您似乎是在说只有开始和结束节点才作为节点感兴趣，因此您可以将这些节点用作顶点并将中间节点显示为边标签，如以下代码和绘图所示。假设 df 包含您的汇总数据。
library(igraph)
last_char <- nchar(as.character(df$Seq))
df_g <- cbind(v1=substr(df$Seq, 1,1),
v2=substr(df$Seq, last_char, last_char), df)
g <- graph.data.frame(df_g)
plot(g, edge.label=paste(E(g)$Seq, "\n", E(g)$Count))
绘图的视觉呈现可以改进，但这显示了聚合数据可以生成定向网络视图的方式。可以想象一些替代方法来表示开始节点和结束节点之间的内部节点，但这些似乎会导致更复杂的情节。
更新 2
您的评论让事情变得更清楚了。获取图表的大部分工作是从序列数据中生成图表的边和顶点。一旦定义好，您就可以格式化并发送到绘图包进行显示。下面的代码构造了一个包含边连接和结束位置的数据框df_g，使用df_g 生成一个包含顶点数据的数据框df_v，然后将两者都传递给igraph 进行绘图。您可以通过检查 df_g 和 df_v 来了解代码在做什么。
library(igraph)
last_char <- nchar(df$Seq)
df <- df[order(substr(df$Seq, last_char, last_char), df$Seq),]
edges <- as.character(df$Seq)
df_g <- data.frame(v1=NA_character_, v2=NA_character_, Seq=NA_character_,
Count=NA_character_, label=NA_character_, arrow.mode = NA_character_, end = NA_character_,
x1 = NA_integer_, x2 = NA_integer_, y1=NA_integer_, y2=NA_integer_, type=NA_character_,
stringsAsFactors=FALSE)
for( i in 1:nrow(df)){
# Make sequence edges
edge <- edges[i]
num_vert <- nchar(edge)
j <- 1:(num_vert-1)
df_g_j <- data.frame( v1=paste(edge, j,sep="_"), v2=paste(edge, j+1,sep="_"),
Seq=edge, Count=df$Count[i], label=sapply(j, function(x) substr(edge, x, x)),
arrow.mode = ">", end=substr(edge,num_vert,num_vert),
x1=j-num_vert, x2=j+1-num_vert, y1=i, y2=i, type="seq", stringsAsFactors=FALSE)
df_g_j[num_vert-1, "arrow.mode"] <- "-" # make connector vertex
df_g_con <- transform(df_g_j[num_vert-1,], v1=v2, v2=paste(end, "connector", sep="_"), x1=0, label=NA, type="connector")
df_g <- rbind(df_g, df_g_j, df_g_con)
}
df_g <- df_g[-1,]
df_g[df_g$type=="connector",] <- within(df_g[df_g$type=="connector",], y2 <- tapply(y2, v2, mean)[v2])
cn_vert <- aggregate(v2 ~ end, data=df_g[df_g$type=="connector", ], length)
colnames(cn_vert) <- c("end","num")
for( end in cn_vert$end){
cn_vert_row <- which(df_g$end == end & df_g$type == "connector")[1]
if( cn_vert$num[cn_vert$end==end] > 1 ) {
df_g <- rbind(df_g,with(df_g[cn_vert_row,],
data.frame(v1=v2, v2=end, Seq=NA_character_, Count=NA_character_, label=NA,
arrow.mode = ">", end=end, x1=x2, x2= 1, y1 = y2, y2=y2, type = "common_end",
stringsAsFactors=FALSE)) ) }
else df_g[cn_vert_row,] <- transform(df_g[cn_vert_row,], v2=end, label=NA, arrow.mode=">", x2=1,type="common_end")
}
# make vertices
df_v <- with(df_g, data.frame(v=v1, label = label, x=x1, y=y1, color = "black", size = 15, stringsAsFactors=FALSE))
df_v <- rbind(df_v, with(df_g[df_g$type == "common_end",],
data.frame(v=end, label = v2, x=x2, y=y2, color="black", size=15, stringsAsFactors=FALSE)))
df_v[is.na(df_v$label),] <- transform(df_v[is.na(df_v$label),], color = NA, size = 0)
#
# make graph from edges and vertices
g <- graph.data.frame(df_g, vertices=df_v)
E(g)$label <- NA # assign Counts as labels to sequence start vertices
e_start <- grep("_1",get.edgelist(g)[,1])
E(g)[e_start]$label <- E(g)[e_start]$Count
# adjust and scale edge label positions
h_jst <- 0 # values between 0 and .2
edge_label_x <- 1 - 2*(1.5 + h_jst - E(g)$x1)/diff(range(V(g)$x))
num_color <-12 # assign colors to Count labels; num_color is number of colors in pallette
counts <- as.integer(E(g)$Count)
edge_label_color <- rainbow(num_color, start=0, end=.75)[num_color-
floor((num_color-1)*(counts-min(counts,na.rm=TRUE))/diff(range(counts,na.rm=TRUE)))]
plot(g, vertex.label.color="white", vertex.frame.color=V(g)$color,
edge.color="blue", edge.arrow.size=.6, edge.label.x= edge_label_x,
edge.label.color=edge_label_color, edge.label.font=2, edge.label.cex=1.1)
对于您的示例数据，这给出了如下所示的图表。放大图时，Count 标签与顶点的距离更大，但您可以通过代码中的变量 h_jst 进一步调整。