无论如何要更改 R 中 ggplot 中值的大小(geom_point)?
Is there anyway to change the size of values in ggplot in R (geom_point)?
这些值会自动设置为 0.25、0.50、0.75 和 1。但是,我想更改这些范围,特别是让它们变小。这是我的代码。我还添加了一些样本数据,如您所见,p 值(我感兴趣的变量)的范围从小到“1.72e-50”到“1”。
library(ggplot2)
data(TFRC, package="ggplot2")
#imports/scans the data from file explorer/spreadsheets
TFRC <- read.csv(file.choose(), header = TRUE)
# bubble chart showing position of polymorphisms on gene, the frequency of each of these polymorphisms, where they are prominent on earth, and p-value
TFRCggplot <- ggplot(TFRC, aes(Position, Frequency))+
geom_jitter(aes(col=Geographical.Location, size=p.value))+
labs(subtitle="Frequency of Various Polymorphisms", title="TFRC") +
scale_size_continuous(range=c(1,5), trans = "reverse")
TFRCggplot + guides(size = guide_legend(reverse = TRUE))
Here is some sample data.
structure(list(Variant = structure(c(28L, 28L, 28L, 28L, 28L,
23L, 23L, 23L, 23L, 23L, 21L, 21L, 21L, 21L, 21L, 6L, 6L, 6L,
6L, 6L, 8L, 8L, 8L, 8L, 8L, 10L, 10L, 10L, 10L, 10L, 14L, 14L,
14L, 14L, 14L, 15L, 15L, 15L, 15L, 15L, 25L, 25L, 25L, 25L, 25L,
16L, 16L, 16L, 16L, 16L, 22L, 22L, 22L, 22L, 22L, 9L, 9L, 9L,
9L, 9L, 7L, 7L, 7L, 7L, 7L, 19L, 19L, 19L, 19L, 19L, 11L, 11L,
11L, 11L, 11L, 1L, 1L, 1L, 1L, 1L, 20L, 20L, 20L, 20L, 20L, 27L,
27L, 27L, 27L, 27L, 5L, 5L, 5L, 5L, 5L, 12L, 12L, 12L, 12L, 12L,
26L, 26L, 26L, 26L, 26L, 24L, 24L, 24L, 24L, 24L, 3L, 3L, 3L,
3L, 3L, 4L, 4L, 4L, 4L, 4L, 13L, 13L, 13L, 13L, 13L, 29L, 29L,
29L, 29L, 29L, 17L, 17L, 17L, 17L, 17L, 18L, 18L, 18L, 18L, 18L,
2L, 2L, 2L, 2L, 2L), .Label = c("rs140316777", "rs141165322",
"rs144131234", "rs149088653", "rs184956956", "rs199637290", "rs200128950",
"rs201408488", "rs34490397", "rs3817672", "rs41295849", "rs41295879",
"rs41298067", "rs41301381", "rs41303529", "rs533268185", "rs534595346",
"rs536971550", "rs537759332", "rs539830157", "rs541010181", "rs541398971",
"rs545061104", "rs559739602", "rs563942755", "rs571673598", "rs572837317",
"rs576156970", "rs577771580"), class = "factor"), Position = c(66L,
66L, 66L, 66L, 66L, 90L, 90L, 90L, 90L, 90L, 138L, 138L, 138L,
138L, 138L, 141L, 141L, 141L, 141L, 141L, 312L, 312L, 312L, 312L,
312L, 426L, 426L, 426L, 426L, 426L, 636L, 636L, 636L, 636L, 636L,
762L, 762L, 762L, 762L, 762L, 810L, 810L, 810L, 810L, 810L, 831L,
831L, 831L, 831L, 831L, 879L, 879L, 879L, 879L, 879L, 891L, 891L,
891L, 891L, 891L, 975L, 975L, 975L, 975L, 975L, 1002L, 1002L,
1002L, 1002L, 1002L, 1011L, 1011L, 1011L, 1011L, 1011L, 1056L,
1056L, 1056L, 1056L, 1056L, 1137L, 1137L, 1137L, 1137L, 1137L,
1143L, 1143L, 1143L, 1143L, 1143L, 1221L, 1221L, 1221L, 1221L,
1221L, 1260L, 1260L, 1260L, 1260L, 1260L, 1692L, 1692L, 1692L,
