PROMALS3D: a tool for multiple protein sequence and structure alignments

Although multiple sequence alignments (MSAs) are essential for a wide range of applications from structure modeling to prediction of functional sites, construction of accurate MSAs for distantly related proteins remains a largely unsolved problem. The rapidly increasing database of spatial structures is a valuable source to improve alignment quality. We explore the use of 3D structural information to guide sequence alignments constructed by our MSA program PROMALS. The resulting tool, PROMALS3D, automatically identifies homologs with known 3D structures for the input sequences, derives structural constraints through structure-based alignments and combines them with sequence constraints to construct consistency-based multiple sequence alignments. The output is a consensus alignment that brings together sequence and structural information about input proteins and their homologs. PROMALS3D can also align sequences of multiple input structures, with the output representing a multiple structure-based alignment refined in combination with sequence constraints. The advantage of PROMALS3D is that it gives researchers an easy way to produce high-quality alignments consistent with both sequences and structures of proteins. PROMALS3D outperforms a number of existing methods for constructing multiple sequence or structural alignments using both reference-dependent and reference-independent evaluation methods.     

Tcoffee@igs: A web server for computing,evaluating and combining multiple sequence alignments

This paper presents Tcoffee@igs, a new server provided to the community by Hewlet Packard computers and the Centre National de la Recherche Scientifique. This server is a web-based tool dedicated to the computation, the evaluation and the combination of multiple sequence alignments. It uses the latest version of the T-Coffee package. Given a set of unaligned sequences, the server returns an evaluated multiple sequence alignment and the associated phylogenetic tree. This server also makes it possible to evaluate the local reliability of an existing alignment and to combine several alternative multiple alignments into a single new one. Tcoffee@igs can be used for aligning protein, RNA or DNA sequences. Datasets of up to 100 sequences (2000 residues long) can be processed. The server and its documentation are available from: http://igs-server.cnrs-mrs.fr/Tcoffee/.     

The Human Phenotype Ontology: a tool for annotating and analyzing human hereditary disease

There are many thousands of hereditary diseases in humans, each of which has a specific combination of phenotypic features, but computational analysis of phenotypic data has been hampered by lack of adequate computational data structures. Therefore, we have developed a Human Phenotype Ontology (HPO) with over 8000 terms representing individual phenotypic anomalies and have annotated all clinical entries in Online Mendelian Inheritance in Man with the terms of the HPO. We show that the HPO is able to capture phenotypic similarities between diseases in a useful and highly significant fashion.     

Greene SCPrimer: a rapid comprehensive tool for designing degenerate primers from multiple sequence alignments

Polymerase chain reaction (PCR) is widely applied in clinical and environmental microbiology. Primer design is key to the development of successful assays and is often performed manually by using multiple nucleic acid alignments. Few public software tools exist that allow comprehensive design of degenerate primers for large groups of related targets based on complex multiple sequence alignments. Here we present a method for designing such primers based on tree building followed by application of a set covering algorithm, and demonstrate its utility in compiling Multiplex PCR primer panels for detection and differentiation of viral pathogens.     

The Mammalian Phenotype Ontology as a tool for annotating,analyzing and comparing phenotypic information

The Mammalian Phenotype (MP) Ontology enables robust annotation of mammalian phenotypes in the context of mutations, quantitative trait loci and strains that are used as models of human biology and disease. The MP Ontology supports different levels and richness of phenotypic knowledge and flexible annotations to individual genotypes. It continues to develop dynamically via collaborative input from research groups, mutagenesis consortia, and biological domain experts. The MP Ontology is currently used by the Mouse Genome Database and Rat Genome Database to represent phenotypic data.     

AltAVisT: comparing alternative multiple sequence alignments

We introduce a WWW-based tool that is able to compare two alternative multiple alignments of a given sequence set. Regions where both alignments coincide are color-coded to visualize the local agreement between the two alignments and to identify those regions that can be considered to be reliably aligned. AVAILABILITY: http://bibiserv.techfak.uni-bielefeld.de/altavist/.     

