Output Files
The following section describes the outputs produced by DRAGEN Array.
PGx CNV VCF File
DRAGEN Array produces one PGx CNV variant call file (VCF) (*.cnv.vcf) per sample to report the CN status on the gene and sub gene level, along with the CN events for PGx targets.
The PGx CNV VCF output file follows the standard VCF format. The QUAL field in the VCF file measures the CNV call quality. The CNV call quality is a Phred-scaled score capped at 60 and the minimal value is 0. Low quality calls (QUAL<7) are flagged by the Q7 filter. Low quality samples with LogRDev greater than a threshold 0.2 are flagged with the SampleQuality flag.
The PGx CNV VCF files are by default bgzipped (Block GZIP) and have the “.gz” extension. The compression saves storage space and facilitates efficient lookup when indexed with the TBI Index File. To view these files as plain text, they can be uncompressed with bgzip from Samtools or other third-party tools. The CNV VCF must be bgzipped and indexed to be used in downstream DRAGEN Array commands, such as star allele calling.
The PGx CNV VCF output file includes the following content.
##fileformat=VCFv4.1
##source=dragena 1.4.0
##genomeBuild=38
##reference=file:///hg38_with_alt/hg38_nochr_MT.fa
##FORMAT=<ID=CN,Number=1,Type=Integer,Description="Copy number genotype for imprecise events. CN=5 indicates 5 or 5+">
##FORMAT=<ID=NR,Number=1,Type=Float,Description="Aggregated normalized intensity">
##ALT=<ID=CNV,Description="Copy number variant region">
##FILTER=<ID=Q7,Description="Quality below 7">
##FILTER=<ID=SampleQuality,Description="Sample was flagged as potentially low-quality due to high noise levels.">
##INFO=<ID=CNVLEN,Number=1,Type=Integer,Description="Number of bases in CNV hotspot">
##INFO=<ID=PROBE,Number=1,Type=Integer,Description="Number of probes assayed for CNV hotspot">
##INFO=<ID=END,Number=1,Type=Integer,Description="End position of CNV hotspot">
##INFO=<ID=SVTYPE,Number=1,Type=String,Description="Structural Variant Type">
##OverallPloidy=1.8
##GCCorrect=True
##contig=<ID=1,length=248956422>
##contig=<ID=4,length=190214555>
##contig=<ID=10,length=133797422>
##contig=<ID=16,length=90338345>
##contig=<ID=19,length=58617616>
##contig=<ID=22,length=50818468>
##contig=<ID=22_KI270879v1_alt,length=304135>
#CHROM POS ID REF ALT QUAL FILTER INFO FORMAT 204619760001_R01C01
1 109687842 CNV:GSTM1:chr1:109687842:109693526 N <CNV> 60 PASS CNVLEN=5685;PROBE=124;END=109693526;SVTYPE=CNV CN:NR 2:0.966631132771593
4 68537222 CNV:UGT2B17:chr4:68537222:68568499 N <CNV> 60 PASS CNVLEN=31278;PROBE=383;END=68568499;SVTYPE=CNV CN:NR 0:0.376696837881692
10 133527374 CNV:CYP2E1:chr10:133527374:133539096 N <CNV> 60 PASS CNVLEN=11723;PROBE=194;END=133539096;SVTYPE=CNV CN:NR 2:0.980059731860893
16 28615068 CNV:SULT1A1:chr16:28603587:28613544 N <CNV> 57 PASS CNVLEN=8315;PROBE=164;END=28623382;SVTYPE=CNV CN:NR 2:0.980552325552963
19 40844791 CNV:CYP2A6.intron.7:chr19:40844791:40845293 N <CNV> 60 PASS CNVLEN=503;PROBE=38;END=40845293;SVTYPE=CNV CN:NR 2:0.9663775484762
19 40850267 CNV:CYP2A6.exon.1:chr19:40850267:40850414 N <CNV> 60 PASS CNVLEN=148;PROBE=21;END=40850414;SVTYPE=CNV CN:NR 2:0.9663775484762
22 42126498 CNV:CYP2D6.exon.9:chr22:42126498:42126752 N <CNV> 48 PASS CNVLEN=255;PROBE=370;END=42126752;SVTYPE=CNV CN:NR 2:0.981703411438716
22 42129188 CNV:CYP2D6.intron.2:chr22:42129188:42129734 N <CNV> 10 PASS CNVLEN=547;PROBE=333;END=42129734;SVTYPE=CNV CN:NR 2:0.965498002434641
22 42130886 CNV:CYP2D6.p5:chr22:42130886:42131379 N <CNV> 60 PASS CNVLEN=494;PROBE=172;END=42131379;SVTYPE=CNV CN:NR 2:0.970341562236357
22_KI270879v1_alt 270316 CNV:GSTT1:chr22_KI270879v1_alt:270316:278477 N <CNV> 60 PASS CNVLEN=8162;PROBE=91;END=278477;SVTYPE=CNV CN:NR 2:1.01191145130511Cytogenetics VCF File
DRAGEN Array produces one cytogenetics Variant Call File (VCF) (*.cnv.vcf) per sample to report the CN and LOH status of the detected variants.
The cytogenetics CNV VCF output file follows the standard VCF format. The QUAL field in the VCF file measures the CNV/LOH call quality. It reflects the probability that the called state (e.g., deletion, duplication, or LOH) is correct. This probability is converted into a Phred-scaled score using the standard formula: QUAL = -10 * log10(1 - probability of the called state). The Phred-scaled score is capped at 60 and the minimum value is 0. Low quality calls (QUAL<10) are flagged by the Q10 filter. Low quality samples with LogRDev greater than a threshold 0.2 are flagged with the SampleQuality flag.
The cytogenetics CNV VCF files are by default bgzipped (Block GZIP) and have the “.gz” extension. The compression saves storage space and facilitates efficient lookup when indexed with the TBI Index File. To view these files as plain text, they can be uncompressed with bgzip from Samtools or other third-party tools. The CNV VCF must be bgzipped and indexed to be used in downstream DRAGEN Array commands, such as cyto annotate.
One example file can be found below:
SNV VCF File
The software produces one genotyping variant call file (*.snv.vcf) file per sample, covering single nucleotide variants (SNV) and indels for the sample. It reports GenCall score (GS), B Allele Frequency (BAF), and Log R Ratio (LRR) per variant. The VCF file output follows VCF4.1 format.
Some additional details:
The FILTER column is hardcoded to
PASSand is not dependent on theGTvalue. It does not reflect the underlying quality of the call. Refer to theGSvalue for quality information.Genotypes are adjusted to reflect the sample ploidy. Calls are haploid for loci on Y, MT, and non-PAR chromosome X for males.
Multiple SNPs in the input manifest which are mapped to the same chromosomal coordinate (e.g. tri-allelic loci or duplicated sites) are collapsed into one VCF entry and a combined genotype generated. To produce the combined genotype, the set of all possible genotypes is enumerated based on the queried alleles. Genotypes which are not possible based on called alleles and assay design limitations (e.g. Infinium II designs cannot distinguish between A/T and C/G calls) are filtered. If only one consistent genotype remains after the filtering process, then the site is assigned this genotype. Otherwise, the genotype is ambiguous (more than 1) or inconsistent (less than 1) and a no-call is returned.
Certain SNV and indel calls will be skipped when reported in the VCF. Skipped data can include unmapped loci (i.e.,
Chris0in the manifest), intensity-only probes used for CNV identification, and indels that do not map back to the genome. See Warning/Error Messages and Logs for messages that may be seen with DRAGEN Array Local related to the skipped data.The BAF and LRR are oriented with Ref as A and Alt as B relative to the reference genome, while GS is agnostic to the reference genome. Users familiar with GenomeStudio may observe BAF and LRR reported in the VCF as 1 minus the value reported in GenomeStudio depending on the Ref Alt allele orientation with the reference genome. GenomeStudio reports these values based on the information in the manifest without knowledge of the reference genome.
The SNV VCF files are by default bgzipped (Block GZIP) and have the “.gz” extension. The compression saves storage space and facilitates efficient lookup when indexed with the TBI Index File. To view these files as plain text, they can be uncompressed with bgzip from Samtools or other third-party tools. The SNV VCF must be bgzipped and indexed to be used in downstream DRAGEN Array commands, such as star allele calling.
The SNV VCF output file includes the following content. The last row shows an example of variant call.
Note on Multi-Allelic Variants (MAV)
Illumina Microarrays are inherently bi-allelic assays made up of Infinium I or Infinium II probe designs which require special design considerations and have some inherent limitations. However, DRAGEN Array can combine multiple assays with different target bases but the same genomic position to make multi-allelic variant calls (MAVs). In this context, the MAV nomenclature is not only referring to an actual multi-ALT allelic variant call (i.e., GT=1/2 being the only possible outcome from a read-driven, single-sample VCF) but rather, any site where there are multiple ALTs in the VCF (e.g., REF=A,ALT=T,C). In other words, unlike NGS small variant callers like DRAGEN, which will dynamically call variants based on the reads present, DRAGEN Array creates the REF and ALTs for each entry in the SNV VCF based on theoretical, a-priori information from the manifest and reference genome files. It then only "fills in" the GT entry based on the core genotyping algorithm. This is how from DRAGEN Array single-sample SNV VCFs, it is possible to get GT calls like 0/2, 2/3, 1/3, etc.
