如何在热图中建立分解颜色梯度

时间:2016-10-22 12:36:58

标签: r ggplot2 colors heatmap

我有这个用R中的ggplot2生成的图。 enter image description here

产生图的代码如下:

ggplot(mockdata) + 
  facet_grid(~ type, scales='free_x', space="free_x") +
  geom_tile(aes(variable, Measurement, fill = mockdata$plotval), colour = "dark red")  + 
  scale_fill_gradient2(limits=c(-20, 20),high = "firebrick3", low = "dodgerblue4") + 
  theme_minimal() + 
  theme(axis.text.x=element_text(size=28, angle=90), axis.text.y=element_text(size=28)) + 
  labs(title="", x="", y="", fill="") 

从图表和代码中都可以看出,颜色方案的范围是-20到20.我的数据中的plotval实际上代表了P值的-log10,所以总是一个正数,但我把它拆分了根据效果的方向(mockdata中的方向列)将其乘以1或-1,分为正数和负数。

我想要做的是将渐变色条分成两个,使其范围从0到20,但我仍然希望每个瓷砖为红色或蓝色,我想要蓝色和红色的强度可以在colorbar上并排看到。我还想增加颜色条的大小,但我想这绝对是另一个问题

dput(mockdata)
structure(list(Measurement = structure(c(20L, 19L, 18L, 17L, 
16L, 15L, 14L, 13L, 12L, 11L, 10L, 9L, 8L, 7L, 6L, 5L, 4L, 3L, 
2L, 1L, 20L, 19L, 18L, 17L, 16L, 15L, 14L, 13L, 12L, 11L, 10L, 
9L, 8L, 7L, 6L, 5L, 4L, 3L, 2L, 1L, 20L, 19L, 18L, 17L, 16L, 
15L, 14L, 13L, 12L, 11L, 10L, 9L, 8L, 7L, 6L, 5L, 4L, 3L, 2L, 
1L, 20L, 19L, 18L, 17L, 16L, 15L, 14L, 13L, 12L, 11L, 10L, 9L, 
8L, 7L, 6L, 5L, 4L, 3L, 2L, 1L, 20L, 19L, 18L, 17L, 16L, 15L, 
14L, 13L, 12L, 11L, 10L, 9L, 8L, 7L, 6L, 5L, 4L, 3L, 2L, 1L, 
20L, 19L, 18L, 17L, 16L, 15L, 14L, 13L, 12L, 11L, 10L, 9L, 8L, 
7L, 6L, 5L, 4L, 3L, 2L, 1L, 20L, 19L, 18L, 17L, 16L, 15L, 14L, 
13L, 12L, 11L, 10L, 9L, 8L, 7L, 6L, 5L, 4L, 3L, 2L, 1L, 20L, 
19L, 18L, 17L, 16L, 15L, 14L, 13L, 12L, 11L, 10L, 9L, 8L, 7L, 
6L, 5L, 4L, 3L, 2L, 1L, 20L, 19L, 18L, 17L, 16L, 15L, 14L, 13L, 
12L, 11L, 10L, 9L, 8L, 7L, 6L, 5L, 4L, 3L, 2L, 1L), .Label = c("1", 
"2", "3", "4", "5", "6", "7", "8", "9", "10", "11", "12", "13", 
"14", "15", "16", "17", "18", "19", "20", "21", "22", "23", "24", 
"25", "26", "27", "28", "29", "30", "31", "32", "33", "34", "35", 
"36", "37", "38", "39", "40", "41", "42"), class = "factor"), 
    category = structure(c(3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 6L, 
    6L, 6L, 6L, 6L, 7L, 7L, 7L, 7L, 7L, 7L, 8L, 3L, 4L, 4L, 4L, 
    5L, 5L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 7L, 7L, 7L, 7L, 7L, 7L, 
    8L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 7L, 
    7L, 7L, 7L, 7L, 7L, 8L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 6L, 
    6L, 6L, 6L, 6L, 7L, 7L, 7L, 7L, 7L, 7L, 8L, 3L, 4L, 4L, 4L, 
    5L, 5L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 7L, 7L, 7L, 7L, 7L, 7L, 
    8L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 7L, 
    7L, 7L, 7L, 7L, 7L, 8L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 6L, 
    6L, 6L, 6L, 6L, 7L, 7L, 7L, 7L, 7L, 7L, 8L, 3L, 4L, 4L, 4L, 
    5L, 5L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 7L, 7L, 7L, 7L, 7L, 7L, 
    8L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 7L, 
    7L, 7L, 7L, 7L, 7L, 8L), .Label = c("x1", "x2", "x3", "x4", 
    "x5", "x6", "x7", "x8", "x9"), class = "factor"), variable = structure(c(1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
    2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 
    3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 
    4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
    4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 
    5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 6L, 6L, 6L, 6L, 6L, 6L, 
    6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 7L, 
    7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 
    7L, 7L, 7L, 7L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 
    8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 9L, 9L, 9L, 9L, 9L, 9L, 
    9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L), .Label = c("A", 
    "B", "C", "a", "b", "c", "d", "e", "f"), class = "factor"), 
    Pval = c(6760.4856938748, 2.03462777623711e-09, 41.184282929783, 
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    51891.7266692688, 0.194178098258849, 1026.89550294706, 7389.35002875074, 
    8.72167728953903e-05, 0.615710674200898, 90613.5488833331, 
    0.0001007185458695, 0.329336214710806, 58860.1232768614, 
    0.000150880187013758, 0.00043394288165634, 589.188126109299, 
    13.3763683418565, 467886.366054549, 248.393646104426, 189074.428816151, 
    303206.257085955, 204105.426845067, 6538706.25322294, 5.70435826167575, 
    1223246.72689726, 98.8553275302565, 3.01666336637105e-10, 
    0.000421841985089921, 0.00158775289621832, 889227.11315509, 
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    0.241251203711246, 0.0679836008245645, 3.24194712523739, 
    12.3229213534339, 4.00236477738573, 3.65965017262511, 12.6636282554106, 
    484.9507381133, 33.498634194894, 9133015.34747621, 854.088489555501, 
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    12.5369593061199, 883.371244544336, 2188355.36818768, 6.82570529049995, 
    7.51815377289302, 2.10761714681621e-05, 0.222448185938361, 
    5.45130776104763, 327.118134199018, 60383.600655089, 1520.1609648366, 
    1481664.13388885, 34818.2575270259, 4060744.53269009, 0.000329878093050015, 
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非常感谢你的帮助

0 个答案:

没有答案