用Excel绘制南丁格尔玫瑰图
一位审稿人曾经说:“我看稿件的顺序是题目、摘要、图表、前言、参考文献和正文。”可见论文图片质量非常重要,图片质量的高低很大程度上决定了论文能否被顺利录用。毋庸置疑,拥有赏心悦目的配图的稿件更加能够获得审稿人的青睐!登高望远,学习高分文献中的精美配图是提高自身文章配图水平的不二法门。今天半就给大家分享从一篇2020年2月26日发表的Cell文献【1】中学习绘制南丁格尔玫瑰图、GO富集图等,权当抛砖引玉。 首先,我为什么分享使用Excel绘图?1、 几乎所有人电脑上都安装有Excel;2、 Excel功能强大,可绘制出不逊于编程与其他专业软件的图形效果;3、 可导出高分辨图片;4、 Excel还能够实现一些常用软件(如Graphpad prism)绘制不了的图形。Excel绘制南丁格尔玫瑰图南丁格尔玫瑰图(Rose diagrams)是英国护士和统计学家弗罗伦斯·南丁格尔(Florence Nightingale)发明的一种圆形的直方图。其优点是使数据易于理解,让人印象深刻。下图是国际顶级期刊Cell文章中使用的玫瑰图【1】,用以说明差异表达基因(DEGs)在不同组织中的分布情况:
![](https://img.haomeiwen.com/i20747879/27439c5168e43831.jpg)
“见贤思齐”,我们该如何绘制南丁格尔玫瑰图呢?尺有所长,寸有所短。目前常用绘图软件GraphPad Prism暂不能绘制南丁格尔玫瑰图,然而几乎所有人电脑中均安装了的软件Excel却可以轻松绘制漂亮的玫瑰图。****绘制步骤:****1. 数据准备模拟与Cell文献中类似的7组数据,每组所占角度为360°除以7为51.4286°:
![](https://img.haomeiwen.com/i20747879/d07a1941ab35c39b.png)
![](https://img.haomeiwen.com/i20747879/68e73f68ee526c6b.png)
![](https://img.haomeiwen.com/i20747879/35655222e46cda2f.png)
![](https://img.haomeiwen.com/i20747879/185b6dbec357334b.png)
2. 绘制玫瑰图选择步骤1得到的数据,菜单栏点击插入 -> 插入图表 -> 雷达图下选择填充雷达图:
![](https://img.haomeiwen.com/i20747879/cc6aa767d66edbb4.png)
![](https://img.haomeiwen.com/i20747879/6e2ca2b94d6e276b.png)
3. 美化玫瑰图3.1 选择并删除玫瑰图外围的数字:
![](https://img.haomeiwen.com/i20747879/19c9706df6e70908.png)
![](https://img.haomeiwen.com/i20747879/ba69794f92c7cd4a.png)
![](https://img.haomeiwen.com/i20747879/7273709ac63e19d8.png)
![](https://img.haomeiwen.com/i20747879/098ee4707de350d3.png)
![](https://img.haomeiwen.com/i20747879/51c186e4b8e962ee.png)
![](https://img.haomeiwen.com/i20747879/2adaf31c7af21880.png)
4. 添加序列标签添加序列标签前准备好如下辅助数据:
![](https://img.haomeiwen.com/i20747879/2d3a8fda701c4251.png)
![](https://img.haomeiwen.com/i20747879/2728960efaaabd02.png)
![](https://img.haomeiwen.com/i20747879/12b8781f56b3355a.png)
![](https://img.haomeiwen.com/i20747879/c833b2c359abd49d.png)
![](https://img.haomeiwen.com/i20747879/302e2219cc131ae1.png)
![](https://img.haomeiwen.com/i20747879/2b10b38028acb0e9.png)
5. 导出高清图片使用XL toolbox(https://www.xltoolbox.net/)插件Import&Export下导出高清Tiff图片:
![](https://img.haomeiwen.com/i20747879/a600ecb734e144ed.png)
![](https://img.haomeiwen.com/i20747879/b28fa8ec01fe3c26.png)
Excel提取配色方案
相信很多人都曾经为绘图配色而苦恼,无论怎么调整都觉得自己的配色“辣眼睛”。向高分文章学习漂亮的配色方案是一个不错的选择。在此继续以Cell文章【1】为例向大家分享Excel提取配色的方法!下图是Cell文章中7个不同组织的颜色:
![](https://img.haomeiwen.com/i20747879/f53371cd36e51115.png)
步骤:****1. EasyCharts插件链接:http://easychart.github.io/post/Easycharts/ 。下载完成后按照说明进行安装:
![](https://img.haomeiwen.com/i20747879/811e5e1a27bdc4e4.png)
安装完成后在菜单栏可见EasyCharts插件。2. 使用颜色拾取进行配色提取将想参考配色图片截图导入Excel,点击E asyCharts中的颜色拾取,逐一提取各组颜色,保存获得各颜色对应的RGB值:
![](https://img.haomeiwen.com/i20747879/0ab78c17a61561c4.png)
![](https://img.haomeiwen.com/i20747879/bbffb53e6738dc79.jpg)
![](https://img.haomeiwen.com/i20747879/a710d4ff4d4661b4.png)
![](https://img.haomeiwen.com/i20747879/128ad5ad25b90b4e.png)
4. 在其他绘图软件使用配色以GraphPad Prism为例,填充颜色时选择More colors,在RGB处填入提取的RGB值,Add to custom colors可以保存颜色后续使用,不需要再次输入:
![](https://img.haomeiwen.com/i20747879/b3b394cb5757e3f8.png)
![](https://img.haomeiwen.com/i20747879/60a695ac26f6ba57.png)
扩展:1. EasyCharts插件除可以进行颜色拾取外色轮参考亦可辅助配色:
![](https://img.haomeiwen.com/i20747879/e3a123dbdc4c37bf.jpg)
![](https://img.haomeiwen.com/i20747879/07cdd4ce445f4c63.png)
