Empowering biologists with multi-omics data: colorectal cancer as a paradigm

被引:21
|
作者
Zhu, Jing [1 ]
Shi, Zhiao [2 ,3 ]
Wang, Jing [1 ]
Zhang, Bing [1 ,4 ]
机构
[1] Vanderbilt Univ, Dept Biomed Informat, Nashville, TN 37235 USA
[2] Vanderbilt Univ, Adv Comp Ctr Res & Educ, Nashville, TN 37235 USA
[3] Vanderbilt Univ, Dept Elect Engn & Comp Sci, Nashville, TN 37235 USA
[4] Vanderbilt Univ, Dept Canc Biol, Nashville, TN 37235 USA
关键词
NETWORK VISUALIZATION; PROMOTER METHYLATION; AKAP12; PROMOTER; COLON; GENES; CARCINOMA; BROWSER;
D O I
10.1093/bioinformatics/btu834
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Motivation: Recent completion of the global proteomic characterization of The Cancer Genome Atlas (TCGA) colorectal cancer (CRC) cohort resulted in the first tumor dataset with complete molecular measurements at DNA, RNA and protein levels. Using CRC as a paradigm, we describe the application of the NetGestalt framework to provide easy access and interpretation of multi-omics data. Results: The NetGestalt CRC portal includes genomic, epigenomic, transcriptomic, proteomic and clinical data for the TCGA CRC cohort, data from other CRC tumor cohorts and cell lines, and existing knowledge on pathways and networks, giving a total of more than 17 million data points. The portal provides features for data query, upload, visualization and integration. These features can be flexibly combined to serve various needs of the users, maximizing the synergy among omics data, human visualization and quantitative analysis. Using three case studies, we demonstrate that the portal not only provides user-friendly data query and visualization but also enables efficient data integration within a single omics data type, across multiple omics data types, and over biological networks.
引用
收藏
页码:1436 / 1443
页数:8
相关论文
共 50 条
  • [1] ExpOmics: a comprehensive web platform empowering biologists with robust multi-omics data analysis capabilities
    Li, Douyue
    Min, Zhuochao
    Guo, Jia
    Chen, Yubin
    Zhang, Wenliang
    BIOINFORMATICS, 2024, 40 (08)
  • [2] A multi-omics approach on hereditary colorectal cancer
    Eiengard, Frida
    Rohlin, Anna
    Ellegard, Rada
    Palmeback, Pia
    Rosliden, Monica
    Andersson, Daniel Madan
    Olausson, Torbjorn
    Nordling, Margareta
    EUROPEAN JOURNAL OF HUMAN GENETICS, 2024, 32 : 585 - 585
  • [3] Multi-omics Analysis of Colorectal Cancer Metabolism
    Soga, Tomoyoshi
    CANCER SCIENCE, 2018, 109 : 193 - 193
  • [4] Integrated analysis of multi-omics data for the discovery of biomarkers and therapeutic targets for colorectal cancer
    Zafari, Nima
    Bathaei, Parsa
    Velayati, Mahla
    Khojasteh-Leylakoohi, Fatemeh
    Khazaei, Majid
    Fiuji, Hamid
    Nassiri, Mohammadreza
    Hassanian, Seyed Mahdi
    Ferns, Gordon A.
    Nazari, Elham
    Avan, Amir
    COMPUTERS IN BIOLOGY AND MEDICINE, 2023, 155
  • [5] Multi-omics analysis to identify driving factors in colorectal cancer
    Xu, Xi
    Gong, Chaoju
    Wang, Yunfeng
    Hu, Yanyan
    Liu, Hong
    Fang, Zejun
    EPIGENOMICS, 2020, 12 (18) : 1633 - 1650
  • [6] Multi-omics analyses of glucose metabolic reprogramming in colorectal cancer
    Huang, Maosen
    Wu, Yancen
    Cheng, Linyao
    Fu, Lihua
    Yan, Haochao
    Ru, Haiming
    Mo, Xianwei
    Yan, Linhai
    Su, Zijie
    FRONTIERS IN IMMUNOLOGY, 2023, 14
  • [7] Multi-omics analysis to identify susceptibility genes for colorectal cancer
    Yuan, Yuan
    Bao, Jiandong
    Chen, Zhishan
    Diez Villanueva, Anna
    Wen, Wanqing
    Wang, Fangqin
    Zhao, Dejian
    Fu, Xianghui
    Cai, Qiuyin
    Long, Jirong
    Shu, Xiao-Ou
    Zheng, Deyou
    Moreno, Victor
    Zheng, Wei
    Lin, Weiqiang
    Guo, Xingyi
    HUMAN MOLECULAR GENETICS, 2021, 30 (05) : 321 - 330
  • [8] Integrated multi-omics characterization of KRAS mutant colorectal cancer
    Chong, Wei
    Zhu, Xingyu
    Ren, Huicheng
    Ye, Chunshui
    Xu, Kang
    Wang, Zhe
    Jia, Shengtao
    Shang, Liang
    Li, Leping
    Chen, Hao
    THERANOSTICS, 2022, 12 (11): : 5138 - 5154
  • [9] Survey on Multi-omics, and Multi-omics Data Analysis, Integration and Application
    Shahrajabian, Mohamad Hesam
    Sun, Wenli
    CURRENT PHARMACEUTICAL ANALYSIS, 2023, 19 (04) : 267 - 281
  • [10] Multi-omics data of gastric cancer cell lines
    Seo, Eun-Hye
    Shin, Yun-Jae
    Kim, Hee-Jin
    Kim, Jeong-Hwan
    Kim, Yong Sung
    Kim, Seon-Young
    BMC GENOMIC DATA, 2023, 24 (01):