parseDoc {ssrch} | R Documentation

## parse a document and place content in a DocSet

### Description

parse a document and place content in a DocSet

### Usage

    parseDoc(csv, DocSetInstance = new("DocSet"), doctitle = NA_character_,
      docabst = NA_character_, rec_id_field = "experiment.accession",
      exclude_fields = c("study.accession"),
      substrings_to_omit = c("http://purl.obolibrary.org/obo/"),
      patterns_to_kill = "....-..-..|.*...,...",
      token_fixups = list(c("t''", "t'"), c(":$", "")), max_tok_nchar = 25,
      min_tok_nchar = 4, cleanFields = list("..*id$", ".name$", "_name$",
      "checksum", "isolate", "filename", "^ID$", "barcode", "Sample.Name"))

### Arguments

`csv` | a character(1) CSV file path
`DocSetInstance` | if missing, DocSet is initialized in this function, otherwise the instance is updated with new content
`doctitle` | character(1) document title
`docabst` | character(1) a string: the document abstract
`rec_id_field` | character(1) field in CSV identifying records
`exclude_fields` | character vector of fields to ignore while parsing
`substrings_to_omit` | character vector of strings to remove from candidate keywords via gsub
`patterns_to_kill` | character(1) regexp that identifies tokens to be omitted from keyword set
`token_fixups` | a list if character(2) vectors that will be
`max_tok_nchar` | numeric(1) defaults to 25, tokens with more characters will be truncated to this length and suffixed with ellipsis
`min_tok_nchar` | numeric(1) defaults to 4, tokens shorter than this are not in index used with gsub() to repair irregularities. For example ‘c("t”", "t’")‘ will transform 'Burkitt”s' to 'Burkitt’s'
`cleanFields` | list of regular expressions identifying fields to ignore

### Value

instance of DocSet

### Note

The expected use case has 'DocSetInstance' being updated in a loop. Sharing of environments across multiple DocSetInstances can occur and unexpected behaviors may ensue. Note also that many of the parameter defaults to parseDoc are for the use case of processing SRA metadata.

### Examples

    myob = ssrch::docset_cancer68
    td = tempdir()
    alld = ls(docs2kw(myob))
    r1 = retrieve_doc(alld[1], myob)
    expo = write.csv(r1, paste0(td, "/expo.csv"))
    pd = parseDoc(paste0(td, "/expo.csv"), doctitle=ssrch::titles68[alld[1]],
        docabst="qwerty")
    pd
    searchDocs("quer", pd) # query will fail
    searchDocs("qwer", pd) # should succeed

[Package ssrch version 1.10.0 Index]