DRAGEN (Dynamic Read Analysis for GENomics) Array secondary analysis is a powerful bioinformatics software for Illumina Infinium array-based assays. DRAGEN Array uses cutting-edge data analysis tools to provide accurate, comprehensive, and highly efficient secondary analysis to maximize genomic insights and meet your research needs across multiple applications.

DRAGEN Array is offered as a local package with command-line interface (no specialized server or hardware required) and as a cloud-based package with an intuitive graphical user interface, as summerized in the table below.

This product documentation describes the installation and setup, analysis execution, and result outputs. For the latest updates and release details, see the . See for additional details on DRAGEN Array genotyping, PGx CNV calling and PGx star allele annotation.

The following Types of Analysis are currently supported by DRAGEN Array:

• DRAGEN Array – Genotyping

• DRAGEN Array – PGx – CNV calling

• DRAGEN Array – PGx – Star allele annotation

• DRAGEN Array - Methylation QC

DRAGEN Array – Genotyping

DRAGEN Array - PGx – CNV calling

DRAGEN Array – PGx – Star Allele Annotation

DRAGEN Array – Methylation QC

RELEASE DATE

March 2024

RELEASE HIGHLIGHTS

The version history for DRAGEN Array product documentation:

DRAGEN Array star allele calling leverages the star allele definitions provided by PharmVar and PharmGKB. DRAGEN Array star allele phenotype annotation, using the “star-alle annotate” command, is achieved through direct lookup into public PGx guidelines CPIC or DPWG, which is selected by the user when running DRAGEN Array.

See table below for details of the data sources.

DRAGEN Array Cloud Analysis Overview

DRAGEN Array Cloud utilizes the user-friendly graphical interface of BaseSpace Sequence Hub to simplify DRAGEN Array analysis setup and kickoff. Optional integration with the iScan System allows data to be streamed directly from the instrument to the cloud platform. Analysis data is stored on the Illumina Connected Platform providing secure storage for both microarray and sequencing data.

Getting Started

The following prerequisites are needed to get started with DRAGEN Array Cloud:

• Illumina Connected Analytics subscription: An ICA Basic, Professional or Enterprise subscription can be used which include access to BaseSpace Sequence Hub. Follow the to register the software.

• Workgroup setup: Workgroups must be created before login. Using a workgroup allows all members of the workgroup to share access to resources, analyses, and data. Learn more about .

  • Designating a workgroup as ‘Collaborative’ allows projects to be shared with collaborators or Illumina Tech Support to assist with troubleshooting. To create a collaborative workgroup, select the Enable collaborators outside of this domain checkbox during workgroup creation.

Note: Accessioning BeadChips before scanning and starting analysis is no longer a required step and has been automated within the system.

Running Analysis

Before beginning analysis, ensure workgroup context is being used so analysis can be viewed by all members of your workgroup. The name of your workgroup should appear in the top right corner.

Use the following steps to run the Microarray Analysis Setup on BaseSpace Sequence Hub:

1. Select the Runs tab

2. Select New Run

3. Select Microarray Analysis Setup

4. Enter the Analysis Name (Figure 1)

• DRAGEN Array - Genotyping provides flexibility for turning off/on specific output files and adjusting GenCall score cutoff. Its recommended to turn off VCF output for non-human species and Final Report output for large sample numbers.

• DRAGEN Array - Methylation - QC provides options to adjust thresholds as detailed in section DRAGEN Array Methylation QC .

1. Select your preferred option in the Configuration Settings drop-down menu Configuration setup will vary based on the Type of Analysis selected. More details are available in section .

2. Select Next

3. Select either Import Sample Sheet, Select BeadChips, or Import IDAT Files (Figure 3)

• Import Sample Sheet presents a link to upload sample sheet. Users may download a template sample sheet by selecting the Download Template link.

• Select BeadChips allows users to select BeadChips from the displayed list of available BeadChips. If selecting specific samples within the BeadChip is desired the Import Sample Sheet option should be used.