1692L, 1692L, 1791L, 1791L, 1791L, 1791L, 1791L, 1794L, 1794L,
1794L, 1794L, 1794L, 1815L, 1815L, 1815L, 1815L, 1815L, 2031L,
2031L, 2031L, 2031L, 2031L, 2070L, 2070L, 2070L, 2070L, 2070L,
2103L, 2103L, 2103L, 2103L, 2103L, 2172L, 2172L, 2172L, 2172L,
2172L, 2259L, 2259L, 2259L, 2259L, 2259L), Geographical.Location = structure(c(1L,
2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L,
3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L,
4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L,
5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L,
1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L,
2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L,
3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L,
4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L,
5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L
), .Label = c("AFR", "AMR", "EAS", "EUR", "SAS"), class = "factor"),
Frequency = c(0, 0, 0.202, 0, 0, 0, 0.295, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0.192, 0, 0, 0, 0, 0.384, 7.654, 5.934, 30.13571429,
58.955, 26.458, 4.008, 0.598, 0, 0, 3.782, 0, 0.196, 0.1328571429,
0, 0, 4.056, 5.592, 0, 0, 0, 0, 0.196, 0.1257142857, 0, 0,
0, 0, 0, 0, 0, 1.414, 0.404, 0.2814285714, 0.24, 0, 0, 0,
0, 0.265, 0, 0, 0, 0.3357142857, 0, 0, 0, 0, 0, 0, 1.188,
0, 0.232, 0.4414285714, 0, 0, 0, 0, 0, 0.5875, 0, 0.186,
0, 0, 0, 0, 0.186, 0, 0, 0, 0.572, 0, 0, 7.765714286, 0.265,
0, 0, 0, 0, 0, 0, 0, 0, 0.1442857143, 0, 0, 0, 0, 0.2528571429,
0, 0, 0.56, 0, 0.2885714286, 0, 0, 0, 2.692, 0.1328571429,
0, 0, 0.422, 0, 0.1442857143, 0, 0, 0, 0, 0.1485714286, 0,
0, 0, 0, 0, 0, 0, 0, 0.232, 0, 0, 0, 0, 0), p.value = c(1,
1, 0.201, 1, 1, 1, 0.139, 1, 1, 1, 1, 1, 1, 1, 0.195, 1,
1, 0.201, 1, 1, 0.579, 1, 0.183, 0.59, 0.173, 2.69e-30, 1.03e-05,
3.1e-31, 1.72e-50, 3.62e-08, 0.00641, 0.0959, 4.49e-14, 0.0205,
0.0357, 0.264, 1, 1, 1, 1, 1, 1, 1, 0.201, 1, 0.264, 1, 1,
1, 1, 1, 1, 1, 1, 0.195, 0.172, 0.361, 1, 1, 1, 1, 0.139,
1, 1, 1, 0.0696, 1, 1, 1, 1, 0.351, 1, 6.49e-05, 0.607, 0.604,
0.0183, 1, 1, 1, 1, 0.579, 0.0949, 0.589, 0.182, 1, 1, 1,
1, 1, 0.195, 0.571, 1, 0.00812, 1, 1, 7.27e-30, 0.00741,
1.28e-05, 1.27e-05, 1.26e-05, 0.334, 1, 0.59, 0.59, 0.000279,
0.264, 1, 1, 1, 1, 0.0696, 1, 1, 1, 1, 0.0696, 1, 1, 1, 1,
0.264, 1, 1, 1, 1, 0.264, 1, 1, 1, 1, 0.264, 1, 1, 1, 1,
1, 1, 1, 1, 0.195, 1, 1, 1, 0.201, 1)), row.names = c(NA,
145L), class = "data.frame")
> dput(head(TFRC,150))
structure(list(Variant = structure(c(28L, 28L, 28L, 28L, 28L,
23L, 23L, 23L, 23L, 23L, 21L, 21L, 21L, 21L, 21L, 6L, 6L, 6L,
6L, 6L, 8L, 8L, 8L, 8L, 8L, 10L, 10L, 10L, 10L, 10L, 14L, 14L,
