Candidate markers are found by building new classifiers that take as input a small subset of the influenza proteome. The input sets that lead to classifiers that match

the accuracy of the original classifier (which uses the entire proteome as input) highlight the amino acid markers that are important for class discrimination. An see more iterative procedure is used. For the initial step all single amino acid positions are found that separate the two classes (human/avian or high/low mortality rate). The iterative step n identifies the n sized (potentially non-contiguous sequence) combinations that separate the data such that each combination does not contain a smaller sized combination that separates the two classes equally well. This procedure yields a set of non-redundant mutation patterns that separate the two classes. The iterative procedure is important so that a candidate marker is Rabusertib manufacturer only included as part of a distinguishing pattern when it adds to the classification accuracy. So for example if position 21 in the PB2 protein distinguishes avian and human strains, then position 21 would not be included as part of another set of features (say position 22 in the PB2 protein). Only markers that contribute significantly selleck to classification accuracy are included in the final result. Details on selecting candidate functional markers are given

in the Methods section. Host specificity markers Sixteen positions in the influenza genome were found to be associated

Adenosine triphosphate with human host specificity. The markers were found on the non-structural protein 1 (NS1), non-structural protein 2 (NS2), matrix protein 1 (MP1), nucleoprotein (NP), acidic protein (PA) and the basic polymerase 2 (PB2) protein. Each strain was assigned a genotype, which showed whether the human consensus amino acid variant was present at each of the 16 positions. Strains excluded from the marker estimation process, human infections of avian origin [15] and non-human non-avian strains, were checked for evidence of an enrichment of human specificity markers relative to the remaining avian strains. With one exception the human infections of avian origin showed a genotype that was distinct from the most common avian genotype background but the number of accumulated human markers was small. Figure 1 shows the relative frequency of different host specificity genotypes among the sequenced samples with minimum 1% frequency for the three host categories: avian, human infections of avian origin and all other non-human non-avian host types. Redundant sequences that occur within the same region and year are collapsed to prevent over weighting heavily sequenced outbreaks. Columns in the table show each genotype configuration with the last row (Rank) reporting the rank of the genotype’s relative frequency in avian strains.