AlignMiner: a Web-based tool for detection of divergent regions in multiple sequence alignments of conserved sequences

Background  

Multiple sequence alignments are used to study gene or protein function, phylogenetic relations, genome evolution hypotheses and even gene polymorphisms. Virtually without exception, all available tools focus on conserved segments or residues. Small divergent regions, however, are biologically important for specific quantitative polymerase chain reaction, genotyping, molecular markers and preparation of specific antibodies, and yet have received little attention. As a consequence, they must be selected empirically by the researcher. AlignMiner has been developed to fill this gap in bioinformatic analyses.     

A statistical score for assessing the quality of multiple sequence alignments

Background  

Multiple sequence alignment is the foundation of many important applications in bioinformatics that aim at detecting functionally important regions, predicting protein structures, building phylogenetic trees etc. Although the automatic construction of a multiple sequence alignment for a set of remotely related sequences cause a very challenging and error-prone task, many downstream analyses still rely heavily on the accuracy of the alignments.     

MUTAGEN: multi-user tool for annotating genomes

SUMMARY: MUTAGEN is a free prokaryotic annotation system. It offers the advantages of genome comparison, graphical sequence browsers, search facilities and open-source for user-specific adjustments. The web-interface allows several users to access the system from standard desktop computers. The Sulfolobus acidocaldarius genome, and several plasmids and viruses have so far been analysed and annotated using MUTAGEN. AVAILABILITY: MUTAGEN is released as open-source software under GPL. The code is available for download and/or contribution at http://dac.molbio.ku.dk/bioinformatics/MUTAGEN/     

ParaAT: a parallel tool for constructing multiple protein-coding DNA alignments

Constructing multiple homologous alignments for protein-coding DNA sequences is crucial for a variety of bioinformatic analyses but remains computationally challenging. With the growing amount of sequence data available and the ongoing efforts largely dependent on protein-coding DNA alignments, there is an increasing demand for a tool that can process a large number of homologous groups and generate multiple protein-coding DNA alignments. Here we present a parallel tool - ParaAT that is capable of parallelly constructing multiple protein-coding DNA alignments for a large number of homologs. As testified on empirical datasets, ParaAT is well suited for large-scale data analysis in the high-throughput era, providing good scalability and exhibiting high parallel efficiency for computationally demanding tasks. ParaAT is freely available for academic use only at http://cbb.big.ac.cn/software.     

Core column prediction for protein multiple sequence alignments

Background

In a computed protein multiple sequence alignment, the coreness of a column is the fraction of its substitutions that are in so-called core columns of the gold-standard reference alignment of its proteins. In benchmark suites of protein reference alignments, the core columns of the reference alignment are those that can be confidently labeled as correct, usually due to all residues in the column being sufficiently close in the spatial superposition of the known three-dimensional structures of the proteins. Typically the accuracy of a protein multiple sequence alignment that has been computed for a benchmark is only measured with respect to the core columns of the reference alignment. When computing an alignment in practice, however, a reference alignment is not known, so the coreness of its columns can only be predicted.

Results

We develop for the first time a predictor of column coreness for protein multiple sequence alignments. This allows us to predict which columns of a computed alignment are core, and hence better estimate the alignment’s accuracy. Our approach to predicting coreness is similar to nearest-neighbor classification from machine learning, except we transform nearest-neighbor distances into a coreness prediction via a regression function, and we learn an appropriate distance function through a new optimization formulation that solves a large-scale linear programming problem. We apply our coreness predictor to parameter advising, the task of choosing parameter values for an aligner’s scoring function to obtain a more accurate alignment of a specific set of sequences. We show that for this task, our predictor strongly outperforms other column-confidence estimators from the literature, and affords a substantial boost in alignment accuracy.

     

THoR: a tool for domain discovery and curation of multiple alignments

We describe a tool, THoR, that automatically creates and curates multiple sequence alignments representing protein domains. This exploits both PSI-BLAST and HMMER algorithms and provides an accurate and comprehensive alignment for any domain family. The entire process is designed for use via a web-browser, with simple links and cross-references to relevant information, to assist the assessment of biological significance. THoR has been benchmarked for accuracy using the SMART and pufferfish genome databases.     

