Lightweight BWT construction for very large string collections
CPM'11 Proceedings of the 22nd annual conference on Combinatorial pattern matching
Localized genome assembly from reads to scaffolds: practical traversal of the paired string graph
WABI'11 Proceedings of the 11th international conference on Algorithms in bioinformatics
Computing the longest common prefix array based on the burrows-wheeler transform
SPIRE'11 Proceedings of the 18th international conference on String processing and information retrieval
Approximate all-pairs suffix/prefix overlaps
Information and Computation
Parallel and memory-efficient reads indexing for genome assembly
PPAM'11 Proceedings of the 9th international conference on Parallel Processing and Applied Mathematics - Volume Part II
Computing the burrows-wheeler transform of a string and its reverse
CPM'12 Proceedings of the 23rd Annual conference on Combinatorial Pattern Matching
Comparing DNA sequence collections by direct comparison of compressed text indexes
WABI'12 Proceedings of the 12th international conference on Algorithms in Bioinformatics
Computing the longest common prefix array based on the Burrows-Wheeler transform
Journal of Discrete Algorithms
Memory efficient minimum substring partitioning
Proceedings of the VLDB Endowment
Lightweight algorithms for constructing and inverting the BWT of string collections
Theoretical Computer Science
Computing the Burrows-Wheeler transform of a string and its reverse in parallel
Journal of Discrete Algorithms
Hi-index | 3.84 |
Motivation: Sequence assembly is a difficult problem whose importance has grown again recently as the cost of sequencing has dramatically dropped. Most new sequence assembly software has started by building a de Bruijn graph, avoiding the overlap-based methods used previously because of the computational cost and complexity of these with very large numbers of short reads. Here, we show how to use suffix array-based methods that have formed the basis of recent very fast sequence mapping algorithms to find overlaps and generate assembly string graphs asymptotically faster than previously described algorithms. Results: Standard overlap assembly methods have time complexity O(N2), where N is the sum of the lengths of the reads. We use the Ferragina–Manzini index (FM-index) derived from the Burrows–Wheeler transform to find overlaps of length at least τ among a set of reads. As well as an approach that finds all overlaps then implements transitive reduction to produce a string graph, we show how to output directly only the irreducible overlaps, significantly shrinking memory requirements and reducing compute time to O(N), independent of depth. Overlap-based assembly methods naturally handle mixed length read sets, including capillary reads or long reads promised by the third generation sequencing technologies. The algorithms we present here pave the way for overlap-based assembly approaches to be developed that scale to whole vertebrate genome de novo assembly. Contact: js18@sanger.ac.uk