Generalized enhanced suffix array construction in external memory
Background Suffix arrays, augmented by additional data structures, allow solving efficiently many string processing problems. The external memory construction of the generalized suffix array for a string collection is a fundamental task when the size of the input collection or the data structure exc...
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| Published in | Algorithms for molecular biology Vol. 12; no. 1; pp. 26 - 16 |
|---|---|
| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
| Published |
London
BioMed Central
07.12.2017
BioMed Central Ltd BMC |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1748-7188 1748-7188 |
| DOI | 10.1186/s13015-017-0117-9 |
Cover
| Abstract | Background
Suffix arrays, augmented by additional data structures, allow solving efficiently many string processing problems. The external memory construction of the generalized suffix array for a string collection is a fundamental task when the size of the input collection or the data structure exceeds the available internal memory.
Results
In this article we present and analyze
eGSA
[introduced in CPM (External memory generalized suffix and
LCP
arrays construction. In: Proceedings of CPM. pp 201–10,
2013
)], the first external memory algorithm to construct generalized suffix arrays augmented with the longest common prefix array for a string collection. Our algorithm relies on a combination of buffers, induced sorting and a heap to avoid direct string comparisons. We performed experiments that covered different aspects of our algorithm, including running time, efficiency, external memory access, internal phases and the influence of different optimization strategies. On real datasets of size up to 24 GB and using 2 GB of internal memory,
eGSA
showed a competitive performance when compared to
eSAIS
and
SAscan
, which are efficient algorithms for a single string according to the related literature. We also show the effect of disk caching managed by the operating system on our algorithm.
Conclusions
The proposed algorithm was validated through performance tests using real datasets from different domains, in various combinations, and showed a competitive performance. Our algorithm can also construct the generalized Burrows-Wheeler transform of a string collection with no additional cost except by the output time. |
|---|---|
| AbstractList | Suffix arrays, augmented by additional data structures, allow solving efficiently many string processing problems. The external memory construction of the generalized suffix array for a string collection is a fundamental task when the size of the input collection or the data structure exceeds the available internal memory. In this article we present and analyze eGSA $$\mathsf {eGSA}$$ [introduced in CPM (External memory generalized suffix and LCP $$\mathsf {LCP}$$ arrays construction. In: Proceedings of CPM. pp 201-10, 2013)], the first external memory algorithm to construct generalized suffix arrays augmented with the longest common prefix array for a string collection. Our algorithm relies on a combination of buffers, induced sorting and a heap to avoid direct string comparisons. We performed experiments that covered different aspects of our algorithm, including running time, efficiency, external memory access, internal phases and the influence of different optimization strategies. On real datasets of size up to 24 GB and using 2 GB of internal memory, eGSA $$\mathsf {eGSA}$$ showed a competitive performance when compared to eSAIS $$\mathsf {eSAIS}$$ and SAscan $$\mathsf {SAscan}$$ , which are efficient algorithms for a single string according to the related literature. We also show the effect of disk caching managed by the operating system on our algorithm. The proposed algorithm was validated through performance tests using real datasets from different domains, in various combinations, and showed a competitive performance. Our algorithm can also construct the generalized Burrows-Wheeler transform of a string collection with no additional cost except by the output time. Background Suffix arrays, augmented by additional data structures, allow solving efficiently many string processing problems. The external memory construction of the generalized suffix array for a string collection is a fundamental task when the size of the input collection or the data structure exceeds the available internal memory. Results In this article we present and analyze eGSA $$\mathsf {eGSA}$$ [introduced in CPM (External memory generalized suffix and LCP $$\mathsf {LCP}$$ arrays construction. In: Proceedings of CPM. pp 201-10, 2013)], the first external memory algorithm to construct generalized suffix arrays augmented with the longest common prefix array for a string collection. Our algorithm relies on a combination of buffers, induced sorting and a heap to avoid direct string comparisons. We performed experiments that covered different aspects of our algorithm, including running time, efficiency, external memory access, internal phases and the influence of different optimization strategies. On real datasets of size up to 24 GB and using 2 GB of internal memory, eGSA $$\mathsf {eGSA}$$ showed a competitive performance when compared to eSAIS $$\mathsf {eSAIS}$$ and SAscan $$\mathsf {SAscan}$$ , which are efficient algorithms for a single string according to the related literature. We also show the effect of disk caching managed by the operating system on our algorithm. Conclusions The proposed algorithm was validated through performance tests using real datasets from different domains, in various combinations, and showed a competitive performance. Our algorithm can