如何显示仅显示值高于特定数字的行？

Question

这是用下面的代码生成的图：

但是我想显示ZIP协同得分为1或以上的数据，如下图：

这是我用来生成第一个图的代码，即 基本上基于 synergyfinder 包和 ggplot，我有 来自这个社区的一些帮助，我真的很感激 它（因为我正在以自学者的身份探索自己的道路），能够走到这一步， 我要特别感谢@kat 的帮助：

library(synergyfinder)
library(tidyverse)


data<- read_xlsx("N+X+syn.xlsx")
head(data)
dput(data)
res <- ReshapeData(
  data = data,
  data_type = "inhibition",
  impute = TRUE,
  impute_method = NULL,
  noise = TRUE,
  seed = 1)

res <- CalculateSynergy(
  data = res,
  method = c("ZIP", "HSA", "Bliss", "Loewe"),
  Emin = NA,
  Emax = NA,
  correct_baseline = "non")


res$drug_pairs



res <- CalculateSensitivity(
  data = res,
  correct_baseline = "non"
)


sensitive_columns <- c(
  "block_id", "drug1", "drug2",
  "ic50_1", "ic50_2",
  "ri_1", "ri_2",
  "css1_ic502", "css2_ic501", "css")
res$drug_pairs[, sensitive_columns]





plt <- PlotMultiDrugBar(          
  data = res,
  plot_block = 1,
  plot_value = c("response", "ZIP_synergy", "Bliss_synergy", "HSA_synergy", "Loewe_synergy"),
  sort_by = "ZIP_synergy",
  highlight_label_size = 4
)


plt + geom_text(data = plt[["layers"]][[1]][["data"]] %>% group_by(metric) %>% 
                  mutate(mnm = min(value)) %>% ungroup(),  # group max val!
                mapping = aes(x = id, y = mnm, 
                              label = sprintf("%.2f", value), hjust = 1),
                size = rel(2.3))+
  geom_bar(stat = "identity", width = 4, show.legend = FALSE) +  # Wider bars
  scale_fill_manual(values = c("lightblue", "red")) +
  theme_minimal() %>% 
  theme(strip.text = element_text(face = "bold", size = rel(.8)), # facet titles
        axis.text = element_text(size = rel(.75))) 