TOPAL 2.0: improved detection of mosaic sequences within multiple alignments

MOTIVATION: The Dss statistic was proposed by McGuire et al. (Mol. Biol. Evol., 14, 1125-1131, 1997) for scanning data sets for the presence of recombination, an important step in some phylogenetic analyses. The statistic, however, could not distinguish well between among-site rate variation and recombination, and had no statistical test for significant values. This paper addresses these shortfalls. RESULTS: A modification to the Dss statistic is proposed which accounts for rate variation to a large extent. A statistical test, based on parametric bootstrapping, is also suggested. AVAILABILITY: The TOPAL package (version 2) may be accessed from http:/ /www.bioss.sari.ac.uk/frank/Genetics and by anonymous ftp from typ://ftp.bioss.sari.ac.uk in the directory pub/phylogeny/topal. CONTACT: frank@bioss.sari.ac.uk     

RASCAL: rapid scanning and correction of multiple sequence alignments

MOTIVATION: Most multiple sequence alignment programs use heuristics that sometimes introduce errors into the alignment. The most commonly used methods to correct these errors use iterative techniques to maximize an objective function. We present here an alternative, knowledge-based approach that combines a number of recently developed methods into a two-step refinement process. The alignment is divided horizontally and vertically to form a 'lattice' in which well aligned regions can be differentiated. Alignment correction is then restricted to the less reliable regions, leading to a more reliable and efficient refinement strategy. RESULTS: The accuracy and reliability of RASCAL is demonstrated using: (i) alignments from the BAliBASE benchmark database, where significant improvements were often observed, with no deterioration of the existing high-quality regions, (ii) a large scale study involving 946 alignments from the ProDom protein domain database, where alignment quality was increased in 68% of the cases; and (iii) an automatic pipeline to obtain a high-quality alignment of 695 full-length nuclear receptor proteins, which took 11 min on a DEC Alpha 6100 computer Availability: RASCAL is available at ftp://ftp-igbmc.u-strasbg.fr/pub/RASCAL. SUPPLEMENTARY INFORMATION: http://bioinfo-igbmc.u-strasbourg.fr/BioInfo/RASCAL/paper/rascal_supp.html     

PROANAL version 2: multifunctional Program for analysis of multiple protein sequence alignments and for studying the structure-activity relationships in protein families

A new version of the program PROANAL is described. A multiplelinear regression analysis of the protein structure–activityrelationship allows one to investigate the combina–tionsof protein sites and factors influencing the activity. The programalso provides the possibility to seek out protein sites, conservativeor variable in variations of physico–chemical characteristics,and regions with high or low values of these characteristics.PROANAL2 may be useful in the simulation of protein–engineeringexperiments and in the search of a number of protein regionssuch as functional sites, secondary structures, solvent-exposedregions, T– and B–cell antigenic determinants, etc.     

Phylo-VISTA: interactive visualization of multiple DNA sequence alignments

MOTIVATION: The power of multi-sequence comparison for biological discovery is well established. The need for new capabilities to visualize and compare cross-species alignment data is intensified by the growing number of genomic sequence datasets being generated for an ever-increasing number of organisms. To be efficient these visualization algorithms must support the ability to accommodate consistently a wide range of evolutionary distances in a comparison framework based upon phylogenetic relationships. RESULTS: We have developed Phylo-VISTA, an interactive tool for analyzing multiple alignments by visualizing a similarity measure for multiple DNA sequences. The complexity of visual presentation is effectively organized using a framework based upon interspecies phylogenetic relationships. The phylogenetic organization supports rapid, user-guided interspecies comparison. To aid in navigation through large sequence datasets, Phylo-VISTA leverages concepts from VISTA that provide a user with the ability to select and view data at varying resolutions. The combination of multiresolution data visualization and analysis, combined with the phylogenetic framework for interspecies comparison, produces a highly flexible and powerful tool for visual data analysis of multiple sequence alignments. AVAILABILITY: Phylo-VISTA is available at http://www-gsd.lbl.gov/phylovista. It requires an Internet browser with Java Plug-in 1.4.2 and it is integrated into the global alignment program LAGAN at http://lagan.stanford.edu     

WebBLAST 2.0: an integrated solution for organizing and analyzing sequence data.

SUMMARY: WebBLAST is a suite of programs intended to assist in organizing sequencing data and to provide first-pass sequence analysis in an automated fashion. Data processing is fully automated, with end-users being presented both graphical and tabular summaries of data that can be viewed using any Web browser. AVAILABILITY: The program is free and available at http://genome.nhgri.nih. gov/webblast.