Requirements and installation

1. miniconda - Follow instruction on https://docs.conda.io/projects/miniconda/en/latest/

   make sure you have the conda version >= 23.7.3, for instance

     conda activate base
     conda install conda=23.7.3 -y
   

2. clone the repository:

     git clone https://github.com/EnvGen/phyloBOTL
   

Installation option 1 - step by step, in case you already have some programs installed or databases downloaded

Make sure you are using the same version as indicated hereafter:

Conda R_env:

     cd phyloBOTL
     conda env create -f conda_envs/R_env.yaml -y
     conda activate R_env
     Rscript --vanilla support/Install_Rpackages.R <numberofcpus>

Snakemake (https://snakemake.readthedocs.io/en/stable/getting_started/installation.html):

     conda create -n phylobotl_env -c bioconda snakemake=7.25.0 Python=3.11.4 -y
     conda activate phylobotl_env
     conda config --set channel_priority strict

Genomad and genomad_db (https://portal.nersc.gov/genomad/index.html)

      conda create -n genomad_env -c conda-forge -c bioconda genomad=1.6.1 -y
      conda activate genomad_env
      mkdir -p <directory_DB_path>/genomad_env/data
      genomad download-database <directory_DB_path>/genomad_env/data
      conda deactivate

EGGNOG: emapper.py and EGGNOG database (https://github.com/eggnogdb/eggnog-mapper/wiki/eggNOG-mapper-v2.1.5-to-v2.1.12#user-content-v2112)

      conda create -n eggnog_mapper_env -c bioconda -c conda-forge eggnog-mapper=2.0.1 -y
      conda activate eggnog_mapper_env
      mkdir -p <directory_DB_path>/eggnog_mapper_env/data
      download_eggnog_data.py --data_dir <directory_DB_path>/eggnog_mapper_env/data -y
      conda deactivate

Installation option 2 - all in one go, in case you want to install/download all the required programs and databases from scratch.

  cd phyloBOTL
  bash install_key_envs.sh <directory_DB_path> <cpus>

<directory_DB_path> a directory where you want to download the databases. number of cpus to download R packages when creating the R_env

Optional

if you want to use gtdb or kSNP4 to build the phylogenetic tree

A. gtdbtk - source: https://ecogenomics.github.io/GTDBTk/installing/index.html#installing - conda: https://ecogenomics.github.io/GTDBTk/installing/bioconda.html

conda create -n gtdb_env -c conda-forge -c bioconda gtdbtk=2.1.1 -y
conda activate gtdb_env
download-db.sh
# Set the environment variable to the directory containing the GTDB-Tk reference data
conda env config vars set GTDBTK_DATA_PATH="/path/to/unarchived/gtdbtk/data"

B. kSNP4 - source: https://sourceforge.net/projects/ksnp/files/latest/download - manual: https://sourceforge.net/projects/ksnp/files/kSNP4.1%20User%20Guide.pdf/download

Usage

Modify config file:

  nano support/config_phylobotl.yaml

  workdir: /abs/path/to/phyloBOTL

  threads: 24  # CPUs
  memory_per_cpu: 4571

  input:
  File_list: GENOME_LIST.txt #csv file <sample name>,<abs/path/to/contig.fasta[.gz]>,<group label>,<special_group_name>
  group_1_label: C #your selection
  group_1_name: Clinical #your selection
  group_2_label: E #your selection
  group_2_name: Environmental #your selection
  Special_group_name: None # your selection or "None". For instance "Baltic Sea"

  tree_file: rooted_boot.treefile # tree file name. If you already have a tree, set the path to it here and the pipeline won't build the tree
  tree_using: iqtree

  iqtree:
  iqtree_params: "-m GTR+I+G -B 1000 -bnni"
  iqtree_rooted: "TRUE" # "TRUE" or "FALSE"
  FastTree_params: "-gtr -nt -gamma"