The MAV calling algorithm currently checks all possible genotypes based on the alleles present in the overlapping assays, retaining only genotypes whose alleles are consistent with all the calls of the individual assays. If either no genotypes remain or if multiple genotypes remain after filtering, the result is considered ambiguous and reported as a NoCall to avoid false positives. The ambiguity often arises when one assay is a NoCall due to presumed probe failure rather than missing signal. In such cases, its potential genotypes are not excluded, contributing to ambiguity. When DRAGEN Array outputs a NoCall because of the described behaviors, they are logged as warnings (e.g., Failed to combine genotypes due to inconsistencies...).
Overall, the current algorithm errs on the side of caution to ensure quality calls, but produces some idiosyncratic behavior and potential false NoCalls when genotypes are biologically consistent but differ due to probe designs.
Some illustrative examples are below to help understand the current limitations:
Inf II [A/G] -> AA + Inf I [T/G] -> TT
AT
NoCall
The Inf II assay cannot differentiate A versus T alleles, hence AA call for the Inf II assay is consistent with AA, AT, or TT genotypes. The Inf I assay TT call, however, is consistent with AT or TT genotypes. Combining the two assays results in a NoCall due to the AT or TT ambiguity.
Inf I [T/A] -> AA + Inf II [A/G] -> NC
AA
NoCall
NoCall for Inf II probe leaves possibility of AG. Ambiguity between AG or AA leads to NoCall.
Variants of this type also only output the GT and GS fields. They do not output BAF or LRR values at this time. The GT field is determined via the algorithm described above. The GS field is simply the minimum GS of all the overlapping assays.
Using Infinium I NoCall Information
In v1.4, some additional behavior was added to improve the overall call rate and accuracy of MAV calling. When the option --use-infI-nc-info is enabled, the algorithm constrains possible genotypes by ruling out Infinium I probe no call related alleles not present in the other assays (i.e., reversing the underlying assumption - presuming missing signal, not probe failure). This reduces the chance of ambiguity after filtering possible genotypes but also increases false positive rate. Note: Using this option requires an update to your cluster file to cluster "zeroed-out" MAV assays. Without doing this, accuracy will drop when using this option. Reach out to techsupport@illumina.com for more details.
Note on delimiters in the "ID" field
By default, when multiple probes are present for a given variant, all probe names are included in the "ID" field of the resulting VCF file.
For SNP entries, probe names are separated by commas (,).
For Indel entries, probe names are separated by semicolons (;).
Note on REF/ALT "flipping" for INDELs
Expected REF and ALTs for INDELS may not match the dbSNP annotations in rare cases. E.g., an expected "Deletion" with the REF = "ATCG" and the ALT = "A" may be "flipped" to an "Insertion" variant with REF="A" and ALT="ACTG". The corresponding genotype output will take this into account so the actual VCF is still correct. This is simply a notation issue in some of the manifest files.
Note on PLINK compatibility
It is possible to make DRAGEN Array genotype VCF files compatible for conversion to PED/MAP format with preprocessing using tabix (v1.19.1), BCFtools (v1.21) and PLINK (v1.9). The following three commands demonstrate the basic process.
bcftools merge -l vcf_list.txt -Oz -o merged.vcf.gzcreates a single compressed VCFs from individual sample VCFs listed in thevcf_list.txttext file.tabix -p vcf merged.vcf.gzcreates a binary index for the merged file.plink --vcf merged.vcf.gz --recode --out mergedcreates .ped and .map files with the prefix provided to--out.
Some optional arguments may be provided to PLINK depending on the content of the VCFs to be converted and the downstream analysis.
For VCFs containing non-standard human chromosomes (e.g. haplotype chromosomes or unplaced contigs), the
--allow-extra-chrflag can be used.If using non-human data, refer to the PLINK documentation for the
--chr-setargument and supported options.By default, PLINK will only consider the most common ALT allele for multi-allelic variants. The
--biallelic-onlyargument can be provided to exclude multi-allelic variants altogether. As an alternative, usingbcftools norm -m - in.vcf.gz -Oz -o out.vcf.gz, can be used upstream of PLINK to split multi-allelic variants into bi-allelic records to retain them for downstream processing.
For more info on the options described and others, refer the PLINK VCF conversion documentation.
Genotype Call (GTC) File
The genotype call algorithm produces one genotype call file (.gtc) per sample analyzed. The Genotype Call (GTC) file contains the small variant (SNV and indel) genotype for each marker specified by the product and sample quality metrics. The sample marker location is not included and must be extracted from the manifest file. Binary proprietary format can be parsed using the Illumina open-source tool BeadArray Library File Parser.
Note on lack of i18n: GTCs are binary/fixed format files designed before modern internationalization and localization tools. There is a related known issue that makes the GTCs unable to be used in downstream analyses. Refer to the same issue to see a workaround.
Note on legacy GTCs: Other Illumina software (such as AutoConvert and Beeline) also produce GTC files.
These "legacy GTC" files will work in DRAGEN Array genotyping commands such as genotype gtc-to-vcf but they will not work with all other downstream analyses such as Cytogenetics analysis and PGx. We recommend using DRAGEN Array end-to-end starting from IDATs for these analyses.
BedGraph Files
The BedGraph files contains the Log R Ratios (LRR.bedgraph) and B-Allele Frequencies (BAF.bedgraph) from the genotyping algorithm for use in visual tools.
PGx Star Allele Dat File
The Star Allele Dat file is an intermediate file generated by the pgx star-allele call command and serves as the input to the pgx star-allele annotate command.
PGx Star Allele CSV Files
The following files are output from the pgx star-allele annotate command. Each CSV file also contains meta information marked by # at the top of the file for the genome build and PGx database used for the star allele calling. The structure of the output files is shown below.
Diplotype Summary CSV
The file diplotype_summary.csv contains all the star allele calls for all samples in a run. Each row in the file provides either a star allele diplotype or simple variant call for a PGx-related gene. Star allele diplotype calls for a sample and a gene may span multiple lines where alternative solutions can be listed.
The diplotype_summary.csv file contains the following details per sample:
Sample
Sentrix barcode and position of the sample.
Solution Id
Rank of a single star allele solution for a gene. The top solution based on quality score is ranked as 1, with alternative solutions ranked lower.
Gene or Variant
The gene symbol for haplotype calls, or gene symbol plus rsID (or variant identifier) for variant-level calls.
Type
PGx calling type: Haplotype (star allele–based call) or Variant (individual variant call).
Solution
Star allele or variant solution. For diploid calls, the format is Allele1/Allele2. Variant calls may include explicit nucleotide changes or reference calls.
Array‑Equivalent Alleles (Allele 1)
Star alleles for allele 1 that are indistinguishable from the reported solution given the content of the genotyping array and no‑call variants. The allele with the highest population frequency is reported in the solution.
Array‑Equivalent Alleles (Allele 2)
Star alleles for allele 2 that are indistinguishable from the reported solution given the content of the genotyping array and no‑call variants. The allele with the highest population frequency is reported in the solution.
No Call Variants
Variants that are not called in the sample SNV VCF.
Alleles Impacted by No‑Call
Star alleles whose definitions are impacted by missing or no‑call variants.
Background Alleles
Background or reference star alleles relevant to the gene, often used to contextualize indistinguishable or default calls.
Variant Change
Observed variant change, structural variant, or notation explaining an unresolved or no‑call condition (e.g., explicit genomic coordinates or deletion events).
Score
A probability score representing the likelihood of the inferred solution based on the SNV and CNV inputs, input quality, and population frequencies of PGx alleles. The score ranges from 0 to 1.
Raw Score
Raw probability score of the solution excluding population frequency. The score ranges from 0 to 1.
Copy Number Solution
Estimated copy number for each gene region. The field is formatted as GeneRegion=CopyNumber (e.g., CYP2D6.exon.9=2).
Below is an example of the first 4 columns from a diplotype summary CSV file:
Sample,Solution Id,Gene or Variant,Type,Solution
204650490282_R02C01,1,CYP2C9,Haplotype,*9/*11
204650490282_R02C01,1,CYP2C19,Haplotype,*2/*10
Diplotype Annotation CSV
The diplotype_annotations.csv file contains aggregated genotype annotations and their corresponding clinical interpretations for pharmacogenomics (PGx)–related genes across all samples in a run. Each row represents the final, resolved genotype result for a single sample–gene pair, along with any associated activity score and phenotype interpretation based on CPIC guidelines.
Sample
Unique identifier for the sample within the run. Each sample appears on multiple rows, one per reported gene.
Gene
Gene or genomic locus associated with the reported PGx result (e.g., CYP2C9, SLCO1B1, MT‑RNR1).
PGx Guideline
Clinical pharmacogenomics guideline used for interpretation. Values may include CPIC (Clinical Pharmacogenetics Implementation Consortium) or DPWG (Dutch Pharmacogenetics Working Group).
