External memory BWT and LCP computation for sequence collections with applications

Background Sequencing technologies produce larger and larger collections of biosequences that have to be stored in compressed indices supporting fast search operations. Many compressed indices are based on the Burrows–Wheeler Transform (BWT) and the longest common prefix (LCP) array. Because of the...

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Published in	Algorithms for molecular biology Vol. 14; no. 1; pp. 6 - 15
Main Authors	Egidi, Lavinia, Louza, Felipe A., Manzini, Giovanni, Telles, Guilherme P.
Format	Journal Article
Language	English
Published	London BioMed Central 08.03.2019 BioMed Central Ltd Springer Nature B.V BMC
Subjects	Algorithms All pairs suffix–prefix overlaps Arrays Bioinformatics Biomedical and Life Sciences Burrows-Wheeler transform Cellular and Medical Topics Collection Computation Computational biology Computational Biology/Bioinformatics Computer science Construction Data collection Data structures External memory algorithms Life Sciences Longest common prefix array Maximal repeats Physiological Random access memory Selected papers from WABI 2018 Succinct de Bruijn graph Technology All pairs suffix–prefix overlaps Maximal repeats External memory algorithms Burrows–Wheeler Transform Longest common prefix array Succinct de Bruijn graph
Online Access	Get full text
ISSN	1748-7188 1748-7188
DOI	10.1186/s13015-019-0140-0

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Abstract	Background Sequencing technologies produce larger and larger collections of biosequences that have to be stored in compressed indices supporting fast search operations. Many compressed indices are based on the Burrows–Wheeler Transform (BWT) and the longest common prefix (LCP) array. Because of the sheer size of the input it is important to build these data structures in external memory and time using in the best possible way the available RAM. Results We propose a space-efficient algorithm to compute the BWT and LCP array for a collection of sequences in the external or semi-external memory setting. Our algorithm splits the input collection into subcollections sufficiently small that it can compute their BWT in RAM using an optimal linear time algorithm. Next, it merges the partial BWTs in external or semi-external memory and in the process it also computes the LCP values. Our algorithm can be modified to output two additional arrays that, combined with the BWT and LCP array, provide simple, scan-based, external memory algorithms for three well known problems in bioinformatics: the computation of maximal repeats, the all pairs suffix–prefix overlaps, and the construction of succinct de Bruijn graphs. Conclusions We prove that our algorithm performs O ( n maxlcp ) sequential I/Os, where n is the total length of the collection and maxlcp is the maximum LCP value. The experimental results show that our algorithm is only slightly slower than the state of the art for short sequences but it is up to 40 times faster for longer sequences or when the available RAM is at least equal to the size of the input.
AbstractList	Background Sequencing technologies produce larger and larger collections of biosequences that have to be stored in compressed indices supporting fast search operations. Many compressed indices are based on the Burrows–Wheeler Transform (BWT) and the longest common prefix (LCP) array. Because of the sheer size of the input it is important to build these data structures in external memory and time using in the best possible way the available RAM. Results We propose a space-efficient algorithm to compute the BWT and LCP array for a collection of sequences in the external or semi-external memory setting. Our algorithm splits the input collection into subcollections sufficiently small that it can compute their BWT in RAM using an optimal linear time algorithm. Next, it merges the partial BWTs in external or semi-external memory and in the process it also computes the LCP values. Our algorithm can be modified to output two additional arrays that, combined with the BWT and LCP array, provide simple, scan-based, external memory algorithms for three well known problems in bioinformatics: the computation of maximal repeats, the all pairs suffix–prefix overlaps, and the construction of succinct de Bruijn graphs. Conclusions We prove that our algorithm performs O ( n maxlcp ) sequential I/Os, where n is the total length of the collection and maxlcp is the maximum LCP value. The experimental results show that our algorithm is only slightly slower than the state of the art for short sequences but it is up to 40 times faster for longer sequences or when the available RAM is at least equal to the size of the input. Sequencing technologies produce larger and larger collections of biosequences that have to be stored in compressed indices supporting fast search operations. Many compressed indices are based on the Burrows-Wheeler Transform (BWT) and the longest common prefix (LCP) array. Because of the sheer size of the input it is important to build these data structures in external memory and time using in the best possible way the available RAM. We propose a space-efficient algorithm to compute the BWT and LCP array for a collection of sequences in the external or semi-external memory setting. Our algorithm splits the input collection into subcollections sufficiently small that it can compute their BWT in RAM using an optimal linear time algorithm. Next, it merges the partial BWTs in external or semi-external memory and in the process it also computes the LCP values. Our algorithm can be modified to output two additional arrays that, combined with the BWT and LCP array, provide simple, scan-based, external memory algorithms for three well known problems in bioinformatics: the computation of maximal repeats, the all pairs suffix-prefix overlaps, and the construction of succinct de Bruijn graphs. We prove that our algorithm performs O(nmaxlcp) $${\mathcal {O}}(n\, \mathsf {maxlcp})$$ sequential I/Os, where n is the total length of the collection and maxlcp $$\mathsf {maxlcp}$$ is the maximum LCP value. The experimental results show that our algorithm is only slightly slower than the state of the art for short sequences but it is up to 40 times faster for