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• W3131575902 abstract "Abstract Background Specialized data structures are required for online algorithms to efficiently handle large sequencing datasets. The counting quotient filter (CQF), a compact hashtable, can efficiently store k-mers with a skewed distribution. Result Here, we present the mixed-counters quotient filter (MQF) as a new variant of the CQF with novel counting and labeling systems. The new counting system adapts to a wider range of data distributions for increased space efficiency and is faster than the CQF for insertions and queries in most of the tested scenarios. A buffered version of the MQF can offload storage to disk, trading speed of insertions and queries for a significant memory reduction. The labeling system provides a flexible framework for assigning labels to member items while maintaining good data locality and a concise memory representation. These labels serve as a minimal perfect hash function but are ~ tenfold faster than BBhash, with no need to re-analyze the original data for further insertions or deletions. Conclusions The MQF is a flexible and efficient data structure that extends our ability to work with high throughput sequencing data." @default.
• W3131575902 created "2021-03-01" @default.
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• W3131575902 date "2021-02-16" @default.
• W3131575902 modified "2023-10-17" @default.
• W3131575902 title "MQF and buffered MQF: quotient filters for efficient storage of k-mers with their counts and metadata" @default.
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• W3131575902 doi "https://doi.org/10.1186/s12859-021-03996-x" @default.
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