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Geoffrey J Barton

Publications and source records attributed to Geoffrey J Barton.

5 recordsLinked to original sources

GOtcha: a new method for prediction of protein function assessed by the annotation of seven genomes.

BACKGROUND: The function of a novel gene product is typically predicted by transitive assignment of annotation from similar sequences. We describe a novel method, GOtcha, for predicting gene product function by annotation with Gene Ontology (GO) terms. GOtcha predicts GO term associations with term-specific probability (P-score) measures of confidence. Term-specific probabilities are a novel feature of GOtcha and allow the identification of conflicts or uncertainty in annotation. RESULTS: The GOtcha method was applied to the recently sequenced genome for Plasmodium falciparum and six other genomes. GOtcha was compared quantitatively for retrieval of assigned GO terms against direct transitive assignment from the highest scoring annotated BLAST search hit (TOPBLAST). GOtcha exploits information deep into the 'twilight zone' of similarity search matches, making use of much information that is otherwise discarded by more simplistic approaches. At a P-score cutoff of 50%, GOtcha provided 60% better recovery of annotation terms and 20% higher selectivity than annotation with TOPBLAST at an E-value cutoff of 10(-4). CONCLUSIONS: The GOtcha method is a useful tool for genome annotators. It has identified both errors and omissions in the original Plasmodium falciparum annotation and is being adopted by many other genome sequencing projects.

Animals↗

The Jalview Java alignment editor.

Multiple sequence alignment remains a crucial method for understanding the function of groups of related nucleic acid and protein sequences. However, it is known that automatic multiple sequence alignments can often be improved by manual editing. Therefore, tools are needed to view and edit multiple sequence alignments. Due to growth in the sequence databases, multiple sequence alignments can often be large and difficult to view efficiently. The Jalview Java alignment editor is presented here, which enables fast viewing and editing of large multiple sequence alignments.

Algorithms↗

OXBench: a benchmark for evaluation of protein multiple sequence alignment accuracy.

BACKGROUND: The alignment of two or more protein sequences provides a powerful guide in the prediction of the protein structure and in identifying key functional residues, however, the utility of any prediction is completely dependent on the accuracy of the alignment. In this paper we describe a suite of reference alignments derived from the comparison of protein three-dimensional structures together with evaluation measures and software that allow automatically generated alignments to be benchmarked. We test the OXBench benchmark suite on alignments generated by the AMPS multiple alignment method, then apply the suite to compare eight different multiple alignment algorithms. The benchmark shows the current state-of-the art for alignment accuracy and provides a baseline against which new alignment algorithms may be judged. RESULTS: The simple hierarchical multiple alignment algorithm, AMPS, performed as well as or better than more modern methods such as CLUSTALW once the PAM250 pair-score matrix was replaced by a BLOSUM series matrix. AMPS gave an accuracy in Structurally Conserved Regions (SCRs) of 89.9% over a set of 672 alignments. The T-COFFEE method on a data set of families with <8 sequences gave 91.4% accuracy, significantly better than CLUSTALW (88.9%) and all other methods considered here. The complete suite is available from http://www.compbio.dundee.ac.uk. CONCLUSIONS: The OXBench suite of reference alignments, evaluation software and results database provide a convenient method to assess progress in sequence alignment techniques. Evaluation measures that were dependent on comparison to a reference alignment were found to give good discrimination between methods. The STAMP Sc Score which is independent of a reference alignment also gave good discrimination. Application of OXBench in this paper shows that with the exception of T-COFFEE, the majority of the improvement in alignment accuracy seen since 1985 stems from improved pair-score matrices rather than algorithmic refinements. The maximum theoretical alignment accuracy obtained by pooling results over all methods was 94.5% with 52.5% accuracy for alignments in the 0-10 percentage identity range. This suggests that further improvements in accuracy will be possible in the future.

Amino Acid Sequence↗

Increased coverage obtained by combination of methods for protein sequence database searching.

MOTIVATION: Sequence alignment methods that compare two sequences (pairwise methods) are important tools for the detection of biological sequence relationships. In genome annotation, multiple methods are often run and agreement between methods taken as confirmation. In this paper, we assess the advantages of combining search methods by comparing seven pairwise alignment methods, including three local dynamic programming algorithms (PRSS, SSEARCH and SCANPS), two global dynamic programming algorithms (GSRCH and AMPS) and two heuristic approximations (BLAST and FASTA), individually and by pairwise intersection and union of their result lists at equal p-value cut-offs. RESULTS: When applied singly, the dynamic programming methods SCANPS and SSEARCH gave significantly better coverage (p=0.01) compared to AMPS, GSRCH, PRSS, BLAST and FASTA. Results ranked by BLAST p-values gave significantly better coverage compared to ranking by BLAST e-values. Of 56 combinations of eight methods considered, 19 gave significant increases in coverage at low error compared to the parent methods at an equal p-value cutoff. The union of results by BLAST (p-value) and FASTA at an equal p-value cutoff gave significantly better coverage than either method individually. The best overall performance was obtained from the intersection of the results from SSEARCH and the GSRCH62 global alignment method. At an error level of five false positives, this combination found 444 true positives, a significant 12.4% increase over SSEARCH applied alone.

Algorithms↗

Visual representation of database search results: the RHIMS Plot.

SUMMARY: An algorithm and software are described that provide a fast method to produce a novel, function-oriented visualization of the results of a sequence database search. Text mining of sequence annotations allows position specific plots of potential functional similarity to be compared in a simple compact representation. AVAILABILITY: The application can be accessed via a web server at http://www.compbio.dundee.ac.uk. The RHIMS software may be obtained by request to the authors.

Algorithms↗