Sequence-based detection of emerging antigenically novel influenza A viruses

The detection of evolutionary transitions in influenza A (H3N2) viruses' antigenicity is a major obstacle to effective vaccine design and development. In this study, we describe NIAViD, an unsupervised machine learning tool, adept at identifying these transitions, using HA1 sequence and associated physicochemical properties. NIAViD, performed with 88.9% (95% CI, 56.5%–98.0%) and 72.7% (95% CI,43.4%– 90.3%) sensitivity in training and validation respectively, outperforming the uncalibrated null model – 33.3% (95% CI,12.1%–64.6%) and does not require the need for potentially biased, time-consuming and costly laboratory assays. The pivotal role of Boman’s index, indicative of the virus’s cell surface binding potential, is underscored, enhancing the precision of detecting antigenic transitions. NIAViD's efficacy is not only in identifying influenza isolates that belong to novel antigenic clusters, but also in pinpointing potential sites driving significant antigenic changes, without the rel..., , , # Sequence-based detection of emerging antigenically novel influenza A viruses

[https://doi.org/10.5061/dryad.pnvx0k6vb](https://doi.org/10.5061/dryad.pnvx0k6vb)

####  Description of the data and file structure

The data for this study includes dependencies (in R), environments (in R), and scripts (in Python) needed to reproduce the results. Finally, a Python implementation of our NIAViD pipeline and associated physicochemical properties (**sequence_physioproperties_data.csv**) including hydrophobicity, charge, boman, instability, and isoelectric point are provided.

#### Sharing/Access information

Links to other publicly accessible locations of the data:

* [https://doi.org/10.1126/science.1097211](https://doi.org/10.1126/science.1097211)
* [https://doi.org/10.1093/bioinformatics/bty457 ](https://doi.org/10.1093/bioinformatics/bty457)

Data was derived from the following sources:

D. J. Smith, et al., Mapping the Antigenic and Genetic Evolution of Influenza Virus. *Science* 305, 371...