14L, 14L, 14L, 15L, 15L, 15L, 15L, 15L, 25L, 25L, 25L, 25L, 25L,
16L, 16L, 16L, 16L, 16L, 22L, 22L, 22L, 22L, 22L, 9L, 9L, 9L,
9L, 9L, 7L, 7L, 7L, 7L, 7L, 19L, 19L, 19L, 19L, 19L, 11L, 11L,
11L, 11L, 11L, 1L, 1L, 1L, 1L, 1L, 20L, 20L, 20L, 20L, 20L, 27L,
27L, 27L, 27L, 27L, 5L, 5L, 5L, 5L, 5L, 12L, 12L, 12L, 12L, 12L,
26L, 26L, 26L, 26L, 26L, 24L, 24L, 24L, 24L, 24L, 3L, 3L, 3L,
3L, 3L, 4L, 4L, 4L, 4L, 4L, 13L, 13L, 13L, 13L, 13L, 29L, 29L,
29L, 29L, 29L, 17L, 17L, 17L, 17L, 17L, 18L, 18L, 18L, 18L, 18L,
2L, 2L, 2L, 2L, 2L), .Label = c("rs140316777", "rs141165322",
"rs144131234", "rs149088653", "rs184956956", "rs199637290", "rs200128950",
"rs201408488", "rs34490397", "rs3817672", "rs41295849", "rs41295879",
"rs41298067", "rs41301381", "rs41303529", "rs533268185", "rs534595346",
"rs536971550", "rs537759332", "rs539830157", "rs541010181", "rs541398971",
"rs545061104", "rs559739602", "rs563942755", "rs571673598", "rs572837317",
"rs576156970", "rs577771580"), class = "factor"), Position = c(66L,
66L, 66L, 66L, 66L, 90L, 90L, 90L, 90L, 90L, 138L, 138L, 138L,
138L, 138L, 141L, 141L, 141L, 141L, 141L, 312L, 312L, 312L, 312L,
312L, 426L, 426L, 426L, 426L, 426L, 636L, 636L, 636L, 636L, 636L,
762L, 762L, 762L, 762L, 762L, 810L, 810L, 810L, 810L, 810L, 831L,
831L, 831L, 831L, 831L, 879L, 879L, 879L, 879L, 879L, 891L, 891L,
891L, 891L, 891L, 975L, 975L, 975L, 975L, 975L, 1002L, 1002L,
1002L, 1002L, 1002L, 1011L, 1011L, 1011L, 1011L, 1011L, 1056L,
1056L, 1056L, 1056L, 1056L, 1137L, 1137L, 1137L, 1137L, 1137L,
1143L, 1143L, 1143L, 1143L, 1143L, 1221L, 1221L, 1221L, 1221L,
1221L, 1260L, 1260L, 1260L, 1260L, 1260L, 1692L, 1692L, 1692L,
1692L, 1692L, 1791L, 1791L, 1791L, 1791L, 1791L, 1794L, 1794L,
1794L, 1794L, 1794L, 1815L, 1815L, 1815L, 1815L, 1815L, 2031L,
2031L, 2031L, 2031L, 2031L, 2070L, 2070L, 2070L, 2070L, 2070L,
2103L, 2103L, 2103L, 2103L, 2103L, 2172L, 2172L, 2172L, 2172L,
2172L, 2259L, 2259L, 2259L, 2259L, 2259L), Geographical.Location = structure(c(1L,
2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L,
3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L,
4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L,
5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L,
1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L,
2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L,
3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L,
4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L,
5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L
), .Label = c("AFR", "AMR", "EAS", "EUR", "SAS"), class = "factor"),
Frequency = c(0, 0, 0.202, 0, 0, 0, 0.295, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0.192, 0, 0, 0, 0, 0.384, 7.654, 5.934, 30.13571429,
