TY - JOUR AU - Wang, Yixuan AU - Zhang, Xuanping AU - Xiao, Xiao AU - Zhang, Fei-Ran AU - Yan, Xinxing AU - Feng, Xuan AU - Zhao, Zhongmeng AU - Guan, Yanfang AU - Wang, Jiayin PY - 2020 DA - 2020/03/11 TI - Accurately estimating the length distributions of genomic micro-satellites by tumor purity deconvolution JO - BMC Bioinformatics SP - 82 VL - 21 IS - 2 AB - Genomic micro-satellites are the genomic regions that consist of short and repetitive DNA motifs. Estimating the length distribution and state of a micro-satellite region is an important computational step in cancer sequencing data pipelines, which is suggested to facilitate the downstream analysis and clinical decision supporting. Although several state-of-the-art approaches have been proposed to identify micro-satellite instability (MSI) events, they are limited in dealing with regions longer than one read length. Moreover, based on our best knowledge, all of these approaches imply a hypothesis that the tumor purity of the sequenced samples is sufficiently high, which is inconsistent with the reality, leading the inferred length distribution to dilute the data signal and introducing the false positive errors. SN - 1471-2105 UR - https://doi.org/10.1186/s12859-020-3349-5 DO - 10.1186/s12859-020-3349-5 ID - Wang2020 ER -