• Import IDAT Files allows users to upload the IDAT files from a local folder to the cloud platform for use with the current and future analyses by users within the same workgroup.

1. Select Launch Analysis

View Outputs

1. On the Analyses tab, view the analysis status, e.g., initializing or complete.

2. After the analysis is complete, select the analysis and select the Files tab.

3. From the Files tab, select the Output folder.

DRAGEN Array Methylation QC

Threshold Adjustment

When using DRAGEN Array – Methylation – QC cloud analysis type, additional customization options will appear after product files are selected within Configuration Settings. Adjustments to these thresholds will be saved as part of the Configuration Setting. Thresholds can be adjusted based on study objectives. Adjusting thresholds will impact the pass or fail status of samples in the output files.

Illumina recommends thresholds for MethylationEPIC v1 & v2 and Methylation Screening Array (MSA). Users may use these thresholds as a starting point when defining thresholds for their custom or semi-custom BeadChip or other Infinium Methylation arrays. Further tuning may be required based on BeadChip used, laboratory conditions, iScan settings, bisulfite conversion methods, FPPE sample type, etc. A dataset deemed acceptable to the user based on proportion probes passing can be used for these additional threshold adjustments.

To customize thresholds, use the toggle to allow additional thresholds to be displayed and adjust as desired by typing in a numeric value or using the arrows to adjust up or down. Further detail of these thresholds including calculation method can be found in the section.

The recommended thresholds are pre-set within the software for MethylationEPIC and Methylation Screening Array with the following values:

The first 21 rows in the tables correspond to the 21 control metrics used in the methylation sample QC. See section for details.

DRAGEN Array Methylation QC and GenomeStudio Methylation Module Differences

DRAGEN Array Methylation QC software provides automated methylation sample QC using assay control probes on the Infinium Methylation Arrays. Unlike the manual visual QC in GenomeStudio, DRAGEN Array ultilizes 21 numerical metrics defined based on the control probes and uses standard thresholds to determine pass/fail status of a sample. Unlike GenomeStuio, probe detection rate (proportion of probes passing at a given p-value threshold) is not utilized to determine sample pass/fail status in DRAGEN Array.

DRAGEN Array Methylation QC performs background normalization, dye bias correction, and detection p-value calculation differently in comparison to the GenomeStudio Methylation module, leading to differences in probe detection p-values and detection rates. For the GenomeStudio Methylation Module, non-cancer samples at standard DNA input typically have detection rate > 96%. The detection rates from DRAGEN Array Methylation QC are typically lower compared to GenomeStudio, because the detection p-value from DRAGEN Array is more stringent than that from the GenomeStudio Methylation Module. The table below shows example detection rates from the DRAGEN Array Methylation QC software from MSA (Methylation Screening Array) datasets.

Note that only samples passing QC are included and all samples are at or above 50ng DNA input. Detection p-value threshold 0.05.

Known Issues

DRAGEN Array Methylation QC cloud v1.0.0 is released on BSSH version 7.21. There are two known issues with the BSSH UI that impact Methylation QC analyses.

• Sample sheets with greater than 144 samples lead to undefined failures. The issue impact methylation QC as well as other analysis types. To process larger sample numbers (up to 1152 for DRAGEN Array methylation QC), samples can be separated into batches of 144 when using sample sheet, or by selecting BeadChips directly from the BeadChip table.

• Uploading custom methylation BPM manifests results in upload failure. The issue only impact the methylation QC and not other analysis types. For assistance uploading these manifests, contact .

Troubleshooting and Additional Support

Troubleshooting iScan integration

The firewall protects the iScan control computer by filtering incoming traffic to remove potential threats. The firewall is enabled by default to block all inbound connections. Keep the firewall enabled and allow outbound connections.

For the instrument to connect to BaseSpace Sequence Hub, you will need to add regional platform endpoints and instrument specific endpoints to the allow list on your firewall. Regional endpoints and further detail can be found in .

The following table shows the applicable endpoints for the iScan.