Genotype
Aggregated genotype result for the sample and gene. This may be represented as a star‑allele diplotype (e.g., *1/*1), a combination of specific variants (e.g., rsID‑based calls), or reference/variant notation.
Activity Score
Numeric activity or function score derived from the aggregated genotype for genes with defined scoring systems (e.g., CYP genes, DPYD). Reported as n/a when not applicable.
Phenotype Database Annotation
Clinical phenotype or functional interpretation associated with the aggregated genotype (e.g., Normal Metabolizer, Decreased Function, Ivacaftor non‑responsive). Reported as n/a if no standardized interpretation is available.
Supporting Variants CSV
The supporting_variants.csv lists the variant‑level evidence used to support each allele call reported in diplotype_summary.csv. Each row links a solution‑level allele call to one of its supporting genomic variants, including probe identifiers, genotype, copy number, and quality metrics, enabling full traceability, validation, and troubleshooting.
Sample
Unique identifier for the analyzed sample (e.g., array sample or well ID).
Solution Id
Identifier for the allele solution within a gene. This field corresponds directly to Solution Id in the diplotype_summary file, enabling linkage between allele calls and their supporting variants.
Gene or Variant
Gene symbol for star‑allele–based calls (e.g., CYP2D6) or variant identifier for simple variant–based calls.
Allele
Star allele or allele designation supported by the listed variant (e.g., *1, *2, *36+*10).
HGVS
Genomic variant represented using HGVS nomenclature (e.g., NC_000010.11:g.94842866A>G).
RSID
dbSNP reference SNP identifier (e.g., rs3758581). Provided for external reference and downstream validation; may be empty if not applicable.
Chromosome
Chromosome on which the variant is located (e.g., 1–22, X, MT).
Position
Genomic base‑pair position of the variant on the chromosome.
Ref
Reference allele at the variant position.
Alts
Alternate allele(s) observed at the variant position. May be comma‑separated for multiallelic sites.
Genotype
Observed genotype for the variant in the sample, reported in VCF‑style notation (e.g., 0/1, 1/1, 0/2).
Variant Copy Number
Estimated copy number of the variant allele, reflecting zygosity or duplications where applicable.
GS
Genotype score representing confidence or quality of the variant call.
BAF
B‑allele frequency for the variant, used to support genotype and copy‑number interpretation.
ProbeID
Illumina probe identifier(s) used to genotype the variant. Included for downstream validation and troubleshooting.
Unresolved Variants CSV
Explicit reporting of variants that could not be resolved, with accompanying reasons (for example, variants not present on the array or variants with no-call genotype). The unresolved_variants.csv file is analogous to supporting_variants.csv and contains variant‑level details for unresolved variants that are included in the allele definition for each allele call across every gene and solution within a sample.
Sample
Unique identifier for the analyzed sample (e.g., array sample or well ID).
Gene or Variant
Gene symbol associated with the star‑allele call (e.g., CYP2D6, UGT1A1) or the specific variant being evaluated.
Solution Id
Identifier for the allele solution in which this unresolved variant occurs, allowing linkage to solution‑level allele calls. This field corresponds directly to Solution Id in the diplotype_summary.csv file.
Allele
Star allele associated with the unresolved variant (e.g., *1, *2, *10), if applicable.
HGVS
Genomic variant represented using HGVS nomenclature, specifying the precise genomic location and sequence change.
RSID
dbSNP reference SNP identifier for the variant. Provided to support external validation and cross‑reference with public variant databases.
Reason
Reason the variant could not be resolved in the star‑allele call (e.g., Not on Array, No Call).
ProbeID
Identifier(s) for the array probe(s) associated with the variant. Provided to support probe‑level investigation and downstream troubleshooting.
Variants not Covered on Array CSV
The variants_not_covered_on_array.csv file lists the variants that are included in the PGx database used for the star allele calling but are not present in the manifest file used for the analysis.
Gene or Variant
Gene symbol or variant identifier associated with the uncovered variant. This may represent the gene containing the variant or a named variant definition.
HGVS
Variant described using HGVS nomenclature, indicating the genomic or mitochondrial location and sequence change.
RSID
dbSNP reference SNP ID (rsID) for the variant, if available. This field is empty if no rsID is assigned.
Alleles Impacted
List of star alleles or allele definitions that include this variant and may be impacted due to lack of array coverage.
Genotype Summary Files
The software produces genotype summary files (gt_sample_summary.csv and gt_sample_summary.json) that contains the following details per sample:
Sample ID
Sample Name (see Sample Name Determination)
Sample Folder
Autosomal Call Rate
Call Rate
Log R Ratio Std Dev
Sex Estimate
TGA_Ctrl_5716 Norm R
(Optional) User defined fields from the samplesheet
The TGA_Ctrl_5716 Norm R field is specific to PGx products (e.g., Global Diversity Array with enhanced PGx). The field value is the Normalized R value of one probe and is meant as an assay control where < 1 indicates the sample failed in the TGA (Targeted Gene Amplification) process. If the product does not have this probe, it is not included in the gt_sample_summary.
The user defined fields from the samplesheet will appear as-is in the gt_sample_summary files. e.g. for the given samplesheet:
It would produce something like the following gt_sample_summary.csv:
And something like the following gt_sample_summary.json:
Note: As of v1.3, samples that fail during genotyping will still be present in this file. See the details in the release notes.
Final Report
DRAGEN Array Cloud produces a Final Report (gtc_final_report.csv) per analysis batch similar to the one available in GenomeStudio. It contains the following details per locus per sample:
SNP Name
SNP identifier.
SNP
SNP alleles as reported by assay probes. Alleles on the Design strand (the ILMN strand) are listed in order of Allele A/B.
Sample ID
Sample identifier.
Allele 1 – Top
Allele 1 corresponds to Allele A and are reported on the Top strand.
Allele 2 – Top
Allele 2 corresponds to Allele B and are reported on the Top strand.
Allele 1 – Forward
Allele 1 corresponds to Allele A and are reported on the Forward strand.
Allele 2 – Forward
Allele 2 corresponds to Allele B and are reported on the Forward strand.
Allele 1 – Plus
Allele 1 corresponds to Allele A and are reported on the Plus strand.
Allele 2 – Plus
Allele 2 corresponds to Allele B and are reported on the Plus strand.
GC Score
Quality metric calculated for each genotype (data point), and ranges from 0 to 1.
GT Score
The SNP cluster quality. Score for a SNP from the GenTrain clustering algorithm.
Log R Ratio
Base-2 log of the normalized R value over the expected R value for the theta value (interpolated from the R-values of the clusters). For loci categorized as intensity only; the value is adjusted so that the expected R value is the mean of the cluster.
B Allele Freq
B allele frequency for this sample as interpolated from known B allele frequencies of 3 canonical clusters: 0, 0.5 and 1 if it is equal to or greater than the theta mean of the BB cluster. B Allele Freq is between 0 and 1, or set to NaN for loci categorized as intensity only.
Chr
Chromosome containing the SNP.
Position
SNP chromosomal position.
Note: Analyses on products with large numbers of loci (>1 Million) and large numbers of samples (>100) yield a large (50+ Gigabyte) Final Report that are difficult to download and review. It’s recommended to create analysis configurations that do not produce this report if large batches are desired.
For more information on interpreting DNA strand and allele information, see Illumina Knowledge article How to interpret DNA strand and allele information for Infinium genotyping array data.
Locus Summary
DRAGEN Array Cloud produces a Locus Summary (locus_summary.csv) per analysis batch similar to the one available in GenomeStudio. It contains the following details per locus:
Locus_Name
Locus name from the manifest file.
Illumicode_Name
Locus ID from the manifest file.
#No_Calls
Number of loci with GenCall scores below the call region threshold.
#Calls
Number of loci with GenCall scores above the call region threshold.
Call_Freq
Call frequency or call rate calculated as follows: #Calls/(#No_Calls + #Calls)
A/A_Freq
Frequency of homozygote allele A calls.
A/B_Freq
Frequency of heterozygote calls.
B/B_Freq
Frequency of homozygote allele B calls.
Minor_Freq
Frequency of the minor allele.
Gentrain_Score
Quality score for samples clustered for this locus.
50%_GC_Score
50th percentile GenCall score for all samples.
10%_GC_Score
10th percentile GenCall score for all samples.
Het_Excess_Freq
Heterozygote excess frequency, calculated as (Observed -Expected)/Expected for the heterozygote class. If $f_{ab}$ is the heterozygote frequency observed at a locus, and p and q are the major and minor allele frequencies, then het excess calculation is the following: $(f_{ab} - 2pq)/(2pq + \varepsilon)$
ChiTest_P100
Hardy-Weinberg p-value estimate calculated using genotype frequency. The value is calculated with 1 degree of freedom and is normalized to 100 individuals.
Cluster_Sep
Cluster separation score.
AA_T_Mean
Normalized theta angles mean for the AA genotype.
AA_T_Std
Normalized theta angles standard deviation for the AA genotype.
AB_T_Mean
Normalized theta angles mean for the AB genotype.
AB_T_Std
Standard deviation of the normalized theta angles for the AB genotype.
BB_T_Mean
Normalized theta angles mean for the BB genotypes.
BB_T_Std
Standard deviation of the normalized theta angles for the BB genotypes.
