English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

K-mer counting is a requisite process for DNA assembly because it speeds upits overall process. The frequency of K-mers is used for estimating theparameters of DNA assembly, error correction, etc. The process also provides alist of district K-mers which assist in searching large databases and reducingthe size of de Bruijn graphs. Nonetheless, K-mer counting is a data andcompute-intensive process. Hence, it is crucial to implement a lightweight datastructure that occupies low memory but does fast processing of K-mers. Weproposed a lightweight K-mer counting technique, called KmerCo that implementsa potent counting Bloom Filter variant, called countBF. KmerCo has two phases:insertion and classification. The insertion phase inserts all K-mers intocountBF and determines distinct K-mers. The classification phase is responsiblefor the classification of distinct K-mers into trustworthy and erroneous K-mersbased on a user-provided threshold value. We also proposed a novel benchmarkperformance metric. We used the Hadoop MapReduce program to determine thefrequency of K-mers. We have conducted rigorous experiments to prove thedominion of KmerCo compared to state-of-the-art K-mer counting techniques. Theexperiments are conducted using DNA sequences of four organisms. The datasetsare pruned to generate four different size datasets. KmerCo is compared withSqueakr, BFCounter, and Jellyfish. KmerCo took the lowest memory, highestnumber of insertions per second, and a positive trustworthy rate as comparedwith the three above-mentioned methods.

KmerCo: A lightweight K-mer counting technique with a tiny memory footprint