CELLO:a longitudinal data analysis toolbox untangling cancer evolution

作     者：Biaobin Jiang Dong Song Quanhua Mu Jiguang Wang Biaobin Jiang;Dong Song;Quanhua Mu;Jiguang Wang

作者机构：Department of Chemical and Biological EngineeringThe Hong Kong University of Science and Tech no logyHong KongChina Division of Life ScienceThe Hong Kong University of Science and TechnologyHong KongChina Center of Systems Biology and Human HealthThe Hong Kong University of Science and TechnologyHong KongChina State Key Laboratory of Molecular NeuroscieneeThe Hong Kong University of Science and TechnologyHong KongChina 

出 版 物：《Quantitative Biology》 (定量生物学（英文版）)

年 卷 期：2020年第8卷第3期

页      面：256-266页

核心收录：

学科分类：08[工学] 09[农学] 0901[农学-作物学] 0836[工学-生物工程] 090102[农学-作物遗传育种] 

基　　金：This work is supported by the grants from the National Natural Science Foundation of China(31922088) Research Grant Council(N HKUST606/17,26102719,C7065-18GF,C4039-19GF) Innovation and Technology Commission(ITCPD/17-9,ITS/480/18FP) Hong Kong Branch of Southern Marine Science and Engineering Guangdong Laboratory(Guangzhou)(SMSEGL20SC01) 

主　　题：cancer evolution genomics longitudinal sequencing bioinformatics 

摘      要：The complex pattern of cancer evolution poses a huge challenge to precision *** sequencing of tumor samples allows us to monitor the dynamics of mutations that occurred during this clonal evolution ***,we present a versatile toolbox,namely CELLO(Cancer EvoLution for Longitudinal data),accompanied with a step-by-step tutorial,to exemplify how to profile,analyze and visualize the dynamic change of somatic mutational landscape using longitudinal genomic sequencing ***,we customize the hypermutation detection module in CELLO to adapt targeted-DNA and whole-transcriptome sequencing data,and verify the extensive applicability of CELLO in published longitudinal datasets from brain,bladder and breast *** entire tutorial and reusable programs in MATLAB,R and docker versions are open access at https://***/WaiigLabHKUST/CELLO.