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@ARTICLE{Liebhoff:255490,
      author       = {Liebhoff, Anna-Maria and Menden, Kevin and Laschtowitz,
                      Alena and Franke, Andre and Schramm, Christoph and Bonn,
                      Stefan},
      title        = {{P}athogen detection in {RNA}-seq data with {P}athonoia.},
      journal      = {BMC bioinformatics},
      volume       = {24},
      number       = {1},
      issn         = {1471-2105},
      address      = {Heidelberg},
      publisher    = {Springer},
      reportid     = {DZNE-2023-00291},
      pages        = {53},
      year         = {2023},
      note         = {CC BY},
      abstract     = {Bacterial and viral infections may cause or exacerbate
                      various human diseases and to detect microbes in tissue, one
                      method of choice is RNA sequencing. The detection of
                      specific microbes using RNA sequencing offers good
                      sensitivity and specificity, but untargeted approaches
                      suffer from high false positive rates and a lack of
                      sensitivity for lowly abundant organisms.We introduce
                      Pathonoia, an algorithm that detects viruses and bacteria in
                      RNA sequencing data with high precision and recall.
                      Pathonoia first applies an established k-mer based method
                      for species identification and then aggregates this evidence
                      over all reads in a sample. In addition, we provide an
                      easy-to-use analysis framework that highlights potential
                      microbe-host interactions by correlating the microbial to
                      the host gene expression. Pathonoia outperforms
                      state-of-the-art methods in microbial detection specificity,
                      both on in silico and real datasets.Two case studies in
                      human liver and brain show how Pathonoia can support novel
                      hypotheses on microbial infection exacerbating disease. The
                      Python package for Pathonoia sample analysis and a guided
                      analysis Jupyter notebook for bulk RNAseq datasets are
                      available on GitHub.},
      keywords     = {Humans / RNA-Seq / Algorithms / Sequence Analysis, RNA:
                      methods / Base Sequence / Bacteria: genetics / Metagenomics:
                      methods / High-Throughput Nucleotide Sequencing: methods /
                      Metagenomics (Other) / Pathogen detection (Other) / RNA
                      sequencing (Other)},
      cin          = {AG Heutink},
      ddc          = {610},
      cid          = {I:(DE-2719)1210002},
      pnm          = {354 - Disease Prevention and Healthy Aging (POF4-354)},
      pid          = {G:(DE-HGF)POF4-354},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:36803415},
      pmc          = {pmc:PMC9938591},
      doi          = {10.1186/s12859-023-05144-z},
      url          = {https://pub.dzne.de/record/255490},
}