![](https://img.haomeiwen.com/i20747879/b83bdfc06c0321c1.png)
Excel绘制GO分析图
Cell文献还对差异表达基因进行了GO分析,圆圈中的数字对应每一项中富集的基因数量:![](https://img.haomeiwen.com/i20747879/303db29cccbcb44c.png)
步骤:1. 准备GO分析数据,绘图需使用GO分析名称(Description列)、-Log10P与基因数量:
![](https://img.haomeiwen.com/i20747879/346b26ca1edf21e2.png)
![](https://img.haomeiwen.com/i20747879/c655a044fdeceb42.png)
-
美化图片设置柱形图颜色为灰色:
image
![](https://img.haomeiwen.com/i20747879/46692b3089130c1b.png)
![](https://img.haomeiwen.com/i20747879/afee465c07f35656.png)
![](https://img.haomeiwen.com/i20747879/b6d1d795fd7978f1.png)
![](https://img.haomeiwen.com/i20747879/53e9d7ce1c98a8a3.png)
![](https://img.haomeiwen.com/i20747879/b7c2b9265ba8cddf.png)
![](https://img.haomeiwen.com/i20747879/0c80ab6a816ed19f.png)
![](https://img.haomeiwen.com/i20747879/3cc13fc7c09ad1c5.png)
![](https://img.haomeiwen.com/i20747879/cefb459aa10de9d9.png)
![](https://img.haomeiwen.com/i20747879/70b4f5ca6acb0ffa.png)
![](https://img.haomeiwen.com/i20747879/5b5df9b683f2df5a.png)
![](https://img.haomeiwen.com/i20747879/8098142358e71b9b.png)
扩展:Excel绘制另类柱形图:
![](https://img.haomeiwen.com/i20747879/19b4c8ded3a31722.png)
![](https://img.haomeiwen.com/i20747879/c2999d153c5e8d15.png)
![](https://img.haomeiwen.com/i20747879/14b1255beef260ae.png)
![](https://img.haomeiwen.com/i20747879/96dc8dc63b6f5bde.png)
![](https://img.haomeiwen.com/i20747879/3037f51cf50e7160.png)
![](https://img.haomeiwen.com/i20747879/e0c5fe2bb0972af8.png)
![](https://img.haomeiwen.com/i20747879/1c8fa4a79dca5537.png)
![](https://img.haomeiwen.com/i20747879/dbc88dff741f8929.png)
![](https://img.haomeiwen.com/i20747879/44baae40fde149f8.png)
![](https://img.haomeiwen.com/i20747879/8fb9251b20cc7f99.png)
模式图绘制
Cell文章中使用不同组织的模式图,增加了图形的趣味性。今天半夏给大家分享一款高效模式图绘制神器——BioRender。![](https://img.haomeiwen.com/i20747879/848d0f4efb834828.jpg)
BioRender链接:https://biorender.com/ BioRender包含Imuunology、Microbiology、Neuroscience等在内的30多个生命科学领域的数千个模板。需要什么搜索即可挑选自己需要的模式图,例如搜索kidney:
![](https://img.haomeiwen.com/i20747879/0a37339ee6e57511.png)
![](https://img.haomeiwen.com/i20747879/d98703042eab43f6.jpg)
![](https://img.haomeiwen.com/i20747879/b8308463eceee917.png)
实用网站
除了可以从Cell文章学习绘图外,文中还涉及了一些实用网站。1. Metascape链接:http://metascape.orgMetascape【2】整合了GO、KEGG、UniProt和DrugBank等多个权威的数据资源,不仅能完成通路富集和生物过程注释,还能做基因相关的蛋白质网络分析和涉及到的药物分析。作者使用Metascape进行了GO分析。
![](https://img.haomeiwen.com/i20747879/0ac8ac0c14c8bde9.jpg)
2. CellPhoneDB链接:www.cellphonedb.orgCellPhoneDB是一种用以预测潜在的特殊的细胞间互作新型统计工具【3】。
![](https://img.haomeiwen.com/i20747879/8e6a4e9186548b20.jpg)
今天给大家分享从高分文献学习科研绘图就到此为止了,祝大家绘制高质量的图片、发高分文章!
参考文献:1. Ma S, Sun S, Geng L, et al. Caloric Restriction Reprograms the Single-Cell Transcriptional Landscape of Rattus Norvegicus Aging [published online ahead of print, 2020 Feb 26]. Cell. 2020;S0092-8674(20)30152-5. doi:10.1016/j.cell.2020.02.0082. Zhou Y, Zhou B, Pache L, et al. Metascape provides a biologist-oriented resource for the analysis of systems-level datasets. Nat Commun. 2019;10(1):1523. Published 2019 Apr 3. doi:10.1038/s41467-019-09234-63. Vento-Tormo R, Efremova M, Botting RA, et al. Single-cell reconstruction of the early maternal-fetal interface in humans. Nature. 2018;563(7731):347–353. doi:10.1038/s41586-018-0698-6