R：把向量分成区间，测试哪个整数落在哪个区间
R: Dividing vector into intervals, and test which integer falls into what interval
我有23条染色体和它们的长度
chromosome length
1 249250621
2 243199373
3 198022430
4 191154276
5 180915260
6 171115067
.. .........
Y 59373566
对于每条染色体，我想创建 5000 bins/intervals 个大小相等的染色体。
Chr1:
bin_number start end
1 1 49850
2 49851 99700
.... ..... .....
5000 249200771 249250621
我已经尝试使用 "cut" 和 "cut2" 来达到这个目的。 "cut2" 无法处理染色体的长度和崩溃，而 cut 为每个单独的位置提供一个间隔（249250621 个间隔！）。
cut2(1:249250621, g=5000, onlycuts = TRUE)
cut(1:249250621, breaks=5000)
当我有间隔时，我想分配每个 bin/interval 50.000 个变体。
我的数据（1 号染色体）：
variant chromosome position
1:20000_G/A 1 20000
1:30000_C/CCCCT 1 30000
1:60000_G/T 1 60000
.............. .. .......
我想要的：
variant chromosome position bin_number
1:20000_G/A 1 20000 1
1:30000_C/CCCCT 1 30000 1
1:60000_G/T 1 60000 2
.............. .. ....... ...
对于与将我的染色体分成间隔相关的方法的任何建议，我将不胜感激。当我有区间时，我需要可以快速测试变体属于哪个区间的方法。
如果 bin 范围是恒定的，这有效：
mydata <- data.frame(position = c(20000, 30000, 60000,
49850, 49851, 99700, 99701))
mydata$bin <- ceiling(mydata$position / 49850)
更一般地说，如果 bin 范围不是常数，但您已经定义了切点，则可以使用 cut，方法是将其指定为 breaks。
cutpoints <- c(0, 49850, 99700, 149550)
mydata$bin2 <- cut(mydata$position, breaks = cutpoints)
您可以稍微调整一下来编辑标签。
mydata$bin3 <- cut(mydata$position, breaks = cutpoints,
labels = seq(length(cutpoints)-1))
感谢您的意见。我选择使用一个简单的循环来创建间隔，以确保间隔具有所需的大小。
我创建了一个 data.frame 染色体大小
chrSizes <- data.frame(chromosome = c("1", "2", "3", "4", "5", "6", "7", "8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18", "19", "20", "21", "22", "X", "Y"), length = c("249250621","243199373", "198022430", "191154276", "180915260", "171115067", "159138663", "146364022", "141213431", "135534747", "135006516", "133851895", "115169878", "107349540", "102531392", "90354753", "81195210", "78077248", "59128983", "63025520", "48129895", "51304566", "155270560", "59373566"), stringsAsFactors = FALSE)
然后我通过找到精确的块大小然后向下舍入来循环创建间隔的每个染色体。余数然后用于在前许多间隔中加一个。
numOfBins <- 10000
chrBinList <- list()
for (i in 1:24) {
chrBins <- c()
chrLength <- as.numeric(chrSizes[i,2])
chunkSize <- floor(chrLength/numOfBins)
remainder <- chrLength %% chunkSize
counter <- 1
# Adding remainder to the first intervals
for (j in 1:(remainder-1)) {
chrBins <- c(chrBins, counter)
counter <- counter + chunkSize + 1
chrBins <- c(chrBins, counter)
}
# Adding normal sized chunks to remaining intervals
for (k in remainder:numOfBins) {
chrBins <- c(chrBins, counter)
counter <- counter + chunkSize
chrBins <- c(chrBins, counter)
}
# Creating a data.frame with intervals
interval.df <- as.data.frame(matrix(chrBins,ncol = 2, byrow = TRUE))
colnames(interval.df) <- c("start", "end")
# Adding to list
chrBinList[[chrSizes[i,1]]] <- interval.df
}