Sharing a project

Project sharing allows a user to share files with users outside the workgroup for collaboration or with Illumina Tech Support for troubleshooting. To share a project on BaseSpace Sequence Hub, first set the Workgroup type as ‘Collaborative’ during , and then use the following steps to obtain a link to your project. The project can then be accessed by anyone with the link. All files in the project are shared.

1. Navigate to the Projects tab

2. Click the button next to the desired project

3. Select the Share button above to list (Figure 3)

4. Select the Get Link Option to Activate a link for the project

Note: The project owner maintains ownership and write access. If project owner deletes the data, the collaborators lose access to it.

Technical Support

For support, questions, and feedback on DRAGEN Array, please contact Illumina Tech Support at .

Additional Resources

The following versions of DRAGEN Array have been released:

1. Is DRAGEN Array analysis a local (on-premises) or cloud solution? DRAGEN Array analysis is available locally (on-premises) and cloud.\

   DRAGEN Array Local Analysis utilizes a command-line interface for power users to have granular control and flexibility to support large scale microarray genomic studies. Deployed on Windows or Linux operating systems, the local package is CPU-based and does not require a specialized server or hardware.\

   DRAGEN Array Cloud Analysis utilizes the user-friendly, graphical interface of BaseSpace Sequence Hub to simplify analysis setup and kickoff.\

2. Which Infinium arrays is DRAGEN Array compatible with? Genotyping: DRAGEN Array can produce GTC files for any Infinium genotyping array. For customers interested in obtaining a genotyping VCF file, any human genotyping array is supported. Conversion to VCF requires a FASTA file input. Illumina provides FASTA files for human genome build 37 and 38 on the support site.\

   Pharmacogenomics: Global Diversity Array with Enhanced PGx is supported for PGx CNV calling and star allele calling. Manifest version E and later should be used.\

3. How many samples are needed per analysis? Genotyping: As few as one sample can be used for genotyping. Multiple analysis batches can be kicked off and run in parallel.\

   Pharmacogenomics: A minimum of 24 samples is required for PGx CNV calling with 22 passing QC. Passing QC is defined as Log R Dev < 0.2. 96 samples are recommended for the most accurate CNV results. Multiple analysis batches can be kicked off and run in parallel.\

4. Which PGx CNVs and star alleles are available? Please refer to the DRAGEN Array .\

5. Where can I find demo data? Demo data is available in BaseSpace under the “Demo Data” section. All array data starts with “iScan:” and includes the name of the type of analysis. Supported types of analysis can be found in the section.\

RELEASE DATE

December 2023

RELEASE HIGHLIGHTS

• Improved star allele calling accuracy for Global Diversity Array with enhanced PGx (GDA-ePGx) BeadChips.

• Reports star allele calls with quality scores for greater transparency and confidence.

• Provides missing variant reporting to improve data quality.

NEW FEATURES IN DETAIL

• Star Allele Calling

  • Star allele calling for genes listed in

    • For in-silico datasets, call rate ≥99%, diplotyping accuracy ≥ 90%

KNOWN ISSUES

• Corrupt or invalid GTC files will abort with an error instead of skipping. The corrupt or invalid GTC files will need to be removed before proceeding.

• In the gtc-to-vcf subcommand a mismatch between BPM and CSV manifests will not cause the command to abort with an error. The mismatch will need to be addressed before proceeding.

• For gtc-to-vcf, multi-allelic variants designed with multiple assays might not always collapse into one variant correctly and be reported as two separate variants instead. Some indel variants are missing from SNV VCF due to mapping issue between the designed indels and the reference genome.

KNOWN LIMITATIONS

• PGx CNV calling and star allele calling and annotation were only validated and intended to be used with GDA_PGx_E2 product files.

• Using subcommands “unsquash-duplicates” and “filter loci” during gtc-to-vcf conversion should not be used when star allele calling is desired.

• Only CPIC guidelines are available for star allele annotation (metabolizer status calling) for the cloud offering. For local, CPIC and DPWG are available.

Copy number variation can be detected for genes and regions listed below. The chromosome locations are GRCh38 based.

