PSI-Search: iterative HOE-reduced profile SSEARCH searching

Li, Weizhong; McWilliam, Hamish; Goujon, Mickael; Cowley, Andrew Peter; López, Rodrigo; Pearson, William R.

doi:10.1093/bioinformatics/bts240

Cited by 34 publications

(29 citation statements)

References 17 publications

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“…The aforementioned reverse coverage test can be used to assess the rate and coverage of de novo false hits, but another possible source of false coverage is so-called ‘homologous overextension’ (10), the extension of a hit beyond the true bounds of a true instance and into flanking non-homologous sequence. Consider a region of sequence matched by multiple tools: all tools are expected to match this region in a repeated search, and some tools might extend into flanking sequence; the concern is establishing whether that extension is legitimate (a result of better sensitivity to the signal of true flanking match) or not (a result of overly permissive extension of hits).…”

Section: Sensitivity and False Discoverymentioning

confidence: 99%

Dfam: a database of repetitive DNA based on profile hidden Markov models

Wheeler

Clements

Eddy

et al. 2012

Nucleic Acids Research

260

233

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We present a database of repetitive DNA elements, called Dfam (http://dfam.janelia.org). Many genomes contain a large fraction of repetitive DNA, much of which is made up of remnants of transposable elements (TEs). Accurate annotation of TEs enables research into their biology and can shed light on the evolutionary processes that shape genomes. Identification and masking of TEs can also greatly simplify many downstream genome annotation and sequence analysis tasks. The commonly used TE annotation tools RepeatMasker and Censor depend on sequence homology search tools such as cross_match and BLAST variants, as well as Repbase, a collection of known TE families each represented by a single consensus sequence. Dfam contains entries corresponding to all Repbase TE entries for which instances have been found in the human genome. Each Dfam entry is represented by a profile hidden Markov model, built from alignments generated using RepeatMasker and Repbase. When used in conjunction with the hidden Markov model search tool nhmmer, Dfam produces a 2.9% increase in coverage over consensus sequence search methods on a large human benchmark, while maintaining low false discovery rates, and coverage of the full human genome is 54.5%. The website provides a collection of tools and data views to support improved TE curation and annotation efforts. Dfam is also available for download in flat file format or in the form of MySQL table dumps.

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Section: Sensitivity and False Discoverymentioning

confidence: 99%

Dfam: a database of repetitive DNA based on profile hidden Markov models

Wheeler

Clements

Eddy

et al. 2012

Nucleic Acids Research

260

233

View full text Add to dashboard Cite

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“…Sequence similarity/homology searches including FASTA (11), BLAST (12,13) and PSI-Search (14) against the databases are available through the web form submissions (http://www.ebi.ac.uk/Tools/sss/) and also through the corresponding EMBL-EBI SOAP/REST web services (15). …”

Section: Data Access and Usagementioning

confidence: 99%

The Annotation-enriched non-redundant patent sequence databases

Kondratowicz

McWilliam

et al. 2013

Database

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The EMBL-European Bioinformatics Institute (EMBL-EBI) offers public access to patent sequence data, providing a valuable service to the intellectual property and scientific communities. The non-redundant (NR) patent sequence databases comprise two-level nucleotide and protein sequence clusters (NRNL1, NRNL2, NRPL1 and NRPL2) based on sequence identity (level-1) and patent family (level-2). Annotation from the source entries in these databases is merged and enhanced with additional information from the patent literature and biological context. Corrections in patent publication numbers, kind-codes and patent equivalents significantly improve the data quality. Data are available through various user interfaces including web browser, downloads via FTP, SRS, Dbfetch and EBI-Search. Sequence similarity/homology searches against the databases are available using BLAST, FASTA and PSI-Search. In this article, we describe the data collection and annotation and also outline major changes and improvements introduced since 2009. Apart from data growth, these changes include additional annotation for singleton clusters, the identifier versioning for tracking entry change and the entry mappings between the two-level databases.Database URL: http://www.ebi.ac.uk/patentdata/nr/

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“…Because of its usefulness and availability, many modifications have been proposed since PSI-BLAST was first published, including introduction of compositionbased statistics, optimizing cache utilization, and revising pseudo-count strategy (Altschul et al 2009;Aspnas et al 2010;Schaffer et al 2001). Overcoming the problem of "homologous over extension" also improves the PSI-BLAST accuracy (Gonzalez & Pearson 2010;Li et al 2012). In this study, we describe that PSI-BLAST can be improved further by slightly changing the sequence weighting method.…”

Section: Introductionmentioning

confidence: 99%

Simple adjustment of the sequence weight algorithm remarkably enhances PSI-BLAST performance

Oda¹,

Lim²,

Tomii³

2016

Preprint

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Background: PSI-BLAST, an extremely popular tool for sequence similarity search, features the utilization of PositionSpecific Scoring Matrix (PSSM) constructed from a multiple sequence alignment (MSA). PSSM allows the detection of more distant homologs than a general amino acid substitution matrix does. An accurate estimation of the weights for sequences in an MSA is crucially important for PSSM construction. PSI-BLAST divides a given MSA into multiple blocks, for which sequence weights are calculated. When the block width becomes very narrow, the sequence weight calculation can be odd. Results: We demonstrate that PSI-BLAST indeed generates a significant fraction of blocks having width less than 5, thereby degrading the PSI-BLAST performance. We revised the code of PSI-BLAST to prevent the blocks from being narrower than a given minimum block width (MBW). We designate the modified application of PSI-BLAST as PSI-BLASTexB. When MBW is 25, PSI-BLASTexB notably outperforms PSI-BLAST consistently for three independent benchmark sets. The performance boost is even more drastic when an MSA, instead of a sequence, is used as a query.Conclusions: Our results demonstrate that the generation of narrow-width blocks during the sequence weight calculation is a critically important factor that restricts the PSI-BLAST search performance. By preventing narrow blocks, PSI-BLASTexB upgrades the PSI-BLAST performance remarkably. Binaries and source codes of PSI-BLASTexB (MBW = 25) are available at https://github.com/kyungtaekLIM/PSI-BLASTexB.

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PSI-Search: iterative HOE-reduced profile SSEARCH searching

Cited by 34 publications

References 17 publications

Dfam: a database of repetitive DNA based on profile hidden Markov models

Dfam: a database of repetitive DNA based on profile hidden Markov models

The Annotation-enriched non-redundant patent sequence databases

Simple adjustment of the sequence weight algorithm remarkably enhances PSI-BLAST performance

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