r - 如何从 df 的不同列中获取闪避的 geom_bar (ggplot2)
问题描述
显示数据框df
:
ID gene1 gene2
4602 TET2 TET2
4602 TP53 TP53
4602 TET2 TET2
5095 ASXL1 ASXL1
5095 DNMT3A DNMT3A
5095 NPM1 <NA>
我一直在尝试获取一个匹配的条形图,显示列gene1
和gene2
. 该gene1
方法是标准,而gene2是另一个应该比较的突变检测器gene1
。如您所见,在样本中5095
仅检测到 2 个突变,而第 3 个未复制。
我如何制作一个带有两个条的条形图,每个条ID
显示计数gene1
和gene2
?
这里 dput()
structure(list(ID = c(4602, 4602, 4602, 5095, 5095, 5095, 5095,
4649, 4649, 4649, 5069, 5069, 5069, 5146, 5132, 5132, 5132, 5132,
5132, 5132, 4297, 4297, 4297, 4297, 4297, 4345, 4345, 4345, 4345,
4345, 4356, 4356, 4356, 4356, 4385, 4385, 4385, 4385, 4385, 4385,
4437, 4437, 4437, 4437, 4437, 4437, 4442, 4442, 4442, 4442, 4442,
4479, 4479, 4479, 4479, 4479, 4479, 4479, 4479, 4479, 4479, 4479,
4479, 4479, 4479, 4479, 4487, 4487, 4487, 4487, 4487, 4487, 4537,
4537, 4537, 4537, 4537, 4537, 4621, 4621, 4621, 4621, 4621, 4621,
4621, 4624, 4624, 4624, 4624, 4624, 4665, 4736, 4736, 4736, 4736,
4736, 4895, 4895, 4895, 4895, 4895, 4903, 4903, 4903, 4903, 4691,
4691, 4691, 4691, 4261, 4261, 4261, 4261, 4394, 4394, 4394, 4394,
4424, 4424, 4424, 4424, 4943, 4943, 4943, 5073, 5169, 5169),
gene1 = c("TET2", "TP53", "TET2", "ASXL1", "DNMT3A", "NPM1",
"PTPN11", "TP53", "TP53", "TET2", "DNMT3A", "TET2", "TET2",
"negative", "JAK2", "ASXL1", "BRAF", "CBL", "TET2", "TET2",
"DNMT3A", "IDH1", "NPM1", "CREBBP", "FLT3", "DNMT3A", "FLT3",
"NPM1", "BCOR", "KIT", "DNMT3A", "IDH1", "NRAS", "BCOR",
"KRAS", "NPM1", "PTPN11", "ETV6", "PHF6", "TET2", "DNMT3A",
"KRAS", "NPM1", "WT1", "TET2", "WT1", "DNMT3A", "FLT3", "NPM1",
"NRAS", "WT1", "DNMT3A", "IDH2", "NPM1", "SRSF2", "ATRX",
"CUX1", "CUX1", "FLT3", "GNAS", "PHF6", "PIGA", "PIGA", "PRPF40B",
"PTPN11", "TET2", "IDH1", "IDH2", "RUNX1", "U2AF1", "TET2",
"TP53", "DNMT3A", "IDH2", "ATRX", "GATA2", "STAG2", "TP53",
"IDH2", "SRSF2", "ASXL1", "GATA1", "KDM6A", "STAG2", "TP53",
"IDH2", "JAK2", "SRSF2", "ASXL1", "RIT1", "KRAS", "NPM1",
"NRAS", "NRAS", "BCOR", "MYD88", "FLT3", "NPM1", "NRAS",
"TET2", "TET2", "DNMT3A", "IDH1", "NPM1", "CREBBP", "DNMT3A",
"IDH1", "IDH2", "NPM1", "FLT3", "FLT3", "GATA2", "SH2B3",
"FLT3", "NPM1", "KDM6A", "SMC1A", "IDH2", "SRSF2", "ASXL2",
"RUNX1", "IDH2", "JAK2", "NPM1", "JAK2", "SRSF2", "STAG2"
), gene2 = c("TET2", "TP53", "TET2", "ASXL1", "DNMT3A", NA,
"PTPN11", "TP53", "TP53", "TET2", "DNMT3A", NA, "TET2", "PTEN",
NA, NA, "BRAF", "CBL", "TET2", "TET2", "JAK2", "SRSF2", NA,
"DNMT3A", "IDH1", "NPM1", NA, "FLT3", "DNMT3A", "FLT3", "NPM1",
NA, NA, "DNMT3A", "IDH1", "NRAS", "BCOR", "KRAS", "NPM1",
"PTPN11", "ETV6", "PHF6", "TET2", "DNMT3A", "KRAS", "NPM1",
NA, "TET2", NA, "DNMT3A", "FLT3", "NPM1", "NRAS", NA, NA,
"IDH2", "NPM1", "SRSF2", NA, "CALR", NA, NA, NA, NA, NA,
NA, NA, NA, NA, "IDH1", "IDH2", "RUNX1", "U2AF1", "TET2",
NA, "DNMT3A", "IDH2", NA, NA, NA, NA, "IDH2", "SRSF2", "ASXL1",
NA, NA, "KMT2D", "TP53", "IDH2", "JAK2", "SRSF2", "ASXL1",
NA, "KRAS", "NPM1", "NRAS", "NRAS", NA, NA, "FLT3", "NPM1",
"NRAS", "TET2", "TET2", "DNMT3A", "IDH1", "NPM1", "CREBBP",
"DNMT3A", "IDH1", "IDH2", "NPM1", "FLT3", "FLT3", NA, NA,
"FLT3", "NPM1", NA, "SMC1A", "IDH2", "SRSF2", NA, "RUNX1",
"IDH2", "JAK2", "NPM1")), class = "data.frame", row.names = c(NA,
-127L))
解决方案
多一个:
df %>%
group_by(ID) %>%
add_count(gene1, gene2) %>%
pivot_longer(
cols = contains("gene")
) %>%
ungroup() %>%
ggplot(aes(factor(name), n, fill=value, group=value, label=value)) +
geom_col() +
facet_wrap(.~ID, scales = "free_y") +
geom_text(size = 3, position = position_stack(vjust = 0.5)) +
theme_classic()+
xlab("") +
guides(fill=FALSE)
最后一次尝试,现在应该可以了。现在我们在旋转之前计算:
df %>%
group_by(ID) %>%
add_count(gene1, gene2) %>%
pivot_longer(
cols = contains("gene")
) %>%
ungroup() %>%
ggplot(aes(factor(name), n, fill=value, group=value)) +
geom_col() +
facet_wrap(.~ID, scales = "free_y") +
theme(legend.position = "bottom")+
guides(fill=guide_legend(nrow=2))
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