Conference Paper

Indexing Nucleotide Databases for Fast Query Evaluation.

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Abstract

A query to a nucleotide database is a DNA sequence. Answers are similar sequences, that is, sequences with a high-quality local alignment. Existing techniques for finding answers use exhaustive search, but it is likely that, with increasing database size, these algorithms will become prohibitively expensive. We have developed a partitioned search approach, in which local alignment string matching techniques are used in tandem with an index. We show that fixedlength substrings, or intervals, are a suitable basis for indexing in conjunction with local alignment on likely answers. By use of suitable compression techniques the index size is held to an acceptable level, and queries can be evaluated several times more quickly than with exhaustive search techniques.

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... In the next chapter, we focus on methods for searching sequence databanks. We begin with descriptions of the popular heuristic search algorithms such as fasta [Pearson and Lipman, 1988] and blast as well as index-based approaches such as cafe [Williams and Zobel, 1996;, PatternHunter [Ma et al., 2002; and blat [Kent, 2002]. We then describe distributed search schemes and iterative algorithms such as psi-blast [Altschul et al., 1997] and sam ]. ...
... Unlike the exhaustive schemes, index-based approaches do not rely on the entire collection fitting into main-memory for reasonable search performance [Williams, 2003]. Early approaches to indexed-base search included scan [Orcutt and Barker, 1984], flash [Califano and Rigoutsos, 1993], ramdb [Fondrat and Dessen, 1995], rapid [Miller et al., 1999] and the work by Myers [1994], however the most successful approach is the cafe indexed-based homology search tool [Williams and Zobel, 1996;. ...
... Several index-based methods for homology search have been proposed, where an inverted index of the collection is used to identify hits without exhaustively scanning the entire database. Schemes such as cafe [Williams and Zobel, 1996;, scan [Orcutt and Barker, 1984], flash [Califano and Rigoutsos, 1993], ramdb [Fondrat and Dessen, 1995], and rapid [Miller et al., 1999] employ an on-disk index and are suitable for searching large collections such as GenBank. Cafe is the most successful approach to employ an on-disk index with substantially faster search times and a small reduction in search accuracy when compared to blast [Chen, 2004]. ...
... Sequencing initiatives are contributing exponentially increasing quantities of nucleotide data to databases such as GenBank (Benson et al., 1993). We propose a new direct coding compression scheme for use in homology search applications such as FASTA (Pearson and Lipman, 1988), BLAST (Altschul et al., 1990), and CAFE (Williams and Zobel, 1996a). This scheme yields compact storage, is lossless—nucleotide bases and wildcards are represented—and has extremely fast decompression. ...
... We have used the Elias gamma codes to encode each count w and Golomb codes to represent each sequence of offsets. These techniques are a variation on techniques used for inverted file compression, which has been successfully applied to large text databases (Bell et al., 1993) and to genomic databases (Williams and Zobel, 1996a; Williams and Zobel, 1996b). Compression with Golomb codes, given the appropriate choice of a pre-calculated parameter, is better than with Elias coding. ...
... We therefore expect that use of direct coding in a retrieval system would significantly reduce retrieval times overall. To further test this hypothesis we incorporated the scheme into cafe, our genomic database retrieval engine (Williams and Zobel, 1996a ), and found that retrieval times fell by over 20%. In BLAST (Altschul et al., 1990) a simple approach is taken to nucleotide compression. ...
Article
Motivation: International sequencing efforts are creating huge nucleotide databases, which are used in searching applications to locate sequences homologous to a query sequence. In such applications, it is desirable that databases are stored compactly, that sequences can be accessed independently of the order in which they were stored, and that data can be rapidly retrieved from secondary storage, since disk costs are often the bottleneck in searching. Results: We present a purpose-built direct coding scheme for fast retrieval and compression of genomic nucleotide data. The scheme is lossless, readily integrated with sequence search tools, and does not require a model. Direct coding gives good compression and allows faster retrieval than with either uncompressed data or data compressed by other methods, thus yielding significant improvements in search times for high-speed homology search tools. Availability: The direct coding scheme (cino) is available free of charge by anonymous ftp from goanna.cs.rmit.edu.au in the directory pub/rmit/cino. Contact: E-mail: [email protected] /* */
... Sequencing initiatives are contributing exponentially increasing quantities of nucleotide data to databases such as GenBank (Benson et al., 1993). We propose a new direct coding compression scheme for use in homology search applications such as FASTA (Pearson and Lipman et al., 1988), BLAST (Altschul et al., 1990) and CAFE (Williams and Zobel, 1996a). This scheme yields compact storage, is lossless—nucleotide bases and wildcards are represented— and has extremely fast decompression. ...