The following section describes the input files required by DRAGEN Array.

IDAT Files

For each sample a pair of raw intensity files (.idat) are generated from the iScan System or NextSeq550 (for non-methylation arrays). They provide intensities in the red and green channels for each probe on the Infinium array.

An IDAT file is identified by the BeadChip Barcode (12-digit unique Sentrix ID, i.e. 123456789101), BeadChip Position (row and column of the sample, i.e. R01C01), and Grn (Green) or Red for the specific channel.

The genes and star alleles listed below can be detected by DRAGEN Array v1.0 if available on the microarray. Known and novel star alleles not in the below list will not be reported. Star allele definitions are sourced from PharmVar and PharmGKB.

DRAGEN Array Local Overview

DRAGEN Array provides accurate, comprehensive, and efficient analysis of Infinium microarray data. The local command-line interface makes it easy for power users to have granular control and flexibility to support large scale microarray genomic studies.

Getting Started

DRAGEN Array Local utilizes a command-line interface which allows full user control of software functionality and easy automation of tasks. The software is designed to be used by power users and bioinformaticians. If new to using command-line interface, please review the .

Computing Requirements

Before downloading and installing the software, ensure the following specifications are met for best performance:

Quota Specifications

The star-allele call command in DRAGEN Array Local requires quota to run. The quota is charged per sample analyzed and can be purchased on the . Quota is used for all samples analyzed including re-analysis or low-quality samples.

The credential provided in the activation email after purchasing should be used as an input to the star-allele call command through the "--license-server-url" option. During runtime, the will record the remaining quota at the beginning and the end of the analysis.

Internet is required to do a software license check and ensure paid quota is available for all samples in the analysis batch. For the software license check, the following endpoint is used: license.edicogenome.com.

Installation

Please follow the steps below to install the software on your compute infrastructure:

1. Click on the DRAGEN Array v1.0 installation package for the platform of your choice. Installers for Windows and Linux are available on the . Once download is completed, move the DRAGEN Array v1.0 installation package to the desired folder. Administrative permissions may be required for system folders, for example /usr/local/bin for Linux, and C:\Program Files for Windows. Note: Throughout the remaining of the document, Linux will be assumed in the examples.\

2. Unzip and extract the package. The executable can be found in the dragena subfolder of the software download after extraction.

The version of the software will be displayed in the terminal window when the installation was successful.

Run DRAGEN Array Local

For CNV PGx analysis, a minimum of 24 samples is required to run analysis. For a successful analysis, 22 samples must pass QC defined as having log R dev < 0.2. With a standard hardware specification in section , up to 500 GDA-ePGx samples can be processed per analysis batch.

For genotyping analysis, there is no sample minimum required to run analysis.

To optimize performance of the targeted PGx CNV caller and minimize batch effect, it is recommended to:

• Analyze samples that were processed together in one batch

• Avoid combining sample batches processed on different reagent lots.

• Analyze batches of 96 samples or more

• Use the CN Model and PGx Database File provided as part of the standard product files

Quick Start

Use the following instructions to start the full PGx analysis, covering genotyping, PGx CNV and PGx star allele calling. Refer to for parameters for all commands.

Review section for information on input files to use, sample minimums per analysis type and other best practices.

Command examples show analysis for a Linux system using folders instead of sample sheets. For Windows users, make sure to substitute the file paths in the commands following windows conventions, e.g., using backslash (\) instead of forward-slash (/). A sample sheet can be used to select specific samples out of a folder.

1. Open a command prompt (Windows) or terminal window (Linux) and navigate to the directory where the software was installed. Or a different, desired directory if the executable was added to the PATH environmental variable.

