The Journal of Open Source SoftwareBioinformaticsPeer-reviewed journal article
Back to sequences: find the origin of kmers
Anthony Baire, Pierre MarijoniD, Francesco AndreaceiD, Pierre PeterlongoiD
Abstract
A vast majority of bioinformatics tools dedicated to the treatment of raw sequencing data heavily use the concept of k-mers. This enables us to reduce the data redundancy (and thus the memory pressure), to discard sequencing errors, and to dispose of objects of fixed size that can be manipulated and easily compared to each others. A drawback is that the link between each k-mer and the original set of sequences it belongs to is generally lost. Given the volume of data considered in this context, finding back this association is costly. In this work, we present "back_to_sequences", a simple tool designed to index a set of k-mers of interests, and to stream a set of sequences, extracting those containing at least one of the indexed k-mer. In addition, the number of occurrences of k-mers in the sequences is provided. Our results show that back_to_sequences streams{approx} 200 short read per millisecond, enabling to search k-mers in hundreds of millions of reads in a matter of a few minutes. Availabilitygithub.com/pierrepeterlongo/back_to_sequences
- Citations
- 6
- FWCI
- 0.82
- Field percentile
- top 32%
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