58.955, 26.458, 4.008, 0.598, 0, 0, 3.782, 0, 0.196, 0.1328571429,
0, 0, 4.056, 5.592, 0, 0, 0, 0, 0.196, 0.1257142857, 0, 0,
0, 0, 0, 0, 0, 1.414, 0.404, 0.2814285714, 0.24, 0, 0, 0,
0, 0.265, 0, 0, 0, 0.3357142857, 0, 0, 0, 0, 0, 0, 1.188,
0, 0.232, 0.4414285714, 0, 0, 0, 0, 0, 0.5875, 0, 0.186,
0, 0, 0, 0, 0.186, 0, 0, 0, 0.572, 0, 0, 7.765714286, 0.265,
0, 0, 0, 0, 0, 0, 0, 0, 0.1442857143, 0, 0, 0, 0, 0.2528571429,
0, 0, 0.56, 0, 0.2885714286, 0, 0, 0, 2.692, 0.1328571429,
0, 0, 0.422, 0, 0.1442857143, 0, 0, 0, 0, 0.1485714286, 0,
0, 0, 0, 0, 0, 0, 0, 0.232, 0, 0, 0, 0, 0), p.value = c(1,
1, 0.201, 1, 1, 1, 0.139, 1, 1, 1, 1, 1, 1, 1, 0.195, 1,
1, 0.201, 1, 1, 0.579, 1, 0.183, 0.59, 0.173, 2.69e-30, 1.03e-05,
3.1e-31, 1.72e-50, 3.62e-08, 0.00641, 0.0959, 4.49e-14, 0.0205,
0.0357, 0.264, 1, 1, 1, 1, 1, 1, 1, 0.201, 1, 0.264, 1, 1,
1, 1, 1, 1, 1, 1, 0.195, 0.172, 0.361, 1, 1, 1, 1, 0.139,
1, 1, 1, 0.0696, 1, 1, 1, 1, 0.351, 1, 6.49e-05, 0.607, 0.604,
0.0183, 1, 1, 1, 1, 0.579, 0.0949, 0.589, 0.182, 1, 1, 1,
1, 1, 0.195, 0.571, 1, 0.00812, 1, 1, 7.27e-30, 0.00741,
1.28e-05, 1.27e-05, 1.26e-05, 0.334, 1, 0.59, 0.59, 0.000279,
0.264, 1, 1, 1, 1, 0.0696, 1, 1, 1, 1, 0.0696, 1, 1, 1, 1,
0.264, 1, 1, 1, 1, 0.264, 1, 1, 1, 1, 0.264, 1, 1, 1, 1,
1, 1, 1, 1, 0.195, 1, 1, 1, 0.201, 1)), row.names = c(NA,
145L), class = "data.frame")
问题的主要问题是使要点更易于阅读。 在评论中提出的建议解决了这个问题。
第二个问题是让图例将 log10
标签显示为 10 的幂。由于我还没有找到解决这个问题的方法,所以在 Whosebug 帖子中肯定没有,这里就是。它使用 scales::math_format
的方式与用于轴标签的方式不同。
library(ggplot2)
library(scales)
TFRCggplot <- ggplot(TFRC, aes(Position, Frequency)) +
geom_jitter(aes(colour = Geographical.Location, size = log10(p.value))) +
labs(subtitle="Frequency of Various Polymorphisms", title="TFRC") +
scale_size_continuous(range = c(1, 5),
breaks = seq(0, -50, by = -10),
labels = math_format(10^.x),
trans = "reverse")
TFRCggplot + guides(size = guide_legend(reverse = TRUE))
这些值会自动设置为 0.25、0.50、0.75 和 1。但是,我想更改这些范围,特别是让它们变小。这是我的代码。我还添加了一些样本数据,如您所见,p 值(我感兴趣的变量)的范围从小到“1.72e-50”到“1”。
library(ggplot2)
data(TFRC, package="ggplot2")
#imports/scans the data from file explorer/spreadsheets
TFRC <- read.csv(file.choose(), header = TRUE)
# bubble chart showing position of polymorphisms on gene, the frequency of each of these polymorphisms, where they are prominent on earth, and p-value
TFRCggplot <- ggplot(TFRC, aes(Position, Frequency))+
geom_jitter(aes(col=Geographical.Location, size=p.value))+
labs(subtitle="Frequency of Various Polymorphisms", title="TFRC") +
scale_size_continuous(range=c(1,5), trans = "reverse")
TFRCggplot + guides(size = guide_legend(reverse = TRUE))
Here is some sample data.