至于测试值是否落在不同的区间内，我想出了一个使用 apply 的缓慢解决方案。但是，我目前正在研究并行应用函数。
如果我理解你的算法，你将把每条染色体分成 10000 个 bin。所以你会得到每个范围的不同尺寸。我曾经应用这个算法来创建独立于染色体的 same-size 范围。
chrSizes <- data.frame(chromosome = c("1", "2", "3", "4", "5", "6", "7", "8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18", "19", "20", "21", "22", "X", "Y"),
length = c("249250621","243199373", "198022430", "191154276", "180915260", "171115067", "159138663", "146364022", "141213431", "135534747", "135006516", "133851895", "115169878", "107349540", "102531392", "90354753", "81195210", "78077248", "59128983", "63025520", "48129895", "51304566", "155270560", "59373566"),
stringsAsFactors = FALSE)
sizerange <- 5000000
lastranges <- NA
h <- 0
for (i in 1:24)
{
thelast <- 1
bynum <- format(sizerange, scientific = FALSE)
chrlist <- c(paste0(chrSizes$chromosome[i],":1-",bynum))
biggest <- chrSizes$length[i]
while(thelast < biggest)
{
bynum1 <- format(as.numeric(bynum)+1, scientific = FALSE)
bynum2 <- format(as.numeric(bynum1)+sizerange-1, scientific = FALSE)
berria <- paste0(paste0(chrSizes$chromosome[i],":",bynum1,"-",as.character(bynum2)))
chrlist <- c(chrlist,berria)
thelast <- as.numeric(bynum2)+sizerange
bynum <- format(as.numeric(bynum)+sizerange, scientific = FALSE)
}
azkenreg <- paste0(paste0(chrSizes$chromosome[i],":",bynum,"-",as.character(biggest)))
chrlist <- c(chrlist,azkenreg)
lastranges <- c(lastranges,chrlist)
}
lastranges <- lastranges[-1]
df <- data.frame(lastranges)
write.table(df,file = "fastacontigs_splited_bysize2.txt",quote = FALSE, row.names = FALSE, col.names = FALSE)
在这种情况下，结果是：
1:1-5000000
1:5000001-10000000
1:10000001-15000000
1:15000000-249250621
2:1-5000000
2:5000001-10000000
2:10000001-15000000
2:15000000-243199373
3:1-5000000
3:5000001-10000000
3:10000001-15000000
3:15000000-198022430
4:1-5000000
4:5000001-10000000
4:10000001-15000000
4:15000000-191154276
5:1-5000000
5:5000001-10000000
5:10000001-15000000
5:15000000-180915260
6:1-5000000
6:5000001-10000000
6:10000001-15000000
6:15000000-171115067
7:1-5000000
7:5000001-10000000
7:10000001-15000000
7:15000000-159138663
8:1-5000000
8:5000001-10000000
8:10000001-15000000
8:15000000-146364022
9:1-5000000
9:5000001-10000000
9:10000001-15000000
9:15000000-141213431
10:1-5000000
10:5000001-10000000
10:10000001-15000000
10:15000000-135534747
11:1-5000000
11:5000001-10000000
11:10000001-15000000
11:15000000-135006516
12:1-5000000
12:5000001-10000000
12:10000001-15000000
12:15000000-133851895
13:1-5000000
13:5000001-10000000
13:10000001-15000000
13:15000000-115169878
14:1-5000000
14:5000001-10000000
14:10000001-15000000
14:15000000-107349540
15:1-5000000
15:5000001-10000000
15:10000001-15000000
15:15000000-102531392
16:1-5000000
16:5000001-10000000
16:10000001-15000000
16:15000001-20000000