longer sequences or when the available RAM is at least equal to the size of the input. Abstract Background Sequencing technologies produce larger and larger collections of biosequences that have to be stored in compressed indices supporting fast search operations. Many compressed indices are based on the Burrows–Wheeler Transform (BWT) and the longest common prefix (LCP) array. Because of the sheer size of the input it is important to build these data structures in external memory and time using in the best possible way the available RAM. Results We propose a space-efficient algorithm to compute the BWT and LCP array for a collection of sequences in the external or semi-external memory setting. Our algorithm splits the input collection into subcollections sufficiently small that it can compute their BWT in RAM using an optimal linear time algorithm. Next, it merges the partial BWTs in external or semi-external memory and in the process it also computes the LCP values. Our algorithm can be modified to output two additional arrays that, combined with the BWT and LCP array, provide simple, scan-based, external memory algorithms for three well known problems in bioinformatics: the computation of maximal repeats, the all pairs suffix–prefix overlaps, and the construction of succinct de Bruijn graphs. Conclusions We prove that our algorithm performs $${\mathcal {O}}(n\, \mathsf {maxlcp})$$ O(nmaxlcp) sequential I/Os, where n is the total length of the collection and $$\mathsf {maxlcp}$$ maxlcp is the maximum LCP value. The experimental results show that our algorithm is only slightly slower than the state of the art for short sequences but it is up to 40 times faster for longer sequences or when the available RAM is at least equal to the size of the input. Sequencing technologies produce larger and larger collections of biosequences that have to be stored in compressed indices supporting fast search operations. Many compressed indices are based on the Burrows-Wheeler Transform (BWT) and the longest common prefix (LCP) array. Because of the sheer size of the input it is important to build these data structures in external memory and time using in the best possible way the available RAM. We propose a space-efficient algorithm to compute the BWT and LCP array for a collection of sequences in the external or semi-external memory setting. Our algorithm splits the input collection into subcollections sufficiently small that it can compute their BWT in RAM using an optimal linear time algorithm. Next, it merges the partial BWTs in external or semi-external memory and in the process it also computes the LCP values. Our algorithm can be modified to output two additional arrays that, combined with the BWT and LCP array, provide simple, scan-based, external memory algorithms for three well known problems in bioinformatics: the computation of maximal repeats, the all pairs suffix-prefix overlaps, and the construction of succinct de Bruijn graphs. We prove that our algorithm performs sequential I/Os, where is the total length of the collection and is the maximum LCP value. The experimental results show that our algorithm is only slightly slower than the state of the art for short sequences but it is up to 40 times faster for longer sequences or when the available RAM is at least equal to the size of the input. Background Sequencing technologies produce larger and larger collections of biosequences that have to be stored in compressed indices supporting fast search operations. Many compressed indices are based on the Burrows-Wheeler Transform (BWT) and the longest common prefix (LCP) array. Because of the sheer size of the input it is important to build these data structures in external memory and time using in the best possible way the available RAM. Results We propose a space-efficient algorithm to compute the BWT and LCP array for a collection of sequences in the external or semi-external memory setting. Our algorithm splits the input collection into subcollections sufficiently small that it can compute their BWT in RAM using an optimal linear time algorithm. Next, it merges the partial BWTs in external or semi-external memory and in the process it also computes the LCP values. Our algorithm can be modified to output two additional arrays that, combined with the BWT and LCP array, provide simple, scan-based, external memory algorithms for three well known problems in bioinformatics: the computation of maximal repeats, the all pairs suffix-prefix overlaps, and the construction of succinct de Bruijn graphs. Conclusions We prove that our algorithm performs O(nmaxlcp) $${\mathcal {O}}(n\, \mathsf {maxlcp})$$ sequential I/Os, where n is the total length of the collection and maxlcp $$\mathsf {maxlcp}$$ is the maximum LCP value. The experimental results show that our algorithm is only slightly slower than the state of the art for short sequences but it is up to 40 times faster for longer sequences or when the available RAM is at least equal to the size of the input. Keywords: Burrows-Wheeler Transform, Longest common prefix array, Maximal repeats, All pairs suffix-prefix overlaps, Succinct de Bruijn graph, External memory algorithms Sequencing technologies produce larger and larger collections of biosequences that have to be stored in compressed indices supporting fast search operations. Many compressed indices are based on the Burrows-Wheeler Transform (BWT) and the longest common prefix (LCP) array. Because of the sheer size of the input it is important to build these data structures in external memory and time using in the best possible way the available RAM.BACKGROUNDSequencing technologies produce larger and larger collections of biosequences that have to be stored in compressed indices supporting fast search operations. Many compressed indices are based on the Burrows-Wheeler Transform (BWT) and the longest common prefix (LCP) array. Because of the sheer size of the input it is important to build these data structures in external memory and time using in the best possible way the available RAM.We propose a space-efficient algorithm to compute the BWT and LCP array for a collection of sequences in the external or semi-external memory setting. Our algorithm splits the input collection into subcollections sufficiently small that it can compute their