Individuals can be identified by a small number of globally distributed, temporally persistent resident phage families
Please see the following jupyter notebooks where much of the time series and machine learning analysis was performed:
phageprint_machine_learning_modeling.ipynb- the purpose of this notebook is to analyze the HB1 time series dataset.
phageprint_machine_learning_modeling_HA.ipynb- this notebook is very similar to the one above but is for the time series analysis of the HA phage family.
In addition to these notebooks, there are three custom python scripts that we wrote to complement the QIIME package:
seqQualityFilters.py- performs sequence quality control
processOtuTable.py- performs additional quality control and denoising of the OTU table
createNetwork.py- creates a network where OTUs are connected to the samples that they are found in with weighted edges based on OTU relative abundance
Lastly, we provide examples of the QIIME scripts used in the document called examples_of_QIIME_commands