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MotiFF

An open source software for recognition of consensus motifs in proteomics

Overview

MotiFF is a tool for large scale proteomics that discovers the enriched amino acid patterns containing modified amino acids in the results of proteomic analysis. MotiFF implements calculation of the binomial probabilities and χ2 criterion to identify statistically significant amino acid patterns or motifs for the modified peptides. The algorithm was implemented in Python as an open-source command-line tool available at https://github.com/lineva642/PTM.

Installation

Download from Github repository https://github.com/lineva642/PTM. In the directory containing setup.py file run the following command:

pip install .

Usage

MotiFF [dataset] [fasta] [-h] [--name_sample NAME_SAMPLE] [--interval_length INTERVAL_LENGTH] [--modification MODIFICATION] [--modification_site MODIFICATION_SITE] [--working_dir WORKING_DIR] [--algorithm ALGORITHM] [--p_value P_VALUE] [--occurrences OCCURRENCES] [-v {0,1,2}]

positional arguments:
dataset               Path to experimental dataset
fasta                 Path to FASTA

optional arguments:
-h, --help            show this help message and exit
--name_sample NAME_SAMPLE
                      Name of examined sample
--interval_length INTERVAL_LENGTH
                      Number of amino acids before & after modified amino acid (default=6)
--modification MODIFICATION
                      Name of modification(ex.PHOSPHORYLATION)
--modification_site MODIFICATION_SITE
                      Modified amino acid (ex.S,T)
--working_dir WORKING_DIR
                      Working dir for program (default=".")
--algorithm ALGORITHM
                      Enter algorithm name: binom or chi2(default="chi2")
--p_value P_VALUE     Enter p_value(default=0.000005)
--occurrences OCCURRENCES
                      Enter number of motif occurrences in experimental dataset (default=20)
-v {0,1,2}, --verbosity {0,1,2}
                      Output verbosity

Examples

Output files

MotiFF produces summary table (motifs.csv) with discovered amino acid motifs and additional information:

Column name Description
motif Enriched amino acid pattern containing modified amino acid
p_value Probability of the identified motif
fg_matches Number of modified peptides containing this enriched amino acid pattern
fg_size Number of modified peptides among which search is carried out
bg_size Number of FASTA peptides among which search is carried out
bg_matches Number of FASTA peptides containing this enriched amino acid pattern

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