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r - R - 在定义的阈值上选择矩阵列表中存在的相同行的省时方法

问题描述

我有一个包含 68 个矩阵的列表。每个矩阵基本上是一个边缘列表，由三列和数千行组成。前两列分别命名为 Node1 和 Node2，包含基因名称。每行代表图中的一条边，即基因之间的相互作用。第三列包含每条边的权重。

目标是获得一个最终表格，其中存在于 75% 或更多矩阵中且具有不同权重的边被折叠成单行。每个最终边的权重将对应于相同边的权重的平均值。

我想知道一个更省时的代码，用于将大型矩阵与数百万行进行比较。

例子

  1. 矩阵

    edgelist1<-matrix(data = c("ABCD1","EFGH1","DFEC","JEKC4",0.1314,1.1231),nrow = 2,ncol = 3,dimnames = list(c(),c("Node1","Node2","Weight")))
edgelist1

edgelist2<-matrix(data = c("ABCD1","DEIR3","CGESL","DFEC","KMN3","PME2",1.7564,0.6573,0.5478),nrow = 3,ncol = 3,dimnames = list(c(),c("Node1","Node2","Weight")))
edgelist2

edgelist3<-matrix(data = c("ACCD1","DEIR3","GUESL","DFEC","KMN3","PMKE2",1.264,0.8573,0.7458),nrow = 3,ncol = 3,dimnames = list(c(),c("Node1","Node2","Weight")))
edgelist3

edgelist4<-matrix(data = c("KPF2","NDM1","GUESL","ABCD1","KMN3","PMKE2","LTRC5","DFEC",1.142,0.9273,0.1358,0.3456),nrow = 4,ncol = 3,dimnames = list(c(),c("Node1","Node2","Weight")))
edgelist4

  2. 列表

    list<-list(edgelist1,edgelist2,edgelist3,edgelist4)

  3. 期望的输出

    finaledgelist<-matrix(c("ABCD1","DFEC","0.7445"),nrow=1,ncol = 3,dimnames = list(c(),c("Node1","Node2","Weight")))
finaledgelist

我的代码

#Combining all edgelists into one
alledges<-do.call(rbind,list)

#Merging column 1 and column 2
alledges<-data.frame(list(Edges=paste(alledges[,1],alledges[,2]),Weights=alledges[,3]))

#Table to see the frequencies of appearance of each edge
as.data.frame(table(alledges$Edge))->frequencies

# Selection of the edges present in 75% or more of the original edgelists
frequencies[frequencies$Freq>=3,]->selection

#Selection of each edge that appears three or more times
alledges[alledges$Edge %in% selection$Var1,]->repeated

#Collapse by edge name and compute mean of the weights
finaledgelist<-repeated %>%
  group_by(Edges) %>%
  dplyr::summarize(Weights=mean(as.numeric(as.character(Weights)), na.rm = TRUE))

#Final edge list as data frame
finaledgelist<-as.data.frame(cbind(Node1=unlist(strsplit(as.vector(finaledgelist$Edges),split=" "))[2*(1:nrow(finaledgelist))-1],Node2=unlist(strsplit(as.vector(finaledgelist$Edges),split=" "))[2*(1:nrow(finaledgelist))],Weights=finaledgelist$Weights))
finaledgelist$Weights<-as.numeric(as.character(finaledgelist$Weights))

标签： rdataframematrixcomparerow

解决方案

这是一种使用 tidyverse 的方法

library(tidyverse)

do.call(rbind, list1) %>% #bind all matrices together
  as.data.frame %>% #convert to data frame
  group_by(Node1, Node2) %>% #group by nodes
  mutate(n1 = n()) %>% #count members of each group
  filter(n1 >= (0.75 * length(list1))) %>% #filter those that are present in less than 75% of list elements
  summarise(weight = mean(as.numeric(as.character(Weight)))) #get mean weight for those that are left

#output#
A tibble: 1 x 3
# Groups: Node1 [?]
  Node1 Node2 weight
  <fct> <fct>  <dbl>
1 ABCD1 DFEC   0.744

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