2. Use the genotype call command to call genotypes and generate GTC files using IDAT files as input. dragena genotype call --bpm-manifest /user/productfiles/manifest.bpm --cluster-file /user/productfiles/clusterfile.egt –-idat-folder /user/IDATs –-output-folder /user/gtc

3. Use the genotype gtc-to-vcf command to create SNV VCF files from the GTC files generated by the genotype call command. dragena genotype gtc-to-vcf --bpm-manifest /user/productfiles/manifest.bpm --csv-manifest /user/productfiles/manifest.csv --genome-fasta-file /user/productfiles/genome.fa --gtc-folder /user/gtc --output-folder /user/vcf

Command Index

Use the following syntax when using the command-line interface:

dragena [command] [required parameters] [optional parameters]

copy-number

The root command for actions that act on copy number variants.

copy-number call

The command used to call copy number variants. A batch of 24 samples or more are required for analysis. For a successful analysis, 22 samples must pass QC defined as having log R dev < 0.2.

copy-number help

Displays help information for a copy-number command.

copy-number train

Trains copy number (CN) model for a set of samples. Generate a new CN model if using a customized cluster file (.egt) optimized for the specific data set.

• Execute the train command using the data sets that were used to optimize the cluster file.

• To use a CN model generated by the train command, the mask file for the manifest must be saved in the same directory as the manifest.

• A minimum of 96 samples is required to use the copy-number train command. For optimal performance, at least 150 is recommended.

See for further details.

copy-number version

Displays version information for copy-number command.

genotype

The root command for genotype calling.

genotype call

Determines genotype calls (GTC) from IDAT files.

genotype gtc-to-bedgraph

Converts GTC to BedGraph files, producing BedGraph formatted visualization files from the log R ratio data contained in the GTC intermediate files.

genotype gtc-to-vcf

Converts GTC to . The command is only applicable for produced by DRAGEN Array.

genotype help

Displays the help information for a genotype command.

genotype version

Displays current DRAGEN Array Local version.

help

Displays the help information.

version

Displays current DRAGEN Array Local version.

star-allele

The root command PGx star allele calling.

star-allele help

Displays help information for a star-allele command.

star-allele version

Displays version information for star-allele.

star-allele call

Calls PGx star allele diplotypes. The SNV VCF files should be generated using the DRAGEN Array gtc-to-vcf command with unsquash-duplicates off (default) and without filter loci.

star-allele annotate

Annotates and summarizes the star-alleles, specifically for metabolizer statuses and outputs in a consolidated JSON report. Metatolizer status is determined through direct lookup into public PGx guidelines CPIC or DPWG as specified by the user.

Troubleshooting and Additional Support

Tips for using the Command-line interface

DRAGEN Array Local utilizes a command-line interface which allows full user control of software functionality and easy automation of tasks. The software is designed to be used by power users and bioinformaticians.

When using command-line consider the following tips:

• Spaces cannot be part of a file name in a command. If the file name has spaces, use quotes around the file name

• To correct a typing error in a previously entered command, use the up arrow to repeat the previous command, then correct the error before re-entering it.

• Double check the command. Misspelling, extra, or missing dashes, etc. will cause the command to be unrecognizable by the software.

Optimizing cluster files and copy number models

A (.egt) contains the cluster positions of every probe used for genotyping analysis. Illumina provides a standard cluster file for all commercial Infinium BeadChips. It may be desirable to create a custom cluster file if the one provided does not fit the data well or if a semi-custom or custom BeadChip, that do not come with a cluster file, are used. is the software used to create custom cluster files.

To facilitate the review and optimization of PGx variant GenTrain cluster positions, a GenomeStudio auxiliary file is provided for each PGx Array product through the and array product files page, e.g. . The auxiliary file is a tab-delimited text file that can be imported into GenomeStudio through Column Import. The file contains the Infinium Assay to PGx star allele mapping, covering the variants involved in DRAGEN Array PGx star allele calling.

When updating the cluster file for pharmacogenomic applications, understand the specifications for the copy number model file before beginning.

Before creating a custom cluster file, review the , the , and .

A (.dat) contains the data needed to make accurate copy number calls for pharmacogenomics. This file is used in the creation CNV VCFs which are inputs to the star allele calling command. Illumina provides a standard CN model file for all commercial PGx Infinium BeadChips. If it is determined the cluster file needs to be customized, the CN Model File should also be updated using the copy-number train command available with DRAGEN Array Local only. Review the for details of this command.

