MiMSI

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UID: 11463

Author(s): Jayakumaran, Gowtham*, Ziegler, John Scott*, Biederstedt, Evan, Rana, Satshil* * MSK affiliated

Description: Description from GitHub:

"Microsatellite Instability (MSI) is a phenotypic measure of deficiencies in DNA mismatch repair (MMR) machinery. These deficiencies lead to replication slippage in microsatellite regions, resulting in varying lengths of deletions in tumor samples. Detecting proper MSI status with high sensitivity and specificity in cancer patients is a critical priority in clinical genomics, especially after the FDA's approval of a targeted therapy for advanced cancer patients with MSI-high phenotype regardless of cancer type.

Current methods that determine MSI status using sequencing data compare the distributions of nucleotide deletion lengths between tumor and a matched normal with a statistical test. These methods lose sensitivity to accurately assess MSI status in some clinical situations, like low tumor purity samples or samples with low sequencing coverage. MiMSI is a multiple instance learning (MIL) model for predicting MSI phenotype from next-generation sequencing data that demonstrates very high sensitivity even in clinical situations where low purity samples are common"

Subject(s)

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