Tensorial blind source separation for improved analysis of multi-omic data
文献类型：期刊论文
| 作者 | Teschendorff, Andrew E.1,2,3; Jing, Han1; Jing, Han4; Paul, Dirk S.5; Virta, Joni6; Nordhausen, Klaus7; , |
| 刊名 | GENOME BIOLOGY
 |
| 出版日期 | 2018 |
| 卷号 | 19期号:-页码:76 |
| 关键词 | Multi-omic Tensor Dimensional reduction Independent component analysis mQTL Epigenome-wide association study Cancer |
| ISSN号 | 1474-760X |
| DOI | 10.1186/s13059-018-1455-8 |
| 文献子类 | Article |
| 英文摘要 | There is an increased need for integrative analyses of multi-omic data. We present and benchmark a novel tensorial independent component analysis (tICA) algorithm against current state-of-the-art methods. We find that tICA outperforms competing methods in identifying biological sources of data variation at a reduced computational cost. On epigenetic data, tICA can identify methylation quantitative trait loci at high sensitivity. In the cancer context, tICA identifies gene modules whose expression variation across tumours is driven by copy-number or DNA methylation changes, but whose deregulation relative to normal tissue is independent of such alterations, a result we validate by direct analysis of individual data types. |
| 学科主题 | Biotechnology & Applied Microbiology ; Genetics & Heredity |
| WOS关键词 | INDEPENDENT COMPONENT ANALYSIS ; DNA METHYLATION CHANGES ; GENOMIC DATA ; CANCER ; DECOMPOSITION ; CELLS ; MICROARRAY ; SIGNATURES ; LANDSCAPE ; DISCOVERY |
| 语种 | 英语 |
| WOS记录号 | WOS:000434947000001 |
| 出版者 | BIOMED CENTRAL LTD |
| 版本 | 出版稿 |
| 源URL | [http://202.127.25.144/handle/331004/1027]  |
| 专题 | 中国科学院上海生命科学研究院营养科学研究所 |
| 作者单位 | 1.Chinese Acad Sci, Shanghai Inst Biol Sci, CAS MPG Partner Inst Computat Biol, CAS Key Lab Computat Biol, 320 Yue Yang Rd, Shanghai 200031, Peoples R China; 2.UCL, UCL Elizabeth Garrett Anderson Inst Womens Hlth, Dept Womens Canc, 74 Huntley St, London WC1E 6BT, England; 3.UCL, UCL Canc Inst, 74 Huntley St, London WC1E 6BT, England; 4.Univ Chinese Acad Sci, 19A Yuquan Rd, Beijing 100049, Peoples R China; 5.Univ Cambridge, Dept Publ Hlth & Primary Care, Strangeways Res Lab, Cardiovasc Epidemiol Unit, Cambridge CB1 8RN, England; 6.Univ Turku, Turku 20014, Finland; 7.Vienna Univ Technol, Wiedner Hauptstr 7, A-1040 Vienna, Austria, |
| 推荐引用方式 GB/T 7714 | Teschendorff, Andrew E.,Jing, Han,Jing, Han,et al. Tensorial blind source separation for improved analysis of multi-omic data[J]. GENOME BIOLOGY,2018,19(-):76. |
| APA | Teschendorff, Andrew E..,Jing, Han.,Jing, Han.,Paul, Dirk S..,Virta, Joni.,...&,.(2018).Tensorial blind source separation for improved analysis of multi-omic data.GENOME BIOLOGY,19(-),76. |
| MLA | Teschendorff, Andrew E.,et al."Tensorial blind source separation for improved analysis of multi-omic data".GENOME BIOLOGY 19.-(2018):76. |
入库方式： OAI收割
来源：上海营养与健康研究所
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