AA_R_Mean
Normalized R value mean for the AA genotypes.
AA_R_Std
Standard deviation of the normalized R value for the AA genotypes.
AB_R_Mean
Normalized R value mean for the AB genotypes.
AB_R_Std
Standard deviation of the normalized R value for the AB genotypes.
BB_R_Mean
Normalized R value mean for the BB genotypes.
BB_R_Std
Standard deviation of the normalized R value for the BB genotypes.
Plus/Minus Strand
Designated "+" or "-" with respect to the reference genome strand. "U" designates unknown.
CN Summary File
The sample summary contains per sample key stats for each sample in a batch that contains the following details per sample:
Sample ID
Sample Name
Sample Folder
Copy Number Batch File
The copy number batch summary file (cn_batch_summary.csv) shows the total copy number gain, loss, and neutral (CN=2) values for each target region across all the samples in the analysis.
Example copy number batch summary file content:
Target Region,Total CN gain,Total CN loss,Total CN neutral
CYP2A6.exon.1,0,1,47
CYP2A6.intron.7,0,1,47
CYP2D6.exon.9,2,4,42
CYP2D6.intron.2,7,2,39
CYP2D6.p5,13,2,33
CYP2E1,2,0,46
GSTM1,0,42,6
GSTT1,0,33,15
SULT1A1,0,0,48
UGT2B17,0,34,14
All Target Regions,24,119,337
Warning/Error Messages and Logs
The following scenarios result in a warning or error message:
Manifest file used to generate GTC is not the same as the manifest file used to generate the CN model.
FASTA files and FASTA index files do not match.
For the following scenarios, the software reports messages to the terminal output (as either a warning or an error):
Indel processing for GTC to VCF conversion failed.
The input folder does not contain the required input files.
An input file is corrupt.
Examples of such notifications can include the following:
Failed to normalize and gencall sample: {sample_id}, it will be skipped. Error: The given key '{loci_id}' was not present in the dictionary.
Warning
This generally occurs because of a mismatch between the manifest (bpm) and cluster file (egt) (i.e., the cluster file was generated via a different manifest). To remedy the issue, use the manifest and cluster files intended for use together.
Reference allele is not queried for locus: {identifier}
Warning
True reference allele does not match any alleles in the manifest. The error is common for MNVs and will be addressed in future versions of the software.
Skipping non-mapped locus: {identifier}
Warning
Locus has no chromosome position (usually 0) These loci may be used for quality purposes or CNV calling only.
Skipping intensity only locus: {identifier}
Warning
Similar to non-mapped loci, intensity only probes have applications outside creating variants for SNV VCFs such as CNV calling.
Skipping indel: {identifier}
Warning
Indel context (deletion/insertion) could not be determined.
Failed to process entry for record: {identifier}
Warning
Unable to determine reference allele for indel.
Incomplete match of source sequence to genome for indel: {identifier}
Warning
Indel not properly mapped to the reference genome.
Failed to combine genotypes due to inconsistencies - exm1068284 (InfiniumII): TT, ilmnseq_rs1131690890_mnv (InfiniumII): AA, rs1131690890_mnv (InfiniumII): AA
Warning
Detailed information about a NoCall ("./.”) in the VCF as a result of combining multiple probes that assay the same variant with conflicting results. The example here is two probes with homozygous REF genotypes (AA) and one probe with homozygous ALT probe (TT)
Failed to combine genotypes all were No Calls - exm1068284 (InfiniumII): NC, ilmnseq_rs1131690890_mnv (InfiniumII): NC, rs1131690890_mnv (InfiniumII): NC
Warning
Detailed information about a NoCall ("./.”) in the VCF as a result of combining multiple probes that assay the same variant in which all the probes were No Calls.
Cluster file ({GTC.egt}) is not the same as CN Model Cluster file ({CN_Model.egt}).
Warning
Cluster file used to generated GTCs used for copy number calling is not the same as was used for the GTCs used during copy number training that created the input CN model. Though CNV model is robust to minor cluster file updates, CNV training should be considered when there are significant updates in the cluster file. To remove the warning, copy number training needs to be re-run with the new GTCs generated via the new cluster file during genotyping, a different CN model with the expected cluster file needs to be used, or different GTCs should be used for copy number calling that were generated using the same cluster file as was used during the generation of the input CN model.
{numPassingSamples} sample(s) passed QC.
Requires at least {minPassingSamples} samples to proceed.
Error
CNV calling is batch dependent and requires a certain number of samples with high-quality to make accurate calls. More high-quality samples need to be added to analysis batch to resolve error.
Invalid manifest file path {manifestPath}
Error
Application could not find manifest file provided or user error.
Failed to load cluster file: {e.Message}
Error
Corrupted file or unsupported version.
System.IO.EndOfStreamException: Unable to read beyond the end of the stream.
Error
Likely failure to read a GTC file, see this known issue for more details on root cause and a workaround
Star allele JSON File
The star allele JSON file is produced per sample. It contains the fields present in the star allele CSV file as well as additional meta data and annotations.
Fields included in the star allele JSON header are described below.
softwareVersion
DRAGEN Array software version, e.g. dragena 1.0.0.
genomeBuild
Genome build, e.g hg38.
starAlleleDatabaseSources
Public databases with versions used as the sources of the star allele definitions and population frequencies.
phenotypeDatabaseSources
Public databases with versions used as the sources of the star allele phenotypes.
mappingFile
The PGx database file used for the star allele calling.
pgxGuideline
The PGx guidelines used for metabolizer status/phenotype annotations, e.g. CPIC or DPWG
sampleId
Sentrix barcode and position of the sample.
locusAnnotations
The star allele call information.
Fields included in the star allele call (locusAnnotations) information are described below.
gene
The gene symbol.
callType
‘Star Allele’ or ‘Variant’ PGx calling type.
genotype
Most likely star allele or variant solution. If diploid, variant solutions have the format of Allele1/Allele2. More than one solution meeting threshold requirements can be reported. Multiple top solutions are separated by a semi-colon.
arrayEquivalentAlleles
Star alleles for the given alleleId that are indistinguishable from the reported solution allele given the content of the genotyping array.
activityScore
Activity score annotation of the determined genotype of the gene determined based on public PGx guidelines CPIC or DPWG.
phenotypeDatabaseAnnotation
Metabolizer status and function annotations of the determined genotype of the gene based on lookup into public PGx guidelines CPIC or DPWG per user choice.
qualityScore
Quality score of the solution including the population frequency of PGx alleles. The score ranges from 0 to 1.
rawScore
Raw quality score of the solution without including the population frequency of PGx alleles. The score ranges from 0 to 1.
supportingVariants
All variants present in the array that support the star allele solution. The field provides an array (list) of supporting Variants.
Each supporting variant is listed with essential information extracted from the SNV VCF to assist with troubleshooting, including Chromosome (chrom), Location (pos), Reference allele (ref), Alternative allele (alt), Genotype (gt), GenCall score (gs), B-allele frequency (baf), the variant ID (id), the variant rsid (rsid), and the associated star allele IDs (alleleIds).
variantNoCalls
Variants that are no calls in the sample SNV VCF
allelesImpactedByNoCalls
Star alleles in the solution or array equivalent alleles, whose definitions are impacted by no‑call variants.
candidateSolutions
The set of alternative star allele calling solutions, this is only relevant for genes of the ‘Star Allele’ call type.
variantsNotCoveredOnArray
All core variants that are not covered on the array for star allele calling for this gene. For star alleles, the field provides an array (list) of variant "id" and impacted "alleleIds" pairs
allelesTested
Alleles that are covered by the star allele caller. The capability to call star alleles is also dependent on array content coverage and data quality. This field is defined by the array's content and will be the same across all samples.
Fields included in the candidateSolution section, only available for star allele call type, are described below.
rank
Rank of a single star allele solution for a gene. The top solution based on quality score is ranked as 1 with the alternative solutions ranked lower.
genotype
Star allele or variant solution. If diploid, variant solutions have the format of Allele1/Allele2.
activityScore
Activity score annotation of the determined genotype of the gene determined based on public PGx guidelines CPIC or DPWG.
phenotypeDatabaseAnnotation
Metabolizer status and function annotations of the determined genotype of the gene based on lookup into public PGx guidelines CPIC or DPWG per user choice.
qualityScore
Quality score of the solution including the population frequency of PGx alleles. The score ranges from 0 to 1.
rawScore
Raw quality score of the solution without including the population frequency of PGx alleles. The score ranges from 0 to 1.
alleles
The composite alleles of the candidate genotype solution.
supportingVariants
All variants present in the array that support the star allele solution. The field provides an array (list) of supporting Variants.
Each supporting variant is listed with essential information extracted from the SNV VCF to assist with troubleshooting, including Chromosome (chrom), Location (pos), Reference allele (ref), Alternative allele(s) (alts), Genotype (gt), GenCall score (gs), B-allele frequency (baf), HGVS tag (hgvs), variant RSID (rsid) and the associated star allele IDs (alleleIds).
unresolvedVariantSites
All variants not present in the array or not called in the SNV VCF file for the star allele solution. The field provides an array (list) of missing variants.
arrayEquivalentAlleles
Star alleles that cannot be distinguished from the solution star allele given the input array’s content. The field has the following format: Star-Allele Id: (List of collapsed star alleles).
