MAP: model-based analysis of proteomic data to detect proteins with significant abundance changes
文献类型：期刊论文
| 作者 | Li, Mushan2; Tu, Shiqi2; Tan, Fengxiang2,3; Zhang, Yuannyu2; Shao, Zhen2; Tu, Shiqi3; Li, Zijia4; Liu, Jian6; Zhang, Yijing6; Wang, Qian1 |
| 刊名 | CELL DISCOVERY
 |
| 出版日期 | 2019 |
| 卷号 | 5期号:-页码:40 |
| 关键词 | brain transcriptome WGCNA neurodevelopmental disorders differentially expressed genes cerebral cortex |
| ISSN号 | 1664-042X |
| DOI | 10.1038/s41421-019-0107-9 |
| 文献子类 | Article |
| 英文摘要 | Isotope-labeling-based mass spectrometry (MS) is widely used in quantitative proteomic studies. With this technique, the relative abundance of thousands of proteins can be efficiently profiled in parallel, greatly facilitating the detection of proteins differentially expressed across samples. However, this task remains computationally challenging. Here we present a new approach, termed Model-based Analysis of Proteomic data (MAP), for this task. Unlike many existing methods, MAP does not require technical replicates to model technical and systematic errors, and instead utilizes a novel step-by-step regression analysis to directly assess the significance of observed protein abundance changes. We applied MAP to compare the proteomic profiles of undifferentiated and differentiated mouse embryonic stem cells (mESCs), and found it has superior performance compared with existing tools in detecting proteins differentially expressed during mESC differentiation. A web-based application of MAP is provided for online data processing at http://bioinfo.sibs.ac.cn/shaolab/MAP. |
| 学科主题 | Cell Biology |
| WOS关键词 | QUANTITATIVE-ANALYSIS ; MESSENGER-RNA ; EXPRESSION ; DISCOVERY ; IDENTIFICATION ; STRATEGY ; MIXTURES |
| 语种 | 英语 |
| WOS记录号 | WOS:000482230500001 |
| 出版者 | NATURE PUBLISHING GROUP |
| 版本 | 出版稿 |
| 源URL | [http://202.127.25.144/handle/331004/1296]  |
| 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.Fudan Univ, Inst Biomed Sci, Shanghai Med Coll, Shanghai 200032, Peoples R China; 2.Chinese Acad Sci, Shanghai Inst Biol Sci, Shanghai Inst Nutr & Hlth,CAS Key Lab Computat Bi, Collaborat Innovat Ctr Genet & Dev Biol,CAS MPG P, Shanghai 200031, Peoples R China; 3.Univ Chinese Acad Sci, Beijing 100049, Peoples R China; 4.Gansu Prov Hosp, Dept Immunol & Rheumatol, Lanzhou 730000, Gansu, Peoples R China; 5.Univ Texas Southwestern Med Ctr Dallas, Childrens Med Ctr, Dept Pediat, Res Inst, Dallas, TX 75390 USA, 6.Chinese Acad Sci, Shanghai Inst Biol Sci, Inst Plant Physiol & Ecol, Natl Lab Plant Mol Genet,CAS Ctr Excellence Mol P, Shanghai, Peoples R China; |
| 推荐引用方式 GB/T 7714 | Li, Mushan,Tu, Shiqi,Tan, Fengxiang,et al. MAP: model-based analysis of proteomic data to detect proteins with significant abundance changes[J]. CELL DISCOVERY,2019,5(-):40. |
| APA | Li, Mushan.,Tu, Shiqi.,Tan, Fengxiang.,Zhang, Yuannyu.,Shao, Zhen.,...&,.(2019).MAP: model-based analysis of proteomic data to detect proteins with significant abundance changes.CELL DISCOVERY,5(-),40. |
| MLA | Li, Mushan,et al."MAP: model-based analysis of proteomic data to detect proteins with significant abundance changes".CELL DISCOVERY 5.-(2019):40. |
入库方式： OAI收割
来源：上海营养与健康研究所
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