... as, 1975) and the Golomb codes (Golomb, 1966). We have used the Elias gamma codes to encode each count w and Golomb codes to represent each sequence of offsets. These techniques are a variation on techniques used for inverted file compression, which has been successfully applied to large text databases (Bell et al., 1993) and to genomic databases (Williams and Zobel. 1996a.b). ...
... To test this hypothesis further, we incorporated the scheme into cafe, our genomic database retrieval engine (Williams and Zobel, 1996a), and found that retrieval times fell by >20%. ...
Article
Full-text available
Motivation: International sequencing e#orts are creating huge nucleotide databases, which are used in searching applications to locate sequences homologous to a query sequence. In such applications, it is desirable that databases are stored compactly; that sequences can be accessed independently of the order in which they were stored; and that data can be rapidly retrieved from secondary storage, since disk costs are often the bottleneck in searching.
... Variable-byte codes for selected integers in the range 1-30 are shown in Table 1. A typical application is the coding of index term and inverted list file offset pairs for an inverted index [10]. ...
... Elias coding [2] is a non-parameterised method of coding integers that is, for example, used in large text database indexes [8] and specialist applications [10,11]. Elias coding, like the other schemes described in this paper, allows unambiguous coding of integers and does not require separators between each integer of a stored array. ...
... Each postings array contains a sorted list of document identifiers and, in many indexes, interspersed between each document identifier is a sorted array of one or more word positions of that term in the document. We experiment with an uncompressed index postings list of 630.5 Mb (vector) extracted from a much larger carefully compressed 3,596 Mb postings file used in the cafe [10] indexed genomic retrieval sys-tem. 1 This postings list contains both document identifiers and interleaved word positions. ...
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Past access to files of integers is crucial for the efficient resolution of queries to databases. Integers are the basis of indexes used to resolve queries, for example, in large internet search systems, and numeric data forms a large part of most databases. Disk access costs can be reduced by compression, if the cost of retrieving a compressed representation from disk and the CPU cost of decoding such a representation is less than that of retrieving uncompressed data. In this paper we show experimentally that, for large or small collections, storing integers in a compressed format reduces the time required for either sequential stream access or random access. We compare different approaches to compressing integers, including the Elias gamma and delta codes, Golomb coding, and a variable-byte integer scheme. As a conclusion, we recommend that, for fast access to integers, files be stored compressed.
... Conventional databases use indexing to provide efficient access to the data. Williams and Zobel [6] use an inverted-list indexing technique to support alignment queries on nucleotide databases. In their approach the processing of queries is partitioned in two phases: ...
... In other words, the variant GNAT is same as the original, after replacing (5) by (6). The detailed algorithm is as follows. ...
... Conventional databases use indexing to provide efficient access to the data. Williams and Zobel [6] use an inverted-list indexing technique to support alignment queries on nucleotide databases. In their approach the processing of queries is partitioned in two phases: ...
... In other words, the variant GNAT is same as the original, after replacing (5) by (6). The detailed algorithm is as follows. ...
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A genomic database consists of a set of nucleotide sequences, for which an important kind of query is the focal sequence alignment. The paper investigates two different indexing techniques, namely the variations of GNAT trees and M-trees to support fast query evaluation for local alignment, by transforming the alignment problem to a variant metric space neighborhood search problem
... The edit distance family of string matching techniques is suitable for this task [11,12], and have been widely applied in related applications including genomics and phonetic name matching [27,28]. Three kinds of edit distance are applicable. ...
... This approach has the disadvantage, however, that a piece that matches well overall but has intermittent differences will not score highly. A more flexible method, successfully used in string matching and genomic retrieval [27], is to use n-grams: count the number of matching substrings of some fixed length n. The ngram count should be normalised by string length, because long pieces are statistically more likely to have an n-gram match. ...
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... Conventional databases use indexing to provide efficient access to the data. Williams and Zobel [6] use an inverted-list indexing technique to support alignment queries on nucleotide databases. In their approach the processing of queries is partitioned in two phases: ...
