An efficient representation for sparse sets
ACM Letters on Programming Languages and Systems (LOPLAS)
Suffix arrays: a new method for on-line string searches
SODA '90 Proceedings of the first annual ACM-SIAM symposium on Discrete algorithms
STOC '00 Proceedings of the thirty-second annual ACM symposium on Theory of computing
Succinct indexable dictionaries with applications to encoding k-ary trees and multisets
SODA '02 Proceedings of the thirteenth annual ACM-SIAM symposium on Discrete algorithms
Succinct Representation of Balanced Parentheses and Static Trees
SIAM Journal on Computing
High-order entropy-compressed text indexes
SODA '03 Proceedings of the fourteenth annual ACM-SIAM symposium on Discrete algorithms
Opportunistic data structures with applications
FOCS '00 Proceedings of the 41st Annual Symposium on Foundations of Computer Science
Succinct static data structures
Succinct static data structures
Dictionary matching and indexing with errors and don't cares
STOC '04 Proceedings of the thirty-sixth annual ACM symposium on Theory of computing
ACM Computing Surveys (CSUR)
Linear pattern matching algorithms
SWAT '73 Proceedings of the 14th Annual Symposium on Switching and Automata Theory (swat 1973)
Succinct Orthogonal Range Search Structures on a Grid with Applications to Text Indexing
WADS '09 Proceedings of the 11th International Symposium on Algorithms and Data Structures
Succinct Text Indexing with Wildcards
SPIRE '09 Proceedings of the 16th International Symposium on String Processing and Information Retrieval
A Compressed Enhanced Suffix Array Supporting Fast String Matching
SPIRE '09 Proceedings of the 16th International Symposium on String Processing and Information Retrieval
Faster entropy-bounded compressed suffix trees
Theoretical Computer Science
High Throughput Short Read Alignment via Bi-directional BWT
BIBM '09 Proceedings of the 2009 IEEE International Conference on Bioinformatics and Biomedicine
Space efficient indexes for string matching with don't cares
ISAAC'07 Proceedings of the 18th international conference on Algorithms and computation
Succinct dictionary matching with no slowdown
CPM'10 Proceedings of the 21st annual conference on Combinatorial pattern matching
Faster compressed dictionary matching
SPIRE'10 Proceedings of the 17th international conference on String processing and information retrieval
Computing matching statistics and maximal exact matches on compressed full-text indexes
SPIRE'10 Proceedings of the 17th international conference on String processing and information retrieval
A succinct index for hypertext
SPIRE'11 Proceedings of the 18th international conference on String processing and information retrieval
Compressed text indexing with wildcards
SPIRE'11 Proceedings of the 18th international conference on String processing and information retrieval
Journal of Discrete Algorithms
Compressed text indexing with wildcards
Journal of Discrete Algorithms
Compressed indexes for text with wildcards
Theoretical Computer Science
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We study the problem of indexing text with wildcard positions, motivated by the challenge of aligning sequencing data to large genomes that contain millions of single nucleotide polymorphisms (SNPs)--positions known to differ between individuals. SNPs modeled as wildcards can lead to more informed and biologically relevant alignments. We improve the space complexity of previous approaches by giving a succinct index requiring (2 + o(1))n log σ + O(n) + O(d log n) + O(k log k) bits for a text of length n over an alphabet of size σ containing d groups of k wildcards. The new index is particularly favourable for larger alphabets and comparable for smaller alphabets, such as DNA. A key to the space reduction is a result we give showing how any compressed suffix array can be supplemented with auxiliary data structures occupying O(n) + O(d log n/d) bits to also support efficient dictionary matching queries. We present a new query algorithm for our wildcard index that greatly reduces the query working space to O(dm + m log n) bits, where m is the length of the query. We note that compared to previous results this reduces the working space by two orders of magnitude when aligning short read data to the Human genome.