Clustal Omega

Clustal Omega
Name	Clustal Omega
Title	Clustal Omega
Developer	European Bioinformatics Institute; Wellcome Trust Sanger Institute
Released	2011
Latest release	1.2.4
Programming language	C (programming language)
Operating system	Linux, macOS, Microsoft Windows
License	GNU General Public License

Clustal Omega is a multiple sequence alignment program widely used in bioinformatics for aligning protein sequences. It is a successor to earlier tools developed by groups at the European Bioinformatics Institute and the Wellcome Trust Sanger Institute, and is commonly integrated into pipelines at institutions such as the National Institutes of Health, the European Molecular Biology Laboratory, and software suites like EMBOSS. The software emphasizes scalability for large datasets and interoperability with formats used by repositories such as UniProt, GenBank, and Protein Data Bank.

Overview

Clustal Omega was developed to address growing dataset sizes encountered by researchers at the European Bioinformatics Institute and in consortiums including the 1000 Genomes Project and ENCODE Project. It builds on lineage from earlier alignment programs created by researchers including Desmond Higgins and Paul Higgins at the University College Dublin and developers associated with the Wellcome Trust. The project is associated with community infrastructures such as ELIXIR and is commonly distributed via package managers maintained by Debian and Bioconda. It is often compared to contemporaries like MAFFT, MUSCLE, and T-Coffee.

Algorithm and Implementation

Clustal Omega uses a progressive alignment strategy with improvements inspired by algorithms developed in the field by groups around Temple F. Smith and Michael Waterman. It constructs sequence profiles using k-mer based distance estimation related to methods from BLAST and FASTA and employs a modified version of the guide tree construction similar to neighbor-joining techniques proposed by Saitou and Nei. Implementation leverages the HHsearch/HHpred concept of profile HMMs for profile–profile alignment, and uses the UCLUST approach for clustering at scale. The codebase is written in C (programming language) with optional parallelization via POSIX threads and integration points for OpenMP and high-performance computing environments such as those used at Argonne National Laboratory and Lawrence Berkeley National Laboratory.

Input and Output Formats

Clustal Omega accepts common sequence formats used by databases like UniProt, GenBank, RefSeq, and tools such as EMBOSS and BioPerl. Supported input encodings include FASTA and Stockholm and it emits output in formats compatible with viewers like Jalview, AliView, and visualization tools from NCBI and EBI. Output options include alignment formats accepted by phylogenetics packages such as RAxML, MrBayes, and IQ-TREE, enabling downstream analyses employed by projects like The Cancer Genome Atlas and the Tree of Life Web Project.

Performance and Accuracy

Benchmarks frequently compare Clustal Omega to algorithms like MAFFT, MUSCLE, ProbCons, and PRANK. Studies by groups at University of California, Santa Cruz and European Bioinformatics Institute evaluated speed and accuracy on datasets from Pfam, SMART (protein domain), and SCOP; results show Clustal Omega scales to tens of thousands of sequences with competitive accuracy relative to MAFFT (multiple sequence alignment). Performance profiles consider metrics used by the Critical Assessment of Protein Structure Prediction and incorporate scoring schemes from BLOSUM and PAM matrices developed by researchers like Henikoff and Henikoff.

Applications and Usage

Clustal Omega is used in workflows across institutions such as Harvard University, Stanford University, University of Oxford, and industry labs at Pfizer and Novartis for tasks including phylogenetic inference, comparative genomics, and protein family characterization. It integrates into pipelines alongside tools like HMMER, InterProScan, BLAST+, and Samtools and is used in educational settings at universities including Massachusetts Institute of Technology and University of Cambridge. Applications span research projects like Human Microbiome Project, vaccine design efforts at GAVI, and structural modeling in collaboration with repositories such as the Protein Data Bank.

Limitations and Criticisms

Critiques from groups at Max Planck Society and reviews in journals associated with Nature Methods and Bioinformatics (journal) note that while Clustal Omega prioritizes scalability, it may not match the accuracy of iterative refinement methods from T-Coffee or probabilistic aligners like ProbCons on small, difficult datasets. Others highlight limitations when handling highly gapped sequences typical in analyses from the 1000 Genomes Project or ancient DNA studies curated by institutions such as the British Museum and Natural History Museum, London. Computational resource considerations have prompted integration with accelerators promoted by NVIDIA and cloud infrastructures like Amazon Web Services for large-scale deployments.

Category:Bioinformatics software