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Updated: Feb 9, 2026

A Virtual Machine Platform for Non-Computer Professionals for Using Deep Learning to Classify Biological Sequences of Metagenomic Data
Published on: September 25, 2021
LiveKraken--real-time metagenomic classification of illumina data
Simon H Tausch1,2, Benjamin Strauch1, Andreas Andrusch1,2
1Bioinformatics Unit (MF1).
Motivation:
In metagenomics, Kraken is one of the most widely used tools due to its robustness and speed. Yet, the overall turnaround time of metagenomic analysis is hampered by the sequential paradigm of wet and dry lab. In urgent experiments, it can be crucial to gain a timely insight into a dataset.
Results:
Here, we present LiveKraken, a real-time read classification tool based on the core algorithm of Kraken. LiveKraken uses streams of raw data from Illumina sequencers to classify reads taxonomically. This way, we are able to produce results identical to those of Kraken the moment the sequencer finishes. We are furthermore able to provide comparable results in early stages of a sequencing run, allowing saving up to a week of sequencing time on an Illumina HiSeq in High Throughput Mode. While the number of classified reads grows over time, false classifications appear in negligible numbers and proportions of identified taxa are only affected to a minor extent.
Availability And Implementation:
LiveKraken is available at https://gitlab.com/rki_bioinformatics/LiveKraken.
Supplementary Information:
Supplementary data are available at Bioinformatics online.
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