我有基因,样本的数据框(tcell_pdx_log_wgene_melt)和某些基因的表达值。 我的数据框架如下:
gene sample log_fpkm
ITGB1 Sample_7630_T1_PDX_mousereads 4.4667698
ADIPOR1 Sample_7630_T1_PDX_mousereads 3.7562811
ADIPOR2 Sample_7630_T1_PDX_mousereads 2.4823200
RYK Sample_7630_T1_PDX_mousereads 2.4521252
JAG1 Sample_7630_T1_PDX_mousereads 1.7713867
ITGB1 Sample_NYA_MT.05_primary_mousereads 1.9555776
ADIPOR1 Sample_NYA_MT.05_primary_mousereads 1.7365991
ADIPOR2 Sample_NYA_MT.05_primary_mousereads 2.1131181
RYK Sample_NYA_MT.05_primary_mousereads 1.1464496
JAG1 Sample_NYA_MT.05_primary_mousereads 0.6931472
ITGB1 Sample_7630_T1_PDX_humanreads 4.5363987
ADIPOR1 Sample_7630_T1_PDX_humanreads 3.5718399
ADIPOR2 Sample_7630_T1_PDX_humanreads 2.4756977
RYK Sample_7630_T1_PDX_humanreads 1.8449842
JAG1 Sample_7630_T1_PDX_humanreads 1.7451918
下面的图表按字母顺序排列这些基因,但我希望按照变量类型“Sample_7630_T1_PDX_humanreads”之一对图表进行排序
tcell_pdx_log_wgene_melt$sample <- as.character(tcell_pdx_log_wgene_melt$sample)
tcell_pdx_log_wgene_melt$sample <- factor(tcell_pdx_log_wgene_melt$sample, levels=unique(tcell_pdx_log_wgene_melt$sample))
p <- ggplot(tcell_pdx_log_wgene_melt,aes(gene,log_fpkm,group=sample)) +
geom_point()
p + geom_line(aes(color=sample))
答案 0 :(得分:0)
不确定您要找的是什么,但我dput()
并在下面绘制了您的数据。也许你可以用它来解释你想要做什么?如果您制作一个可重复性最小的示例来与您的问题一起使用。我们可以使用的东西,用于向您展示如何解决您的问题。您可以查看this SO post如何在R中制作出色的可重复示例。
tcell_pdx_log_wgene_melt <- structure(list(gene = structure(c(3L, 1L, 2L, 5L, 4L,
3L, 1L, 2L, 5L, 4L, 3L, 1L, 2L, 5L, 4L),
.Label = c("ADIPOR1", "ADIPOR2",
"ITGB1", "JAG1", "RYK"), class = "factor"),
sample = structure(c(2L,
2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L, 1L),
.Label = c("Sample_7630_T1_PDX_humanreads",
"Sample_7630_T1_PDX_mousereads", "Sample_NYA_MT.05_primary_mousereads"
), class = "factor"), log_fpkm = c(4.4667698, 3.7562811, 2.48232,
2.4521252, 1.7713867, 1.9555776, 1.7365991, 2.1131181, 1.1464496,
0.6931472, 4.5363987, 3.5718399, 2.4756977, 1.8449842, 1.7451918
)), .Names = c("gene", "sample", "log_fpkm"),
class = "data.frame", row.names = c(NA, -15L))
# install.packages("ggplot2", dependencies = TRUE)
library(ggplot2)
p <- ggplot( tcell_pdx_log_wgene_melt,aes(gene,log_fpkm,group=sample))
+ geom_point()
p + geom_line(aes(color=sample))