这是输出：

dput(data)
structure(list(block_id = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1), drug1 = c("X", "X", "X", "X", "X", "X", 
"X", "X", "X", "X", "X", "X", "X", "X", "X", "X", "X", "X", "X", 
"X", "X", "X", "X", "X", "X", "X", "X", "X", "X", "X", "X", "X", 
"X", "X", "X", "X", "X", "X", "X", "X", "X", "X", "X", "X", "X", 
"X", "X", "X", "X", "X", "X", "X", "X", "X", "X", "X", "X", "X", 
"X", "X", "X", "X", "X", "X", "X", "X", "X", "X", "X", "X", "X", 
"X", "X", "X", "X", "X", "X", "X", "X", "X", "X"), drug2 = c("N", 
"N", "N", "N", "N", "N", "N", "N", "N", "N", "N", "N", "N", "N", 
"N", "N", "N", "N", "N", "N", "N", "N", "N", "N", "N", "N", "N", 
"N", "N", "N", "N", "N", "N", "N", "N", "N", "N", "N", "N", "N", 
"N", "N", "N", "N", "N", "N", "N", "N", "N", "N", "N", "N", "N", 
"N", "N", "N", "N", "N", "N", "N", "N", "N", "N", "N", "N", "N", 
"N", "N", "N", "N", "N", "N", "N", "N", "N", "N", "N", "N", "N", 
"N", "N"), cell_line_name = c("A", "A", "A", "A", "A", "A", "A", 
"A", "A", "A", "A", "A", "A", "A", "A", "A", "A", "A", "A", "A", 
"A", "A", "A", "A", "A", "A", "A", "A", "A", "A", "A", "A", "A", 
"A", "A", "A", "A", "A", "A", "A", "A", "A", "A", "A", "A", "A", 
"A", "A", "A", "A", "A", "A", "A", "A", "A", "A", "A", "A", "A", 
"A", "A", "A", "A", "A", "A", "A", "A", "A", "A", "A", "A", "A", 
"A", "A", "A", "A", "A", "A", "A", "A", "A"), conc1 = c(0, 10, 
3.333, 1.111, 0.37, 0.123, 0.041, 0.014, 0.005, 10, 3.333, 1.111, 
0.37, 0.123, 0.041, 0.014, 0.005, 10, 3.333, 1.111, 0.37, 0.123, 
0.041, 0.014, 0.005, 10, 3.333, 1.111, 0.37, 0.123, 0.041, 0.014, 
0.005, 10, 3.333, 1.111, 0.37, 0.123, 0.041, 0.014, 0.005, 10, 
3.333, 1.111, 0.37, 0.123, 0.041, 0.014, 0.005, 10, 3.333, 1.111, 
0.37, 0.123, 0.041, 0.014, 0.005, 10, 3.333, 1.111, 0.37, 0.123, 
0.041, 0.014, 0.005, 10, 3.333, 1.111, 0.37, 0.123, 0.041, 0.014, 
0.005, 0, 0, 0, 0, 0, 0, 0, 0), conc2 = c(0, 0, 0, 0, 0, 0, 0, 
0, 0, 150, 150, 150, 150, 150, 150, 150, 150, 50, 50, 50, 50, 
50, 50, 50, 50, 16.67, 16.67, 16.67, 16.67, 16.67, 16.67, 16.67, 
16.67, 5.56, 5.56, 5.56, 5.56, 5.56, 5.56, 5.56, 5.56, 1.85, 
1.85, 1.85, 1.85, 1.85, 1.85, 1.85, 1.85, 0.62, 0.62, 0.62, 0.62, 
0.62, 0.62, 0.62, 0.62, 0.21, 0.21, 0.21, 0.21, 0.21, 0.21, 0.21, 
0.21, 0.07, 0.07, 0.07, 0.07, 0.07, 0.07, 0.07, 0.07, 150, 50, 
16.67, 5.56, 1.85, 0.62, 0.21, 0.07), response = c(0, 94.7124199185235, 
93.1970077742489, 94.9121253949008, 92.6627816399623, 90.6942562299578, 
86.7432204326113, 48.8019769163964, -2.019990126606, 99.7699471228007, 
99.7643531318657, 99.8387532113004, 99.6921906488051, 99.7039380297684, 
99.7800163064836, 99.7251951953212, 99.7140072134513, 99.6300973494272, 
99.7033786306749, 99.7979170774754, 99.7464523608739, 99.6166717711834, 
99.6837996624026, 99.6088401838745, 99.5780732337323, 99.6446417258581, 
99.8689607623491, 99.7050568279554, 99.6390477349231, 99.7772193110161, 
99.7945606829144, 99.7207200025732, 99.5780732337323, 99.5484250817772, 
99.7190418052928, 99.6888342542441, 99.566325852769, 99.5881424174152, 
99.6485575195125, 99.4751438005295, 98.9370018725885, 98.8228844575157, 
98.9990951719663, 99.1876126664737, 98.7663851490729, 98.937561271682, 
98.7585535617639, 98.3658553981313, 95.1935031389282, 95.5710975270365, 
96.8308642855844, 97.3986543654806, 97.0109907936894, 94.7661222314989, 
92.3651813222237, 61.1669344789827, 35.6409944437685, 92.832279565291, 
95.5559937515121, 94.2240645099035, 93.8056339879701, 89.7701289275061, 
85.7827321890825, 17.6205120459602, -15.2531350822946, 92.5413920366742, 
95.9811370625674, 95.9156873686286, 95.6835367448287, 96.19930270903, 
91.2323981578988, 28.2244812622281, -0.782599331797783, 100.146982111815, 
99.5322025080658, 99.7486899572479, 99.293339095144, 98.126432586116, 
82.4643767664774, -3.55274364277894, -8.35518486042292), conc_unit = c("μM", 
"μM", "μM", "μM", "μM", "μM", "μM", "μM", "μM", "μM", 
"μM", "μM", "μM", "μM", "μM", "μM", "μM", "μM", "μM", 
"μM", "μM", "μM", "μM", "μM", "μM", "μM", "μM", "μM", 
"μM", "μM", "μM", "μM", "μM", "μM", "μM", "μM", "μM", 
"μM", "μM", "μM", "μM", "μM", "μM", "μM", "μM", "μM", 
"μM", "μM", "μM", "μM", "μM", "μM", "μM", "μM", "μM", 
"μM", "μM", "μM", "μM", "μM", "μM", "μM", "μM", "μM", 
"μM", "μM", "μM", "μM", "μM", "μM", "μM", "μM", "μM", 
"μM", "μM", "μM", "μM", "μM", "μM", "μM", "μM")), class = c("tbl_df", 
"tbl", "data.frame"), row.names = c(NA, -81L))

我尝试过一些功能，如过滤器，但失败了，因为 if 无法识别 res 的输出。

Answer 1

过滤

synergy_scores

组件，然后通过对“block_id”、“conc1”和“conc2”使用半连接来过滤

repsonse

组件的相应行。

res1 <- res
res1$synergy_scores <- filter(res1$synergy_scores, ZIP_synergy>=1)
res1$response <- semi_join(res1$response, res1$synergy_scores, by=c("block_id", "conc1", "conc2"))

plt.zip1 <- PlotMultiDrugBar(          
  data = res1,
  plot_block = 1,
  plot_value = c("response", "ZIP_synergy", "Bliss_synergy", "HSA_synergy", "Loewe_synergy"),
  sort_by = "ZIP_synergy",
  highlight_label_size = 4
)

plt.zip1 + geom_text(data = plt.zip1[["layers"]][[1]][["data"]] %>% group_by(metric) %>% 
                  mutate(mnm = min(value)) %>% ungroup(),  # group max val!
                mapping = aes(x = id, y = mnm, 
                              label = sprintf("%.2f", value), hjust = 1),
                size = rel(2.3))+
  geom_bar(stat = "identity", width = 4, show.legend = FALSE) +  # Wider bars
  scale_fill_manual(values = c("lightblue", "red")) +
  theme_minimal() %>% 
  theme(strip.text = element_text(face = "bold", size = rel(.8)), # facet titles
        axis.text = element_text(size = rel(.75)))  +
  scale_y_continuous(lim=c())

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