  GTDB:
  gtdb_params: "--bacteria"
  taxa_filter: p__Proteobacteria
  outgroup_taxon: p__Firmicutes

  KSNP:
  kSNP4_param_phylo_method: ML # Maximum Likelihood
  kSNP4_param_genome_fraction: core
  Path_to_kSNP4pkg: /abs/path/to/kSNP4pkg

  Prokka_params: "--rawproduct --quiet"
  Proteome_dir: proteome # Directory containing the protein files <sample name>.faa. If not exiting, it will be generated

  orthology:
  orthofinder_parameters: "-f proteome -a 4 -S diamond -og"  #double check that name in -f <Proteom_dir> corresponds to "Proteome_dir" above
  ortholog_count_table: Orthogroups.GeneCount.tsv
  ortholog_table: Orthogroups.tsv
  path_to_orthologs_sequences: Orthologues/Results_dir/Orthogroup_Sequences  # If you provide a full path to existing "ortholog_count_table","ortholog_table" and "path_to_orthologs_sequences" files, the pipeline won't run orthofinder

  up_to_Eggnog_all_orthologs: False #Set to True if you want to perform only the EggNOG annotation of orthologs groups. Phyloglm and synteny_visualization won't be executed.
  Eggnog_all_orthologs_selection: longest # Options : "longest", "random". criterium for selection one sequences from the groups of orthologs group, either the longest sequence or one randomly selected.
  path_to_eggnog_db: /mnt/isilon/projects/ecosystem_biology/01_Infectome/phyloBOTL/DATABASES/eggnog_mapper_env/data # abs path to eggnog database directory.

  PHYLOGLM:
  phyloglm_Bootnumber: 0 # phyloglm parameter, number of independent bootstrap replicates, 0 means no bootstrap.
  p_adj_value_cutoff: 0.05
  orthologue_ratio_in_genome_dataset: 0.95 #In this case if the orthologue is present/absent in 95% of the genomes, it won't be considered in the analysis.
  phyloglm_btol_number: 10 #phyloglm parameter, (logistic regression only) bound on the linear predictor to bound the searching space.
  phyloglm_outfiles_prefix: Vv # your selection

  synteny_visualization:
  present_in_at_least_n_genomes: 10 #parameter used when creating the Graph, representing the weigth cutoff to be included in graph
  locus_size_window: 40000  # bps, window used when looking for enriched orthologs locilised in the region
  max_n_genomes_per_fig: 22  #22 representative genomes will be included in the .pdf figure
  tax_specific_protein_annotation: #if you want to annotated Enriched and depleted orthologs using a specific database. For instance UniRef90 Vibrionacea
  status: false
  path_to_database: /abs/path/to/Your_Specific_database.fasta

  genomad:
  include: false #Set to True in you want to predict plasmid and Virus on genomes using genomad
  path_to_genomad_db: /abs/path/to/genomad_db/ #abs path to genomad database directory
  Genomad_score_cut_off: 0.8 #Minimum score to classify a contig as plasmid (or Virus)
  params_genomad: "--cleanup --conservative" #genomad parameters. The flag --enable-score-calibration will work if there are more than 1000 sequences in the fasta file (in a genome file)
  output_dir: Results # Output directory name

and save CTRL+x, y

Run:

Option 1:

Using a laptop or one node on a HPC.

	conda activate phylobotl_env
  		snakemake -s phylobotl.smk --use-conda --conda-frontend conda --cores <numberofcpus>

Option 2:

If you want to run the pipeline using several nodes in a HPC:

	a. Download cookiecutter:

	conda create -n cookiecutter_env -c conda-forge cookiecutter -y
	conda activate  cookiecutter_env

	b. Create the profile directory and answer the questions:

	profile_dir="/abs/path/to/phyloBOTL/.config/snakemake"
	mkdir -p "$profile_dir"
	template="gh:Snakemake-Profiles/slurm"
	cookiecutter --output-dir "$profile_dir" "$template"
	conda deactivate

	c. Run the pipeline:

		conda activate phylobotl_env
		snakemake --profile .config/snakemake/<your_selection> -s phylobotl.smk --use-conda --conda-frontend conda

