FluClass: A novel algorithm and approach to score and visualize the phylogeny of the influenza virus using mass spectrometry

• We develop an algorithm to classify of influenza virus from mass spectral (MS) data.
• A novel method for scoring MS data against nodes of phylogenetic trees is described.
• Influenza viruses are correctly classified to seasonal and regional strains.

A novel computer algorithm FluClass has been developed to facilitate the phylogenetic classification of influenza virus using mass spectral data. FluClass accepts a DNA or protein-based phylogenetic tree as input and generates theoretical peptide mass lists for each node. An experimental mass spectrum from an influenza virus protein digest is then placed onto the phylogenetic tree using a novel random resampling function (Z-score) that allows the scoring of spectrum against both internal and leaf nodes. Testing of the algorithm using hemagglutinin protein sequences from human-host influenza viruses showed that the Z-score performs comparably to the Profound scoring method for the scoring of leaf nodes and is substantially better at scoring internal nodes. Scoring of internal nodes allows colorizations of nodes of the phylogenetic tree enabling the classification of the query spectrum to be rapidly visualized. Finally we demonstrate the utility of FluClass on experimental spectra from six strains. Given that mass spectrometry data can be generated rapidly for influenza virus proteins, FluClass provides a fast and direct method for phylogenetic analysis of influenza proteins.

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