I have a character vector in R with 330000 values e.g.
我在R中有一个带有330000个值的字符向量，例如
amp184660
amp947
amp53303
amp364886
amp121615
amp184660 amp947 amp53303 amp364886 amp121615
and and a data frame like this:
和一个像这样的数据框：
I want to find each value from my character vector in first column of the data frame i.e. "Assay Name" and then output its corresponding chromosome position i.e "Chrom" into a new vector. I want to do this as quickly as possible as there are about 330k entries and doing this via grep over a loop will take about 12 hours to finish.
我想在数据帧的第一列中找到我的字符向量中的每个值，即“测定名称”，然后将其相应的染色体位置，即“Chrom”输出到新的向量中。我希望尽可能快地做到这一点，因为有大约330k条目，并且通过循环grep执行此操作将需要大约12个小时才能完成。
Any ideas? Thanks Jason.
有任何想法吗？谢谢杰森。
3 个解决方案
#1
1
I would suggest %in%, which is likely to be faster than merge. Here's a toy example:
我会建议％in％，这可能比合并更快。这是一个玩具示例：
## Assume that "x" is your data.frame
set.seed(1)
x <- data.frame(Assay = sample(letters, 30, replace = TRUE),
Chrom = 4, ChromPos = rnorm(30))
## And that "y" is your vector you want to match
y <- c("a", "b", "c", "d", "e")
## Here's how you can use %in%
x[x$Assay %in% y, ]
# Assay Chrom ChromPos
# 10 b 4 0.6198257
# 12 e 4 -0.1557955
# 24 d 4 1.1000254
# 27 a 4 -0.2533617
## And can also directly extract a specific column
x[x$Assay %in% y, "ChromPos"]
# [1] 0.6198257 -0.1557955 1.1000254 -0.2533617
#2
0
# assume your df called your_data_frame and vector called your_character_vector
vector_frame<-data.frame("Assay Name"=your_character_vector)
merge(vector_frame,your_data_frame,by="Assay Name")[,3]
note I changed the column notation from $Chrom to [,3] because I saw you wanted the third column and R will rename the column in the $ call e.g. to Chrom.Pos..bp. or something similar - if you type the $ and press TAB in the RStudio editor it'll give you the options
注意我将列符号从$ Chrom更改为[，3]，因为我看到你想要第三列，R将重命名$ call中的列，例如到Chrom.Pos..bp。或类似的东西 - 如果你输入$并在RStudio编辑器中按TAB它会给你选项
#3
0
Just in case runtime is still a problem, using the data.table package is approx. 100x faster than merge and 50x faster than %in%:
为了防止运行时仍然存在问题，使用data.table包大约是。比合并快100倍，比％％快50倍：
library(data.table)
dt <- as.data.table( yourDataFrame )
setkey( dt, Assay )
dt[ J(yourVector) ]
#1
1
I would suggest %in%, which is likely to be faster than merge. Here's a toy example:
我会建议％in％，这可能比合并更快。这是一个玩具示例：
## Assume that "x" is your data.frame
set.seed(1)
x <- data.frame(Assay = sample(letters, 30, replace = TRUE),
Chrom = 4, ChromPos = rnorm(30))
## And that "y" is your vector you want to match
y <- c("a", "b", "c", "d", "e")
## Here's how you can use %in%
x[x$Assay %in% y, ]
# Assay Chrom ChromPos
# 10 b 4 0.6198257
# 12 e 4 -0.1557955
# 24 d 4 1.1000254
# 27 a 4 -0.2533617
## And can also directly extract a specific column
x[x$Assay %in% y, "ChromPos"]
# [1] 0.6198257 -0.1557955 1.1000254 -0.2533617
#2
0
# assume your df called your_data_frame and vector called your_character_vector
vector_frame<-data.frame("Assay Name"=your_character_vector)
merge(vector_frame,your_data_frame,by="Assay Name")[,3]
note I changed the column notation from $Chrom to [,3] because I saw you wanted the third column and R will rename the column in the $ call e.g. to Chrom.Pos..bp. or something similar - if you type the $ and press TAB in the RStudio editor it'll give you the options
注意我将列符号从$ Chrom更改为[，3]，因为我看到你想要第三列，R将重命名$ call中的列，例如到Chrom.Pos..bp。或类似的东西 - 如果你输入$并在RStudio编辑器中按TAB它会给你选项
#3
0
Just in case runtime is still a problem, using the data.table package is approx. 100x faster than merge and 50x faster than %in%:
为了防止运行时仍然存在问题，使用data.table包大约是。比合并快100倍，比％％快50倍：
library(data.table)
dt <- as.data.table( yourDataFrame )
setkey( dt, Assay )
dt[ J(yourVector) ]