The most frequent star allele based on the population frequency of PGx alleles will be the star allele in the solution.
backgroundAllele
Background star-allele haplotype for a given structural variant in the solution
copyNumberRegions
Gene regions for the copy numbers listed in CopyNumberSolution.
copyNumberSolution
Estimated copy number for each gene region listed in CopyNumberRegions
Example of JSON file content:
Guidance on alternative star-allele results
Typically, the star allele solution with highest quality score is accepted as the final genotype (i.e. star allele diplotype) for the PGx locus. In rare cases, there are lower ranked star allele solutions with quality scores no less than 50% of the highest quality score, these lower ranked solutions are considered feasible and they are all listed in the genotype field of the locus annotation of the PGx gene in the PGx JSON file. Alternative solutions should also be considered if there are supporting variants for those solutions with low (less than 0.15) GS scores. The clustering of low GS scoring supporting variants should also be evaluated for cluster quality and any potential cluster shift.
Cytogenetics Annotation JSON File
DRAGEN Array produces one cytogenetics annotation JSON (*.json) per sample to report more sample-level, chromosome-level, and event-level metrics and annotations.
Example of JSON file content:
The fields in the annotation JSON for each sample are described as follows.
annotateDb
File name of the database annotation file.
softwareVersion
Version of DRAGEN Array used for the analysis.
referenceGenome
File name of the reference genome.
annotationType
Integer representing annotation methodology where 0=Constitutional and 1=Oncology.
genomeBuild
Genome build e.g. hg19, hg38.
databaseSources
Release versions of annotation data.
iscnVersion
Release date of ISCN formatting used.
sampleId
ID string assigned to the sample.
sampleName
gcCorrect
Boolean indicating whether GC correction was enabled.
minDelProbes
Deletions must contain this many probes to be reported.
minDupProbes
Duplications must contain this many probes to be reported.
minLOHProbes
LOH variants must contain this many probes to be reported.
minDelSize
Minimum length filter for reporting deletions in kilobases (kb).
minDupSize
Minimum length filter for reporting a duplication in kb.
minLOHSize
Minimum length filter for reporting a loss-of-heterzygozity (LOH) variant in kb.
minQual
Minimum quality score filter for reporting a variant.
overallPloidy
Arithmetic mean of the ploidy across the genome. This value accounts for the length of all variant calls. The baseline ploidy value without any variants will differ by sex.
callRate
Frequency of expected calls i.e. #Calls/(#No_Calls + #Calls).
logRDev
Standard deviation of the Log R ratio values for all probes.
bafDev
Standard deviation of the B allele frequency values for each assigned genotype (AA/AB/BB).
numLOHOver1M
Count of LOH (including GAINLOH) variants detected > 1 Mbp in length.
numLOHOver8M
Count of LOH (including GAINLOH) variants detected > 8 Mbp in length.
totalSizeLOHOver1M
Cumulative length of all detected LOH (including GAINLOH) variants > 1 Mbp in length.
copyNumberMedian
Length-normalized genome-wide median copy number value. Copy number values are assigned to contiguous segements of variable size in the genome by the algorithm. The length-weighted copy numbers of each variant are aggregated to calculate the overall median.
percentLOH
Percent of the genome comprised of LOH variants.
sexEstimate
Detected sex of the sample.
traditionalNomenclature
Simplified ISCN format designation for all detected variants in the sample.
microarrayNomenclature
ISCN format designation for all detected variants in the sample.
chromosomeAnnotations
Counts of each type of variant detected per chromosome, including mosaic calls.
locusAnnotations
Locus level statistics (see additional table for locus-level statistics).
The fields for each chromosome under the chromosomeAnnotations field of the Cyto annotation JSON are described below.
id
Chromosome name.
size
Chromosome size.
percentHet
Percent of probes in the chromosome called as heterzygous i.e. AB.
hasMosaicism
Boolean indicating presence of any mosaic variant on the chromosome.
lrrMedian
Median log R ratio value of the probes within the chromosome.
lrrMean
Mean log R ratio value of the probes within the chromosome.
lrrDev
Standard deviation of the log R ratio values of the probes within the chromosome.
numLOHOver1M
Count of LOH variants (excluding GAINLOH) detected > 1 Mbp in length.
numLOHOver8M
Count of LOH variants (excluding GAINLOH) detected > 8 Mbp in length.
totalSizeLOHOver1M
Cumulative length of all detected LOH (excluding GAINLOH) variants > 1 Mbp in length.
percentLOH
Percent of the genome comprised of LOH variants.
copyNumberMedian
Copy number median of the chromosome.
copyNumberMean
Copy number mean of the chromosome.
minLogRRatio
Minimum Log R ratio of the chromosome.
maxLogRRatio
Maximum Log R ratio of the chromosome.
medianMosaicFraction
Median mosaic fraction of mosaic events on the chromosome.
numberDel
Number of deletion events on the chromosome.
numberDup
Number of duplication events on the chromosome.
numberLOH
Number of LOH events on the chromosome.
numberGainLOH
Number of GAIN LOH events on the chromosome.
numberMosaic
Number of mosaic events on the chromosome.
The fields within each variant (CNV/LOH event) under the locusAnnotations field of the Cyto annotation JSON are described below.
id
Unique variant ID containing variant type, chromosome and the start and end positions.
chrom
Chromosome of the variant.
start
Variant start position.
end
Variant end position.
callType
Variant class (DEL, DUP, LOH).
mosaicState
Boolean indicating whether the locus is a mosaic variant.
copyNumber
Copy number of the locus.
qualityScore
Phred-scaled score of the variant call quality.
size
Length of the variant.
effectiveSize
Gap-excluded length of the variant. A gap is defined when probe spacing is more than 150 times the median probe spacing. In that case, the gap is replaced with the median probe spacing.
probeCount
Number of probes contained in the called variant region.
percentHet
Percent of probes in the region call as heterzygous i.e. AB.
lrrMedian
Median log R ratio value of the probes within the variant.
lrrDev
Standard deviation of the log R ratio values of the probes within the variant.
bafDev
Standard deviation of the B allele frequency values of the probes within the variant.
startCytoBand
Cytoband in which the variant starts.
endCytoBand
Cytoband in which the variant ends.
traditionalNomenclature
Simplified ISCN format designation for the detected variant.
microarrayNomenclature
ISCN format designation for the detected variant.
geneCount
Count of annotated genes within the variant region.
genes
List of names of all annotated genes within the variant region.
The traditionalNomenclature field is used to describe individual and cumulative copy number variants at a coarse resolution. They show gains (dup) and losses (del) according to their chromosome number, arm (p or q), and band (e.g., p36.13). The microarrayNomenclature field follows the Comparative Genomic Hybridization or SNP array conventions. Values are prefixed with arr[] to indicate array data as the source, along with the genome build e.g. GRCh38. These data can more precisely describe the location (start_end in bp) and copy number (x1 for loss, x3 for gain, etc).
The genes list field for each variant include those with transcript coordinates that intersect with the described variant. The values included are a combination of HGNC gene symbols taken from NCBI RefSeq database (e.g. TBC1D3I), as well as the subset of Ensembl gene accessions unmatched to a gene symbol (ENSG00000278395).
TBI Index File
The TBI (TABIX) index file is associated with the bgzipped VCF files. It allows for data line lookup in VCF files for quick data retrieval. The format is a tab-delimited genome index file developed by Samtools as part of the HTSlib utilities. For more information, visit the Samtools website.
Methylation Control Probe Output File
The software produces a control probe output file ({BeadChipBarcode}_{Position}_ctrl.tsv.gz) per sample that includes the raw methylated and unmethylated values for each control probe.
Each control probe has an address, type, color channel, name, and probe ID. It also provides the raw signal for methylated green (MG), methylated red (MR), unmethylated green (UG) and unmethylated red (UR).
The file can help identify which probes are available on a given BeadChip.
Methylation CG Output File
The software produces a CG output file ({BeadChipBarcode}_{Position}_cgs.tsv.gz) per sample that includes beta values, m-values and detection p-values for each CG site.
Beta values measure methylation levels in a linear fashion for easy interpretation. Unmethylated probes are close to zero and methylated probes are close to 1.
M-values are a log transformed beta value which provides a more representative measure of methylation.
Detection p-values measure the likelihood that the signal is background noise. It is recommended that p-value >0.05 are excluded from analysis as they are likely background noise.
see High-throughput Infinium methylation array QC using DRAGEN Array Methylation QC software tech note for further detail on calculation of these metrics.
Methylation Sample QC Summary Files
The software produces methylation sample QC summary in .xlsx and .tsv file formats (sample_qc_summary.xlsx and sample_qc_summary.tsv) per analysis batch, which provides per sample QC data for all samples in the batch.
The QC summary provides details on 21 controls metrics (see tables below), which are computed in same way as in the BeadArray Controls Reporter software from Illumina. In addition, it provides average red and green raw and normalized signals, time of scanning, proportion of probes passing, overall sample pass/fail status, and the failure codes for control metrics that did not pass. The sample pass status is defined as the passing of all 21 control metrics. The QC summary .xlsx file further highlights failing parameters for easy viewing.
