Processes/Workflows

This module provides common processes/workflows when using the BioMedQuery utilities. For instance, searching PubMed, requires calling the NCBI e-utils in a particular order. After the search, the results are often saved to the database. This module contains pre-assembled functions performing all necessary steps. To see sample scripts that use this processes, refer to the following section

Import

using BioMedQuery.Processes

Index

Functions

# BioMedQuery.Processes.export_citation — Function.

export_citation(entrez_email, pmids::Vector{Int64}, citation_type, output_file,verbose)

Export, to an output file, the citation for collection of PubMed articles identified by the given pmids

Arguments

  • citation_type::String: At the moment supported types include: "endnote"

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# BioMedQuery.Processes.export_citation — Function.

export_citation(entrez_email, pmid::Int64, citation_type, output_file,verbose)

Export, to an output file, the citation for PubMed article identified by the given pmid

Arguments

  • citation_type::String: At the moment supported types include: "endnote"

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# BioMedQuery.Processes.map_mesh_to_umls! — Method.

map_mesh_to_umls!(db, c::Credentials)

Build and store in the given database a map from MESH descriptors to UMLS Semantic Concepts

Arguments

  • db: Database. Must contain TABLE:mesh_descriptor. For each of the

descriptors in that table, search and insert the associated semantic concepts into a new (cleared) TABLE:mesh2umls

  • c::Credentials: UMLS username and password

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# BioMedQuery.Processes.map_mesh_to_umls_async! — Method.

map_mesh_to_umls_async!(db, c::Credentials; timeout, append_results, verbose) Build (using async UMLS-API calls) and store in the given database a map from MESH descriptors to UMLS Semantic Concepts. For large queies this function will be faster than it's synchrounous counterpart

Arguments

  • db: Database. Must contain TABLE:mesh_descriptor. For each of the

descriptors in that table, search and insert the associated semantic concepts into a new (cleared) TABLE:mesh2umls

  • c::Credentials: UMLS username and password
  • append_results::Bool : If false a NEW and EMPTY mesh2umls database table in creted

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# BioMedQuery.Processes.pubmed_search_and_save — Function.

pubmed_search_and_save(email, search_term, article_max::Int64, db_path, verbose=false)

Arguments

  • email: valid email address (otherwise pubmed will block you)
  • search_term : search string to submit to PubMed

e.g (asthma[MeSH Terms]) AND ("2001/01/29"[Date - Publication] : "2010"[Date - Publication]) see http://www.ncbi.nlm.nih.gov/pubmed/advanced for help constructing the string

  • article_max : maximum number of articles to return. Defaults to 600,000
  • db_path: path to output database
  • verbose: if true, the NCBI xml response files are saved to current directory

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# BioMedQuery.Processes.umls_semantic_occurrences — Method.

umls_semantic_occurrences(db, umls_semantic_type)

Return a sparse matrix indicating the presence of MESH descriptors associated with a given umls semantic type in all articles of the input database

Output

  • des_ind_dict: Dictionary matching row number to descriptor names
  • disease_occurances : Sparse matrix. The columns correspond to a feature

vector, where each row is a MESH descriptor. There are as many columns as articles. The occurance/abscense of a descriptor is labeled as 1/0

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