also construct the generalized Burrows-Wheeler transform of a string collection with no additional cost except by the output time. Keywords: Suffix array, LCP array, Burrows-Wheeler transform, External memory algorithms, String collections Suffix arrays, augmented by additional data structures, allow solving efficiently many string processing problems. The external memory construction of the generalized suffix array for a string collection is a fundamental task when the size of the input collection or the data structure exceeds the available internal memory.BACKGROUNDSuffix arrays, augmented by additional data structures, allow solving efficiently many string processing problems. The external memory construction of the generalized suffix array for a string collection is a fundamental task when the size of the input collection or the data structure exceeds the available internal memory.In this article we present and analyze [Formula: see text] [introduced in CPM (External memory generalized suffix and [Formula: see text] arrays construction. In: Proceedings of CPM. pp 201-10, 2013)], the first external memory algorithm to construct generalized suffix arrays augmented with the longest common prefix array for a string collection. Our algorithm relies on a combination of buffers, induced sorting and a heap to avoid direct string comparisons. We performed experiments that covered different aspects of our algorithm, including running time, efficiency, external memory access, internal phases and the influence of different optimization strategies. On real datasets of size up to 24 GB and using 2 GB of internal memory, [Formula: see text] showed a competitive performance when compared to [Formula: see text] and [Formula: see text], which are efficient algorithms for a single string according to the related literature. We also show the effect of disk caching managed by the operating system on our algorithm.RESULTSIn this article we present and analyze [Formula: see text] [introduced in CPM (External memory generalized suffix and [Formula: see text] arrays construction. In: Proceedings of CPM. pp 201-10, 2013)], the first external memory algorithm to construct generalized suffix arrays augmented with the longest common prefix array for a string collection. Our algorithm relies on a combination of buffers, induced sorting and a heap to avoid direct string comparisons. We performed experiments that covered different aspects of our algorithm, including running time, efficiency, external memory access, internal phases and the influence of different optimization strategies. On real datasets of size up to 24 GB and using 2 GB of internal memory, [Formula: see text] showed a competitive performance when compared to [Formula: see text] and [Formula: see text], which are efficient algorithms for a single string according to the related literature. We also show the effect of disk caching managed by the operating system on our algorithm.The proposed algorithm was validated through performance tests using real datasets from different domains, in various combinations, and showed a competitive performance. Our algorithm can also construct the generalized Burrows-Wheeler transform of a string collection with no additional cost except by the output time.CONCLUSIONSThe proposed algorithm was validated through performance tests using real datasets from different domains, in various combinations, and showed a competitive performance. Our algorithm can also construct the generalized Burrows-Wheeler transform of a string collection with no additional cost except by the output time. Abstract Background Suffix arrays, augmented by additional data structures, allow solving efficiently many string processing problems. The external memory construction of the generalized suffix array for a string collection is a fundamental task when the size of the input collection or the data structure exceeds the available internal memory. Results In this article we present and analyze $$\mathsf {eGSA}$$ eGSA [introduced in CPM (External memory generalized suffix and $$\mathsf {LCP}$$ LCP arrays construction. In: Proceedings of CPM. pp 201–10, 2013)], the first external memory algorithm to construct generalized suffix arrays augmented with the longest common prefix array for a string collection. Our algorithm relies on a combination of buffers, induced sorting and a heap to avoid direct string comparisons. We performed experiments that covered different aspects of our algorithm, including running time, efficiency, external memory access, internal phases and the influence of different optimization strategies. On real datasets of size up to 24 GB and using 2 GB of internal memory, $$\mathsf {eGSA}$$ eGSA showed a competitive performance when compared to $$\mathsf {eSAIS}$$ eSAIS and $$\mathsf {SAscan}$$ SAscan , which are efficient algorithms for a single string according to the related literature. We also show the effect of disk caching managed by the operating system on our algorithm. Conclusions The proposed algorithm was validated through performance tests using real datasets from different domains, in various combinations, and showed a competitive performance. Our algorithm can also construct the generalized Burrows-Wheeler transform of a string collection with no additional cost except by the output time. Suffix arrays, augmented by additional data structures, allow solving efficiently many string processing problems. The external memory construction of the generalized suffix array for a string collection is a fundamental task when the size of the input collection or the data structure exceeds the available internal memory. In this article we present and analyze [Formula: see