To retrain the CN model file, 96 samples must be used at minimum with 90 of those samples passing QC defined as Log R Dev less than or equal to 0.2. It is recommended to train with at least 150 samples. A greater number of samples can be advantageous, but diminishing returns and longer computation times are seen after 3,000 samples.

It is recommended to manually QC the training samples and remove samples that have Log R Dev > 0.2, call rate < 0.99, or TGA Control probe < 1.0 so only the highest quality sample are used in the training. The same samples used to create the new cluster file should be used to retrain the CN Model. To minimize batch effect in the training sample set, the samples should be analyzed in as few batches as possible and come from the same reagent lots.

The copy-number train algorithm is designed with the assumption that the copy number distribution resembles the standard population distributions. This ensures the updated CN model file is representative of the normal populations in which it will be used to calculate copy number for key pharmacogenomic targets.

Pharmacogenomic analysis for semi-custom arrays

Semi-custom arrays add additional content or other pre-designed to enhance the commercial array content. This additional content can be analyzed for to obtain information on SNV and indel calls.

For , PGx CNV and star allele calls are limited to content included on the commercial Infinium PGx arrays. Additional semi-custom content will not be included in the pharmacogenomic results.

When designing a semi-custom array using a commercial Infinium PGx array backbone, such as the Global Diversity Array with enhanced PGx, it is important to retain all backbone content in the design as removing content could decrease the quality of result.

Pharmacogenomic analysis for semi-custom arrays should be run using . The genotype call, copy-number call, and star-allele call commands should all be run using the commercial Infinium PGx array product files.

The following section describes the outputs produced by DRAGEN Array.

CNV VCF File

DRAGEN Array produces one 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 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 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 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 CNV VCF output file includes the following content.

##fileformat=VCFv4.1

##source=dragena 1.0.0

##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">

##CNVOverallPloidy=1.8

##CNVGCCorrect=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:chr16:28615068:28623382 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 2:1.01191145130511

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 GenCell score (GS), B Allele Frequency (BAF), and Log R Ratio (LRR) per variant.

Certain SNV and indel calls can be skipped when reported in the VCF. Skipped data can include unmapped loci, intensity-only probes used for CNV identification, and indels that do not map back to the genome. See 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 . To view these files as plain text, they can be uncompressed with 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.

##fileformat=VCFv4.1

##source=dragena 1.0.0

##genomeBuild=38

##reference=file:///genomes/38/genome.fa

##FORMAT=<ID=GT,Number=1,Type=String,Description="Genotype">

##FORMAT=<ID=GS,Number=1,Type=Float,Description="GenCall score. For merged multi-assay or multi-allelic records, min GenCall score is reported.">

##FORMAT=<ID=BAF,Number=1,Type=Float,Description="B Allele Frequency">

##FORMAT=<ID=LRR,Number=1,Type=Float,Description="LogR ratio">

##contig=<ID=1,length=248956422>

##contig=<ID=2,length=242193529>

##contig=<ID=3,length=198295559>

##contig=<ID=4,length=190214555>

##contig=<ID=5,length=181538259>

##contig=<ID=6,length=170805979>

##contig=<ID=7,length=159345973>

##contig=<ID=8,length=145138636>

##contig=<ID=9,length=138394717>

##contig=<ID=10,length=133797422>

##contig=<ID=11,length=135086622>

##contig=<ID=12,length=133275309>

##contig=<ID=13,length=114364328>

##contig=<ID=14,length=107043718>

##contig=<ID=15,length=101991189>

##contig=<ID=16,length=90338345>

##contig=<ID=17,length=83257441>

##contig=<ID=18,length=80373285>

##contig=<ID=19,length=58617616>

##contig=<ID=20,length=64444167>

##contig=<ID=21,length=46709983>

##contig=<ID=22,length=50818468>

##contig=<ID=MT,length=16569>

##contig=<ID=X,length=156040895>

##contig=<ID=Y,length=57227415>

#CHROM POS ID REF ALT QUAL FILTER INFO FORMAT 202937470021_R06C01

1 2290399 rs878093 G A . PASS . GT:GS:BAF:LRR 0/1:0.7923:0.50724137:0.14730307

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 .

