match_hmdb

Script to match mz's to the HMDB database.

In other words, given a feature table with a column labeled mz, find all HMDB features within a certain ppm tolerance for each of the mz's in that column. If a feature doesn't have a mass match in HMDB, the output file will have one row corresponding to that mz, with the feature name, adduct type, and corresponding neutral mass.

Most of the parsing I did in this code is based off of Isaac Rockafellow's code, which you can find on his github.

Usage

1. Clone this repo: git clone https://github.mit.edu/duvallet/match_hmdb.git

2. Gunzip the hmdb_metabolites_clean.xml.gz file: gunzip data/hmdb_metabolites_clean.xml.gz

3. Run the code:

   python match_hmdb.py -x data/hmdb_metabolites_clean.xml -f data/toy_feature_table.csv -s , -p 2 -o tmp.out

   Where the -f flag corresponds to the feature table with the mz's you want to search against HMDB.

4. See more options for running the code:

   python blast_hmdb.py --help

Input data

hmdb_metabolites.xml was download from the HMDB website and contains all of the HMDB metabolites (at least as of summer 2016). When you download multiple HMDB metabolites, it just concatenates the individual xml files into one file. However, this breaks downstream parsers. Isaac wrote remove_excess_xml_declarations.py to clean up the downloaded file into one that can be parsed by a parser. You only need to use this if you want to use a newly downloaded xml file from HMDB. Otherwise, you can just use hmdb_metabolites_clean.xml, which Isaac already downloaded and cleaned up for us.

hmdb_metabolites_clean.xml is the cleaned up version containing all HMDB metabolites, and should be the default input HMDB file to match_hmdb.py.

Check out the toy_feature_table.csv for an example of what your feature table can look like.

You should gunzip the hmdb_metabolites_clean.xml.gz file before trying to use it.

To do

• store the parsed HMDB dict as a pickle file, so users don't have to re-calculate it every time the script is run

Contributors

• Claire Duvallet (duvallet at mit dot edu)
• Isaac Rockafellow

Exact masses

This code doesn't need exact masses (since it uses m/z's in your feature table and m/z's in HMDB), but just for reference:

m = {'C': 12.0,
     'H': 1.007825,
     'O': 15.994915,
     'N': 14.003074,
     'S': 31.972072,
     'Cl': 34.968853,
     'F': 18.998403,
     'B': 10.012938,
     'D': 2.014102,
     'Na': 22.989770,
     'e-': 0.000548579909}