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REvolutionH-tl: Reconstruction of Evolutionary Histories tool

Project description

REvolutionH-tl logo.

Bioinformatics tool for the reconstruction of evolutionaty histories. Input: best-match data, Output: event labeled gene trees and reconciliations.

Bioinformatics & complex networks lab


REvolutionHtl analyzes putative best matches for the inference of event-labeled gene trees. Moreover, the tool performs tree reconciliation if a species tree is provided.

If you don't have best-match data, you can use proteinortho and revolutionhtl for its generation.

Install

pip install --upgrade revolutionhtl

Dependencies

  • pandas
  • networkx
  • os
  • itertools
  • argparse
  • numpy
  • tqdm

Usage

python -m revolutionhtl [-h] [-steps [STEPS ...]] [-prt_path PRT_PATH]
                        [-gene_trees GENE_TREES]
                        [-species_tree SPECIES_TREE] [-hit_list HIT_LIST]
                        [-og ORTHOGROUP_COLUMN] [-o OUTPUT_PREFIX]
                        [-rod RECON_OUTPUT_DIR] [-f F_VALUE]

Arguments

  • -h, --help show this help message and exit.
  • -steps [STEPS ...] list of steps to run (default: 0 1 2 3).
  • -prt_path PRT_PATH path to a directory containing proteinortho output files.
  • -gene_trees GENE_TREES .tsv file containing a .nhx for each line at column "tree"
  • -species_tree SPECIES_TREE .nhx file containing a species tree.
  • -hit_list HIT_LIST .tsv file containing hits.
  • -og ORTHOGROUP_COLUMN, --orthogroup_column ORTHOGROUP_COLUMN column in -hit_list and -gene_trees specifying orthogroups (default: OG).
  • -o OUTPUT_PREFIX, --output_prefix OUTPUT_PREFIX prefix used for output files (default "tl_project").
  • -rod RECON_OUTPUT_DIR, --recon_output_dir RECON_OUTPUT_DIR directory for reconciliation maps.
  • -f F_VALUE, --f_value F_VALUE number between 0 and 1 used for the adaptative threshhold for best matches selection (default 0.95, see proteinortho paper for a deep explanation).

Pipeline

The methodology consists of 3 main steps, starting with best-hits data and a species tree. You can use proteinortho and step 0 for the generation of input data.

  1. Convert proteinortho output to best-hit list Required arguments: -prt_path Optional arguments: -f
  2. Conver best hits to best match graphs (cBMGs) Required arguments: -hit_list
  3. Conver cBMGs to gene trees Required arguments: -hit_list
  4. Reconciliate gene trees and species tree Required arguments: -gene_trees, -species_tree Optional arguments: -rod

Input data format

-prt_path

A directory containing the output files of proteinortho:

  • .proteinortho.tsv file containing orthogroups (*).
  • proteinortho_cache/ directory containing bidirectional pairwise BLAST-like analysis (hits).

You can generate these files running proteinortho with the flags -keep, and temp=<the directory used for output files (probably ./)>

(*) An orthogroup is a set of co-orthologous genes.

-hit_list

A hit is a relationship $x\rightarrow y$, where $x$ is the query accession and $y$ is the target accession. $x$ and $y$ are genes found in different species. Each hit relationship $x\rightarrow y$ is contained in one orthogroup.

The argument -hit_list is a .tsv file containing the columns:

  • OG Orthogroup identifier.
  • Query_accession Gene identifier.
  • Target_accession Gene identifier.
  • Query_species Species of query gene.
  • Target_species Species of target gene.

-gene_trees

A .tsv file containing the columns:

  • OG Orthogroup identifier.
  • tree Tree in nhxx format (extended-extended-newick, see here a descripton), where leaf names are gene identifiers, the name of inner nodes are evolutionary events (S for speciation, P for duplication), and leafs have the attribute "species".

-species_tree

A .nhxx file containing a single species tree in nhxx format (extended-extended-newick, see here a descripton). The name of the leafs must include the species present in the gene trees attributes.

Example

In the directory test_set are three sets of simmulated genomes (12noD, 3noD, 5noD).

Let's run the analysis for 12 species:

Wi will work in the same directory where the data is stored

$ cd 12noD

Use proteinortho for hits and orthogroups assigment.

$ proteinortho6.pl -project=D12 -temp=./ -keep -singles -p=diamond *fa

Create a directory for storage of reconciliation maps.

$ mkdir recon_maps

Now run revolutionH-tl. Note that we are including the step 0, that takes as input the files generate by proteinortho, and outputs a list of best hits.

$ python -m revolutionhtl -steps 0 1 2 3 -species_tree S12.pruned.tree -rod recon_maps

REvolutionH-tl
Running steps 0, 1, 2, 3

Step 0: Convert proteinortho output to best hit list
----------------------------------------------------
Reading .proteinortho.tsv file and hits directory...
Selecting best hits by dynamic threshold...
Filtering best hits by orthogroup...
Best hits successfully writen to tl_project.best_hits.tsv
This file will be used as input for step 1.

Step 1: Conver best hit graphs to cBMGs
---------------------------------------
Reading hit graphs...
Editing to best match graphs (cBMGs)...
Best match graphs successfully writen to tl_project.cBMGs.tsv
This file will be used as input of step 2.

Step 2: Reconstruct gene trees
------------------------------
Reading best match graphs...
Reconstructing gene trees...
Labeling gene tree nodes with evolutionary events...
Gene trees successfully writen to tl_project.gene_trees.tsv
This file will be used as input of step 3.

Step 3: Reconciliate gene and species trees
-------------------------------------------
Reading trees...
Reconciliating trees...
Resolved gene trees successfully writen to tl_project.resolved_trees.tsv
Reconciliation maps successfully writen at recons/
Indexed species tree successfully writen to tl_project.labeled_species_tree.nhxx

In the case when you alrready have a best-hits list, you can ommit step 0, and use the argument -hit_list.

$ python -m revolutionhtl -hit_list tl_project.best_hits.tsv -species_tree S12.pruned.tree -rod recon_maps

REvolutionH-tl
Running steps 1, 2, 3

Step 1: Conver best hit graphs to cBMGs
---------------------------------------
Reading hit graphs...
Editing to best match graphs (cBMGs)...
Best match graphs successfully writen to tl_project.cBMGs.tsv
This file will be used as input of step 2.

Step 2: Reconstruct gene trees
------------------------------
Reading best match graphs...
Reconstructing gene trees...
Labeling gene tree nodes with evolutionary events...
Gene trees successfully writen to tl_project.gene_trees.tsv
This file will be used as input of step 3.

Step 3: Reconciliate gene and species trees
-------------------------------------------
Reading trees...
Reconciliating trees...
Resolved gene trees successfully writen to tl_project.resolved_trees.tsv
Reconciliation maps successfully writen at recons/
Indexed species tree successfully writen to tl_project.labeled_species_tree.nhxx

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