Output files

├── Genomes   -- Folder with all the genomes that will be used
│   ├── <isolate1>.fa -- expample of genome name file

├── Annotations
│   ├── GBK_files -- Prokka output gbk files for each genome
│   ├── GFF_files -- Prokka output gff files for each genome
│   ├── Orthologues/orthologues_gff.tsv -- gff file format of orthologs present in genomes
│   └── Rep_seq_Orth_groups -- Folder with representative sequence (randomly selected or the longest) eggNOG annotation for each Ortholog group

├── Genes
│   ├── <isolate1>.ffn -- Gene sequences, Prokka output

├── Orthologues
│   └── Results_dir -- Orthofinder output directory
├── Pangenome_graph -- Pangenome output directory
│   ├── pangenome.h5
│   ├── MSA -- Folder with the core msa file.

├── phyloglm_input -- intermediare file used as input for phyloBOTL.R, generated bu the pipeline.
│   ├── Annotations.txt
│   └── Orthogroups.tsv
├── Prokka_out -- Rest of proka output files

├── proteome -- folder with proteins sequences for each genome
│   ├── <isolate1>.faa

├── GENOMAD -- folder with GENOMAD output for each genome
│   ├── Genomad_output_<isolate1>

├── Trees -- Output directory from phylogenetic tree software used (e.g, IQTREE)
│   ├── IQ_TREE.bionj


In <output_dir>: -- Output result directory based on user-defined groups
	├── Annotations
	│   ├── Depleted_eggNOG
	│   ├── Depleted_GBK_files
	│   ├── Depleted_KEGG
	│   ├── Depleted_KEGG_core
	│   ├── Depleted_Loci -- co-localization depleted orthologs EggNOG/KEGG annotation folder
	│   ├── Enriched_eggNOG
	│   ├── Enriched_GBK_files
	│   ├── Enriched_KEGG
	│   ├── Enriched_KEGG_core
	│   ├── Loci -- co-localization Enriched orthologs EggNOG/KEGG annotation folder
	│   ├── Specific_db
	│   ├── Vv_Candidates_depleted_orthologues.tsv
	│   ├── Vv_Candidates_enriched_orthologues.tsv
	│   ├── Vv_core_depleted_orthologues.tsv
	│   ├── Vv_core_enriched_orthologues.tsv
	│   ├── Vv_depleted_core_orthologues_annotation.tsv
	│   ├── Vv_Depleted_orthologues_annotation.tsv
	│   ├── Vv_Enriched_core_orthologues_annotation.tsv
	│   └── Vv_Enriched_orthologues_annotation.tsv
	├── co_localization_figures -- Enriched orthologues
	├── co_localization_figures_Depleted -- Depleted orthologues
	├── Depleted_Orthologues_DNA_sequences
	│   ├──<OrthologD1>.fna
	├── Enriched_Orthologues_DNA_sequences
	│   ├──<OrthologE1>.fna
	├── Unsupervise -- Several unsupervised machine learning methods output directory based on enriched and depleted orthologues
	├── Unsupervise_core -- Several unsupervised machine learning methods output directory based on core enriched and depleted orthologues
	├── Visualization
	│   ├── Vv_Tree_with_core_orthologues_fan_branch.length.pdf
	│   ├── Vv_Tree_with_depleted_core_orthologues_fan_branch.length.pdf
	│   ├── Vv_Tree_with_enriched_core_orthologues_fan_branch.length.pdf
	│   └── Vv_Tree_with_Selected_orthologues_fan_branch.length.pdf
	├── Vv_Depleted_core.txt -- List of core Depleted orthologues
	├── Vv_Depleted.txt -- List of Depleted orthologues
	├── Vv_Enriched_core.txt -- List of core Enriched orthologues
	└── Vv_Enriched.txt -- List of Enriched orthologues