library("reutils")

# NB: to grab FASTA of accession number x, do this:
#
#    f <- content(efetch(x, db="nuccore", rettype="fasta", retmode="text"))
#
# Result is a string, with \n separators.

grab.results <- function (term) {
        # Search for the given term on nuccore. This gives us a list of
        # record IDs.
        ids <- esearch(term, db="nuccore")

        # Grab summaries for the given record IDs, as a sort-of data frame.
        sum <- esummary(ids, db="nuccore")
        data <- content(sum, as="parsed")

        # For some reason, this parser gives us lists of lists instead of a
        # proper data frame (which should be lists of vectors). Return a
        # fixed-up version. Also turn Slen into an integer column.
        f <- data.frame(lapply(data, as.character), stringsAsFactors=FALSE)
        f$Slen <- as.integer(f$Slen)
        f
}

first.of.type <- function (results, type) {

        filtered <- results

        # Sort by Slen (biggest first)
        filtered <- filtered[order(filtered$Slen, decreasing=TRUE),]

        # Return the first accession number
        filtered$OSLT[1]
}

scrape.genbank <- function (species, genes) {
        # Create dataset skeleton
        data <- data.frame(Species=species)
        for (i in genes) {
                data[,i] <- rep(NA, length(species))
        }

        # Look up data for each species
        for (i in 1:length(species)) {
                for (g in genes) {
                        n <- species[i]
                        print(sprintf("Looking up %s (%s) (%d/%d)...",
                                      n, g, i, length(species)))


                        query <- sprintf("%s AND %s", n, g)

                        tryCatch({
                                r <- grab.results(query)
                                data[i,g] <- first.of.type(r, g)
                        }, error = function(e) {

                        })
                }
        }

        data
}


rebuild <- function () {
        data <- read.csv("highlightedSkates.csv", stringsAsFactors=FALSE)
        data <- scrape.genbank(unique(data$Host), c("NADH", "COI", "CO1", "RAG1"))
        write.csv(data, "Skate_allmarkers_accessions.csv")


}