IPGQC

A working repository for Identical Protein Group content assessment tool.

Principle

Given a full list of Identical Protein Group entries (IPGs) for a selected taxon and a query containing translated reading frames from a genome assembly, the tool a) hashes the reference file and populates the SQL database with the hashed entries, and b) hashes the query sequences

Use

1. Download Main.cpp, md5.cpp, and md5.h scripts. (The other scripts in the current repository attest to IPG content assessment and do not affect the tool's performance)
2. Compile Main.cpp as following: g++ Main.cpp -lsqlite3;
3. Launch the compiled script as following:

./<scriptname> -d <database> <names> -s <query> - if script is run for the first time and no database is available

./<scriptname> -s <query> - if the database is already built

Here, <database> refers to the FASTA reference file for selected taxon(-a), <query> refers to protein content of genome assembly in question, and <names> is a file containing protein ID to IPG ID mapping for reference file. For sequential launches of IPGQC with the same database, only the first use needs -d parameter specified. NOTE: The current version does not support differential database use. If you switch to another database, the previous one will be overriden. This is to be fixed soon.

Auxiliary scripts

Script IPG_stats_hists_upd.R contains code used for figure production as presented at BiATA 2021 (Saint Petersburg, Russia, held online). The scripts directory contain Shell scripts used for genome assembly, respective IPG content and IPG statistics retrieval.

Expected updates

The first major update is going to have the following features:

1. Main script - database construction independent of query search; multithreading; multiple database handling for independent launches;
2. Auxiliary scripts - a full suite for user-friendly IPG sequence and statistics retrieval.

Reference

IPGQC has not been published. For project rationale, refer to the following abstract: Yury V. Malovichko, Ruslan O. Alagov, Anton E. Shikov, Alexander V. Predeus, Anton A. Nizhnikov, Kirill S. Antonets. Identical Protein Group content and resequencing statistics as a naive metric of biological assembly quality: An evaluation study and draft tool implementation. From abstract book: Bioinformatics: From Algorithms to Applications (BiATA). July 12-13, Saint Petersburg, Russia.