TY - GEN T1 - Pipasic: similarity and expression correction for strain-level identification and quantification in metaproteomics AU - Penzlin, Anke AU - Lindner, Martin S. AU - Döllinger, Jörg AU - Dabrowski, Piotr Wojtek AU - Nitsche, Andreas AU - Renard, Bernhard Y. AB - Motivation: Metaproteomic analysis allows studying the interplay of organisms or functional groups and has become increasingly popular also for diagnostic purposes. However, difficulties arise owing to the high sequence similarity between related organisms. Further, the state of conservation of proteins between species can be correlated with their expression level, which can lead to significant bias in results and interpretation. These challenges are similar but not identical to the challenges arising in the analysis of metagenomic samples and require specific solutions. Results: We introduce Pipasic (peptide intensity-weighted proteome abundance similarity correction) as a tool that corrects identification and spectral counting-based quantification results using peptide similarity estimation and expression level weighting within a non-negative lasso framework. Pipasic has distinct advantages over approaches only regarding unique peptides or aggregating results to the lowest common ancestor, as demonstrated on examples of viral diagnostics and an acid mine drainage dataset. KW - Algorithms KW - Mass Spectrometry KW - Software KW - Peptides/chemistry KW - Bacterial Proteins/metabolism KW - Environmental Microbiology KW - Cowpox virus/classification KW - Proteome/chemistry KW - Proteome/metabolism KW - Proteomics/methods KW - 610 Medizin PY - 2014 LA - eng PB - Robert Koch-Institut, Biologische Sicherheit VL - 30 IS - 12 DO - 10.1093/bioinformatics/btu267 ER -