE_CODE
OncoTree code specifying the tumor type for OncoKB queries (default: None)
--oncokb_exclusive Limit biomarker reporting to OncoKB only - skip CIViC and CGI sources
(default: False)
--oncokb_maf_query_all
Query OncoKB for all variant classes, including non-coding variants
(IGR, Intron, UTR, flanking regions). By default, non-coding variants
are filtered out before OncoKB annotation to reduce processing time.
Intended for TARGETED/WES assays only - enabling for WGS may result in
very long MafAnnotator.py runtimes (default: False)
Other options:
--force_overwrite Force overwrite of existing result files (default: False)
--version Show program's version number and exit
--no_reporting Run VEP/vcfanno annotation only; skip tier assignment, MSI, TMB, signatures,
and report generation (default: False)
--no_html Do not generate HTML report (default: False)
--debug Print full commands to log
--pcgrr_conda PCGRR_CONDA
pcgrr conda environment name (default: pcgrr)Example run
The examples folder contains input VCF files from two tumor samples sequenced within TCGA. A molecular interpretation report for a colorectal tumor sample can be generated by running the following command in your terminal window (this assumes you have installed PCGR through Conda, and that you have downloaded the necessary reference data files, VEP cache, see Installation):
$ (base) conda activate pcgr
$ (pcgr)
pcgr \
--refdata_dir /Users/you/dir2/data \
--vep_dir /Users/you/dir3/vep/.vep \
--output_dir /Users/you/dir4/pcgr_outputs \
--sample_id T001-COAD \
--genome_assembly grch37 \
--input_vcf /Users/you/pcgr/examples/T001-COAD.grch37.vcf.gz \
--tumor_dp_tag TDP \
--tumor_af_tag TVAF \
--tumor_site 9 \
--input_cna /Users/you/pcgr/examples/T001-COAD.grch37.cna.tsv \
--input_rna_fusion /Users/you/pcgr/examples/T001-COAD.grch37.fusions.tsv \
--sex MALE \
--tumor_purity 0.9 \
--tumor_ploidy 2.0 \
--assay WES \
--estimate_signatures \
--estimate_msi \
--estimate_tmb \
--force_overwriteThis command will run the Conda-based PCGR workflow and produce the following files in the /Users/you/dir4/pcgr_outputs folder:
| N | File | Description |
|---|---|---|
| 1 | <sample_id>.pcgr.grch37.html | An interactive HTML report for clinical interpretation (quarto-based) |
| 2 | <sample_id>.pcgr.grch37.xlsx | An excel workbook with multiple sheets of annotations (Assay & sample info/SNVs & InDels/CNAs/biomarkers/TMB/MSI), suitable for aggregation analysis across multiple samples |
| 3 | <sample_id>.pcgr.grch37.vcf.gz (.tbi) | Bgzipped VCF file with rich set of variant annotations to support interpretation |
| 4 | <sample_id>.pcgr.grch37.pass.vcf.gz (.tbi) | Bgzipped VCF file with rich set of variant annotations to support interpretation (PASS variants only) |
| 5 | <sample_id>.pcgr.grch37.pass.tsv.gz | Compressed vcf2tsv-converted file with rich set of variant annotations to support interpretation |
| 6 | <sample_id>.pcgr.grch37.conf.yaml | PCGR configuration data file (YAML), as generated by pre-reporting annotation workflow |
| 7 | <sample_id>.pcgr.grch37.cna_segment.tsv.gz | Tab-separated values file with raw copy number segments, per affected transcript |
| 8 | <sample_id>.pcgr.grch37.cna_gene_ann.tsv.gz | Tab-separated values file with annotated gene copy number alteration events, including actionability assessment |
| 9 | <sample_id>.pcgr.grch37.fusion_ann.tsv.gz | Tab-separated values file with annotated RNA fusion events, including actionability assessment |
| 10 | <sample_id>.pcgr.grch37.tmb.tsv | Tab-separated values file with information on tumor mutational burden (TMB) estimates |
| 11 | <sample_id>.pcgr.grch37.maf | Annotated SNVs/InDels, converted to the Mutation Annotation Format (MAF) |
| 12 | <sample_id>.pcgr.grch37.msigs.tsv.gz | Tab-separated values file with information on the contribution of mutational signatures in the tumor sample |
| 13 | <sample_id>.pcgr.grch37.snv_indel_ann.tsv.gz | Tab-separated values file with key SNV/InDel variant annotations, including oncogenicity and clinical actionability assessment |