The QC summary files contain the following fields:
Sentrix_ID
12-digit BeadChip Barcode associated with the sample.
Sentrix_Position
Row and column on the BeadChip ie R01C01
Sample_ID
Optional field that can be indicated using IDAT Sample Sheet
User Defined Meta Data
Optional field(s) that can be indicated using IDAT Sample Sheet. Any number of fields indicated will appear in this output file.
restoration
The default threshold is 0.
If using the FFPE DNA Restore Kit, the restoration control identifies success of the FFPE restoration chemistry. Change the threshold from 0 to 1 if the FFPE DNA Restore Kit was used.
The green channel intensity is higher than Background. Therefore, the metric provided is the Green Channel Intensity/Background.
staining_green
staining_red
Staining controls are used to examine the efficiency of the staining step in both the red and green channels. These controls are independent of the hybridization and extension step.
The green channel shows a higher signal for biotin staining when compared to biotin background, whereas the red channel shows higher signal for DNP staining when compared to DNP background.
The metric provided for green is the (Biotin High value)/ (Biotin Bkg) and the metric provided for red is (DNP High value)/(DNP Bkg value)
The default threshold is 5. This threshold can be increased on some scanners.
extension_green
extension_red
Extension controls test the extension efficiency of A, T, C, and G nucleotides from a hairpin probe, and are therefore sample independent.
In the green channel, the lowest intensity for C or G is always greater than the highest intensity for A or T.
The metric provided is the (lowest of the C or G intensity)/ (highest of A or T extension) for a single sample.
The default threshold is 5. This threshold can be increased on some scanners.
hybridization_high_medium
hybridization_medium_low
Hybridization controls test the overall performance of the Infinium Assay using synthetic targets instead of amplified DNA. These synthetic targets complement the sequence on the array, allowing the probe to extend on the synthetic target as a template. Synthetic targets are present in the Hybridization Buffer at 3 levels, monitoring the response from high-concentration (5 pM), medium concentration (1 pM), and low concentration (0.2 pM) targets. All bead type IDs result in signals with various intensities, corresponding to the concentrations of the initial synthetic targets.
The value for high concentration is always higher than medium and the value for medium concentration is always higher than low.
The metric provided is the value of high/medium and the value of medium/low.
The default thresholds are 1. Do not change the default threshold.
target_removal1
target_removal2
Target removal controls test the efficiency of the stripping step after the extension reaction. In contrast to allele-specific extension, the control oligos are extended using the probe sequence as a template. This process generates labeled targets. The probe sequences are designed such that extension from the probe does not occur. All target removal controls result in low signal compared to the hybridization controls, indicating that the targets were removed efficiently after extension. Target removal controls are present in the Hybridization Buffer.
The Background for the same sample is close to or larger than either control.
The metric provided is Background/Control Intensity.
The default threshold is 1. Do not change the default threshold; however, the offset correction can be changed.
bisulfite_conversion1_green
bisulfite_conversion1_background_green
bisulfite_conversion1_red
bisulfite_conversion1_background_red
These controls assess the efficiency of bisulfite conversion of the genomic DNA. The Infinium Methylation probes query a [C/T] polymorphism created by bisulfite conversion of non-CpG cytosines in the genome.
These controls use Infinium I probe design and allele-specific single base extension to monitor efficiency of bisulfite conversion. If the bisulfite conversion reaction was successful, the "C" (Converted) probes matches the converted sequence and get extended. If the sample has unconverted DNA, the "U" (Unconverted) probes get extended. There are no underlying C bases in the primer landing sites, except for the query site itself.
The calculation is done in both the green and red channels separately to provide 2 unique sets of values:
Green Channel
Lowest value of C1 or C2 / Highest value of U1 or U2. The default threshold is 1. This value can be increased for some scanners.
Background/(U1, or U2). The default threshold is 1. Do not change the default threshold; however, the offset correction can be changed.
Red Channel
Lowest value of C3, 4, or 5 / Highest value of U3, 4, or 5. The default threshold is 1. This value can be increased for some scanners.
Background /(Highest value of U4, U5, or U6). The default threshold is 1. Do not change the default threshold; however, the offset correction can be changed.
bisulfite_conversion2
bisulfite_conversion2_background
These controls assess the efficiency of bisulfite conversion of the genomic DNA. The Infinium Methylation probes query a [C/T] polymorphism created by bisulfite conversion of non-CpG cytosines in the genome.
These controls use Infinium II probe design and single base extension to monitor efficiency of bisulfite conversion. If the bisulfite conversion reaction was successful, the "A" base gets incorporated and the probe has intensity in the red channel. If the sample has unconverted DNA, the "G" base gets incorporated across the unconverted cytosine, and the probe has elevated signal in the green channel.
The calculation is done using both channels for 1 set of numbers returned.
The following metrics are provided:
(Lowest of red C 1, 2, 3, or 4) / (Highest of green C 1, 2, 3, or 4). The default threshold is 1. This value can be increased for some scanners.
Background/(Highest C1, C2, C3, or C4 green). The default threshold is 1. Do not change the default threshold; however, the offset correction can be changed.
specificity1_green
specificity1_red
Specificity controls are designed to monitor potential nonspecific primer extension for Infinium I and Infinium II assay probes. Specificity controls are designed against nonpolymorphic T sites.
These controls are designed to monitor allele-specific extension for Infinium I probes. The methylation status of a particular cytosine is carried out following bisulfite treatment of DNA by using query probes for unmethylated and methylated state of each CpG locus. In assay oligo design, the A/T match corresponds to the unmethylated status of the interrogated C, and G/C match corresponds to the methylated status of C. G/T mismatch controls check for nonspecific detection of methylation signal over unmethylated background. PM controls correspond to A/T perfect match and give high signal. MM controls correspond to G/T mismatch and give low signal.
The metrics provided are the ratio of the lowest PM/highest MM in each channel.
The default threshold is 1. Do not change the default threshold.
specificity2
specificity2_background
Specificity controls are designed to monitor potential nonspecific primer extension for Infinium I and Infinium II assay probes. Specificity controls are designed against nonpolymorphic T sites.
These controls are designed to monitor extension specificity for Infinium II probes and check for potential nonspecific detection of methylation signal over unmethylated background. Specificity II probes incorporate the "A" base across the nonpolymorphic T and have intensity in the Red channel. If there was nonspecific incorporation of the "G" base, the probe has elevated signal in the Green channel.
The following metrics are provided:
(Lowest intensity of S1, S2, or S3 red) / (Highest intensity of S1, S2, or S3 green). The default threshold is 1. Do not change the default threshold.
Background/(Highest intensity S1, S2, S3, or S4 green). The default threshold is 1. Do not change the default threshold; however, the offset correction can be changed.
nonpolymorphic_green
nonpolymorphic_red
Nonpolymorphic controls test the overall performance of the assay, from amplification to detection, by querying a particular base in a nonpolymorphic region of the genome. They let you compare assay performance across different samples. One nonpolymorphic control has been designed for each of the 4 nucleotides (A, T, C, and G).
In the green channel, the lowest intensity of C or G is always greater than the highest intensity of A or T.
The metric provided is the (lowest intensity for C or G) /(highest intensity for A or T) for a single sample.
The default threshold is 5. This value can be increased for some scanners.
avg_green_raw
avg_red_raw
Average green and red raw signal for the given sample.
avg_green_norm
avg_red_norm
Average green and red signal after dye bias correction and noob normalization for the given sample.
ScanTime
The date (MM/DD/YY) and time (HH:MM) that the sample was scanned by the iScan system.
NProbes
Number of probes on the BeadChip, including SNP and CG probes
NPassDetection
Number of probes on the BeadChip that passed detection p-value at the threshold defined.
prop_probes_passing
The proportion of probes passing defined as the number of probes passing detection p-value divided by the total number of probes on the BeadChip.
passQC
1 = sample passed all QC metrics for the thresholds defined
0 = sample did not pass all QC metrics for the thresholds defined
failCodes
The list of parameters that failed QC for the thresholds defined.
The control metrics in the QC summary files are calculated as follows. The default value for background correction offset (x) of 3,000 can be modified and applies to all background calculations indicated with (bkg + x). Note that the table uses default thresholds for EPIC arrays as an example, and the default thresholds change with the methylation arrays. See section Threshold Adjustment for additional details.
Control
Calculation
Additional Information
Restoration Green > bkg
(Green/(bkg+x))> 0
If using the FFPE Restore kit, change the default threshold from 0 to 1.
bkg = Extension Green highest A or T intensity
Staining Green
Biotin High > Biotin Bkg
(High/Biotin Bkg) > 5
Staining Red
DNP High > DNP Bkg
(High/DNP Bkg) > 5
Extension Green Lowest CG/Highest AT
(C or G/A or T) > 5
Green channel—Lowest C or G intensity is used; highest A or T intensity is used.
Extension Red
Lowest AT/Highest CG
(A or T/C or G) > 5
Red channel—Lowest A or T intensity is used; highest C or G intensity is used.