16:20000001-25000000
16:25000001-30000000
16:30000001-35000000
16:35000001-40000000
16:40000001-45000000
16:45000001-50000000
16:50000001-55000000
16:55000001-60000000
16:60000001-65000000
16:65000001-70000000
16:70000001-75000000
16:75000001-80000000
16:80000001-85000000
16:85000000-90354753
17:1-5000000
17:5000001-10000000
17:10000001-15000000
17:15000001-20000000
17:20000001-25000000
17:25000001-30000000
17:30000001-35000000
17:35000001-40000000
17:40000001-45000000
17:45000001-50000000
17:50000001-55000000
17:55000001-60000000
17:60000001-65000000
17:65000001-70000000
17:70000001-75000000
17:75000000-81195210
18:1-5000000
18:5000001-10000000
18:10000001-15000000
18:15000001-20000000
18:20000001-25000000
18:25000001-30000000
18:30000001-35000000
18:35000001-40000000
18:40000001-45000000
18:45000001-50000000
18:50000001-55000000
18:55000001-60000000
18:60000001-65000000
18:65000000-78077248
19:1-5000000
19:5000001-10000000
19:10000001-15000000
19:15000001-20000000
19:20000001-25000000
19:25000001-30000000
19:30000001-35000000
19:35000001-40000000
19:40000001-45000000
19:45000000-59128983
20:1-5000000
20:5000001-10000000
20:10000001-15000000
20:15000001-20000000
20:20000001-25000000
20:25000001-30000000
20:30000001-35000000
20:35000001-40000000
20:40000001-45000000
20:45000001-50000000
20:50000001-55000000
20:55000000-63025520
21:1-5000000
21:5000001-10000000
21:10000001-15000000
21:15000001-20000000
21:20000001-25000000
21:25000001-30000000
21:30000001-35000000
21:35000000-48129895
22:1-5000000
22:5000001-10000000
22:10000001-15000000
22:15000001-20000000
22:20000001-25000000
22:25000001-30000000
22:30000001-35000000
22:35000001-40000000
22:40000001-45000000
22:45000000-51304566
X:1-5000000
X:5000001-10000000
X:10000001-15000000
X:15000000-155270560
Y:1-5000000
Y:5000001-10000000
Y:10000001-15000000
Y:15000001-20000000
Y:20000001-25000000
Y:25000001-30000000
Y:30000001-35000000
Y:35000001-40000000
Y:40000001-45000000
Y:45000000-59373566
我有23条染色体和它们的长度
chromosome length
1 249250621
2 243199373
3 198022430
4 191154276
5 180915260
6 171115067
.. .........
Y 59373566
对于每条染色体，我想创建 5000 bins/intervals 个大小相等的染色体。
Chr1:
bin_number start end
1 1 49850
2 49851 99700
.... ..... .....
5000 249200771 249250621
我已经尝试使用 "cut" 和 "cut2" 来达到这个目的。 "cut2" 无法处理染色体的长度和崩溃，而 cut 为每个单独的位置提供一个间隔（249250621 个间隔！）。
cut2(1:249250621, g=5000, onlycuts = TRUE)
cut(1:249250621, breaks=5000)
当我有间隔时，我想分配每个 bin/interval 50.000 个变体。
我的数据（1 号染色体）：
variant chromosome position
1:20000_G/A 1 20000
1:30000_C/CCCCT 1 30000
1:60000_G/T 1 60000
.............. .. .......
我想要的：
variant chromosome position bin_number
1:20000_G/A 1 20000 1
1:30000_C/CCCCT 1 30000 1
1:60000_G/T 1 60000 2
.............. .. ....... ...
