KEGGREST using keggGet() for over 10 results and URL errors for unexisting records

Question

[gualapuro.moises]

1. Over 10 results

I am trying to get pathway names using a list of 16 list of enzymes (list of lists). I used lapply and works correctly for the first 10 enzymes from each list.

# list of 16 list of enzymes    
list_Enz <- lapply(read_files, function(z) paste0("ec:",z[,3]))

# example enzymes 

    x<- c("ec:1.1.1.2", "ec:6.2.1.1", "ec:1.2.4.1", "ec:2.3.1.12", "ec:1.8.1.4", "ec:1.2.1.51", 
"ec:1.1.1.27", "ec:1.2.1.4", "ec:1.2.1.5", "ec:2.7.1.11", "ec:4.1.2.13", "ec:2.7.1.40", 
"ec:1.2.1.49", "ec:2.7.2.3", "ec:5.3.1.9", "ec:5.3.1.1", "ec:2.7.1.1", "ec:2.7.1.2", 
"ec:2.7.1.147", "ec:5.4.2.2", "ec:5.4.2.5", "ec:5.4.2.6", "ec:5.2.2.2", "ec:5.1.3.3", "ec:2.7.1.1")

    y <- c("ec:1.1.1.1", "ec:1.1.1.71", "ec:1.1.1.27", "ec:1.2.1.4", "ec:1.2.1.5", "ec:2.7.1.11", 
"ec:4.2.1.11", "ec:3.6.1.7", "ec:1.2.1.12", "ec:4.1.2.13", "ec:1.2.4.1", "ec:2.3.1.12", 
"ec:2.7.1.147", "ec:5.3.1.9", "ec:3.2.1.20", "ec:3.2.1.28", "ec:2.4.1.186", "ec:2.4.1.11", 
"ec:2.4.1.11", "ec:2.4.1.18", "ec:2.4.1.1", "ec:3.2.1.1")

  # trial 25 enzymes
  list_Enzh<- list(x,y)
  listpaths <- lapply(list_Enzh, function(m) keggGet(m))

How could I use a for or while loops to got all the information?. Tried a nested loop and it doesn't work:

for (k in 1:16){
  for (l in 1:25){
    listpaths2 <- lapply(list_Enzh, function(m) keggGet(m[[k]][[l]]))
  }
}

Error in m[[k]][[l]] : subscript out of bounds

2. Error for some enzyme records I used while loop for a single list of enzymes. It works correctly, but for "ec:5.2.2.2" (x example list) gives an error message.

paths <- c()
i<- 1
while (i < length (x)){
paths[i] <- keggGet(x[i])
}

Error in .getUrl(url, .flatFileParser) : Not Found (HTTP 404).

I appreciate a lot any help!

Answer 1

[gualapuro.moises]

So far I found the following code works and avoid URL errors:

for(i in 1:length(enz)){
  data_all[i] <- tryCatch(keggGet(enz[i]), error=function(e) NULL)
}

If anyone could like to check, I reviewed line 89 in: https://github.com/GuangchuangYu/clusterProfiler/blob/master/R/kegg-utilities.R#L88