Hybridization Green High > Medium > Low
(High/Med) > 1 (Med/Low) > 1
Target Removal Green ctrl 1 ≤ bkg
((bkg + x)/ctrl) > 1
bkg = Extension Green highest A or T intensity
Target Removal Green ctrl 2 ≤ bkg
((bkg + x)/ctrl) > 1
bkg = Extension Green highest A or T intensity
Bisulfite Conversion I Green
C1, 2 > U1, 2
(C/U) > 1
Lowest C intensity is used. Highest U intensity is used.
Bisulfite Conversion I Green
U ≤ bkg
((bkg + x)/U) > 1
For MSA arrays, the default is 0.5
Highest U intensity is used.
Green channel—bkg = Extension Green highest AT
Bisulfite Conversion I Red C3, 4, 5 > U3, 4, 5
(C/U) >1
Lowest C intensity is used. Highest U intensity is used.
Bisulfite Conversion I Red U ≤ bkg
((bkg + x)/U) > 1
For MSA arrays, the default is 0.5
Highest U intensity is used.
Red Channel—bkg = Extension Red highest CG
Bisulfite Conversion II C Red > C Green
(C Red/ C Green) > 1
For MSA arrays, the default is 0.5
Lowest C Red intensity is used. Highest C Green intensity is used.
Bisulfite Conversion II C green ≤ bkg
((bkg + x)/C Green) > 1
For MSA arrays, the default is 0.5
Highest C Green intensity is used.
Green channel—bkg = Extension Green highest AT
Specificity I Green PM > MM
(PM/MM) > 1
Lowest PM intensity is used. Highest MM intensity is used
Specificity I Red PM > MM
(PM/MM) > 1
Lowest PM intensity is used. Highest MM intensity is used
Specificity II
S Red > S Green
(S Red/ S Green) > 1
Lowest S Red intensity is used. Highest S Green intensity is used.
Specificity II
S Green ≤ bkg
((bkg + x)/ S green) > 1
bkg = Extension Green highest A or T intensity
Highest S Green intensity is used.
Nonpolymorphic Green Lowest CG/ Highest AT
(C or G/ A or T) > 5
Lowest C or G intensity is used; highest A or T intensity is used
For MSA arrays, the default threshold is 2.5
Nonpolymorphic Red Lowest AT/ Highest CG
(A or T/ C or G) >5
Lowest A or T intensity is used; highest C or G intensity is used
For MSA arrays, the default threshold is 3
Methylation Sample QC Summary Plots
The software produces methylation sample QC summary plots (sample_qc_summary.pdf) per analysis batch which provides visual depictions of two QC summary plots for quick visual review.
The file contains the following control plots:
Proportion of Probes Passing Threshold
Histogram of the proportion of probes passing the p-value detection threshold. Samples passing QC are shown in one color, and samples failing QC are shown in another color.
Principal Component Analysis (PCA)
Uses beta values for all analytical probes to compare samples. Principal component analysis (PCA) is applied to the beta values to reduce the dimensionality of the data to two “principal components” that reflect the most variation across samples. If more than 100 samples are used in the analysis, a random subset of 10,000 probes are used for the PCA analysis to reduce computational burden. PCA control plot assigns unique colors to each sample group defined by the IDAT Sample Sheet. If no groups were assigned, all samples will appear the same color. Sample groups may cluster together and can be used to explain some of the variation. Coordinates used to plot each sample in the PCA control plot are provided in the pcs.tsv.gz output file (see below).
Methylation Principal Component Summary
The software produces a methylation principal component summary file (pcs.tsv.gz) per analysis batch which provides principal component data for each sample within the batch. This can be used to identify the specific samples associated with points on the PCA control plot within the Methylation Sample QC Control Plots output file.
The files contain the following fields:
blank
BeadChip Barcode and Position ie 123456789101_R01C01
principal component 1
The variable of the first axis for the Principal Component Analysis
principal component 2
The variable of the second axis for the Principal Component Analysis
Sample_Group
Sample group defined by the user in the IDAT Sample Sheet. If no sample group was defined, all samples will show NA.
Methylation Manifest Files
The software produces two methylation manifest files
Manifest in Sesame format (probes.csv)
Additional information for control probes (controls.csv)
The probes.csv file has the following columns:
Probe_ID
This is a unique identifier for each probe. It corresponds to the IlmnID column in the standard Illumina manifest format or ctl_[AddressA_ID] for control probes.
U
This is corresponds to the AddressA_ID column in the standard Illumina manifest format.
M
This corresponds to the AddressB_ID column in the standard Illumina manifest format.
col
This is the color channel for Infinium I probes (R/G). For Infinium I probes, this column will be NA.
The controls.csv file has the following columns:
Address
The address of the probe
Type
The control probe type
Color_Channel
A color used to denote certain control probes in legacy software
Name
A human readable identifier for certain control probes
Probe_ID
This is a unique identifier for each probe. It corresponds to the IlmnID column in the standard Illumina manifest format or ctl_[AddressA_ID] for control probes.
Methylation Warning/Error Messages and Logs
The following scenarios result in a warning or error message:
Missing IDATs or manifest
Incorrect sample sheet formatting
Duplicate BeadChip Barcode and Position within the sample sheet
Missing control or assay probes
Missing required columns in the manifest
Unable to compute certain metrics
Examples of such notifications can include the following:
Log
Error
Type
Cause
write_samplesheet.log
No IDATs found
Error
No IDATs provided for analysis
format_samplesheet.log
No samples in sample sheet
Error
No samples in user’s sample sheet input
format_samplesheet.log
Sample sheet not correctly formatted
Error
Sample sheet is not in CSV format or header lines do not start with “<”
format_samplesheet.log
beadChipName and sampleSectionName columns are required for the sample sheet.
Error
Sample sheet does not contain required columns: beadChipName and sampleSectionName.
format_samplesheet.log
Warning: <Number> samples have duplicate Sample_ID
Warning
X lines in the sample sheet have duplicate <beadChipName>_<sampleSectionName>. Duplicates are dropped from analysis.
convert_manifest_ilmn_sesame.log
Missing control probes in manifest
Error
Missing “[Controls]” line in CSV manifest
convert_manifest_ilmn_sesame.log
Probe section not found
Error
Missing “[Assay]” line in CSV manifest
convert_manifest_ilmn_sesame.log
Missing required columns: IlmnID, AddressA_ID, AddressB_ID, Color_Channel
Error
Missing one of required columns in Assay section of manifest
convert_manifest_ilmn_sesame.log
Controls not formatted correctly. Must have 4 columns (Address,Type,Color_Channel,Name)
Error
Missing one of required columns in Control section of manifest
run_sesame_gs.log
Missing sample: <Sample_ID>
Error
Missing idats for a particular sample
run_sesame_gs.log
No scan time available
Warning
No scan time in idat
run_sesame_gs.log
Prep failed
Error
Dye bias correction or noob failure for sample
run_sesame_gs.log
Warning: missing control probe types <Missing probes>
Warning
Missing control probe types to compute a BACR metric. Metric will be set to NA.
run_sesame_gs.log
Warning: missing control probe names <Missing probe types>
Warning
Missing control probes to compute a BACR metric. Metric will be set to NA.
qc.log
No features, skipping PCA plot
Warning
No common betas found in all samples. This may occur if a sample has no signal intensity in the IDAT files.
QC metrics files
The DRAGEN Array CLI produces QC metrics CSV files per analysis batch to support quality review and downstream QC reporting. These files capture raw control-probe intensities and summarized per-sample control QC metrics. These files can be generated for any array-type using the qc call command, and they are also generated automatically with any genotype call command for genotyping arrays, including in cloud pipelines that use this command.
controls.raw_metrics.csv
Raw control-probe intensity file with one row per control probe measurement per sample. This file includes fields such as sample ID, control category, beadtype, control name, color channel, and green/red intensity values. It is used to support probe-level QC review and visualizations in the QC report.
controls.qc_metrics.csv
Summarized per-sample control QC metrics file with one row per sample. This file includes sample metadata and derived control QC metrics such as staining, extension, hybridization, target removal, stringency, non-specific binding, non-polymorphic, and other array-type-specific QC metrics. It is used by the QC report for sample-level QC evaluation.
These files are the required control-metrics inputs for the local qc report command.
The controls.raw_metrics.csv file contains the following fields.
SampleId
Unique sample identifier.
Category
High-level control category, such as Staining, Extension, Hybridization, Stringency, or Non-Polymorphic.
Beadtype
Control probe beadtype identifier from the array design.
Control
Human-readable control probe name, such as Biotin (High), DNP (Bgnd), or String (PM).
Color
Legacy control color annotation associated with the probe.
GreenIntensity
Raw green-channel intensity for the control probe measurement.
RedIntensity
Raw red-channel intensity for the control probe measurement.
The controls.qc_metrics.csv file contains the following fields, along with a set of QC metric columns.
SampleId
Unique sample identifier.
ImagingDate
Imaging date extracted from IDAT files.
SamplePlate
Sample plate extracted from IDAT files.
SampleWell
Sample well extracted from IDAT files.
ScannerId
iScan identifier extracted from IDAT files.
