An iterative and automated computational pipeline for untargeted strain-level identification using MS/MS spectra from pathogenic samples

Mathias Kuhring; Joerg Doellinger; Andreas Nitsche; Thilo Muth; Bernhard Y. Renard

The copyright holder for this preprint (which was not peer-reviewed) is the author/funder. . https://doi.org/10.1101/812313 doi: bioRxiv preprint Figure 1 . Overview of the TaxIt workflow. In up to three stages, MS/MS spectra are searched against a host proteome to pre-filter host proteins (optional), against an untargeted database for global species identification (primary iteration) and against a targeted, species-based and automatically fetched database for strain level identification (secondary iteration). The copyright holder for this preprint (which was not peer-reviewed) is the author/funder. . https://doi.org/10.1101/812313 doi: bioRxiv preprint The copyright holder for this preprint (which was not peer-reviewed) is the author/funder. The copyright holder for this preprint (which was not peer-reviewed) is the author/funder. . https://doi.org/10.1101/812313 doi: bioRxiv preprint RSS, resident set size; TOF, time-of-flight All rights reserved. No reuse allowed without permission.