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 Tools annual

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 Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

Adequate read filtering is critical when processing high-throughput data inmarker-gene-based studies. Sequencing errors can cause the mis-clustering ofotherwise similar reads, artificially increasing the number of retrievedOperational Taxonomic Units (OTUs) and therefore leading to the overestimationof microbial diversity. Sequencing errors will also result in OTUs that are notaccurate reconstructions of the original biological sequences. Herein wepresent a novel and sensitive sequence filtering algorithm that minimizes bothproblems by calculating the exact error-probability distribution of a sequencefrom its quality scores. In order to validate our method, we quality-filteredthirty-seven publicly available datasets obtained by sequencing mock andenvironmental microbial communities with the Roche 454, Illumina MiSeq andIonTorrent PGM platforms, and compared our results to those obtained withprevious approaches such as the ones included in mothur, QIIME and UPARSE. Ouralgorithm retained substantially more reads than its predecessors, whileresulting in fewer and more accurate OTUs. This improved sensitiveness producedmore faithful representations, both quantitatively and qualitatively, of thetrue microbial diversity present in the studied samples. Furthermore, themethod introduced in this work is computationally inexpensive and can bereadily applied in conjunction with any existent analysis pipeline.

A read-filtering algorithm for high-throughput marker-gene studies that greatly improves OTU accuracy