Stephen Lindsly, Can Chen, Sijia Liu, Scott Ronquist, Samuel Dilworth, Michael Perlman, Indika Rajapakse
{"title":"4DNvestigator: time series genomic data analysis toolbox.","authors":"Stephen Lindsly, Can Chen, Sijia Liu, Scott Ronquist, Samuel Dilworth, Michael Perlman, Indika Rajapakse","doi":"10.1080/19491034.2021.1910437","DOIUrl":null,"url":null,"abstract":"<p><p>Data on genome organization and output over time, or the 4D Nucleome (4DN), require synthesis for meaningful interpretation. Development of tools for the efficient integration of these data is needed, especially for the time dimension. We present the '4DNvestigator', a user-friendly network-based toolbox for the analysis of time series genome-wide genome structure (Hi-C) and gene expression (RNA-seq) data. Additionally, we provide methods to quantify network entropy, tensor entropy, and statistically significant changes in time series Hi-C data at different genomic scales.</p>","PeriodicalId":74323,"journal":{"name":"Nucleus (Austin, Tex.)","volume":"12 1","pages":"58-64"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/19491034.2021.1910437","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nucleus (Austin, Tex.)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/19491034.2021.1910437","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10
Abstract
Data on genome organization and output over time, or the 4D Nucleome (4DN), require synthesis for meaningful interpretation. Development of tools for the efficient integration of these data is needed, especially for the time dimension. We present the '4DNvestigator', a user-friendly network-based toolbox for the analysis of time series genome-wide genome structure (Hi-C) and gene expression (RNA-seq) data. Additionally, we provide methods to quantify network entropy, tensor entropy, and statistically significant changes in time series Hi-C data at different genomic scales.