BWT in RAM using an optimal linear time algorithm. Next, it merges the partial BWTs in external or semi-external memory and in the process it also computes the LCP values. Our algorithm can be modified to output two additional arrays that, combined with the BWT and LCP array, provide simple, scan-based, external memory algorithms for three well known problems in bioinformatics: the computation of maximal repeats, the all pairs suffix-prefix overlaps, and the construction of succinct de Bruijn graphs.RESULTSWe propose a space-efficient algorithm to compute the BWT and LCP array for a collection of sequences in the external or semi-external memory setting. Our algorithm splits the input collection into subcollections sufficiently small that it can compute their BWT in RAM using an optimal linear time algorithm. Next, it merges the partial BWTs in external or semi-external memory and in the process it also computes the LCP values. Our algorithm can be modified to output two additional arrays that, combined with the BWT and LCP array, provide simple, scan-based, external memory algorithms for three well known problems in bioinformatics: the computation of maximal repeats, the all pairs suffix-prefix overlaps, and the construction of succinct de Bruijn graphs.We prove that our algorithm performs O ( n maxlcp ) sequential I/Os, where n is the total length of the collection and maxlcp is the maximum LCP value. The experimental results show that our algorithm is only slightly slower than the state of the art for short sequences but it is up to 40 times faster for longer sequences or when the available RAM is at least equal to the size of the input.CONCLUSIONSWe prove that our algorithm performs O ( n maxlcp ) sequential I/Os, where n is the total length of the collection and maxlcp is the maximum LCP value. The experimental results show that our algorithm is only slightly slower than the state of the art for short sequences but it is up to 40 times faster for longer sequences or when the available RAM is at least equal to the size of the input. Background Sequencing technologies produce larger and larger collections of biosequences that have to be stored in compressed indices supporting fast search operations. Many compressed indices are based on the Burrows–Wheeler Transform (BWT) and the longest common prefix (LCP) array. Because of the sheer size of the input it is important to build these data structures in external memory and time using in the best possible way the available RAM. Results We propose a space-efficient algorithm to compute the BWT and LCP array for a collection of sequences in the external or semi-external memory setting. Our algorithm splits the input collection into subcollections sufficiently small that it can compute their BWT in RAM using an optimal linear time algorithm. Next, it merges the partial BWTs in external or semi-external memory and in the process it also computes the LCP values. Our algorithm can be modified to output two additional arrays that, combined with the BWT and LCP array, provide simple, scan-based, external memory algorithms for three well known problems in bioinformatics: the computation of maximal repeats, the all pairs suffix–prefix overlaps, and the construction of succinct de Bruijn graphs. Conclusions We prove that our algorithm performs ${\mathcal {O}}(n\, \mathsf {maxlcp})$ sequential I/Os, where n is the total length of the collection and $\mathsf {maxlcp}$ is the maximum LCP value. The experimental results show that our algorithm is only slightly slower than the state of the art for short sequences but it is up to 40 times faster for longer sequences or when the available RAM is at least equal to the size of the input.
ArticleNumber	6
Audience	Academic
Author	Louza, Felipe A. Manzini, Giovanni Telles, Guilherme P. Egidi, Lavinia
Author_xml	– sequence: 1 givenname: Lavinia surname: Egidi fullname: Egidi, Lavinia organization: DiSIT, University of Eastern Piedmont – sequence: 2 givenname: Felipe A. orcidid: 0000-0003-2931-1470 surname: Louza fullname: Louza, Felipe A. email: louza@usp.br organization: Department of Computing and Mathematics, University of São Paulo – sequence: 3 givenname: Giovanni surname: Manzini fullname: Manzini, Giovanni organization: DiSIT, University of Eastern Piedmont, IIT CNR – sequence: 4 givenname: Guilherme P. surname: Telles fullname: Telles, Guilherme P. organization: Institute of Computing, University of Campinas
BackLink	https://www.ncbi.nlm.nih.gov/pubmed/30899322$$D View this record in MEDLINE/PubMed
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Keywords	All pairs suffix–prefix overlaps Maximal repeats External memory algorithms Burrows–Wheeler Transform Longest common prefix array Succinct de Bruijn graph
Language	English
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PublicationTitle	Algorithms for molecular biology
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Snippet	Background Sequencing technologies produce larger and larger collections of biosequences that have to be stored in compressed indices supporting fast search... Sequencing technologies produce larger and larger collections of biosequences that have to be stored in compressed indices supporting fast search operations.... Background Sequencing technologies produce larger and larger collections of biosequences that have to be stored in compressed indices supporting fast search... Abstract Background Sequencing technologies produce larger and larger collections of biosequences that have to be stored in compressed indices supporting fast...
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SubjectTerms	Algorithms All pairs suffix–prefix overlaps Arrays Bioinformatics Biomedical and Life Sciences Burrows-Wheeler transform Cellular and Medical Topics Collection Computation Computational biology Computational Biology/Bioinformatics Computer science Construction Data collection Data structures External memory algorithms Life Sciences Longest common prefix array Maximal repeats Physiological Random access memory Selected papers from WABI 2018 Succinct de Bruijn graph Technology
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Title	External memory BWT and LCP computation for sequence collections with applications
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