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Due to heterogeneity, the tumor tissue samples for a single cancer type can be divided into multiple distinct subtypes (inter-tumor heterogeneity) and are composed of non-cancerous and cancerous cells (intra-tumor heterogeneity). If tumor heterogeneity is ignored when inferring gene networks, the edges specific to individual cancer subtypes and cell types cannot be characterized. However, most existing network reconstruction methods do not simultaneously take inter-tumor and intra-tumor heterogeneity into account.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>In this article, we propose a new Gaussian graphical model-based method for jointly estimating multiple cancer gene networks by simultaneously capturing inter-tumor and intra-tumor heterogeneity. Given gene expression data of heterogeneous samples for different cancer subtypes, a non-cancerous network shared across different cancer subtypes and multiple subtype-specific cancerous networks are estimated jointly. Tumor heterogeneity can be revealed by the difference in the estimated networks. The performance of our method is first evaluated using simulated data, and the results indicate that our method outperforms other state-of-the-art methods. We also apply our method to The Cancer Genome Atlas breast cancer data to reconstruct non-cancerous and subtype-specific cancerous gene networks. Hub nodes in the networks estimated by our method perform important biological functions associated with breast cancer development and subtype classification.<\/jats:p><\/jats:sec><jats:sec><jats:title>Availability and implementation<\/jats:title><jats:p>The source code is available at https:\/\/github.com\/Zhangxf-ccnu\/NETI2.<\/jats:p><\/jats:sec><jats:sec><jats:title>Supplementary information<\/jats:title><jats:p>Supplementary data are available at Bioinformatics online.<\/jats:p><\/jats:sec>","DOI":"10.1093\/bioinformatics\/btaa014","type":"journal-article","created":{"date-parts":[[2020,1,18]],"date-time":"2020-01-18T12:09:42Z","timestamp":1579349382000},"page":"2755-2762","source":"Crossref","is-referenced-by-count":7,"title":["Joint reconstruction of multiple gene networks by simultaneously capturing inter-tumor and intra-tumor heterogeneity"],"prefix":"10.1093","volume":"36","author":[{"given":"Jia-Juan","family":"Tu","sequence":"first","affiliation":[{"name":"Department of Statistics , Hubei Key Laboratory of Mathematical Sciences, School of Mathematics and Statistics, Central China Normal University, Wuhan 430079, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Le","family":"Ou-Yang","sequence":"additional","affiliation":[{"name":"College of Electronics and Information Engineering , Shenzhen University, Shenzhen 518060, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hong","family":"Yan","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering , City University of Hong Kong, Hong Kong 999077, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5052-9725","authenticated-orcid":false,"given":"Xiao-Fei","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Statistics , Hubei Key Laboratory of Mathematical Sciences, School of Mathematics and Statistics, Central China Normal University, Wuhan 430079, China"},{"name":"Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University) , Ministry of Education, Shanghai 200433, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hong","family":"Qin","sequence":"additional","affiliation":[{"name":"Department of Statistics , Hubei Key Laboratory of Mathematical Sciences, School of Mathematics and Statistics, Central China Normal University, Wuhan 430079, China"},{"name":"Department of Statistics , Zhongnan University of Economics and Law, Wuhan 430073, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2020,1,23]]},"reference":[{"key":"2023013110294430800_btaa014-B1","doi-asserted-by":"crossref","first-page":"8971","DOI":"10.1038\/ncomms9971","article-title":"Systematic pan-cancer analysis of tumour purity","volume":"6","author":"Aran","year":"2015","journal-title":"Nat. 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