有没有更好的方法在R中实现这一点？
我朋友今天给了我一个文件，看起来像这样：有没有更好的方法在R中实现这一点？,r,database,sorting,R,Database,Sorting,我朋友今天给了我一个文件，看起来像这样： ID genotype snp.id 1 PT86 CA 192902098 2 PT8 CA 192902098 3 PT33 TC 191571437 4 PT27 GA 191026838 5 PT2 TG 188482874 6 PT1 GC 18
ID genotype snp.id
1 PT86 CA 192902098
2 PT8 CA 192902098
3 PT33 TC 191571437
4 PT27 GA 191026838
5 PT2 TG 188482874
6 PT1 GC 186443061
7 PT70 GC 186443061
8 PT59 GA 185444226
9 PT48 GA 185152161
10 PT54 GA 185152161
11 PT18 GA 185152161
12 PT27 GA 185152161
id rs185152161 rs185444226 rs186443061 rs188482874 rs191026838 rs191571437 rs192902098
1 PT1 <NA> <NA> GC <NA> <NA> <NA> <NA>
2 PT18 GA <NA> <NA> <NA> <NA> <NA> <NA>
3 PT2 <NA> <NA> <NA> TG <NA> <NA> <NA>
and so on....
ID genotype snp.id
1 PT86 CA 192902098
2 PT8 CA 192902098
3 PT33 TC 191571437
4 PT27 GA 191026838
5 PT2 TG 188482874
6 PT1 GC 186443061
7 PT70 GC 186443061
8 PT59 GA 185444226
9 PT48 GA 185152161
10 PT54 GA 185152161
11 PT18 GA 185152161
12 PT27 GA 185152161
id rs185152161 rs185444226 rs186443061 rs188482874 rs191026838 rs191571437 rs192902098
1 PT1 <NA> <NA> GC <NA> <NA> <NA> <NA>
2 PT18 GA <NA> <NA> <NA> <NA> <NA> <NA>
3 PT2 <NA> <NA> <NA> TG <NA> <NA> <NA>
and so on....
mat=matrix(list(),ncol=1,nrow=13)
for (i in 1:7) {
mat[[i,1]]=subset(raw,snp.id==snpids[[i]])[,1:2]
names(mat[[i,1]])=c('id',paste("rs",snpids[[i]],sep=""))
}
df1= Reduce(function(x,y) merge(x,y,all=T),mat[1:7,1])
df2=df1[!duplicated(df1$id),]
id rs185152161 rs185444226 rs186443061 rs188482874 rs191026838 rs191571437 rs192902098
1 PT1 <NA> <NA> GC <NA> <NA> <NA> <NA>
2 PT18 GA <NA> <NA> <NA> <NA> <NA> <NA>
3 PT2 <NA> <NA> <NA> TG <NA> <NA> <NA>
4 PT27 GA <NA> <NA> <NA> GA <NA> <NA>
5 PT33 <NA> <NA> <NA> <NA> <NA> TC <NA>
6 PT48 GA <NA> <NA> <NA> <NA> <NA> <NA>
7 PT54 GA <NA> <NA> <NA> <NA> <NA> <NA>
8 PT59 <NA> GA <NA> <NA> <NA> <NA> <NA>
9 PT70 <NA> <NA> GC <NA> <NA> <NA> <NA>
10 PT8 <NA> <NA> <NA> <NA> <NA> <NA> CA
11 PT86 <NA> <NA> <NA> <NA> <NA> <NA> CA
id rs185152161 rs185444226 rs186443061 rs188482874 rs191026838 rs191571437 rs192902098
1 PT1 GC
2 PT18 GA
3pt2tg
4 PT27 GA
5 PT33 TC
6 PT48 GA
7 PT54 GA
8 PT59 GA
9 PT70 GC
10 PT8钙
11 PT86 CA
dat对于从长格式到宽格式的转换，始终有
重塑library(reshape)
reshape(data, idvar = "ID", timevar = "snp.id", direction = "wide")
+------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+
| ID | genotype.192902098 | genotype.191571437 | genotype.191026838 | genotype.188482874 | genotype.186443061 | genotype.185444226 | genotype.185152161 |
+------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+
| PT86 | CA | NA | NA | NA | NA | NA | NA |
+------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+
| PT8 | CA | NA | NA | NA | NA | NA | NA |
+------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+
| PT33 | NA | TC | NA | NA | NA | NA | NA |
+------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+
| PT27 | NA | NA | GA | NA | NA | NA | GA |
+------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+
| PT2 | NA | NA | NA | TG | NA | NA | NA |
+------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+
| PT1 | NA | NA | NA | NA | GC | NA | NA |
+------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+
| PT70 | NA | NA | NA | NA | GC | NA | NA |
+------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+
| PT59 | NA | NA | NA | NA | NA | GA | NA |
+------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+
| PT48 | NA | NA | NA | NA | NA | NA | GA |
+------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+
| PT54 | NA | NA | NA | NA | NA | NA | GA |
+------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+
| PT18 | NA | NA | NA | NA | NA | NA | GA |
+------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+
在基因型列中，我得到的是数字而不是基因型。我还收到以下警告消息：“聚合函数丢失：默认为长度”@dOctOr这可能是因为每个组合有多个条目。我的代码基于您提供的示例。你能展示一个显示警告信息的非常小的示例数据吗？@dOctOr I针对每个组合有多个条目的病例进行了更新
dat$indx <- with(dat, ave(seq_along(ID), ID, FUN=seq_along))
dcast(dat, ID+indx~snp.id, value.var="genotype")[,-2]
library(reshape)
reshape(data, idvar = "ID", timevar = "snp.id", direction = "wide")
+------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+
| ID | genotype.192902098 | genotype.191571437 | genotype.191026838 | genotype.188482874 | genotype.186443061 | genotype.185444226 | genotype.185152161 |
+------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+
| PT86 | CA | NA | NA | NA | NA | NA | NA |
+------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+
| PT8 | CA | NA | NA | NA | NA | NA | NA |
+------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+
| PT33 | NA | TC | NA | NA | NA | NA | NA |
+------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+
| PT27 | NA | NA | GA | NA | NA | NA | GA |
+------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+
| PT2 | NA | NA | NA | TG | NA | NA | NA |
+------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+
| PT1 | NA | NA | NA | NA | GC | NA | NA |
+------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+
| PT70 | NA | NA | NA | NA | GC | NA | NA |
+------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+
| PT59 | NA | NA | NA | NA | NA | GA | NA |
+------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+
| PT48 | NA | NA | NA | NA | NA | NA | GA |
+------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+
| PT54 | NA | NA | NA | NA | NA | NA | GA |
+------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+
| PT18 | NA | NA | NA | NA | NA | NA | GA |
+------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+