如何使用ggplot2使每个栏在分组的条形图中脱颖而出（带边框）？

时间：2016-08-30 10:51:20

标签： r ggplot2 bar-chart 

structure(list(coord = structure(c(1L, 2L, 3L, 4L, 5L, 6L, 7L, 
8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 
21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L, 31L, 32L, 33L, 
34L, 35L, 36L, 37L, 38L, 39L, 40L, 41L, 42L, 43L, 44L, 45L, 46L, 
47L, 48L, 49L, 50L, 51L, 52L, 53L, 54L, 55L, 56L, 57L, 58L, 59L, 
60L, 61L, 62L, 63L, 64L, 65L, 66L, 67L, 68L, 69L, 1L, 2L, 3L, 
4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 
18L, 19L, 20L, 21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L, 
31L, 32L, 33L, 34L, 35L, 36L, 37L, 38L, 39L, 40L, 41L, 42L, 43L, 
44L, 45L, 46L, 47L, 48L, 49L, 50L, 51L, 52L, 53L, 54L, 55L, 56L, 
57L, 58L, 59L, 60L, 61L, 62L, 63L, 64L, 65L, 66L, 67L, 68L, 69L, 
1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 
15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 24L, 25L, 26L, 27L, 
28L, 29L, 30L, 31L, 32L, 33L, 34L, 35L, 36L, 37L, 38L, 39L, 40L, 
41L, 42L, 43L, 44L, 45L, 46L, 47L, 48L, 49L, 50L, 51L, 52L, 53L, 
54L, 55L, 56L, 57L, 58L, 59L, 60L, 61L, 62L, 63L, 64L, 65L, 66L, 
67L, 68L, 69L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 
12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 24L, 
25L, 26L, 27L, 28L, 29L, 30L, 31L, 32L, 33L, 34L, 35L, 36L, 37L, 
38L, 39L, 40L, 41L, 42L, 43L, 44L, 45L, 46L, 47L, 48L, 49L, 50L, 
51L, 52L, 53L, 54L, 55L, 56L, 57L, 58L, 59L, 60L, 61L, 62L, 63L, 
64L, 65L, 66L, 67L, 68L, 69L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 
9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 
22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L, 31L, 32L, 33L, 34L, 
35L, 36L, 37L, 38L, 39L, 40L, 41L, 42L, 43L, 44L, 45L, 46L, 47L, 
48L, 49L, 50L, 51L, 52L, 53L, 54L, 55L, 56L, 57L, 58L, 59L, 60L, 
61L, 62L, 63L, 64L, 65L, 66L, 67L, 68L, 69L), .Label = c("21906057-21916057", 
"21916057-21926057", "21976057-21986057", "21986057-21996057", 
"22006057-22016057", "22016057-22026057", "22036057-22046057", 
"22046057-22056057", "22056057-22066057", "22066057-22076057", 
"22076057-22086057", "22096057-22106057", "22106057-22116057", 
"22116057-22126057", "22126057-22136057", "22136057-22146057", 
"22146057-22156057", "22156057-22166057", "22166057-22176057", 
"22176057-22186057", "22186057-22196057", "22196057-22206057", 
"22206057-22216057", "22226057-22236057", "22236057-22246057", 
"22246057-22256057", "22256057-22266057", "22306057-22316057", 
"22316057-22326057", "22326057-22336057", "22336057-22346057", 
"22346057-22356057", "22356057-22366057", "22366057-22376057", 
"22426057-22436057", "22436057-22446057", "22446057-22456057", 
"22466057-22476057", "22476057-22486057", "22506057-22516057", 
"22516057-22526057", "22526057-22536057", "22536057-22546057", 
"22546057-22556057", "22556057-22566057", "22566057-22576057", 
"22576057-22586057", "22586057-22596057", "22596057-22606057", 
"22606057-22616057", "22616057-22626057", "22626057-22636057", 
"22636057-22646057", "22646057-22656057", "22686057-22696057", 
"22726057-22736057", "22736057-22746057", "22746057-22756057", 
"22806057-22816057", "22816057-22826057", "22826057-22836057", 
"22836057-22846057", "22866057-22876057", "22876057-22886057", 
"22886057-22896057", "22896057-22906057", "22906057-22916057", 
"22916057-22926057", "22956057-22966057"), 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, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 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, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
    2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
    2L, 2L, 2L, 2L, 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, 3L, 
    3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
    3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 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, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
    4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
    4L, 4L, 4L, 4L, 4L, 4L, 4L, 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, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 
    5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 
    5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 
    5L, 5L, 5L, 5L, 5L, 5L), .Label = c("gene1", "gene2", "gene3", 
    "gene4", "gene5"), class = "factor"), value = c(0L, 3L, 0L, 
    0L, 0L, 0L, 43L, 0L, 0L, 0L, 0L, 0L, 0L, 56L, 56L, 31L, 31L, 
    31L, 31L, 5L, 11L, 11L, 11L, 1L, 24L, 9805L, 72L, 74L, 74L, 
