At present, some people have posted articles about the analysis process of WGD. I searched for the keyword "wgd pipeline" and found the following:

GenoDup: https:// github.com/MaoYafei/GenoDup-Pipeline
https://peerj.com/articles/6303/
WGDdetector: https:// github.com/yongzhiyang2 012/WGDdetector
https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-019-2670-3
wgd: https:// github.com/arzwa/wgd
https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-016-1142-2#Sec1
https://bmcbiol.biomedcentral.com/articles/10.1186/s12915-017-0399-x
GeNoGAP https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-016-1142-2
https://bmcbiol.biomedcentral.com/articles/10.1186/s12915-017-0399-x
https://github.com/dfguan/purge_dups
https://www.biorxiv.org/content/10.1101/2020.01.24.917997v1

This article introduces the usage of wgd.

Wgd cannot be installed directly with bioconda at present, so it is a little troublesome to install, because it depends on a lot of software. wgd depends on the following software

BLAST
MCL
MUSCLE/MAFFT/PRANK
PAML
PhyML/FastTree
i-ADHoRe

But the good news is that most of the software it depends on can be installed with bioconda

conda create -n wgd python=3.5 blast mcl muscle mafft prank paml fasttree cmake libpng mpi=1.0=mpich
conda activate wgd

Here mpi=1.0=mpich is selected, because i-adhore depends on mpich. If openmpi is installed, an error will appear while loading shared libraries: libmpi_cxx.so.40: cannot open shared object file: No such file or directory

After that, the installation is much simpler

git clone https://github.com/arzwa/wgd.git
cd wgd
pip install .
pip install git+https://github.com/arzwa/wgd.git
For i-ADHoRe, you need to register at http:// bioinformatics.psb.ugent.be /webtools/i-adhore/licensing/Agree to the license to download i-ADHoRe-3.0

Since my miniconda3 installed ~/opt/, the installation path is so~/opt/miniconda3/envs/wgd/

tar -zxvf i-adhore-3.0.01.tar.gz
cd i-adhore-3.0.01
mkdir -p build && cd build
cmake .. -DCMAKE_INSTALL_PREFIX=~/opt/miniconda3/envs/wgd/
make -j 4
make insatall

Take the sugarcane genome Saccharum spontaneum L as an example. The genome is 8-ploid with 32 chromosomes (2n = 4x8 = 32)

Download the tutorial for CDS and GFF annotation files

mkdir -p wgd_tutorial && cd wgd_tutorial
wget http://www.life.illinois.edu/ming/downloads/Spontaneum_genome/Sspon.v20190103.cds.fasta.gz
wget http://www.life.illinois.edu/ming/downloads/Spontaneum_genome/Sspon.v20190103.gff3.gz
gunzip *.gz

First conda activate wgdstart our analysis environment, and then start the analysis

Step 1 : Use to wgd mclidentify homologous genes in the genome

wgd mcl -n 20 --cds --mcl -s Sspon.v20190103.cds.fasta -o Sspon_cds.out

Step 2 : Use to wgd ksdbuild Ks distribution

wgd ksd --n_threads 80 Sspon_cds.out/Sspon.v20190103.cds.fasta.blast.tsv.mcl Sspon.v20190103.cds.fasta

Step 3 : If the quality of the genome is good, then wgd syncollinearity analysis can be used . It can help us find the collinearity block in the genome and the corresponding anchor point

wgd syn --feature gene --gene_attribute ID \
-ks wgd_ksd/Sspon.v20190103.cds.fasta.ks.tsv \
Sspon.v20190103.gff3 Sspon_cds.out/Sspon.v20190103.cds.fasta.blast.tsv.mcl

