IGUA

Iterative Gene clUster Analysis, a fast and flexible gene cluster family delineation method.

Overview

IGUA is a method for high-throughput content-agnostic identification of Gene Cluster Families (GCFs) from gene clusters of genomic and metagenomic origin. It performs three clustering iterations to perform GCF assignment:

1️⃣ Fragment mapping

Reduce the input sequence space by identifying which gene clusters are almost identical fragments from each other. Useful in combining datasets of metagenomic origin, or in combining results from various genome mining tools which may report overlapping gene clusters

2️⃣ Nucleotide deduplication

Find similar gene clusters in genomic space, using linear clustering with lower sequence identity and reciprocical coverage. Effectively combine gene clusters with high conservation while taking into account possible evolutionary events like gene deletion or fusion.

3️⃣ Protein representation

Compute a numerical representation of gene clusters in terms of protein composition, using representatives from a protein sequence clustering, and perform hierarchical clustering. Identify more distant gene clusters which share the same proteins while not necessarily maintaining the same gene architecture.

Compared to similar methods such as BiG-SLiCE or BiG-SCAPE, IGUA does not use Pfam domains to represent gene cluster composition, using instead representatives from a fast unsupervised clustering computed with MMseqs2. This allows IGUA to accurately account for proteins that may not be covered by Pfam, and avoids performing a costly annotation step with HMMER. The resulting protein representatives can be later annotated indepently to transfer annotations to the GCFs.

Setup

Have a look at the Installing page to find the different ways to install IGUA. IGUA depends on some common scientific Python packages (scipy, anndata, pandas) as well as a working MMseqs2 install.

Citation

IGUA is scientific software, with a preprint currently available on bioRxiv.

Library

• User Guide
  • Installing
  • Running IGUA
  • Scripting IGUA
  • Contribution Guide
  • Changelog
  • Copyright Notice
• API Reference
  • Pipeline
  • Clustering Strategy
  • MMSeqs Driver
  • Datasets
• CLI Reference
  • Named Arguments
  • Input
  • Output
  • Parameters
  • MMSeqs2 Deduplication
  • MMSeqs2 Nucleotide Clustering
  • MMSeqs2 Protein Clustering
  • Clustering

License

This library is provided under the GNU General Public License 3.0 or later. See the Copyright Notice section for more information including the complete license text.

This project was co-developed by:

	Martin Larralde PhD Candidate Georg Zeller Associate Professor
	Laura M. Carroll Assistant Professor Josefin Blom PhD Student Hadrien Gourlé Postdoctoral Fellow
	Hale-Seda Radoykova Doctoral Assistant Lucas Paoli Associate Professor