Module: ProDigIS Description: Protein Digestion In Silico Version: 0.2 Last Edit: 21/06/11

Copyright © 2011 Richard J. Edwards - See source code for GNU License Notice

Imported modules: rje rje_db rje_obj rje_seq rje_sequence rje_zen

See SLiMSuite Blog for further documentation. See rje for general commands.

Function

The function of this module is to take one or more lists of proteins, perform in silico digestions using different proteases (and combinations) and then output some predicted stats about peptide numbers etc. It is hoped that this data can be used in time to predict which proteins can be potentially identified by Mass Spec and, for a given proteome, which combination of proteases should maximise coverage.

Commandline

## Basic Input Parameters ##
seqfiles=LIST : Sequence files for input. Wildcards permitted. RJE_SEQ filtering WILL be applied. [*.fas]
source=FILE : File containing source protein data (including UniProt AccNum column) [None]
proteases=LIST : List of proteases to use [tryp,aspn,gluc,lysc]
peptides=FILE : File containing list of identified peptides [None]
pepcut=X : Protease used to generate list of identified peptides [tryp]
positives=FILE : File of positively identified proteins matching peptide lists [None]
## Basic Processing Parameters ##
combcut=T/F : Whether to peform combined digestions with pairs of proteases [True]
nterm=T/F : Whether to include N-terminal peptides [False]
nrpep=T/F : Whether to only include the non-redundant (unique) peptides [False]
cysweight=T/F : Whether to weight peptide probabilities according to cysteine count [True]
## Basic Output Parameters ##
minpeplen=X : Minimum peptide length to consider [0]
maxpeplen=X : Maximum peptide length to individually return [40]
pepmwt=T/F : Whether to output peptide mol weights in addition to lengths [True]
cyscount=T/F : Whether to perform peptide count with Cysteine numbers [True]

See also rje.py generic commandline options.

History Module Version History

    # 0.0 - Initial Compilation.
    # 0.1 - Added probability calculations based on hydrophobicity, serine and cysteine.
    # 0.2 - Added cysteine count and cysteine weighting.