BedGraph File

The BedGraph file contains the log R ratios from the genotyping algorithm for use in visual tools.

Star Allele CSV File

The Star Allele CSV file is an intermediate file generated by the star-allele call command and serves as the input to the star-allele annotate command. It 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 Star Allele 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 star_allele.csv file contains the following details per sample:

Below is an example of the first 4 columns from a star allele CSV file:

Sample,Rank,Gene or Variant,Type,Solution

204650490282_R02C01,1,CYP2C9,Haplotype,*9/*11

204650490282_R02C01,1,CYP2C19,Haplotype,*2/*10

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

• Sample Folder

• Autosomal Call Rate

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.

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:

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 .

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:

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:

Star allele JSON File

The star allele JSON file is produced per sample. It contains the fields present in the as well as additional meta data and annotations.

Fields included in the star allele JSON header are described below.

Fields included in the star allele call (locusAnnotations) information are described below.

Example of JSON file content:

{

"softwareVersion": "dragena 1.0.0",

"genomeBuild": "hg38",

"databaseSources": "PharmVar Version: 6.0.5, PharmGKB Database Version: Snapshot-2023.08.30, CPIC Database Version: 1.30.0",

"mappingFile": "gda_mapping_53e0931.zip",

"pgxGuideline": "CPIC",

"sampleId": "204619760027_R01C01",

"locusAnnotations": [

{

"gene": "CYP2C9",

"callType": "Star Allele",

"genotype": "*1/*1",

"activityScore": "2",

"phenotype": "Normal Metabolizer",

"qualityScore": "0.9999",

"rawScore": "0.9999",

"supportingVariants": "Complete: *1 ( )",

"candidateSolutions": [

{

"rank": 1,

"genotype": "*1/*1",

"activityScore": "2",

"phenotype": "Normal Metabolizer",

"qualityScore": 0.9999,

"rawScore": 0.9999,

"alleles": [

{

"solutionLong": "Complete: *1",

"supportingVariants": "Complete: *1 ( )",

"missingVariants": "Complete: *1 ( )",

"collapsedAlleles": "Complete: *1 ( )"

}

],

"copyNumberRegions": "p5,exon.1,intron.1,exon.2,intron.2,exon.3,intron.3,exon.4,intron.4,exon.5,intron.5,exon.6,intron.6,exon.7,intron.7,exon.8,intron.8,exon.9,p3",

"copyNumberSolution": "2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2"

}

],

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 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.

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 Control 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:

The control metrics in the QC summary files are calculated as following. 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 example, the default thresholds changes with the methylation arrays. See section for additional details.

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:

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:

Methylation Manifest Files

The software produces two methylation manifest files

1. Manifest in Sesame format (probes.csv)

2. Additional information for control probes (controls.csv)

The probes.csv file has the following columns:

The controls.csv file has the following columns:

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

Examples of such notifications can include the following:

RELEASE DATE

May 2024

RELEASE HIGHLIGHTS

• Adjustable thresholds to determine pass/fail status

• Data summary plots for a quick visual check of each analysis batch

• Determining detection p-value, beta-values, and m-values from each methylation sample

• Deployment on BaseSpace™ Sequence Hub user interface for easy analysis kickoff

NEW FEATURES IN DETAIL

• Adjustable thresholds for 21 built in controls, p-value detection, proportion probes passing, and offset correction within BaseSpace Sequence Hub to customize for user’s study needs

  • Thresholds are used to assign pass (1) or fail (0) status to each sample

    • Failed metrics can be highlighted for easy viewing

KNOWN ISSUES

KNOWN LIMITATIONS

• Standard thresholds may not be applicable for all discontinued, semi-custom or custom BeadChips and IDATs originating from NextSeq550

• Built-in controls may not be available on all discontinued, semi-custom or custom BeadChips