structure(list(Variant = structure(c(28L, 28L, 28L, 28L, 28L,
23L, 23L, 23L, 23L, 23L, 21L, 21L, 21L, 21L, 21L, 6L, 6L, 6L,
6L, 6L, 8L, 8L, 8L, 8L, 8L, 10L, 10L, 10L, 10L, 10L, 14L, 14L,
14L, 14L, 14L, 15L, 15L, 15L, 15L, 15L, 25L, 25L, 25L, 25L, 25L,
16L, 16L, 16L, 16L, 16L, 22L, 22L, 22L, 22L, 22L, 9L, 9L, 9L,
9L, 9L, 7L, 7L, 7L, 7L, 7L, 19L, 19L, 19L, 19L, 19L, 11L, 11L,
11L, 11L, 11L, 1L, 1L, 1L, 1L, 1L, 20L, 20L, 20L, 20L, 20L, 27L,
27L, 27L, 27L, 27L, 5L, 5L, 5L, 5L, 5L, 12L, 12L, 12L, 12L, 12L,
26L, 26L, 26L, 26L, 26L, 24L, 24L, 24L, 24L, 24L, 3L, 3L, 3L,
3L, 3L, 4L, 4L, 4L, 4L, 4L, 13L, 13L, 13L, 13L, 13L, 29L, 29L,
29L, 29L, 29L, 17L, 17L, 17L, 17L, 17L, 18L, 18L, 18L, 18L, 18L,
2L, 2L, 2L, 2L, 2L), .Label = c("rs140316777", "rs141165322",
"rs144131234", "rs149088653", "rs184956956", "rs199637290", "rs200128950",
"rs201408488", "rs34490397", "rs3817672", "rs41295849", "rs41295879",
"rs41298067", "rs41301381", "rs41303529", "rs533268185", "rs534595346",
"rs536971550", "rs537759332", "rs539830157", "rs541010181", "rs541398971",
"rs545061104", "rs559739602", "rs563942755", "rs571673598", "rs572837317",
"rs576156970", "rs577771580"), class = "factor"), Position = c(66L,
66L, 66L, 66L, 66L, 90L, 90L, 90L, 90L, 90L, 138L, 138L, 138L,
138L, 138L, 141L, 141L, 141L, 141L, 141L, 312L, 312L, 312L, 312L,
312L, 426L, 426L, 426L, 426L, 426L, 636L, 636L, 636L, 636L, 636L,
762L, 762L, 762L, 762L, 762L, 810L, 810L, 810L, 810L, 810L, 831L,
831L, 831L, 831L, 831L, 879L, 879L, 879L, 879L, 879L, 891L, 891L,
891L, 891L, 891L, 975L, 975L, 975L, 975L, 975L, 1002L, 1002L,
1002L, 1002L, 1002L, 1011L, 1011L, 1011L, 1011L, 1011L, 1056L,
1056L, 1056L, 1056L, 1056L, 1137L, 1137L, 1137L, 1137L, 1137L,
1143L, 1143L, 1143L, 1143L, 1143L, 1221L, 1221L, 1221L, 1221L,
1221L, 1260L, 1260L, 1260L, 1260L, 1260L, 1692L, 1692L, 1692L,
1692L, 1692L, 1791L, 1791L, 1791L, 1791L, 1791L, 1794L, 1794L,
1794L, 1794L, 1794L, 1815L, 1815L, 1815L, 1815L, 1815L, 2031L,
2031L, 2031L, 2031L, 2031L, 2070L, 2070L, 2070L, 2070L, 2070L,
2103L, 2103L, 2103L, 2103L, 2103L, 2172L, 2172L, 2172L, 2172L,
2172L, 2259L, 2259L, 2259L, 2259L, 2259L), Geographical.Location = structure(c(1L,
2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L,
3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L,
