我在单独的列中有相对整齐的数据样本,基因,等位基因和频率.对于每个基因和每个样本,我需要将等位基因及其相应的频率分成不同的列.这就是我拥有的和我需要的东西.
尝试用dplyr/tidyr来做这件事,但我会采取任何我能得到的解决方案.
是)我有的:
data.frame(sample=rep("sample1", 10),
gene=rep(paste0("gene", 1:5), each=2),
allele=c("A", "G", "A", "C", "A", "T", "C", "G", "G", "T"),
freq=c(.9, .1, .8, .2, .7, .3, .6, .4, .5, .5))
# sample gene allele freq
# 1 sample1 gene1 A 0.9
# 2 sample1 gene1 G 0.1
# 3 sample1 gene2 A 0.8
# 4 sample1 gene2 C 0.2
# 5 sample1 gene3 A 0.7
# 6 sample1 gene3 T 0.3
# 7 sample1 gene4 C 0.6
# 8 sample1 gene4 G 0.4
# 9 sample1 gene5 G 0.5
# 10 sample1 gene5 T 0.5
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我想要的是:
data.frame(sample=rep("sample1", 5),
gene=paste0("gene", 1:5),
allele1=c("A", "A", "A", "C", "G"),
allele2=c("G", "C", "T", "G", "T"),
freq1=c(.9, .8, .7, .6, .5),
freq2=c(.1, .2, .3, .4, .5))
# sample gene allele1 allele2 freq1 freq2
# 1 sample1 gene1 A G 0.9 0.1
# 2 sample1 gene2 A C 0.8 0.2
# 3 sample1 gene3 A T 0.7 0.3
# 4 sample1 gene4 C G 0.6 0.4
# 5 sample1 gene5 G T 0.5 0.5
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您可以使用dcastdevel版本的data.tableie.1.9.5+,可以采取多value.var列.我们创建了一个由'sample'和'gene'分组的序列列('indx').然后dcast从长到宽的格式提到value.var列.
library(data.table)#v1.9.5+
setDT(df)[, indx:=1:.N,.(sample, gene)]
dcast(df, sample+gene~indx, value.var=c('allele', 'freq'), sep= '')
# sample gene allele1 allele2 freq1 freq2
#1: sample1 gene1 A G 0.9 0.1
#2: sample1 gene2 A C 0.8 0.2
#3: sample1 gene3 A T 0.7 0.3
#4: sample1 gene4 C G 0.6 0.4
#5: sample1 gene5 G T 0.5 0.5
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注意:安装devel版本的说明是 here
该sep=''参数对于将列名称创建为"allele1","allele2"等非常有用.默认值为"allele_1","allele_2"等(来自@ Arun的评论)
这使用总结而不是真正的重塑,但可能符合要求.
library(dplyr)
foo <- data.frame(sample=rep("sample1", 10),
gene=rep(paste0("gene", 1:5), each=2),
allele=c("A", "G", "A", "C", "A", "T", "C", "G", "G", "T"),
freq=c(.9, .1, .8, .2, .7, .3, .6, .4, .5, .5))
foo %>%
group_by(sample, gene) %>%
summarise(allele1 = first(allele), allele2 = last(allele),
freq1 = first(freq), freq2 = last(freq))
## Source: local data frame [5 x 6]
## Groups: sample
##
## sample gene allele1 allele2 freq1 freq2
## 1 sample1 gene1 A G 0.9 0.1
## 2 sample1 gene2 A C 0.8 0.2
## 3 sample1 gene3 A T 0.7 0.3
## 4 sample1 gene4 C G 0.6 0.4
## 5 sample1 gene5 G T 0.5 0.5
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