Pathways：操作 R 中父子“节点”中的事件列表

我感兴趣的是根据预先指定的事件列表（例如诊断、手术、治疗1、治疗2、死亡）可视化患者的路径。

测试数据集可能如下所示：

df <- structure(list(ID = structure(c(1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 
3L, 3L, 3L, 3L), .Label = c("a", "b", "c"), class = "factor"), 
    Event = structure(c(2L, 3L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 
    5L, 1L), .Label = c("death", "diagnosis", "surgery", "treatment1", 
    "treatment2"), class = "factor"), date = structure(c(14610, 
    14619, 16667, 14975, 14976, 14977, 15074, 15084, 15006, 15050, 
    15051, 15053), class = "Date")), .Names = c("ID", "Event", 
"date"), row.names = c(NA, 12L), class = "data.frame")

> df
   ID      Event       date
1   a  diagnosis 2010-01-01
2   a    surgery 2010-01-10
3   a      death 2015-08-20
4   b  diagnosis 2011-01-01
5   b    surgery 2011-01-02
6   b treatment1 2011-01-03
7   b treatment2 2011-04-10
8   b      death 2011-04-20
9   c  diagnosis 2011-02-01
10  c    surgery 2011-03-17
11  c treatment2 2011-03-18
12  c      death 2011-03-20

数据已按 ID 和日期排序。

我所追求的是以下内容：

> result
  ID     parent      child datediff
1  a  diagnosis    surgery        9
2  a    surgery      death     1950
3  b  diagnosis    surgery        1
4  b    surgery treatment1        1
5  b treatment1 treatment2       90
6  b treatment2      death       10
7  c  diagnosis    surgery       45
8  c    surgery treatment2        1
9  c treatment2      death        2

（请注意，datediff 列中的数字并非实际数字） 即一系列父子节点，它们之间的日期不同。

这将使我能够绘制节点，并对事件之间的时间进行一些进一步的描述性分析。

我找到了一个绘制节点的包（见下文）...有没有一种方法/包可以让箭头宽度反映父子组合的数量？

 require(igraph) # possible package to use
 parents<-c("A","A","A","A","A","A","C","C","F","F","H","I")
 children<-c("I","I","I","I","B","A","D","H","G","H","I","J")
 begats<-data.frame(parents=parents,children=children)
 graph_begats<-graph.data.frame(begats)
 tkplot(graph_begats)

折叠您的数据以给出每个父子组合以及它们发生的次数，例如：

# put the previous event against the current event, and drop the rows before the first event:
df$Event <- as.character(df$Event)
df$PreEvent <- with(df, ave(Event,ID,FUN=function(x) c(NA,head(x,-1)) ) )
result <- df[!is.na(df$PreEvent),c("ID","PreEvent","Event")]

# aggregate the combos by how often they occur:
result <- aggregate(list(count=rownames(result)),result[c("PreEvent","Event")],FUN=length)
#    PreEvent      Event count
#1    surgery      death     1
#2 treatment2      death     2
#3  diagnosis    surgery     3
#4    surgery treatment1     1
#5    surgery treatment2     1
#6 treatment1 treatment2     1

# plot in igraph, adjusting the edge.width to account for how many cases of each
# parent-child combo exist:
library(igraph)
g <- graph.data.frame(result)
plot(g,edge.width=result$count)