... In other words, the variant GNAT is same as the original, after replacing (5) by (6). The detailed algorithm is as follows. ...
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. A genomic database consists of a set of nucleotide sequences, for which an important kind of queries is the local sequence alignment. This paper studies the indexing techniques to support fast query evaluation for local alignment, by transforming the alignment problem to a variant metric space neighborhood search problem. We propose and analyze the corresponding algorithms and structures, and identify several directions for the future work. 1 Introduction Sequence databases are among the most important information repositories in molecular biology. Two types of sequences are found in sequence databases: nucleotide sequences with a four letter alphabet, and an amino acid residue sequences with a twenty letter alphabet. A fundamental access mechanism to sequence databases is by sequence alignment. The relevance of sequence alignment derives from evolutionary relationships between sequences. Thus a typical query against a sequence database is to find for a given sequence x all sequence...
... Importantly, CAFÉ method consists of coarse and fine search is marginally less accurate than BLAST1 and FASTA. From search point of view, CAFE is 8 times faster and efficient than the BLAST2 [29,30]. PropSearch tool is proposed by the scientific and research society [13], have basic idea in database search is to utilize conserved properties in the similar structures. ...
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With the rapid development in the field of life sciences and the flooding of genomic information, the need for faster and scalable searching methods has become urgent. One of the approaches that were investigated is indexing. The indexing methods have been categorized into three categories which are the lengthbased index algorithms, transformation-based algorithms and mixed techniques-based algorithms. In this research, we focused on the transformation based methods. We embedded the N-gram method into the transformation-based method to build an inverted index table. We then applied the parallel methods to speed up the index building time and to reduce the overall retrieval time when querying the genomic database. Our experiments show that the use of N-Gram transformation algorithm is an economical solution; it saves time and space too. The result shows that the size of the index is smaller than the size of the dataset when the size of N-Gram is 5 and 6. The parallel N-Gram transformation algorithm's results indicate that the uses of parallel programming with large dataset are promising which can be improved further.
... They avoid database scanning by using inverted index, which has been proved successful in web search engines. FLASH [2], RAMDB [9], MAP [55], PatternHunter [8] and CAFE [19], [21] are index-based search tools which use pre-built indices on subsequences to speed up the lookup process. CAFE claimed that it could run eight times faster than BLAST and 50 times faster than FASTA. ...
... Though current storage technology is developing rapidly, but considering the sizes of protein sequence collections are also growing exponentially, these are relatively large storage overheads. By introducing techniques such as index compression for nucleotide databases (Williams et al., 1997) and index stopping which discards high-frequency n-grams from the index (Williams et al., 1996), we expect that the index size of ProSeS system can be further reduced to an acceptable level. ...
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Motivation: Though the sequence databases of proteins and DNAs are increas-ing in size exponentially, still exhaustive sequence search systems are commonly used in conducting biological researches. However, due to the advancement of information technology, many information retrieval algorithms have been de-veloped to search strings in large-scale text databases and are proved to be successful. We propose that these algorithms could also be applied to the bio-logical data. Results: Four n-gram indexing methods (tri-gram, tetra-gram, penta-gram, and hexa-gram) were applied to extract indices from protein sequences of the PIR-NREF database, and their retrieval effectiveness and speed were mea-sured. Penta-gram method showed the best results that its retrieval effective-ness matches for BLASTP and its retrieval speed was about 38 times faster than BLASTP program.
... When index processing is complete, the accumulators can be used to identify regions of high similarity, by identifying sequences of similar fragments. A related approach has been successfully applied by Williams and Zobel to querying of nucleotide databases [15]. We therefore believe that such an approach is practical. ...
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... Index-based search tools look up subsequences and their corresponding posting lists in some well-defined data structures. For example, FLASH [1], RAMDB [4], MAP [27] and CAFE [7][8][9][10] have adopted indexing techniques in their search tools. The advantage of index-based search tools over the exhaustive ones is that the pre-built indices can help to speed up the search process. ...
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Indexing and retrieval techniques for homology searching of genomic databases are increasingly important as the search tools are facing great challenges of rapid growth in sequence collection size. Consequently, the indexing and retrieval of possibly gigabytes sequences become expensive. In this paper, we present two new approaches for indexing genomic databases that can enhance the speed of indexing and retrieval. We show experimentally that the proposed methods can be more computationally efficient than the existing ones.
