<![CDATA[BOL: Related items]]> https://bioinformaticsonline.com/related/30966?offset=240 https://bioinformaticsonline.com/pages/view/35386/list-of-visualization-tools-for-network-biology Mon, 29 Jan 2018 05:12:24 -0600 https://bioinformaticsonline.com/pages/view/35386/list-of-visualization-tools-for-network-biology <![CDATA[List of visualization tools for network biology]]> Network analysis is any structured technique used to mathematically analyze a circuit (a “network” of interconnected components). The Network analysis provides the ability to quantify associations between individuals, which makes it possible to infer details about the network as a whole at the species and/or population level. Few tools published in BMC are listed here https://bmcbioinformatics.biomedcentral.com/articles/sections/networks-analysis.

image

Following are the list of standalone applications for network analysis:

Arena 3D

3D visualization of multi-layer networks

http://www.arena3d.org

Biana

Data integration and network management

http://sbi.imim.es/web/BIANA.php

BioLayout Express 3D 

2D/3D network visualization

http://www.biolayout.org/

BiologicalNetworks 

Efficient integrated multi-level analysis of microarray, sequence, regulatory and other data

http://www.biologicalnetworks.org

BioMiner

Modeling, analyzing and visualizing biochemical pathways and networks

http://www.zbi.uni-saarland.de/chair/projects/BioMiner

Cell Illustrator 

Petri nets for modeling and simulating biological networks

http://www.cellillustrator.com

COPASI

Analysis of biochemical networks and their dynamics

http://www.copasi.org/

Cytoscape 

Network visualization and analysis. Over 200 plugins [60]

http://www.cytoscape.org/

Dizzy

Chemical kinetics stochastic simulation software

http://magnet.systemsbiology.net/software/Dizzy/

DyCoNet

Gephi plugin that can be used to identify dynamic communities in networks

https://github.com/juliemkauffman/DyCoNet

GENeVis 

Network and pathway visualization

http://tinyurl.com/genevis/

GEPHI 

Interactive visualization and exploration for any network and complex system, dynamic and hierarchical graph.

https://gephi.org

Igraph

Collection of network analysis tools with the emphasis on efficiency, portability and ease of use

http://igraph.sourceforge.net

Medusa

Semantic and multi-edged simple networks

https://sites.google.com/site/medusa3visualization/

NAViGaTOR

Visualizing and analyzing protein-protein interaction networks

http://tinyurl.com/navigator1/

N-Browse

Interactive graphical browser for biological networks

http://www.gnetbrowse.org/

NeAT

Topological and clustering analysis of networks

http://rsat.ulb.ac.be/neat/

Ondex 

Data integration and visualization of large networks

http://www.ondex.org/

Osprey

Visualization and annotation of biological networks

http://biodata.mshri.on.ca/osprey/servlet/Index

Pajek 

Analysis and visualization of large networks and social network analysis

http://vlado.fmf.uni-lj.si/pub/networks/pajek/

PathwayAssist 

Navigation and analysis of biological pathways, gene regulation networks and protein interaction maps.

http://www.ariadnegenomics.com/downloads/

PIVOT 

Layout algorithms for visualizing protein interactions and families

http://acgt.cs.tau.ac.il/pivot/

ProCope 

Prediction and evaluation of protein complexes from purification data experiments

http://www.bio.ifi.lmu.de/Complexes/ProCope/

ProViz 

Visualization and exploration of interaction networks. Gene Ontology and PSI-MI formats supported

http://cbi.labri.fr/eng/proviz.htm

SpectralNET 

Network analysis and visualizations. Scatter plots and dimensionality reduction algorithms

https://www.broadinstitute.org/software/spectralnet

Tulip 

Enables the development of algorithms, visual encodings, interaction techniques, data models and domain-specific visualizations

http://tulip.labri.fr/TulipDrupal/

VANESA 

Automatic reconstruction and analysis of biological networks and Petri nets based on life-science database information

http://agbi.techfak.uni-bielefeld.de/vanesa/

VANTED 

Network reconstruction, data visualization, integration of various data types, network simulation

http://tinyurl.com/vanted/

yEd

Creation of diagrams manually and import external data

http://tinyurl.com/yEdGraph/

Web tools for network analysis

APID 

Unified protein-protein interactions from BIND, BioGRID, DIP, HPRD, IntAct and MINT

