Skip to content

Latest commit

 

History

History
33 lines (20 loc) · 1.82 KB

README.md

File metadata and controls

33 lines (20 loc) · 1.82 KB
Raw

Python scripts used to process the data

Python scripts were run interactively in iPython console. The input and output were included in the scripts.

in silico digesion of protein sequences

modified from https://github.com/yafeng/trypsin/blob/master/trypsin.py

sample code in Trypsin.py

generation of decoy database

In-house Python scripts were used to remove peptides in the decoy database that are the same to peptides in the target database.

A peptide in the decoy database was also removed if any of its possible variants considering amino acid N=D, Q=E was found in the target database, because N[Deamidated]=D, Q[Deamidated]=E in MS search. For example, peptide AANQ was found in the target database, its variants (AADQ, AANE, and AADE) would be removed from the decoy database.

sample code in generation_of_decoy_database.py

combine comet pin for each project

sample code in combine_comet_pin_for_each_project.py

After running comet, Percolator was run based on each PRIDE project. We need to combine the output files of comet (.pin files) from the same project.

circRNA

6-frame translation of circRNA

circRNA bed file and sequence of Human were downloaded from circAtlas 2.0 database: http://159.226.67.237:8080/new/links.php sample code in circRNA.six_frame_translation.py

other code

other Python scripts were highly relied on the data and the HPC system that were used and can be provided upon request.