revolutionhtl 1.0.13

REvolutionH-tl: Reconstruction of Evolutionary Histories tool

Bioinformatics tool for the reconstruction of evolutionary histories. Input: fasta files or sequence alignment hits, Output: orthology. event-labeled gene trees, and reconciliations.

Bioinformatics & complex networks lab

• José Antonio Ramírez-Rafael [[e-mail]]
• Maribel Hernandez-Rosales [[e-mail] ]

Install

pip install revolutionhtl

Requirements

Python >=3.7

If you want to run sequence alignments using revolutionhtl, then install Diamond.

Usage

Go to the wiki for details and an example.

python -m revolutionhtl <arguments>

Below are described the steps of the program, as well as the arguments to specify input files.

Steps

1. Orthogroup & best hit selection. Input: alignment hits (generate this using revolutionhtl.diamond) .
2. Orthology and gene tree reconstruction. Input: best hits (generate this at step 1).
3. Species tree reconstruction. Input: gene trees (generate this at step 2).
4. Tree reconciliation. Input: gene and species trees (generate this at steps 2 and 3).

Arguments

Input data (Click to expand)

- -h --help
show this help message and exit

-steps [integers]
List of steps to run (default: 1 2 3 4).

-alignment_h --alignment_hits [string]
Directory containing alignment hits, the input of step 1. (default: ./).

-best_h --best_hits [string]
.tsv file containing best hits, the input of step 2. (default: use output of step 1).

-T --gene_trees [string]
.tsv file containing gene trees, the input of steps 3 and 4. (default: use output of step 2).

-S --species_tree [string]
.nhx file containing a species tree, an input of step 4. (default: use output of step 3).

File names (Click to expand)

-o --output_prefix [string]
Prefix used for output files (default "tl_project").

-og --orthogroup_column [string]
Column in -best_h -T, and output files specifying orthogroups (default: OG).

-Nm --N_max [integer]
Indicates the maximum number of genes in a orthogroup, bigger orthogroups are splitted. If 0, no orthogroup is splitted. (default= 2000).

-k --k_size_partition [integer]
Integer indicatng how many best hit graphs will be processed in bunch:: first graphs with

Algorithm parameters (Click to expand)

-bh_heuristic --besthit_heuristic [string]
Indicates how to normalize bit-score in step 1 (default: normal). Normal: no normalization, prt: use proteinortho auxiliary files, smallest: use length of the smallest sequence, target: use target sequence, query: use query sequence, directed: x->y hit, bidirectional: use x->y and y->x hits.
Options: normal, prt, smallest_bidirectional, smallest_directed, query_directed, target_directed, alignment_directed, query_bidirectional, target_bidirectional, alignment_bidirectional

-f --f_value [float]
Real number between 0 and 1, a parameter of step 1. Defines the adaptative threshhold as: f\*max_bit_score (default: 0.95).

-bmg_h --bmg_heuristic [string]
Comunity detection method, an heuristic of step 2. (default: Louvain).
Options: Mincut, BPMF, Karger, Greedy, Gradient_Walk, Louvain, Louvain_Obj

-bmgh_nb --bmgh_no_binary [bool]
Flag, specifies if force binary tree in step 2. (no flag: force binary, flag: do not force binary).

-stree_h --species_tree_heuristic [string]
Comunity detection method, an heuristic of step 3. (default: louvain_weight).
Options: naive, louvain, mincut, louvain_weight

-streeh_repeats --stree_heuristic_repeats [integer]
integer, specifies how many times run the heuristic of step 3. (default: 3)

-streeh_b --streeh_binary [bool]
Flag, specifies if force binary tree in step 3. (no flag: do not force binary, flag: force binary).

-streeh_ndb --streeh_no_doble_build [bool]
Flag, specifies if run build algorithm twice to obtain less resolved tree in step 3. (no flag: double build, flag: single build).