text] [introduced in CPM (External memory generalized suffix and [Formula: see text] arrays construction. In: Proceedings of CPM. pp 201-10, 2013)], the first external memory algorithm to construct generalized suffix arrays augmented with the longest common prefix array for a string collection. Our algorithm relies on a combination of buffers, induced sorting and a heap to avoid direct string comparisons. We performed experiments that covered different aspects of our algorithm, including running time, efficiency, external memory access, internal phases and the influence of different optimization strategies. On real datasets of size up to 24 GB and using 2 GB of internal memory, [Formula: see text] showed a competitive performance when compared to [Formula: see text] and [Formula: see text], which are efficient algorithms for a single string according to the related literature. We also show the effect of disk caching managed by the operating system on our algorithm. The proposed algorithm was validated through performance tests using real datasets from different domains, in various combinations, and showed a competitive performance. Our algorithm can also construct the generalized Burrows-Wheeler transform of a string collection with no additional cost except by the output time. Background Suffix arrays, augmented by additional data structures, allow solving efficiently many string processing problems. The external memory construction of the generalized suffix array for a string collection is a fundamental task when the size of the input collection or the data structure exceeds the available internal memory. Results In this article we present and analyze eGSA [introduced in CPM (External memory generalized suffix and LCP arrays construction. In: Proceedings of CPM. pp 201–10, 2013 )], the first external memory algorithm to construct generalized suffix arrays augmented with the longest common prefix array for a string collection. Our algorithm relies on a combination of buffers, induced sorting and a heap to avoid direct string comparisons. We performed experiments that covered different aspects of our algorithm, including running time, efficiency, external memory access, internal phases and the influence of different optimization strategies. On real datasets of size up to 24 GB and using 2 GB of internal memory, eGSA showed a competitive performance when compared to eSAIS and SAscan , which are efficient algorithms for a single string according to the related literature. We also show the effect of disk caching managed by the operating system on our algorithm. Conclusions The proposed algorithm was validated through performance tests using real datasets from different domains, in various combinations, and showed a competitive performance. Our algorithm can also construct the generalized Burrows-Wheeler transform of a string collection with no additional cost except by the output time. |
| ArticleNumber | 26 |
| Audience | Academic |
| Author | Louza, Felipe A. Ciferri, Cristina D. A. Hoffmann, Steve Telles, Guilherme P. |
| Author_xml | – sequence: 1 givenname: Felipe A. orcidid: 0000-0003-2931-1470 surname: Louza fullname: Louza, Felipe A. organization: Department of Computing and Mathematics, University of São Paulo – sequence: 2 givenname: Guilherme P. surname: Telles fullname: Telles, Guilherme P. organization: Institute of Computing, University of Campinas – sequence: 3 givenname: Steve surname: Hoffmann fullname: Hoffmann, Steve organization: Computational Biology, Leibniz Institute on Aging - Fritz Lipman Institute and Friedrich Schiller University Jena – sequence: 4 givenname: Cristina D. A. surname: Ciferri fullname: Ciferri, Cristina D. A. email: cdac@icmc.usp.br organization: Institute of Mathematics and Computer Science, University of São Paulo |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/29234460$$D View this record in MEDLINE/PubMed |
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| CitedBy_id | crossref_primary_10_1016_j_tcs_2020_11_041 crossref_primary_10_14778_3407790_3407861 crossref_primary_10_1016_j_procs_2018_07_164 crossref_primary_10_1186_s13015_019_0140_0 crossref_primary_10_1016_j_tcs_2020_11_024 crossref_primary_10_1093_bioinformatics_btae333 crossref_primary_10_1186_s12859_020_03628_w crossref_primary_10_1186_s13015_019_0137_8 crossref_primary_10_1016_j_jksuci_2022_04_015 |
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| Keywords | External memory algorithms Burrows–Wheeler transform LCP array Suffix array String collections |
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Suffix arrays, augmented by additional data structures, allow solving efficiently many string processing problems. The external memory construction... Suffix arrays, augmented by additional data structures, allow solving efficiently many string processing problems. The external memory construction of the... Background Suffix arrays, augmented by additional data structures, allow solving efficiently many string processing problems. The external memory construction... Abstract Background Suffix arrays, augmented by additional data structures, allow solving efficiently many string processing problems. The external memory... |
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| SubjectTerms | Algorithms Bioinformatics Biomedical and Life Sciences Burrows–Wheeler transform Cellular and Medical Topics Computational Biology/Bioinformatics External memory algorithms LCP array Life Sciences Physiological String collections Suffix array |
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| Title | Generalized enhanced suffix array construction in external memory |
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