Article Spotlight: GIInger™ supports prediction of HRD and PARPi response from shallow genomic profiles

Published on 02/07/2024

< 1 min read

Discover how a deep learning algorithm, GIInger™, leverages low-coverage sequencing data to identify homologous recombination deficiency (HRD)-induced genomic instability.

Explore this infographic summary to gain insights into the key findings from Pozzorini et al.’s publication on the GIIngerTM deep learning algorithm for prediction of HRD status and patient response to PARPi treatment in ovarian cancer. 

Click here to read the full publication.

02-2024-SG-GIInger-Manuscript-Infographic

Pozzorini C, Andre G, Coletta C, et al. GIInger predicts homologous recombination deficiency and patient response to PARPi treatment from shallow genomic profiles. Cell Rep Med. 2023 Dec 19;4(12):101344. doi: 10.1016/j.xcrm.2023.101344.

GIInger™ data were generated using the SOPHiA DDM™ Dx HRD Solution, available as a CE-IVD product for In Vitro Diagnostic Use in Europe and Turkey only. SOPHiA GENETICS products are for Research Use Only and not for use in diagnostic procedures unless specified otherwise.

About the Author

Niamh O’Connor

Proposition and Content Lead

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