对于与将我的染色体分成间隔相关的方法的任何建议，我将不胜感激。当我有区间时，我需要可以快速测试变体属于哪个区间的方法。
如果 bin 范围是恒定的，这有效：
mydata <- data.frame(position = c(20000, 30000, 60000,
49850, 49851, 99700, 99701))
mydata$bin <- ceiling(mydata$position / 49850)
更一般地说，如果 bin 范围不是常数，但您已经定义了切点，则可以使用 cut，方法是将其指定为 breaks。
cutpoints <- c(0, 49850, 99700, 149550)
mydata$bin2 <- cut(mydata$position, breaks = cutpoints)
您可以稍微调整一下来编辑标签。
mydata$bin3 <- cut(mydata$position, breaks = cutpoints,
labels = seq(length(cutpoints)-1))
感谢您的意见。我选择使用一个简单的循环来创建间隔，以确保间隔具有所需的大小。
我创建了一个 data.frame 染色体大小
chrSizes <- data.frame(chromosome = c("1", "2", "3", "4", "5", "6", "7", "8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18", "19", "20", "21", "22", "X", "Y"), length = c("249250621","243199373", "198022430", "191154276", "180915260", "171115067", "159138663", "146364022", "141213431", "135534747", "135006516", "133851895", "115169878", "107349540", "102531392", "90354753", "81195210", "78077248", "59128983", "63025520", "48129895", "51304566", "155270560", "59373566"), stringsAsFactors = FALSE)
然后我通过找到精确的块大小然后向下舍入来循环创建间隔的每个染色体。余数然后用于在前许多间隔中加一个。
numOfBins <- 10000
chrBinList <- list()
for (i in 1:24) {
chrBins <- c()
chrLength <- as.numeric(chrSizes[i,2])
chunkSize <- floor(chrLength/numOfBins)
remainder <- chrLength %% chunkSize
counter <- 1
# Adding remainder to the first intervals
for (j in 1:(remainder-1)) {
chrBins <- c(chrBins, counter)
counter <- counter + chunkSize + 1
chrBins <- c(chrBins, counter)
}
# Adding normal sized chunks to remaining intervals
for (k in remainder:numOfBins) {
chrBins <- c(chrBins, counter)
counter <- counter + chunkSize
chrBins <- c(chrBins, counter)
}
# Creating a data.frame with intervals
interval.df <- as.data.frame(matrix(chrBins,ncol = 2, byrow = TRUE))
colnames(interval.df) <- c("start", "end")
# Adding to list
chrBinList[[chrSizes[i,1]]] <- interval.df
}
至于测试值是否落在不同的区间内，我想出了一个使用 apply 的缓慢解决方案。但是，我目前正在研究并行应用函数。
如果我理解你的算法，你将把每条染色体分成 10000 个 bin。所以你会得到每个范围的不同尺寸。我曾经应用这个算法来创建独立于染色体的 same-size 范围。
chrSizes <- data.frame(chromosome = c("1", "2", "3", "4", "5", "6", "7", "8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18", "19", "20", "21", "22", "X", "Y"),
length = c("249250621","243199373", "198022430", "191154276", "180915260", "171115067", "159138663", "146364022", "141213431", "135534747", "135006516", "133851895", "115169878", "107349540", "102531392", "90354753", "81195210", "78077248", "59128983", "63025520", "48129895", "51304566", "155270560", "59373566"),
stringsAsFactors = FALSE)
sizerange <- 5000000
lastranges <- NA
h <- 0
for (i in 1:24)
{
thelast <- 1
bynum <- format(sizerange, scientific = FALSE)
chrlist <- c(paste0(chrSizes$chromosome[i],":1-",bynum))
biggest <- chrSizes$length[i]
while(thelast < biggest)
{
bynum1 <- format(as.numeric(bynum)+1, scientific = FALSE)
bynum2 <- format(as.numeric(bynum1)+sizerange-1, scientific = FALSE)
berria <- paste0(paste0(chrSizes$chromosome[i],":",bynum1,"-",as.character(bynum2)))
chrlist <- c(chrlist,berria)
thelast <- as.numeric(bynum2)+sizerange
bynum <- format(as.numeric(bynum)+sizerange, scientific = FALSE)
}
azkenreg <- paste0(paste0(chrSizes$chromosome[i],":",bynum,"-",as.character(biggest)))
chrlist <- c(chrlist,azkenreg)
lastranges <- c(lastranges,chrlist)
}
lastranges <- lastranges[-1]
