如何使用R中的条件/ for循环将单列数据转换为双列矩阵

Question

I have a single column data frame - example data:

1                          >PROKKA_00002 Alpha-ketoglutarate permease
2        MTESSITERGAPELADTRRRIWAIVGASSGNLVEWFDFYVYSFCSLYFAHIFFPSGNTTT
3        QLLQTAGVFAAGFLMRPIGGWLFGRIADRRGRKTSMLISVCMMCFGSLVIACLPGYAVIG
4                                          >PROKKA_00003 lipoprotein
5       MRTIIVIASLLLTGCSHMANDAWSGQDKAQHFLASAMLSAAGNEYAQHQGYSRDRSAAIG

Each sequence of letters is associated with the ">" line above it. I need a two-column data frame with lines starting in ">" in the first column, and the respective lines of letters concatenated as one sequence in the second column. This is what I've tried so far:

 y <- matrix(0,5836,2) #empty matrix with 5836 rows and two columns
 z <- 0
 for(i in 1:nrow(df)){
   if((grepl(pattern = "^>", x = df)) == TRUE){ #tried to set the conditional "if a line starts with ">", execute code"
     z <- z + 1
     y[z,1] <- paste(df[i])
     } else{
     y[z,2] <- paste(df[i], collapse = "")
     }
 }

I would eventually convert the matrix y back to a data.frame using as.data.frame, but my loop keeps getting Error: unexpected '}' in "}". I'm also not sure if my conditional is right. Can anyone help? It would be greatly appreciated!

Answer 1

Although I will stick with packages, here is a solution

initialize data

mydf <- data.frame(x=c(">PROKKA_00002 Alpha-ketoglutarate","MTESSITERGAPEL", "MTESSITERGAPEL",">PROKKA_00003 lipoprotein", "MTESSITERGAPEL"   ,"MRTIIVIASLLLT"), stringsAsFactors = F)

process

ind <- grep(">", mydf$x)
temp<-data.frame(ind=ind, from=ind+1, to=c((ind-1)[-1], nrow(mydf)))

seqs<-rep(NA, length(ind))
for(i in 1:length(ind)) {
  seqs[i]<-paste(mydf$x[temp$from[i]:temp$to[i]], collapse="")
}

fastatable<-data.frame(name=gsub(">", "", mydf[ind,1]), sequence=seqs)


> fastatable
                              name                     sequence
1 PROKKA_00002 Alpha-ketoglutarate MTESSITERGAPELMTESSITERGAPEL
2         PROKKA_00003 lipoprotein  MTESSITERGAPELMRTIIVIASLLLT

Answer 2

Try creating an index of the rows with the target symbol with the column headers. Then split the data on that index. The call cumsum(ind1)[!ind1] first creates an id rows by coercing the logical vector into numeric, then eliminates the rows with the column headers.

ind1 <- grepl(">", mydf$x)

#split data on the index created
newdf <- data.frame(mydf$x[ind1][cumsum(ind1)], mydf$x)[!ind1,]

#Add names
names(newdf) <- c("Name", "Value")
newdf
#            Name               Value
# 2 >PROKKA_00002 Alpha-ketoglutarate
# 3 >PROKKA_00002      MTESSITERGAPEL
# 5 >PROKKA_00003         lipoprotein
# 6 >PROKKA_00003       MRTIIVIASLLLT

Data

mydf <- data.frame(x=c(">PROKKA_00002","Alpha-ketoglutarate","MTESSITERGAPEL", ">PROKKA_00003", "lipoprotein"   ,"MRTIIVIASLLLT"))

Answer 3

You can use plyr to accomplish this if you are able to assigned a section number to your rows appropriately:

library(plyr)
df <- data.frame(v1=c(">PROKKA_00002 Alpha-ketoglutarate permease",
                   "MTESSITERGAPELADTRRRIWAIVGASSGNLVEWFDFYVYSFCSLYFAHIFFPSGNTTT",
                   "QLLQTAGVFAAGFLMRPIGGWLFGRIADRRGRKTSMLISVCMMCFGSLVIACLPGYAVIG",
                   ">PROKKA_00003 lipoprotein",
                   "MRTIIVIASLLLTGCSHMANDAWSGQDKAQHFLASAMLSAAGNEYAQHQGYSRDRSAAIG"))
df$hasMark <- ifelse(grepl(">",df$v1,fixed=TRUE),1, 0)
df$section <- cumsum(df$hasMark)

t <- ddply(df, "section", function(x){
  data.frame(v2=head(x,1),v3=paste(x$v1[2:nrow(x)], collapse=''))
})

t <- subset(t, select=-c(section,v2.hasMark,v2.section)) #drop the extra columns

if you then view 't' I believe this is what you were looking for in your original post