Sign in
BioinformaticsiScience
Peer-reviewed journal article

Raptor: A fast and space-efficient pre-filter for querying very large collections of nucleotide sequences

Enrico SeileriD, Svenja Mehringer, Mitra DarvishiD, Etienne Turc, Knut ReinertiD

Abstract

We present Raptor, a tool for approximately searching many queries in large collections of nucleotide sequences. In comparison with similar tools like Mantis and COBS, Raptor is 12-144 times faster and uses up to 30 times less memory. Raptor uses winnowing minimizers to define a set of representative k-mers, an extension of the Interleaved Bloom Filters (IBF) as a set membership data structure, and probabilistic thresholding for minimizers. Our approach allows compression and a partitioning of the IBF to enable the effective use of secondary memory.

PDFDOI

02 /Specification & Classification

Click any tag to browse matching papers
Citations
18
FWCI
0.62
Field percentile
top 31%

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISPandey '18Martayan '26Robidou '22Levallois '26Robidou '21Conchon-Ker '26
70% semantic matchBioinformatics
Prashant Pandey, Fatemeh Almodaresi, Michael A. Bender+3 more·Cell Systems·Jun 21, 2018· 96 citations