Space-efficient and exact de bruijn graph representation based on a bloom filter
WABI'12 Proceedings of the 12th international conference on Algorithms in Bioinformatics
Efficient bubble enumeration in directed graphs
SPIRE'12 Proceedings of the 19th international conference on String Processing and Information Retrieval
Discrete Applied Mathematics
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Next generation sequencing (NGS) technologies are being applied to many fields of biology, notably to survey the polymorphism across individuals of a species. However, while single nucleotide polymorphisms (SNPs) are almost routinely identified in model organisms, the detection of SNPs in non model species remains very challenging due to the fact that almost all methods rely on the use of a reference genome. We address here the problem of identifying SNPs without a reference genome. For this, we propose an approach which compares two sets of raw reads. We show that a SNP corresponds to a recognisable pattern in the de Bruijn graph built from the reads, and we propose algorithms to identify these patterns, that we call mouths. We outline the potential of our method on real data. The method is tailored to short reads (typically Illumina), and works well even when the coverage is low where it reports few but highly confident SNPs. Our program, called kisSnp, can be downloaded here: http://alcovna.genouest.org/kissnp/.