> For the complete documentation index, see [llms.txt](https://help.tso500software.illumina.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://help.tso500software.illumina.com/dragen-tso-500-guides/mtap-spike-in-resources/supplemental-cnv-analysis-using-dragen-enrichment.md). # Supplemental CNV analysis using DRAGEN Enrichment ## Overview and Prerequisites This page describes use of DRAGEN Enrichment analysis to extend TSO 500 to additional genomic targets captured with spiked-in probes. Specifically, it describes the parameters necessary for CNV analysis. For general DRAGEN Enrichment app usage, input requirements, and supported references, refer to [DRAGEN Enrichment BSSH App Support](https://help.connected.illumina.com/dragen/dragen-v4.5/product-guides/dragen-v4.5/dragen-apps/dragen-enrichment-bssh-app). This workflow has been tested on DRAGEN Enrichment 4.4.4 and 4.4.6 (with TSO 500 data that includes coverage from *MTAP* spike-in add-on probes) and produces the same results using both versions. Input requirements are: 1. FASTQ files from a completed TSO 500 analysis or independently run [BCL Convert](/dragen-tso-500-guides/mtap-spike-in-resources/bcl-conversion-for-supplementary-analysis.md) pipeline 2. The resource files discussed below, such as those provided for [*MTAP* spike-in](/dragen-tso-500-guides/mtap-spike-in-resources/mtap-add-on-workflow-resources.md), and/or self generated (such as your own panel of normals (PON), which can be generated using [this app](https://www.illumina.com/products/by-type/informatics-products/basespace-sequence-hub/apps/dragen-baseline-builder.html); best practices are discussed [here](https://help.dragen.illumina.com/dragen-v4.4/product-guide/dragen-v4.4/dragen-dna-pipeline/cnv-calling/additional-documentation/cnv-preprocessing#panel-of-normals)). ## Instructions for Running on BSSH Launch the [DRAGEN Enrichment BSSH App 4.4.6](https://ilmn-tso500.basespace.illumina.com/apps/18134116) and configure as indicated below and with the appropriate resource files (for instance, those for [*MTAP* spike-in](/dragen-tso-500-guides/mtap-spike-in-resources/mtap-add-on-workflow-resources.md)). For all other app fields, use DRAGEN Enrichment defaults. ### DRAGEN Enrichment Settings | Parameter | Selection | | ------------------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Input FASTQs | Attach the same FASTQ files used for (or generated by) TSO 500 analysis | | Variant Caller Mode | Somatic | | Reference | Select the reference that matches the spike-in resource bundle (e.g., for *MTAP* spike-in, Homo Sapiens \[NCBI] hs37d5 with chr prefix v5) | | Targeted Regions | Custom BED | | Custom Target BED File | Provide the bed file for the regions targeted by the spiked-in probes, including any targeted control sequences | | Systematic Noise Filter (under Somatic Variant Calling) | Uncheck | | Duplicate Marking (under Advanced Settings) | Uncheck | | Additional DRAGEN Command-line Arguments | Check the acknowledgement and enter command-line arguments as specified in the resource bundle. Note that this field accepts command-line arguments without verification of correctness or applicability. | | Additional Resource File | Provide additional resource files as necessary for the supplementary analysis. For *MTAP* spike-in, for instance, this includes the target BED file, BED files for QC and for segment mean calling boundaries, and a panel of normals counts file. | ## Running DRAGEN Enrichment on Local DRAGEN Server See specific resource pages, such as for [*MTAP* spike-in](/dragen-tso-500-guides/mtap-spike-in-resources/mtap-add-on-workflow-resources.md), for full command line arguments. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. 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