README.md

ViPhy

Virus phylogeny system.

Preprocessing process

Translates a nucleotide sequences(DNA) into a sequence of proteins.

The steps in the script are the following:

1. Opens and reads settings.json

2. Downloads the genbank genomes especified in the Json file from NCBI

3. If the analysis_type indicated in the Json file is 'nucleotide':

3.1. Navigate into input files directory until there are no more files to read.

3.1.1. When it finds a fasta file, it checks if the file contains a nucleotide sequence. If not, then returns to the step 3.1..

3.1.2. When it finds a genbank file, it extracts the nucleotide sequence from the file.

3.1.3. Translates the nucleotide sequence into a protein sequence.

3.1.4. Stores the combined protein sequence in a new fasta file

4. If the analysis_type indicated in the Json file is 'protein':

4.1. Navigates into the input files directory until there are no more files to read.

4.1.1. When it finds a fasta file, it checks if the file contains a nucleotide sequence. If so, stores the sequence into a new fasta file.

4.1.2. When it finds a genbank file, it extracts the protein sequence from the file.

4.1.2.1. Stores the combined protein sequence in a new fasta file

Sequence alignment

During this phase, a database formed by the combination of multiple fasta files will be created and it will be stored in the folder named dbFolder.

Then, the sequences will be compared with each other in order to find regions of similarity between an input sequence and the database, in a matter of seconds. More specifically, the program will use Blastp, a version of Blast that compares two protein sequences.

Finally, the distance between them will be also calculated and saved in a distance matrix. This matrix will be saved in the Outputs folder following the phylip format.

Phylogenetic trees

Once the distance matrix has been obtained, the code will generate a phylogenetic tree using the newick format and it will be stored in the Outputs folder.

After this, if the user wishes it, bootstrap will be used to create sub-samples from which the parameters of the model are estimated repeated times.

At the end, a consensus tree will be created with all the samples obtained and stored in the Outputs folder.

Viphy_env.yml

Conda environment created using Phyton38 that contains a specific collection of conda packages installed to ensure the smooth running of the program.

To create the environment from viphy-env.yml file:

$ conda env create -f viphy-env.yml

To activate the viphy-env.yml environment:

$ conda activate viphy-env

To deactivate the conda environment:

$ conda deactivate

Dependencies

• Python 3.8.3
• Biopython 1.78

Settings.json

This file contains important information for the correct operation of the code. Please, don't change this file path!

Structure of the JSON file:

{

"user_email": "[email protected]",

"input_folder" : "genome_data",

"genome_accessions": [["GQ919031.1", "JX182370.1"], ["NC_015464"], ["NC_042011.1"]],

"output_folder" : "results",

"working_folder" : "tmp",

"analysis_type": "nucleotide",

"e_value": 0.0001

"distance_function": "d6",

"replicates": 100,

"cutoff": 0.7,

"majority_or_support_tree": "both",

"get_original_newick_tree": "True",

"get_original_distance_matrix": "True",

"get_bootstrap_distance_matrix": "True"

}

Details of the JSON file:

• "user_email": Email that will be used to identify the user in NCBI
• "analysis_type": Can be "nucleotide" or "protein"
• "input_folder": Folder where you can find the fasta or genbank files that the program will read
• "working_folder": Path for the directory in which all the other files are located
• "output_folder": Folder in which the outgoing files will be located.
• "genome_accessions": List of lists that contains the identifier of the files you want to download from Genbank database.
• "e_value": Number of expected hits of similar score that could be found just by chance
• "distance_function": Type of function that will be used to calculate the distance between two sequences. It should be "d0", "d4" or "d6"
• "replicates": Number of bootstrap samples
• "majority_or_support_tree": Way to calculate a consensus tree. It can be "majority", "support" or "both"
• "cutoff": Threshold used when "majority" consensus tree is selected. It should be a number between 0 and 1.
• "get_original_newick_tree": Indicates using a boolean if you want to get the original newick tree
• "get_original_distance_matrix": Indicates using a boolean if you want to get the original distance matrix in phylip format
• "get_bootstrap_distance_matrix": Indicates using a boolean if you want to get each one of the possible distance matrix for each bootstrap sample

Other files

• Fasta files: Inside Inputs folder. Documents that contain a nucleotide or amino acid sequence that the program will read. If the content is a nucleotide sequence, it will be translates into proteins.

• Genbank files: Inside Inputs folder. Documents where you can obtain a nucleotide or amino acid sequence, together with other relevant information.

• DataBase files: Inside dbFolder folder. Database files that will appear in this folder once you have created a database.

• DataBase.fasta: File that will formed by the combination of all the files stored in the WorkingFolder folder after the preprocessing process.

• Original_tree.nwk: Inside Outputs. File that contains the original phylogenetic tree, in other words, the phylogenetic tree before using bootstrap.

• Support_consensus_tree.nwk: Inside Outputs. File that contains the final consensus phylogenetic tree in newick format with branches support.

• Majority_consensus_tree.nwk: Inside Outputs. File that contains the final consensus phylogenetic tree in newick format following the majority rule.

• Original distance matrix.txt: Inside Outputs folder. This file contains the distance matrix calculated before using bootstrap using the phylip format.

• Bootstrap_distance_matrix.txt: Inside Ouputs folder. File which contains a distance matrix for each sub-sample created using bootstrap. It follows the phylip format. All will be stored in the same file.

• get_accessions_list.py: Inside src folder. File written in Python that can be used to calculate an accession list from a csv file.

• csv_configuration_file.json: Inside src folder. File with the appropriate settings that get_accessions_list.py will need to work correctly. You must add the input file name and the column you want to read. Please, remember that the fist column won't be 1, but 0.

• accessions_list.txt: Output obtained after running get_accessions_list.py. Remember to add a comma after when you add it into settings.json file.

Folders

• src: Folder that contains code files. The file __init__.py includes the main function.

• Inputs: Folder to store the set of files that the program will read.

• WorkingFolder: Folder to store the resulting sequences after the translation ends.

• Outputs: Folder that stores the final results.

• dbFolder: Folder where the database will be stored after its creation.