df <- data.frame(lastranges)
write.table(df,file = "fastacontigs_splited_bysize2.txt",quote = FALSE, row.names = FALSE, col.names = FALSE)
在这种情况下，结果是：
1:1-5000000
1:5000001-10000000
1:10000001-15000000
1:15000000-249250621
2:1-5000000
2:5000001-10000000
2:10000001-15000000
2:15000000-243199373
3:1-5000000
3:5000001-10000000
3:10000001-15000000
3:15000000-198022430
4:1-5000000
4:5000001-10000000
4:10000001-15000000
4:15000000-191154276
5:1-5000000
5:5000001-10000000
5:10000001-15000000
5:15000000-180915260
6:1-5000000
6:5000001-10000000
6:10000001-15000000
6:15000000-171115067
7:1-5000000
7:5000001-10000000
7:10000001-15000000
7:15000000-159138663
8:1-5000000
8:5000001-10000000
8:10000001-15000000
8:15000000-146364022
9:1-5000000
9:5000001-10000000
9:10000001-15000000
9:15000000-141213431
10:1-5000000
10:5000001-10000000
10:10000001-15000000
10:15000000-135534747
11:1-5000000
11:5000001-10000000
11:10000001-15000000
11:15000000-135006516
12:1-5000000
12:5000001-10000000
12:10000001-15000000
12:15000000-133851895
13:1-5000000
13:5000001-10000000
13:10000001-15000000
13:15000000-115169878
14:1-5000000
14:5000001-10000000
14:10000001-15000000
14:15000000-107349540
15:1-5000000
15:5000001-10000000
15:10000001-15000000
15:15000000-102531392
16:1-5000000
16:5000001-10000000
16:10000001-15000000
16:15000001-20000000
16:20000001-25000000
16:25000001-30000000
16:30000001-35000000
16:35000001-40000000
16:40000001-45000000
16:45000001-50000000
16:50000001-55000000
16:55000001-60000000
16:60000001-65000000
16:65000001-70000000
16:70000001-75000000
16:75000001-80000000
16:80000001-85000000
16:85000000-90354753
17:1-5000000
17:5000001-10000000
17:10000001-15000000
17:15000001-20000000
17:20000001-25000000
17:25000001-30000000
17:30000001-35000000
17:35000001-40000000
17:40000001-45000000
17:45000001-50000000
17:50000001-55000000
17:55000001-60000000
17:60000001-65000000
17:65000001-70000000
17:70000001-75000000
17:75000000-81195210
18:1-5000000
18:5000001-10000000
18:10000001-15000000
18:15000001-20000000
18:20000001-25000000
18:25000001-30000000
18:30000001-35000000
18:35000001-40000000
18:40000001-45000000
18:45000001-50000000
18:50000001-55000000
18:55000001-60000000
18:60000001-65000000
18:65000000-78077248
19:1-5000000
19:5000001-10000000
19:10000001-15000000
19:15000001-20000000
19:20000001-25000000
19:25000001-30000000
19:30000001-35000000
19:35000001-40000000
19:40000001-45000000
19:45000000-59128983
20:1-5000000
20:5000001-10000000
20:10000001-15000000
20:15000001-20000000
20:20000001-25000000
20:25000001-30000000
20:30000001-35000000
20:35000001-40000000
20:40000001-45000000
20:45000001-50000000
20:50000001-55000000
20:55000000-63025520
21:1-5000000
21:5000001-10000000
21:10000001-15000000
21:15000001-20000000
21:20000001-25000000
21:25000001-30000000
21:30000001-35000000
21:35000000-48129895
22:1-5000000
22:5000001-10000000
22:10000001-15000000
22:15000001-20000000
22:20000001-25000000
22:25000001-30000000
22:30000001-35000000
22:35000001-40000000
22:40000001-45000000
22:45000000-51304566
X:1-5000000
X:5000001-10000000
X:10000001-15000000
X:15000000-155270560
Y:1-5000000
Y:5000001-10000000
Y:10000001-15000000
Y:15000001-20000000
Y:20000001-25000000
Y:25000001-30000000
Y:30000001-35000000
Y:35000001-40000000
Y:40000001-45000000
Y:45000000-59373566