4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L,
5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L,
1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L,
2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L,
3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L,
4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L,
5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L
), .Label = c("AFR", "AMR", "EAS", "EUR", "SAS"), class = "factor"),
Frequency = c(0, 0, 0.202, 0, 0, 0, 0.295, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0.192, 0, 0, 0, 0, 0.384, 7.654, 5.934, 30.13571429,
58.955, 26.458, 4.008, 0.598, 0, 0, 3.782, 0, 0.196, 0.1328571429,
0, 0, 4.056, 5.592, 0, 0, 0, 0, 0.196, 0.1257142857, 0, 0,
0, 0, 0, 0, 0, 1.414, 0.404, 0.2814285714, 0.24, 0, 0, 0,
0, 0.265, 0, 0, 0, 0.3357142857, 0, 0, 0, 0, 0, 0, 1.188,
0, 0.232, 0.4414285714, 0, 0, 0, 0, 0, 0.5875, 0, 0.186,
0, 0, 0, 0, 0.186, 0, 0, 0, 0.572, 0, 0, 7.765714286, 0.265,
0, 0, 0, 0, 0, 0, 0, 0, 0.1442857143, 0, 0, 0, 0, 0.2528571429,
0, 0, 0.56, 0, 0.2885714286, 0, 0, 0, 2.692, 0.1328571429,
0, 0, 0.422, 0, 0.1442857143, 0, 0, 0, 0, 0.1485714286, 0,
0, 0, 0, 0, 0, 0, 0, 0.232, 0, 0, 0, 0, 0), p.value = c(1,
1, 0.201, 1, 1, 1, 0.139, 1, 1, 1, 1, 1, 1, 1, 0.195, 1,
1, 0.201, 1, 1, 0.579, 1, 0.183, 0.59, 0.173, 2.69e-30, 1.03e-05,
3.1e-31, 1.72e-50, 3.62e-08, 0.00641, 0.0959, 4.49e-14, 0.0205,
0.0357, 0.264, 1, 1, 1, 1, 1, 1, 1, 0.201, 1, 0.264, 1, 1,
1, 1, 1, 1, 1, 1, 0.195, 0.172, 0.361, 1, 1, 1, 1, 0.139,
1, 1, 1, 0.0696, 1, 1, 1, 1, 0.351, 1, 6.49e-05, 0.607, 0.604,
0.0183, 1, 1, 1, 1, 0.579, 0.0949, 0.589, 0.182, 1, 1, 1,
1, 1, 0.195, 0.571, 1, 0.00812, 1, 1, 7.27e-30, 0.00741,
1.28e-05, 1.27e-05, 1.26e-05, 0.334, 1, 0.59, 0.59, 0.000279,
0.264, 1, 1, 1, 1, 0.0696, 1, 1, 1, 1, 0.0696, 1, 1, 1, 1,
0.264, 1, 1, 1, 1, 0.264, 1, 1, 1, 1, 0.264, 1, 1, 1, 1,
1, 1, 1, 1, 0.195, 1, 1, 1, 0.201, 1)), row.names = c(NA,
145L), class = "data.frame")
> dput(head(TFRC,150))
structure(list(Variant = structure(c(28L, 28L, 28L, 28L, 28L,
23L, 23L, 23L, 23L, 23L, 21L, 21L, 21L, 21L, 21L, 6L, 6L, 6L,
6L, 6L, 8L, 8L, 8L, 8L, 8L, 10L, 10L, 10L, 10L, 10L, 14L, 14L,
14L, 14L, 14L, 15L, 15L, 15L, 15L, 15L, 25L, 25L, 25L, 25L, 25L,
