  Motivation: Microsatellite instability (MSI) is a cancer biomarker associated
with cancer prognosis and chemotherapy sensitivity. Since the discovery of MSI,
polymerase chain reaction (PCR)-based testing has been considered the gold
standard for MSI detection. However, with the decrease in sequencing costs,
software that calculates MSI based on next-generation sequencing (NGS) data has
been widely applied. Results: In this study, we evaluated the performance of
the MSIsensor detection software, focusing on the limitations of the chi-square
test algorithm in determining microsatellite stability under high-depth
sequencing data. We demonstrated that the chi-square test algorithm is
insufficient for accurately as-sessing microsatellite stability in this
context. Furthermore, we explored the application of downsampling techniques to
enhance the accuracy of MSIsensor detection. Our findings provide insight into
the limita-tions of current methods and offer potential improvements for more
reliable MSI detection based on NGS data.
