Abstract

Manual interpretation of variants remains rate limiting in precision oncology. The increasing scale and complexity of molecular data generated from comprehensive sequencing of cancer samples requires advanced interpretative platforms as precision oncology expands beyond individual patients to entire populations. To address this unmet need, we introduce a Platform for Oncogenomic Reporting and Interpretation (PORI), comprising an analytic framework that facilitates the interpretation and reporting of somatic variants in cancer. PORI integrates reporting and graph knowledge base tools combined with support for manual curation at the reporting stage. PORI represents an open-source platform alternative to commercial reporting solutions suitable for comprehensive genomic data sets in precision oncology. We demonstrate the utility of PORI by matching 9,961 pan-cancer genome atlas tumours to the graph knowledge base, calculating therapeutically informative alterations, and making available reports describing select individual samples.

Highlights

  • Manual interpretation of variants remains rate limiting in precision oncology

  • Despite previous work demonstrating improvements in clinical comprehension of complex genomic data using interactive over static reports[19], there are currently no open-source web applications for reporting in precision oncology

  • We present a fully open-source research platform that integrates variant annotation through knowledge base matching into a precision oncology workflow and provides users a reporting interface to curate, edit, and interact with the resulting data

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Summary

Introduction

The increasing scale and complexity of molecular data generated from comprehensive sequencing of cancer samples requires advanced interpretative platforms as precision oncology expands beyond individual patients to entire populations. Despite the increasing availability of publicly accessible knowledge bases, these resources are distributed across a broad landscape of clinical and biological knowledge that is often disjointed and of varying structure Integration of these tools into a reporting workflow to improve coverage[12] is essential, yet left largely to individual users. We present a fully open-source research platform that integrates variant annotation through knowledge base matching into a precision oncology workflow and provides users a reporting interface to curate, edit, and interact with the resulting data

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