It is written in Python. It requires Python 3 in your environment. I am using ORTHOSCOPE* on Linux/Mac. Some modification would be needed on Windows.

ORTHOSCOPE* requires seven dependencies in the tools directory: blastp, makeblastdb, mafft, trimal, pal2nal.pl, APE and Rscript in R with R itself, and Notung.jar. For Mac analyses, some newly downloaded softwares may be need to set "Open Anyway" in Security & Privacy, System preferences.

blastp, makeblastdb: BLAST+
Available here: https://ftp.ncbi.nlm.nih.gov/blast/executables/blast+/LATEST/.
Download the appropriate file for your PC. ncbi-blast-x.xx.x+-x64-macosx.tar.gz for Mac users. Copy blastp and makeblastdb files into the tools directory. Then change the permissions.

$ cp DOWNLODED_DIR/bin/blastp tools
$ cp DOWNLODED_DIR/bin/makeblastdb tools

blastp and makeblastdb should be the same version.

mafft: MAFFT v7.475
Available here: https://mafft.cbrc.jp/alignment/software/.
After compilation, copy mafft to the tools directory.

$ which mafft
/usr/local/bin/mafft
$ cp /usr/local/bin/mafft tools

trimal: TRIMAL v1.4.1:
Available here: https://github.com/inab/trimal/releases/tag/v1.4.1.
cd to trimAl/source, and type make.

$ make
$ cp trimal tools

pal2nal.pl: pal2nal.v14
Available here: http://www.bork.embl.de/pal2nal/#Download.

$ cp pal2nal.pl tools

APE, Rscript, APE, R: R
R(4.0.1) is available from here.
APE can be installed from the R console as follows:

> install.packages("ape")

By installing R, Rscript will be installed automatically. After installation, copy Rscript into the tools directory.

$ which Rscript
$ cp /usr/local/bin/Rscript tools

MacOS Big Sur does not show the address with "which Rscript." Instead, try the following script from the R console:

> R.home()
[1] "/Library/Frameworks/R.framework/Resources"

Then you can make sure the Rscript from your Terminal application (on Mac, Applications > Utilities):

$ cd /Library/Frameworks/R.framework/
$ ls
R
Rscript ....

 

Notung.jar: NOTUNG 2.9
Available here: http://amberjack.compbio.cs.cmu.edu/Notung/download29.html.
Download Notung-2.9.x.x.zip file. Modify the file name and copy Notung-2.9.jar into the tools directory. JAVA is neede to run Notung.

$ cp Notung-2.9.jar tools/Notung.jar

 

The downloaded file contains teleost data with the taxon sampling employed in Satoh et al. (2009).

Mode E: Estimating gene trees and orthogroups.

Type:

python3 orthoscope_star.py ENSORLT00000003136.1

Multiple analyses can be tested as follows:

sh command.sh

For genome wide analyses using multiple query sequences, use supercomputer with job schedulers. A script to generate job scripts can be found in below ("Analysis using job schedulers" section).

Mode S: Summarizing results.

This mode uses result files derived from of Mode E analyses. Mode E analyses saves result files in the outdir directory for each query. This mode can be employed on your PC by using the result directory downloaded from the supercomputer.

python3 orthoscope_star.py list_geneIDs.txt

Then, a summary is saved in the results.csv file.

Mode D: Drawing gene trees.
Draw gene trees by using a result derived from the model E analysis. Please make sure >Mode is set as D in the control.txt

python3 orthoscope_star.py ENSORLT00000003136.1

Double click the ENSORLT00000003136.1.html file, you can check estimated gene trees on your web browser:

Version difference between blastp and makeblastdb

[inouejunmp:ORTHOSCOPE_STAR-main]$ ./orthoscope_star.py ENSORLT00000004629.1

############### ENSORLT00000004629.1 ################

##### SpeciesTree draw ######

##### 1st tree: BLAST ######

BLAST Database error: Error: Not a valid version 4 database.
BLAST Database error: Error: Not a valid version 4 database.
......

Use the same version for blastp and makeblastdb.

ORTHOSCOPE* can be conducted by array job systems.

SGE

Split the list_geneIDs.txt file into several files (each file contains 20 gene IDs).

$ -l 100 -a 3 -d list_geneIDs_Oryzias_latipes.txt --numeric-suffixes=1 --additional-suffix=.txt list_geneIDs-

Make a new directory, list_geneIDs_split, and move list_geneIDs-00* files to this new directory.

$ mkdir list_geneIDs_split
$ mv list_geneIDs-00* list_geneIDs_split

Then qsub the following job file.

#$ -S /bin/bash
#$ -cwd
#$ -t 1-7
#$ -tc 7
#$ -l s_vmem=32G
#$ -l mem_req=32G
#$ -N an_array_job

echo running on `hostname`
echo starting at
date
echo -e ""
#echo SGE_TASK_ID $SGE_TASK_ID
#SGE_TASK_ID=`expr $SGE_TASK_ID - 1`
echo SGE_TASK_ID $SGE_TASK_ID

PADDING_N=$(printf "%03d" ${SGE_TASK_ID})
echo PADDING_N $PADDING_N

for gene in `cat ./list_geneIDs_split/list_geneIDs-${PADDING_N}.txt`
do
echo ########### $gene ###########
python3 /home/jun-inoue/ORTHOSCOPE_STAR-main/orthoscope_star_v1.1.7.py ${gene}
done

echo -e ""
echo ending at
date

For a test run, qsub the following batch file.

#!/bin/bash

#$ -cwd
#$ -V
#$ -l short
#$ -l d_rt=00:10:00
#$ -l s_rt=00:10:00
#$ -l s_vmem=16G
#$ -l mem_req=16G
#$ -N an_batchJob
#$ -S /bin/bash

python3 /home/jun-inoue/ORTHOSCOPE_STAR-main/orthoscope_star_v1.1.7.py ENSORLT00000004629.1

Slurm

The downloaded example file contains 910_run_scheduler.py. This Python script produces files for array jobs on a job scheduler, slurm.

1. To make query files (containing query gene IDs) and a job file for slurm jobs, type:

python3 910_run_scheduler.py

Query files: 910_list*.txt
Job file: 920_arrayJob.slurm

2. Then run slurm jobs:

sbatch 920_arrayJob.slurm

ORTHOSCOPE* employs a genome-scale protein-coding gene database (coding and amino acid sequences: gene models) for each species. To count numbers of orthologs in each species, only the longest sequence should be used when transcript variants exist for single locus. Such gene models can be downloaded from the ORTHOSCOPE website:

Data used in Inoue (2022)

# Case Study 1 (Fig. 4A, 9 teleosts)
database_SHN.tar.gz (154 MB).
Control.file

# Case Study 2 (Fig. 4B, 15 teleosts)
Control.file

# Case Study 3 (Fig. 5, 49 metazoans)
Control.file