    74L, 74L, 74L, 74L, 74L, 2187L, 0L, 40L, 54L, 54L, 5L, 5L, 
    5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 1L, 62L, 
    62L, 1L, 26L, 26L, 26L, 3L, 40L, 40L, 6L, 6L, 6L, 6L, 200L, 
    0L, NA, NA, NA, NA, 0L, 49L, NA, NA, 0L, NA, 0L, 0L, NA, 
    36L, NA, 1L, 54L, 54L, NA, NA, NA, NA, NA, 0L, 72L, NA, NA, 
    NA, NA, 0L, NA, NA, NA, 6L, 40L, NA, NA, NA, NA, NA, NA, 
    NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 0L, NA, NA, NA, 1L, 
    NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 60L, NA, NA, 
    NA, NA, NA, 0L, NA, NA, NA, NA, NA, NA, NA, NA, 0L, NA, NA, 
    NA, 5L, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
    NA, NA, 0L, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
    NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
    NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
    NA, NA, NA, NA, NA, NA, 12L, NA, NA, NA, NA, NA, NA, NA, 
    NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
    NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
    NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
    NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
    NA, 31L, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
    NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
    NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
    NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), exp = c("Extremely low", 
    "Very Low", "Extremely low", "Extremely low", "Extremely low", 
    "Extremely low", "Moderately high", "Extremely low", "Extremely low", 
    "Extremely low", "Extremely low", "Extremely low", "Extremely low", 
    "High", "High", "Moderately high", "Moderately high", "Moderately high", 
    "Moderately high", "Low", "Moderate", "Moderate", "Moderate", 
    "Very Low", "Moderate", "Extremely high", "High", "High", 
    "High", "High", "High", "High", "High", "High", "Extremely high", 
    "Extremely low", "Moderately high", "High", "High", "Low", 
    "Low", "Low", "Low", "Low", "Low", "Low", "Low", "Low", "Low", 
    "Low", "Low", "Low", "Low", "Low", "Very Low", "High", "High", 
    "Very Low", "Moderately high", "Moderately high", "Moderately high", 
    "Very Low", "Moderately high", "Moderately high", "Low", 
    "Low", "Low", "Low", "Very high", "Extremely low", NA, NA, 
    NA, NA, "Extremely low", "Moderately high", NA, NA, "Extremely low", 
    NA, "Extremely low", "Extremely low", NA, "Moderately high", 
    NA, "Very Low", "High", "High", NA, NA, NA, NA, NA, "Extremely low", 
    "High", NA, NA, NA, NA, "Extremely low", NA, NA, NA, "Low", 
    "Moderately high", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
    NA, NA, NA, NA, NA, NA, "Extremely low", NA, NA, NA, "Very Low", 
    NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "High", NA, NA, 
    NA, NA, NA, "Extremely low", NA, NA, NA, NA, NA, NA, NA, 
    NA, "Extremely low", NA, NA, NA, "Low", NA, NA, NA, NA, NA, 
    NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "Extremely low", 
    NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
    NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
    NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
    NA, NA, NA, "Moderate", NA, NA, NA, NA, NA, NA, NA, NA, NA, 
    NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
    NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
    NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
    NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "Moderately high", 
    NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
    NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
    NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
    NA, NA, NA, NA, NA, NA, NA, NA, NA)), .Names = c("coord", 
"variable", "value", "exp"), row.names = c(NA, -345L), class = "data.frame")

我想使用ggplot2将此数据绘制为分组条形图。 我执行了以下步骤：

test[is.na(test)] <- 0

q<-ggplot(test, aes(x=coord, y=value, fill=factor(exp))) + geom_bar(aes(fill=exp),stat="identity",position = "dodge")+theme(axis.text.x = element_text(angle = 90, hjust = 1, vjust = 0.5))+scale_y_continuous(trans = "log10")

进入单个群体的条形图没有明确定义，我可以将该条形图中的每个条形图边界化吗？

我也试过这个：

barchart(log10(value) ~ coord, groups=exp, test, auto.key = list(columns = 3))

但我无法控制像旋转x轴标签这样的事情。但是，我更喜欢ggplot2，因为我必须添加另一层数据，其中我必须突出显示几个x轴标签，这些标签将通过引用另一个数据集并合并到现有的“测试”d.f.我使用SO问题/答案的帮助做了很少的情节所以没有问题。

更新： 由于log10（0）将给出-Inf值，正在做 scale_y_continuous（trans =“log10”，expand = c（0,0）） 正确的吗？

0 个答案:

没有答案
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