16L, 16L, 16L, 16L, 16L, 22L, 22L, 22L, 22L, 22L, 9L, 9L, 9L,
9L, 9L, 7L, 7L, 7L, 7L, 7L, 19L, 19L, 19L, 19L, 19L, 11L, 11L,
11L, 11L, 11L, 1L, 1L, 1L, 1L, 1L, 20L, 20L, 20L, 20L, 20L, 27L,
27L, 27L, 27L, 27L, 5L, 5L, 5L, 5L, 5L, 12L, 12L, 12L, 12L, 12L,
26L, 26L, 26L, 26L, 26L, 24L, 24L, 24L, 24L, 24L, 3L, 3L, 3L,
3L, 3L, 4L, 4L, 4L, 4L, 4L, 13L, 13L, 13L, 13L, 13L, 29L, 29L,
29L, 29L, 29L, 17L, 17L, 17L, 17L, 17L, 18L, 18L, 18L, 18L, 18L,
2L, 2L, 2L, 2L, 2L), .Label = c("rs140316777", "rs141165322",
"rs144131234", "rs149088653", "rs184956956", "rs199637290", "rs200128950",
"rs201408488", "rs34490397", "rs3817672", "rs41295849", "rs41295879",
"rs41298067", "rs41301381", "rs41303529", "rs533268185", "rs534595346",
"rs536971550", "rs537759332", "rs539830157", "rs541010181", "rs541398971",
"rs545061104", "rs559739602", "rs563942755", "rs571673598", "rs572837317",
"rs576156970", "rs577771580"), class = "factor"), Position = c(66L,
66L, 66L, 66L, 66L, 90L, 90L, 90L, 90L, 90L, 138L, 138L, 138L,
138L, 138L, 141L, 141L, 141L, 141L, 141L, 312L, 312L, 312L, 312L,
312L, 426L, 426L, 426L, 426L, 426L, 636L, 636L, 636L, 636L, 636L,
762L, 762L, 762L, 762L, 762L, 810L, 810L, 810L, 810L, 810L, 831L,
831L, 831L, 831L, 831L, 879L, 879L, 879L, 879L, 879L, 891L, 891L,
891L, 891L, 891L, 975L, 975L, 975L, 975L, 975L, 1002L, 1002L,
1002L, 1002L, 1002L, 1011L, 1011L, 1011L, 1011L, 1011L, 1056L,
1056L, 1056L, 1056L, 1056L, 1137L, 1137L, 1137L, 1137L, 1137L,
1143L, 1143L, 1143L, 1143L, 1143L, 1221L, 1221L, 1221L, 1221L,
1221L, 1260L, 1260L, 1260L, 1260L, 1260L, 1692L, 1692L, 1692L,
1692L, 1692L, 1791L, 1791L, 1791L, 1791L, 1791L, 1794L, 1794L,
1794L, 1794L, 1794L, 1815L, 1815L, 1815L, 1815L, 1815L, 2031L,
2031L, 2031L, 2031L, 2031L, 2070L, 2070L, 2070L, 2070L, 2070L,
2103L, 2103L, 2103L, 2103L, 2103L, 2172L, 2172L, 2172L, 2172L,
2172L, 2259L, 2259L, 2259L, 2259L, 2259L), Geographical.Location = structure(c(1L,
2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L,
3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L,
4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L,
5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L,
1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L,
2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L,
