Development of a persistent biological index based on generalized suffix arrays
Applying the Perseus Technique to Index Huge Nucleotide Sequences
The social structure of memory and the use of external representation systems: ped...
| Full text | |
| Author(s): |
Louza, Felipe A.
[1]
;
Telles, Guilherme P.
[2]
;
Hoffmann, Steve
[3, 4]
;
Ciferri, Cristina D. A.
[5]
Total Authors: 4
|
| Affiliation: | [1] Univ Sao Paulo, Dept Comp & Math, Av Bandeirantes 3900, BR-14040901 Ribeirao Preto - Brazil
[2] Univ Estadual Campinas, Inst Comp, Av Albert Einstein 1251, BR-13083852 Campinas, SP - Brazil
[3] Fritz Lipman Inst, Leibniz Inst Aging, Computat Biol, Beutenbergstr 11, D-07745 Jena - Germany
[4] Friedrich Schiller Univ Jena, Beutenbergstr 11, D-07745 Jena - Germany
[5] Univ Sao Paulo, Inst Math & Comp Sci, Av Trabalhador Sao Carlense 400, BR-13560970 Sao Carlos, SP - Brazil
Total Affiliations: 5
|
| Document type: | Journal article |
| Source: | Algorithms for Molecular Biology; v. 12, DEC 7 2017. |
| Web of Science Citations: | 3 |
| 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. (AU) | |
| FAPESP's process: | 11/23904-7 - Processing of OLAP queries extended with image similarity predicates and spatial predicates over non-conventional data warehouses |
| Grantee: | Cristina Dutra de Aguiar |
| Support Opportunities: | Regular Research Grants |
| FAPESP's process: | 17/09105-0 - Suffix sorting and string similarity measures |
| Grantee: | Felipe Alves da Louza |
| Support Opportunities: | Scholarships in Brazil - Post-Doctoral |
| FAPESP's process: | 11/15423-9 - Development of a persistent biological index based on generalized suffix arrays |
| Grantee: | Felipe Alves da Louza |
| Support Opportunities: | Scholarships in Brazil - Master |