<TITLE>a </TITLE>

<script type="text/javascript" async src="https://cdn.mathjax.org/mathjax/latest/MathJax.js?config=AM_CHTML"></script>

Bipartite matching generalizations for peptide identification in tandem mass spectrometry

How to use SGM

 <H3>Step 1: Run tide-index of <a href="http://crux.ms/">Crux</a> to generate decoy set.</H3>
 <P>
CRUX tide-index --output-dir [OUTPUT] --clip-nterm-methionine T \<br /> 
--missed-cleavages [Missed cleavage] --peptide-list T \ <br />
--mods-spec [MODS] --nterm-peptide-mods-spec [Nterm] \ <br />    
--enzyme [ENZYME] \ <br />
--overwrite T \ <br />
[TARGETS] [tideindex] <br />
<br />

See <a href="http://crux.ms/commands/tide-index.html">Crux</a> for desired parameters. <br />

Save tide-index.peptides.target.txt and tide-index.peptides.decoy.txt for input of next step. <br />

Step 2: Run "write_msms_bipartite.py" to generate input file for SGM.

python $SHARDDATA \
--spectra [MS2FILE] \
--num_spectra $(grep -c '^S' [MS2FILE]) \
--targets tide-index.peptides.target.txt \
--decoys tide-index.peptides.decoy.txt \
--tol [TOL] \
--shards 1 \
--output_dir [ENCODE] \
--ppm \
--charges [CHARGE]

for pickle in ENCODE/shard-*.pickle
do
python write_msms_bipartite.py--output [ENCODE] --pickle $pickle \
--max_mass 2000 --targets_per_spectrum 100000 \
--normalize fastSequestTransform \
--bin_width 1.0005079 --bin_offset 0.68 --charge [CHARGE] \
--bipartite_file [bipartite-OUTPUT] \
--xcorr_ident_file [xcorrIdent-OUTPUT] \
--do_not_write_all_psms --foreground
done

[ENCODE] is the output folder. [TOL] is the MS1 torrlerance in ppm. [CHARGE] is the precursor charge. [bipartite-OUTPUT] and [xcorrIdent-OUTPUT] are two output files.

Step 3: Run SGM.

Complie and run with following parameters.

option: -h show help information
-c charge
-i [bipartite-OUTPUT]
-o output file
-m ms2file

      </P>

Optional: Merge different charge state.

run merge.py

Optional: Draw absulte plot.

run absplot.py

TODO

Make the codes more user friendly.