http://bioinfow.dep.usal.es/apid/

Arcadia 

Translates text-based descriptions of biological networks (SBML files) into standardized diagrams (Systems Biology Graphical Notation Process Description maps)

http://arcadiapathways.sourceforge.net/

AVIS 

Viewer for signaling networks

http://actin.pharm.mssm.edu/AVIS2

bioPIXIE 

Discovery of biological networks from diverse functional genomic data

http://pixie.princeton.edu/pixie

CellPublisher

Interactive representations of biochemical processes

http://cellpublisher.gobics.de/

Graphle

Distributed network exploration and visualization of interactive large, dense graphs

http://tinyurl.com/graphle/

GraphWeb 

Web server for graph-based analysis of biological networks

http://biit.cs.ut.ee/graphweb/

Hubba

Web-based service to explore the essential nodes in a network

http://hub.iis.sinica.edu.tw/Hubba

NetworkBLAST 

Analysis of protein interaction networks across species to infer protein complexes that are conserved in evolution

http://www.cs.tau.ac.il/~bnet/networkblast.htm

Pathview 

Tool set for pathway-based data integration and visualization

http://Pathview.r-forge.r-project.org/

PINA 

Integrated platform for protein interaction network construction, filtering, analysis, visualization and management

http://cbg.garvan.unsw.edu.au/pina/home.do

ReMatch 

Web-based tool for integration of user-given stoichiometric metabolic models into a database collected from public data sources

http://www.cs.helsinki.fi/group/sysfys/software/rematch/

SNOW 

Gene mapping on a reference or human protein-protein interaction network that SNOW hosts

http://snow.bioinfo.cipf.es

STITCH 

Resource to explore known and predicted interactions of chemicals and proteins

http://stitch.embl.de/

STRING

Protein interaction networks and integration of data such as genomic context, high-throughput experiments, conserved coexpression and previous knowledge derived from the literature

http://string-db.org

TVNViewer 

An interactive visualization tool for exploring networks that change over time or space

http://www.sailing.cs.cmu.edu/main/?page_id=545

tYNA 

System for managing, comparing and mining multiple networks

http://tyna.gersteinlab.org/tyna/

VisANT 

Visualization, mining, analysis and modeling of biological networks, metabolic networks and ecosystems

http://visant.bu.edu/

 

]]> Jit https://bioinformaticsonline.com/opportunity/view/14899/post-doc-positions-at-the-institute-of-evolution-university-of-haifa-haifa-israel Thu, 04 Sep 2014 03:59:38 -0500 <![CDATA[Post-Doc Positions at the Institute of Evolution, University of Haifa, Haifa, Israel]]> We are looking for independent, motivated, diligent, laborious, dedicated Bioinformaticians as post-doctorate fellows for a project aimed at revealing the mechanisms of cancer-resistance and anti-cancer activity of the hypoxia-tolerant subterranean, blind mole-rat, Spalax along its underground evolutionary adaptations. Our project has captured the interest of the scientific community and we have ample financial support for the studies. Generous fellowships ($30K to $40K according to qualifications and performance) are available, immediately, for Post-Docs experts in bioinformatics with a background of good understanding biological questions. That is that can independently handle raw output data of RNA-seq / miR seq/ Genomic, analyze it and can interpret intelligently the relevant biological background. Outstanding candidates for PhD experienced in Bioinformatics will also be considered. Familiarity with cancer research is an advantage. Experience of writing manuscripts for publication and a publication record in relevant journals are expected. English skills both oral and written are required. American, Western-European or Israeli education is a significant benefit.

Our present objectives is to identify and isolate the substances secreted by Spalax cells, resolve with which components they interact that are active only on cancer cells, in order to unravel the biological mechanisms and pathways that evolved in Spalax cell machinery and ultimately lead to the death of cancer-cells. The study could attest to be a breakthrough in cancer research, using the long lived, hypoxia- and cancer-tolerant Spalax as a significant biological resource for biomedical research that hopefully could open new horizons in treatment and prevention of cancer in humans.

