Reformatted data analyzed in Alamil et al. (2018)

Reformatted data analyzed in Alamil et al. (2018; Inferring epidemiological links from deep sequencing data: a statistical learning approach for human, animal and plant diseases). The datasets that are provided concern swine influenza virus (reformatted from Murcia et al., 2012), Ebola virus (reformatted from Gire et al., 2014) and wild salsify potyvirus. Two rds files are provided for swine influenza, the first one for the naive chain, the second one for the vaccinated chain. Ebola rds files are compressed into the archive ebolaRDS.zip. rds files can be loaded in the R statistical software with the command "readRDS(filename)", which returns a list. The list contains a "readme" item describing the contents of the list, as well as a "host.table" item providing metadata about host units and a "set.of.sequences" item providing sequencing data formatted in numeric matrices. R codes are also provided to run analyses proposed by Alamil et al. (2018), namely functions.R that contains R functions required for computations, and influenza.R, ebola.R and potyvirus.R where the analyses are implemented for each case study. Murcia PR, Hughes J, Battista P, Lloyd L, Baillie GJ, Ramirez-Gonzalez RH, et al. Evolution of an Eurasian avian-like influenza virus in naive and vaccinated pigs. PLoS Pathogens. 2012;8(5):e1002730. Gire SK, Goba A, Andersen KG, Sealfon RS, Park DJ, Kanneh L, et al. Genomic surveillance elucidates Ebola virus origin and transmission during the 2014 outbreak. Science. 2014;345:1369–137