scMSI: Accurately inferring the sub-clonal Micro-Satellite status by an integrated deconvolution model on length spectrum

• Published in: PLoS computational biology Vol. 20; no. 12; p. e1012608
• Main Authors: Liu, Yuqian, Chen, Yan, Wu, Huanwen, Zhang, Xuanping, Wang, Yuqi, Yi, Xin, Liang, Zhiyong, Wang, Jiayin
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 02.12.2024; Public Library of Science (PLoS)
• Subjects: Algorithms; Bayes Theorem; Biology and Life Sciences; Biomarkers, Tumor - genetics; Cancer; Computational Biology - methods; Diagnosis; Endometrial Neoplasms - genetics; Endometrial Neoplasms - pathology; Female; Genetic markers; Health aspects; Humans; Medicine and Health Sciences; Microsatellite Instability; Microsatellite Repeats - genetics; Microsatellites (Genetics); Models, Genetic; Physical Sciences; Research and Analysis Methods; China

Microsatellite instability (MSI) is an important genomic biomarker for cancer diagnosis and treatment, and sequencing-based approaches are often applied to identify MSI because of its fastness and efficiency. These approaches, however, may fail to identify MSI on one or more sub-clones for certain c...