千种植物（1KP）项目的数据获取。
Data access for the 1,000 Plants (1KP) project.
作者信息
Matasci Naim, Hung Ling-Hong, Yan Zhixiang, Carpenter Eric J, Wickett Norman J, Mirarab Siavash, Nguyen Nam, Warnow Tandy, Ayyampalayam Saravanaraj, Barker Michael, Burleigh J Gordon, Gitzendanner Matthew A, Wafula Eric, Der Joshua P, dePamphilis Claude W, Roure Béatrice, Philippe Hervé, Ruhfel Brad R, Miles Nicholas W, Graham Sean W, Mathews Sarah, Surek Barbara, Melkonian Michael, Soltis Douglas E, Soltis Pamela S, Rothfels Carl, Pokorny Lisa, Shaw Jonathan A, DeGironimo Lisa, Stevenson Dennis W, Villarreal Juan Carlos, Chen Tao, Kutchan Toni M, Rolf Megan, Baucom Regina S, Deyholos Michael K, Samudrala Ram, Tian Zhijian, Wu Xiaolei, Sun Xiao, Zhang Yong, Wang Jun, Leebens-Mack Jim, Wong Gane Ka-Shu
机构信息
iPlant Collaborative, Tucson 85721, AZ, USA ; Department of Ecology and Evolutionary Biology, University of Arizona, Tucson 85721, AZ, USA.
Department of Microbiology, University of Washington, Seattle 98109, WA, USA.
出版信息
Gigascience. 2014 Oct 27;3:17. doi: 10.1186/2047-217X-3-17. eCollection 2014.
The 1,000 plants (1KP) project is an international multi-disciplinary consortium that has generated transcriptome data from over 1,000 plant species, with exemplars for all of the major lineages across the Viridiplantae (green plants) clade. Here, we describe how to access the data used in a phylogenomics analysis of the first 85 species, and how to visualize our gene and species trees. Users can develop computational pipelines to analyse these data, in conjunction with data of their own that they can upload. Computationally estimated protein-protein interactions and biochemical pathways can be visualized at another site. Finally, we comment on our future plans and how they fit within this scalable system for the dissemination, visualization, and analysis of large multi-species data sets.
千种植物（1KP）项目是一个国际多学科联盟，已从1000多种植物物种中生成了转录组数据，涵盖了绿藻门（绿色植物）进化枝中所有主要谱系的代表物种。在此，我们描述了如何获取首批85个物种的系统发育基因组学分析中使用的数据，以及如何可视化我们的基因树和物种树。用户可以开发计算流程来分析这些数据，并结合自己上传的数据。通过计算估计的蛋白质-蛋白质相互作用和生化途径可在另一个网站上可视化。最后，我们阐述了我们的未来计划，以及这些计划如何融入这个用于传播、可视化和分析大型多物种数据集的可扩展系统。
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