Contact: The applications should be submitted, together with extended CV and bibliography, summary of past accomplishments, and contact information of 3 referees, to Prof of Research Aaron Avivi (aaron@research.haifa.ac.il) AND Dr. Imad Shams (imadshams@gmail.com). (http://bit.ly/1lywShk) aaron@research.haifa.ac.il

More at http://evolution.haifa.ac.il/index.php/29-people/personal-websites/77-personal-site-avivi

]]> https://bioinformaticsonline.com/bookmarks/view/36583/eugi-a-novel-resource-for-studying-genomic-islands-to-facilitate-horizontal-gene-transfer-detection-in-eukaryotes Sat, 12 May 2018 07:26:59 -0500 https://bioinformaticsonline.com/bookmarks/view/36583/eugi-a-novel-resource-for-studying-genomic-islands-to-facilitate-horizontal-gene-transfer-detection-in-eukaryotes <![CDATA[EuGI: a novel resource for studying genomic islands to facilitate horizontal gene transfer detection in eukaryotes]]> SWGIS v2.0 along with the EuGI database, which houses GIs identified in 66 different eukaryotic species, and the EuGI web-resource, provide the first comprehensive resource for studying HGT in eukaryotes.

https://bmcgenomics.biomedcentral.com/articles/10.1186/s12864-018-4724-8

Address of the bookmark: https://bmcgenomics.biomedcentral.com/articles/10.1186/s12864-018-4724-8

]]> Surabhi Chaudhary https://bioinformaticsonline.com/opportunity/view/15030/software-engineercomputational-biologist-equinome-ltd-dublin-ireland Thu, 04 Sep 2014 19:21:26 -0500 <![CDATA[Software engineer/Computational Biologist - Equinome Ltd., Dublin, Ireland]]> Equinome (www.equinome.com) is the world leader in the research and
development of state-of-the-art novel genomic tools to inform the breeding,
selection and training of Thoroughbred racehorses. Since its launch in 2010,
Equinome has successfully commercialised three performance-related genetic
tests, with a pipeline of further genetic tests in development. We work with
many of the world's leading racehorse trainers and breeders in Europe,
Australasia, USA and South Africa. The company has been featured on CNN,
Bloomberg, RTE, BBC, The Guardian, Discovery Channel and Channel 4, among
others.

The Role

We are looking for a Software Engineer - Computational Biologist with 3+
years' experience in a similar role to design and implement a backend system
to support an online individualised genomics interface. This position is a
great opportunity for an ambitious, self-motivated individual to work in a
demanding, challenging and interesting role.

Position Description:
. Participate in planning, design, and implementation of Equinome back
end systems and technologies.
. Implement interfaces and management tools for back end services.
. Manage, analyse, interpret and visualise large genomics data sets.
. Work closely with scientific team to develop new features and
application enhancements
. Design, develop and manage a genomics research database.

Qualification/Experience:
. Minimum MSc in Computer Science, Genetics, Bioinformatics or in a
related field (A Ph.D qualification would be an advantage).
. Proven 3+ years of experience in similar role.
. Highly proficient in Python, SQL, MySQL.
. Excellent knowledge of mammalian genomics, bioinformatics and
statistical/population genetics.
. Hands-on experience working with large data sets.
. Experience with front-end technologies (HTML/CSS/Javascript) an
advantage.
. Experience in rapid web application development: e.g. Django.
. Knowledge or experience of Unix Scripting and R statistical
programming language would be an advantage.
. Ability to work with minimum supervision to deliver high-quality
code on time.
. Fluency in English and good written and communication skills.
. Meticulous attention to detail.

Applications should be submitted before Friday, 26 September 2014 using the
following link:
http://bit.ly/WgbhxS

Note: Full information and application procedure is available at this link:
http://bit.ly/WgbhxS

]]> https://bioinformaticsonline.com/blog/view/38238/list-of-motif-discovery-tools Tue, 20 Nov 2018 03:54:26 -0600 https://bioinformaticsonline.com/blog/view/38238/list-of-motif-discovery-tools <![CDATA[List of motif discovery tools !]]>
In genetics, a sequence motif is a nucleotide or amino-acid sequence pattern that is widespread and has, or is conjectured to have, a biological significance. For proteins, a sequence motif is distinguished from a structural motif, a motif formed by the three-dimensional arrangement of amino acids which may not be adjacent.
 
Following are the list of tools for motif discovery:
 

Perform secondary structure predictions on protein sequences.

Find binding specificity information about DNA-protein complexes.

Find information about the binding specificity of DNA-binding proteins.

Use this web-based sequence motif visualization system to display sequence motif information in its appropriate three-dimensional (3D) context.

Protein function prediction and annotation in an integrated environment powered by web service.

