We present COBS, a compact bit-sliced signature index, which is a cross-over between an inverted index and Bloom filters. Our target application is to index @math -mers of DNA samples or @math -grams from text documents and process approximate pattern matching queries on the corpus with a user-chosen coverage threshold. Query results may contain a number of false positives which decreases exponentially with the query length and the false positive rate of the index determined at construction time. We compare COBS to seven other index software packages on 100 000 microbial DNA samples. COBS' compact but simple data structure outperforms the other indexes in construction time and query performance with Mantis by on second place. However, different from Mantis and other previous work, COBS does not need the complete index in RAM and is thus designed to scale to larger document sets.
Considering @math -grams or @math -mers of a sequence are a staple in bioinformatics @cite_28 . For example, BLAST @cite_10 uses @math -mers for seeding its search for maximal local alignments.
@cite_28 @cite_10
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The analysis of biological sequencing data has been one of the biggest applications of string algorithms. The approaches used in many such applications are based on the analysis of k-mers, which are short fixed-length strings present in a dataset. While these approaches are rather diverse, storing and querying k-mer sets has emerged as a shared underlying component. Sets of k-mers have unique features and applications that, over the last ten years, have resulted in many specialized approaches for their representation. In this survey, we give a unified presentation and comparison of the data structures that have been proposed to store and query k-mer sets. We hope this survey will not only serve as a resource for researchers in the field but also make the area more accessible to outsiders A new approach to rapid sequence comparison, basic local alignment search tool (BLAST), directly approximates alignments that optimize a measure of local similarity, the maximal segment pair (MSP) score. Recent mathematical results on the stochastic properties of MSP scores allow an analysis of the performance of this method as well as the statistical significance of alignments it generates. The basic algorithm is simple and robust; it can be implemented in a number of ways and applied in a variety of contexts including straight-forward DNA and protein sequence database searches, motif searches, gene identification searches, and in the analysis of multiple regions of similarity in long DNA sequences. In addition to its flexibility and tractability to mathematical analysis, BLAST is an order of magnitude faster than existing sequence comparison tools of comparable sensitivity.