 For more reading - There are 9 sub-modules in WGD

• kde: KDE fitting to the Ks distribution
• ksd: Ks distribution construction
• mcl: BLASP comparison of All-vs-ALl + MCL classification analysis.
• mix: Hybrid modeling of Ks distribution.
• pre: preprocess the CDS file
• syn: Call I-ADHoRe 3.0 to use GFF files for collinearity analysis
• viz: draw histogram and density plot
• wf1: Ks standard analysis procedure of the whole genome paranome (paranome), call mcl, ksd and syn
• wf2: Ks standard analysis procedure of one-vs-one homologous gene (ortholog), call wcl and kSD

Responsibilities

Lead teams of scientists in structuring, prototyping, and executing large-scale bioinformatic and other analysis.
Develop novel bioinformatics, statistical, data processing, pathway, data mining and other algorithms to identify biological signals and their clinical correlates in broad kinds of individual and population data.
Develop novel platform-level analytical tools for sequence-based assays (assembly, annotation, variant calling and interpretation, phasing, genome structure, etc.), expression assays (RNAseq and microarray), proteomics, and metabolomics.
Develop statistical models that robustly correlate complex laboratory-derived information with phenotypic and clinical information.
Create scientifically rigorous visualizations, communications, and presentations of results.

Reference @ https://www.google.com/about/careers/search#!t=jo&jid=62095001

Faculty Positions
The Central University of Punjab (CUP), Bathinda will be having the Schools and Departments as given in Table-I. The University invites applications from eligible candidates for the posts of Professors (Pay Band Rs. 37400-67000 with AGP of Rs. 10, 000/-), Associate Professors (Pay Band Rs.37400-67000 with AGP of Rs. 9,000/-) and Assistant Professors (Pay Band Rs.15600-39100 with AGP of Rs. 6,000/-)

POSITION AVAILABLE IN THE AREA OF SPECIALIZTION

3. Bioinformatics,

Procedure to apply: Application forms along with API form complete in all respect along with necessary documents and application fee of Rs. 750/-. (Rs. 250/- for Scheduled Caste/Scheduled Tribe/Person with disabilities) should be sent to:

Registrar (Officiating)
Central University of Punjab
City Campus, Mansa Road
Bathinda-151 001

Application forms from the prospective candidates are accepted upto November 10, 2014.

Based on the qualification of the candidates and the need of the university, the applications received will be processed through appropriately constituted selection committees shortly. Minimum qualification can be relaxed in case of exceptionally outstanding candidate. For further details visit www.cup.ac.in; www.centralunipunjab.com; www.cup.edu.in

The candidate should download the application form available at website www.cup.ac.in;
www.centralunipunjab.com; and submit it complete in all respects on or before 10th November 2014.

Those who have applied earlier need to submit Academic Performance Index (API) form, 5 copies of Summary of the Application Form (available at: www.cup.ac.in; www.centralunipunjab.com and Updated CV if not updated recently (without application fee).

http://cup.edu.in/Faculty_details_and_general_instructions.pdf

http://cup.edu.in/Final%20Application%20and%20summary%20Sheet%20and%20Api%20form.pdf

If you are interested in gene prediction, have a look at GenomeThreader.

http://genometools.org/pub/

Address of the bookmark: http://genometools.org/

Details are available at www.nehu.ac.in and www.bicnehu.ac.in.

Applications must reach the undersigned within 15 days from the date of publication of this advertisement.

Prof. Pramod Tandon. PI/Mr. Devendra Kumar Biswal (Co-PI)

https://ftp.ncbi.nlm.nih.gov/refseq/release/viral/

Address of the bookmark: https://ftp.ncbi.nlm.nih.gov/refseq/release/viral/

Address of the bookmark: http://crossmap.sourceforge.net/

Applicants should hold a PhD or a first class MSc/MTech degree in Bioinformatics of Biotechnology/Life Sciences; experience in using bioinformatics tools, working in Linux and knowledge of computer network administration.

Submit CV and letter of interest by email to: Dr. Dinesh Gupta atdinesh@icgeb.res.in

Address of the bookmark: https://cmdcolin.github.io/awesome-genome-visualization/?latest=true&selected=%23BRIG&tag=Comparative