RiboDetector

RiboDetector is designed to rapidly and accurately detect rRNA sequences from metagenomic, metatranscriptomic, and ncRNA sequencing data. It has been optimized for use with both CPUs and GPUs. It outperforms existing software by delivering 10-50x faster runtime and ~10x fewer false classifications.

53
mentions
4
contributors

What RiboDetector can do for you

RiboDetector is a novel software based on a Bi-directional Long Short-Term Memory (BiLSTM) neural network, which rapidly and accurately identifies rRNA reads from transcriptomic, metagenomic, metatranscriptomic, noncoding RNA, and ribosome profiling sequence data. Compared with state-of-the-art approaches, RiboDetector produced at least six times fewer misclassifications on the benchmark datasets. Importantly, the few false positives of RiboDetector were not enriched in certain Gene Ontology (GO) terms, suggesting a low bias for downstream functional profiling. RiboDetector also demonstrated a remarkable generalizability for detecting novel rRNA sequences that are divergent from the training data with sequence identities of <90%. On a personal computer, RiboDetector processed 40M reads in less than 6 min, which was ∼50 times faster in GPU mode and ∼15 times in CPU mode than other methods. RiboDetector is available under a GPL v3.0 license at https://github.com/hzi-bifo/RiboDetector.

Logo of RiboDetector
Keywords
Programming language
  • Python 100%
License
  • GPL-3.0-only
</>Source code
Packages
anaconda.org
pypi.org
hub.docker.com

Participating organisations

Helmholtz Centre for Infection Research

Reference papers

Mentions

Contributors

ZD
Zhi-Luo Deng
Department for Computational Biology of Infection Research, Helmholtz Center for Infection Research, Braunschweig, Germany
PM
Philipp C Muench
Department for Computational Biology of Infection Research, Helmholtz Center for Infection Research, Braunschweig, Germany
RM
Rene Mreches
Department for Computational Biology of Infection Research, Helmholtz Center for Infection Research, Braunschweig, Germany
AM
Alice C McHardy
Department for Computational Biology of Infection Research, Helmholtz Center for Infection Research, Braunschweig, Germany