ScannerVersion
Scanner software version extracted from IDAT files.
The set of QC metric columns depends on the array type. Columns that do not apply to the given array type are omitted from the CSV. The metrics are calculated from the raw probe intensities as follows.
In the formulas below, bkg_grn is the highest green-channel intensity of Extension (A) or Extension (T), and bkg_red is the highest red-channel intensity of Extension (C) or Extension (G). The background-correction offset x is 3000 for calculations that use (bkg + x).
RestorationQC
Restoration green / (bkg_grn + x)
Restoration green / (bkg_grn + x)
If using the FFPE DNA Restore Kit, the restoration control identifies success of the FFPE restoration chemistry.
StainingGreenQC
Biotin (High) green / Biotin (Bgnd) green
Biotin (High) green / Biotin (Bkg) green
Staining controls are used to examine the efficiency of the staining step in both the red and green channels. These controls are independent of the hybridization and extension step.
The green channel shows a higher signal for biotin staining when compared to biotin background.
StainingRedQC
DNP (High) red / DNP (Bgnd) red
DNP (High) red / DNP (Bkg) red
Red channel equivalent metric for StainingGreenQC using DNP.
ExtensionGreenQC
Lowest Extension (C or G) green / Highest Extension (A or T) green
Lowest Extension (C or G) green / Highest Extension (A or T) green
Extension controls test the extension efficiency of A, T, C, and G nucleotides from a hairpin probe, and are therefore sample independent.
C and G extension is probed in green.
ExtensionRedQC
Lowest Extension (A or T) red / Highest Extension (C or G) red
Lowest Extension (A or T) red / Highest Extension (C or G) red
Red channel equivalent metric for ExtensionGreenQC.
A and T extension is probed in red.
HybridizationHighMediumQC
Hyb (High) green / Hyb (Medium) green
Hyb (High) green / Hyb (Medium) green
Hybridization controls test the overall performance of the Infinium Assay using synthetic targets instead of amplified DNA. These synthetic targets complement the sequence on the array, allowing the probe to extend on the synthetic target as a template. Synthetic targets are present in the Hybridization Buffer at 3 levels, monitoring the response from high-concentration (5 pM), medium concentration (1 pM), and low concentration (0.2 pM) targets. All bead type IDs result in signals with various intensities, corresponding to the concentrations of the initial synthetic targets.
The value for high concentration is always higher than medium and the value for medium concentration is always higher than low.
HybridizationMediumLowQC
Hyb (Medium) green / Hyb (Low) green
Hyb (Medium) green / Hyb (Low) green
Medium to low equivalent of HybridizationHighMediumQC
TargetRemovalIQC
(bkg_grn + x) / Target Removal green
(bkg_grn + x) / Target Removal 1 green
Target removal controls test the efficiency of the stripping step after the extension reaction. In contrast to allele-specific extension, the control oligos are extended using the probe sequence as a template. This process generates labeled targets. The probe sequences are designed such that extension from the probe does not occur. All target removal controls result in low signal compared to the hybridization controls, indicating that the targets were removed efficiently after extension. Target removal controls are present in the Hybridization Buffer.
The Background for the same sample should be close to or larger than either control.
TargetRemovalIIQC
—
(bkg_grn + x) / Target Removal 2 green
See Target Removal 1.
StringencyQC
String (PM) red / String (MM) red
—
In the red channel strong positive signals are expected for String (PM) data points, while String (MM) data points are expected to be at low levels approaching background levels.
NonSpecificBindingGreenQC
(bkg_grn + x) / Highest NSB (Bgnd) green
—
The Non-Specific Binding Controls test sample quality and specificity of the assay. The probe sequences for Non-specific Binding Controls are complementary to bacterial sequences, and signal intensities at background are expected under standard hybridization conditions in both channels.
NonSpecificBindingRedQC
(bkg_red + x) / Highest NSB (Bgnd) red
—
Red channel equivalent metric for NonSpecificBindingGreenQC.
NonPolymorphicGreenQC
Lowest NP (C or G) green / Highest NP (A or T) green
Lowest NP (C or G) green / Highest NP (A or T) green
The Non-Polymorphic Controls assess sample quality and the overall performance of the assay by querying non-polymorphic regions of the human genome.
Strong positive signals are expected for the green NP (C) and blue NP (G) data points, while the red NP (A) and purple NP (T) signals are expected to be at background levels.
NonPolymorphicRedQC
Lowest NP (A or T) red / Highest NP (C or G) red
Lowest NP (A or T) red / Highest NP (C or G) red
Red channel equivalent metric for NonPolymorphicGreenQC.
SpecificityIGreenQC
—
Lowest GT Mismatch 1–3 (PM) green / Highest GT Mismatch 1–3 (MM) green
Specificity I controls are designed to monitor potential nonspecific primer extension for Infinium I. Specificity controls are designed against nonpolymorphic T sites.
These controls are designed to monitor allele-specific extension for Infinium I probes. The methylation status of a particular cytosine is carried out following bisulfite treatment of DNA by using query probes for unmethylated and methylated state of each CpG locus. In assay oligo design, the A/T match corresponds to the unmethylated status of the interrogated C, and G/C match corresponds to the methylated status of C. G/T mismatch controls check for nonspecific detection of methylation signal over unmethylated background. PM controls correspond to A/T perfect match and give high signal. MM controls correspond to G/T mismatch and give low signal.
SpecificityIRedQC
—
Lowest GT Mismatch 4–6 (PM) red / Highest GT Mismatch 4–6 (MM) red
Red channel equivalent of SpecificityIGreenQC
SpecificityIIQC
—
Lowest Specificity II red / Highest Specificity II green
Specificity II are designed to monitor extension specificity for Infinium II probes and check for potential nonspecific detection of methylation signal over unmethylated background. Specificity II probes incorporate the "A" base across the nonpolymorphic T and have intensity in the Red channel. If there was nonspecific incorporation of the "G" base, the probe has elevated signal in the Green channel.
SpecificityIIBgQC
—
(bkg_grn + x) / Highest Specificity II green
See SpecificityIIQC. This metric ensures lack of nonspecific incorporation of the "G" base.
BisulfiteConversionIGreenQC
—
Lowest BS Conversion I-C1–C2 green / Highest BS Conversion I-U1–U2 green
These controls assess the efficiency of bisulfite conversion of the genomic DNA. The Infinium Methylation probes query a [C/T] polymorphism created by bisulfite conversion of non-CpG cytosines in the genome.
These controls use Infinium I probe design and allele-specific single base extension to monitor efficiency of bisulfite conversion. If the bisulfite conversion reaction was successful, the "C" (Converted) probes matches the converted sequence and get extended. If the sample has unconverted DNA, the "U" (Unconverted) probes get extended. There are no underlying C bases in the primer landing sites, except for the query site itself.
BisulfiteConversionIGreenBgQC
—
(bkg_grn + x) / Highest BS Conversion I-U1–U2 green
See BisulfiteConversionIGreenQC. This metric captures whether unconverted DNA is at background levels.
BisulfiteConversionIRedQC
—
Lowest BS Conversion I-C3–C5 red / Highest BS Conversion I-U3–U5 red
Red channel equivalent metric to BisulfiteConversionIGreenQC
BisulfiteConversionIRedBgQC
—
(bkg_red + x) / Highest BS Conversion I-U3–U5 red
Red channel equivalent metric to BisulfiteConversionIGreenBgQC.
BisulfiteConversionIIQC
—
Lowest BS Conversion II red / Highest BS Conversion II green
These controls use Infinium II probe design and single base extension to monitor efficiency of bisulfite conversion. If the bisulfite conversion reaction was successful, the "A" base gets incorporated and the probe has intensity in the red channel. If the sample has unconverted DNA, the "G" base gets incorporated across the unconverted cytosine, and the probe has elevated signal in the green channel.
BisulfiteConversionIIBgQC
—
(bkg_grn + x) / Highest BS Conversion II green
See BisulfiteConversionIIQC. This metric captures whether unconverted DNA is at background levels.
QC report
For local analysis, the qc report command generates a comprehensive QC report designed to facilitate quality control review of genotyping and DNA methylation array datasets. The output always includes an HTML report for interactive review, plus a sample QC table for downstream review.
In cloud analysis, this same QC report is automatically generated for the genotyping and cytogenetics pipelines.
For more information about the HTML report and QC metrics, see DRAGEN Array QC Report.
DRAGENArray_QC_Report_YYYY_MM_DD.html
Interactive HTML report intended to be distributable and viewable offline in a web browser. The report includes dashboards such as Control Dashboard, Automated QC, Sample QC Heatmaps, Trend Analysis, and a QC Metric Config menu for threshold customization. On local analysis, one report can combine multiple datasets for cross-run Trend Analysis. Current cloud reports are generated per dataset, so Trend Analysis summarizes a single dataset at a time.
DRAGENArray_QC_table_YYYY_MM_DD.<xlsx|csv>
Sample QC table (one row per sample) containing functional metrics (when available), derived control metrics, and raw control‑probe intensities. The file extension depends on --output-format (xlsx or csv).
When generating a QC report, the HTML report is always included. The QC table format is controlled by --output-format (default: xlsx).
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