Closed ixxmu closed 1 year ago
常见期刊其实都有图表数量的限制,比如:
Journal | Impact Factor | Number of Figures |
---|---|---|
Nature Cancer | 60.72 | 5-8 |
Science | 47.73 | 6 |
Cancer Cell | 31.74 | 8 |
Journal of Clinical Oncology | 44.54 | 6 |
JAMA Oncology | 31.78 | 5 |
Cell Host and Microbe | 21.02 | 7 |
虽然说一图胜千言,但是成百上千张图就是另外一种啰嗦了,尤其是单细胞时代,很容易跑出来成百上千个图,这个时候首先需要继续汇总信息,其次需要把关键图表拼接起来,这样的话虽然期刊只允许我们给七八张图,但是每个图里面还是可以有十几个小图。
比如2022的一个卵巢癌单细胞文章就是如此:
同样的,我们做常规的表达量差异分析,比如芯片或者转录组数据,都是会有起码三张图, 我在生信技能树的教程:《你确定你的差异基因找对了吗?》提到过,必须要对你的转录水平的全局表达矩阵做好质量控制,最好是看到标准3张图:
如果分组在3张图里面体现不出来,实际上后续差异分析是有风险的。这个时候需要根据你自己不合格的3张图,仔细探索哪些样本是离群点,自行查询中间过程可能的问题所在,或者检查是否有其它混杂因素,都是会影响我们的差异分析结果的生物学解释。比如发表于2021年9月27日,美国康奈尔医学院周乔课题组在Cell Stem Cell 期刊,文章标题是:《SATB2 preserves colon stem cell identity and mediates ileum-colon conversion via enhancer remodeling》,在线阅读链接 是:https://doi.org/10.1016/j.stem.2021.09.004 在附件就提到了这样的三张图:
每个子图都是独立的绘图代码,然后就可以拼接
cowplot
to arrange figuresThe main function to combine figures using cowplot
is plot_grid()
. Let's check out the help documentation using ?plot_grid()
. The first and most important parameter is the list of plots we want to combine, plotlist
.
Let's check out the basic use of this function by calling the plots we want to combine and by providing labels using the labels
argument.
plot_grid(pca,volcano,hmap,sc, labels="AUTO")
或者复杂一点的 In general, there seem to be more options for plot customization (without adding ggplot2 layers) with cowplot
.
plot_grid(pca,volcano,hmap,sc, labels="AUTO",
label_size = 14,
label_fontface = "bold.italic", label_colour ="blue",
label_fontfamily ="Times New Roman",
label_y=0.25)
拼图效果如下所示:
patchwork
The goal of patchwork is to make it ridiculously simple to combine separate ggplots into the same graphic. As such it tries to solve the same problem as gridExtra::grid.arrange() and cowplot::plot_grid but using an API that incites exploration and iteration, and scales to arbitrily complex layouts. ---Thomas Lin Pederson, Patchwork documentation.
Patchwork allows users to combine plots using simple mathematic operations such as +
and /
.
所以,上面的4个图拼接起来,也是超级简单的语法:pca + volcano + hmap + sc
强烈建议你推荐给身边的博士后以及年轻生物学PI,多一点数据认知,让他们的科研上一个台阶:
https://mp.weixin.qq.com/s/4cQIzoBCbQRn5v14B8mpEQ