diff --git a/README.md b/README.md index 2ad6ef7..feafcff 100644 --- a/README.md +++ b/README.md @@ -10,7 +10,7 @@ pip install text2term ## Basic Examples
- Examples of Programmatic Use + Examples of Programmatic Use text2term supports mapping strings specified in different input formats: @@ -46,7 +46,7 @@ dfo = mondo.map_terms(source_terms=["asthma", "acute bronchitis"])
- Examples of Command Line Interface Use + Examples of Command Line Interface Use To show a help message describing all arguments type into a terminal: ```shell @@ -201,7 +201,7 @@ Finally, `cache_exists(ontology_acronym='')` is a simple function that returns `
- Input Preprocessing +

Input Preprocessing

text2term includes regular expression-based preprocessing functionality for input terms. There are functions that take the input terms and a collection of (user-defined) regular expressions, then match each term to each regular expression to simplify the input term. @@ -230,7 +230,7 @@ If an ignore tag `"ignore"` or `"Ignore"` is added to a term, that term will not
-## Command Line Usage +## Command Line Interface Usage After installing, execute the tool from a command line as follows: @@ -246,7 +246,7 @@ To display a help message with descriptions of tool arguments do: `-t TARGET` Path or URL of 'target' ontology to map source terms to. When the chosen mapper is BioPortal or Zooma, provide a comma-separated list of acronyms (eg 'EFO,HPO') or write `'all'` to search all ontologies.
- Optional arguments + Optional arguments `-o OUTPUT` Path to desired output file for the mappings.