... Transformation based index algorithms are all based on special technique(s), and at the same time, these transformations combine properties of genomic data. 4.1 CAFE CAFE34353637 is a partition based search approach, where a coarse search using an inverted index is used to rank sequences by similarity to a query sequence, and a subsequent fine search is used to locally align only a database subset with the query. In our opinion, this method can be extended to other algorithms. ...
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... In practice, fasta is 6.5 times faster than ssearch and almost as accurate (Brenner, Chothia & Hubbard 1998). In 1996, Williams and Zobel proposed the cafe index-based homology search tool (Williams & Zobel 1996, Williams & Zobel 2002). This scheme uses inverted indexing techniques employed in text retrieval (Witten, Moffat & Bell 1999), which are most well-known now for their use in web search engines. ...
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... To allow for queries that start anywhere within a melody, indexing via n-grams could be useful, where an n-gram is a sequence of n consecutive notes and each such sequence is extracted from the music; similar techniques are used for the related problems of string indexing and genomic indexing [22,23]. With melodic data, however, it is not particularly useful to represent the data as an absolute pitch, since the same melody can be played or sung at different pitches. ...
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To provide keyword-based access to a large text file it is usually necessary to invert the file and create an inverted index that stores, for each word in the file, the paragraph or sentence numbers in which that word occurs. Inverting a large file using traditional techniques may take as much temporary disk space as is occupied by the file itself, and consume a great deal of cpu time. Here we describe an alternative technique for inverting large text files that requires only a nominal amount of temporary disk storage, instead building the inverted index in compressed form in main memory. A program implementing this approach has created a paragraph level index of a 132 Mbyte collection of legal documents using 13 Mbyte of main memory; 500 Kbyte of temporary disk storage; and approximately 45 cpu-minutes on a Sun SPARCstation 2.
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The Portable Dictionary of the Mouse Genome is a database for personal computers that contains information on approximately 10,000 loci in the mouse, along with data on homologs in several other mammalian species, including human, rat, cat, cow, and pig. Key features of the dictionary are its compact size, its network independence, and the ability to convert the entire dictionary to a wide variety of common application programs. Another significant feature is the integration of DNA sequence accession data. Loci in the dictionary can be rapidly resorted by chromosomal position, by type, by human homology, or by gene effect. The dictionary provides an accessible, easily manipulated set of data that has many uses--from a quick review of loci and gene nomenclature to the design of experiments and analysis of results. The Portable Dictionary is available in several formats suitable for conversion to different programs and computer systems. It can be obtained on disk or from Internet Gopher servers (mickey.utmen.edu or anat4.utmen.edu), an anonymous FTP site (nb.utmem.edu in the directory pub/genedict), and a World Wide Web server (http://mickey.utmem.edu/front.html).
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Countable prefix codeword sets are constructed with the universal property that assigning messages in order of decreasing probability to codewords in order of increasing length gives an average code-word length, for any message set with positive entropy, less than a constant times the optimal average codeword length for that source. Some of the sets also have the asymptotically optimal property that the ratio of average codeword length to entropy approaches one uniformly as entropy increases. An application is the construction of a uniformly universal sequence of codes for countable memoryless sources, in which the n th code has a ratio of average codeword length to source rate bounded by a function of n for all sources with positive rate; the bound is less than two for n = 0 and approaches one as n increases.
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There are several advantages to be gained by storing the lexicon of a full text database in main memory. In this paper we describe how to use a compressed inverted file index to search such a lexicon for entries that match a pattern or partially specified term. Our experiments show that this method provides an effective compromise between speed and space, running orders of magnitude faster than brute force search, but requiring less memory than other pattern-matching data structures; indeed, in some cases requiring less memory than would be consumed by a single pointer to each string. The pattern search method is based on text indexing techniques and is a successful adaptation of inverted files to main memory databases. 1 Introduction Given the large main memories available on current computers, it is interesting to ask what additional facilities might be incorporated in full text retrieval systems if memory usage is allowed to expand. One possible application for extra memory is to s...
Issues in searching molecular sequence databases
  • S Altschul
  • M Boguski
  • W Gish
  • J Wootton
  • S. Altschul
  • D Benson
  • D J Lipman
  • J Ostell
  • Genbank
  • D. Benson