3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L,
4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L,
5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L
), .Label = c("AFR", "AMR", "EAS", "EUR", "SAS"), class = "factor"),
Frequency = c(0, 0, 0.202, 0, 0, 0, 0.295, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0.192, 0, 0, 0, 0, 0.384, 7.654, 5.934, 30.13571429,
58.955, 26.458, 4.008, 0.598, 0, 0, 3.782, 0, 0.196, 0.1328571429,
0, 0, 4.056, 5.592, 0, 0, 0, 0, 0.196, 0.1257142857, 0, 0,
0, 0, 0, 0, 0, 1.414, 0.404, 0.2814285714, 0.24, 0, 0, 0,
0, 0.265, 0, 0, 0, 0.3357142857, 0, 0, 0, 0, 0, 0, 1.188,
0, 0.232, 0.4414285714, 0, 0, 0, 0, 0, 0.5875, 0, 0.186,
0, 0, 0, 0, 0.186, 0, 0, 0, 0.572, 0, 0, 7.765714286, 0.265,
0, 0, 0, 0, 0, 0, 0, 0, 0.1442857143, 0, 0, 0, 0, 0.2528571429,
0, 0, 0.56, 0, 0.2885714286, 0, 0, 0, 2.692, 0.1328571429,
0, 0, 0.422, 0, 0.1442857143, 0, 0, 0, 0, 0.1485714286, 0,
0, 0, 0, 0, 0, 0, 0, 0.232, 0, 0, 0, 0, 0), p.value = c(1,
1, 0.201, 1, 1, 1, 0.139, 1, 1, 1, 1, 1, 1, 1, 0.195, 1,
1, 0.201, 1, 1, 0.579, 1, 0.183, 0.59, 0.173, 2.69e-30, 1.03e-05,
3.1e-31, 1.72e-50, 3.62e-08, 0.00641, 0.0959, 4.49e-14, 0.0205,
0.0357, 0.264, 1, 1, 1, 1, 1, 1, 1, 0.201, 1, 0.264, 1, 1,
1, 1, 1, 1, 1, 1, 0.195, 0.172, 0.361, 1, 1, 1, 1, 0.139,
1, 1, 1, 0.0696, 1, 1, 1, 1, 0.351, 1, 6.49e-05, 0.607, 0.604,
0.0183, 1, 1, 1, 1, 0.579, 0.0949, 0.589, 0.182, 1, 1, 1,
1, 1, 0.195, 0.571, 1, 0.00812, 1, 1, 7.27e-30, 0.00741,
1.28e-05, 1.27e-05, 1.26e-05, 0.334, 1, 0.59, 0.59, 0.000279,
0.264, 1, 1, 1, 1, 0.0696, 1, 1, 1, 1, 0.0696, 1, 1, 1, 1,
0.264, 1, 1, 1, 1, 0.264, 1, 1, 1, 1, 0.264, 1, 1, 1, 1,
1, 1, 1, 1, 0.195, 1, 1, 1, 0.201, 1)), row.names = c(NA,
145L), class = "data.frame")
问题的主要问题是使要点更易于阅读。
第二个问题是让图例将 log10
标签显示为 10 的幂。由于我还没有找到解决这个问题的方法,所以在 Whosebug 帖子中肯定没有,这里就是。它使用 scales::math_format
的方式与用于轴标签的方式不同。
library(ggplot2)
library(scales)
TFRCggplot <- ggplot(TFRC, aes(Position, Frequency)) +
geom_jitter(aes(colour = Geographical.Location, size = log10(p.value))) +
labs(subtitle="Frequency of Various Polymorphisms", title="TFRC") +
scale_size_continuous(range = c(1, 5),
breaks = seq(0, -50, by = -10),
labels = math_format(10^.x),
trans = "reverse")
TFRCggplot + guides(size = guide_legend(reverse = TRUE))