Use to predict function from de novo protein sequences.

Search for short active protein sequences with demonstrated biological activities.

Search for ungapped segments corresponding to the most highly conserved regions of proteins.

Identify and measure surface accessible pockets as well as interior inaccessible cavities, for proteins and other molecules.

To search for catalytic residue annotation for enzymes in the Protein Data Bank.

Predict protein function using Gene Ontology.

Automatically calculate evolutionary conservation scores of key amino acid residues and map them on protein structures.

Mine the protein structure space.

Predict short linear motifs (3-8 residues) in a set of protein sequences.

A web client for visualizing protein sequence feature information using DAS.

Identify the domain architecture within a protein sequence.

Predict functional sites in eukaryotic proteins.

Use a collection of tools for protein analyses.

Predict potential protein post-translational modifications and find potential single amino acid substitutions in peptides.

Search for information related to the catalytic mechanisms of enzymes.

An integrated feature-based function prediction server for vertebrate proteomes.

Identify the closest matching PRINTS sequence motif fingerprints in a protein sequence.

Search for functional annotation of important sites in proteins with known structures.

Produce 3D conformations of small drug compounds.

A database presenting experiment-based results in human proteomics.

Conduct exhaustive intermediate profile searches of a set of homologous protein sequences.

Design protein mutations in site-directed mutagenesis.

Annotate protein using this integrated annotation resource.

Identify protein family (and DNA) domains, patterns, motifs, protein families, and functional sites.

Interactive forecasting of protein interaction hot spots.

Database containing pairs of structural analogs and their alignments.

Find sequence patterns in DNA and protein sequences.

A web server for knowledge-based modeling of protein-peptide complexes, specifically peptides in complex with major histocompatibility complex (MHC) proteins and kinases.

Find structural segments or motifs for protein structures.

Visualize protein sequence motifs on the 3D protein structures.

Find presence of any known protein motif (Prosite and Pfam) in a protein sequence.

Recognize spatial chemical binding patterns common to a set of protein structures.

Analyze proteins for the presence of N-terminal N-myristoylation site.

Find the presence of N-Glycosylation sites in human proteins.

Find the presence of O-GalNAc (mucin type) glycosylation sites in mammalian proteins.

Analyze eukaryotic proteins for the presence of serine, threonine and tyrosine phosphorylation sites.

Find possible kinase specific phosphorylation sites in eukaryotic proteins.

Predict cleavage sites at basic amino acid locations in neuropeptide precursor sequences.

Find information about patented nucleotide and protein sequences.

Search for information about glycoproteins with O-linked and C-linked glycosylation sites.

Find information about protein sequence annotations.

A server to predict protein active site residues.

Search for structural and functional information on the protein functional sites.

Search 3D protein fragments similar in structure to known active, binding and posttranslational modification sites.

Conduct genome wide functional and structural analysis.

Search for phosphorylation data of any protein of interest.

Search for information on prokaryotic proteins that undergo serine, threonine, or tyrosine phosphorylation.

Determine correct names for proteins.

Web application for predicting protein disorder by using physicochemical features and reduced amino acid set of a position-specific scoring matrix.

Find homologous protein-protein interactions across multiple species.

Search your query sequence against PROSITE pattern database for protein motifs.

Find information about protein-RNA complexes from the Protein Data Bank (PDB).

Identify protein families and domains for a given protein sequence.

A comprehensive database of pattern-recognition receptors and their ligands.

Search for short nucleotide or peptide sequences such as cis-elements in nucleotide sequences or small domains and motifs in protein sequences.

Database specialized in documenting human PPBD-containing proteins and PPBD-mediated interactions.

Predicts potential protease cleavage sites and sites cleaved by chemicals in a given protein sequence.

Predict combined transmembrane topology and signal peptides.

Search for eukaryotic phosphorylation sites.

Search for 3D structure and functional annotation of phosphorylation sites in proteins.

Search the database of in vivo phosphorylation sites of human and mouse proteins

Find information about polyglutamine (polyQ) repeats.

Find the presence of protein motifs and patterns in an amino acid sequence.

Predict signal peptide sequences and their cleavage positions in bacterial and eukaryotic amino acid sequences.

Predict protein functions based on known structures.

Predict the location of potential protein-protein binding sites for unbound proteins.

Identify short linear signatures in protein termini.

Analyze and identify newly obtained protein sequences.

Predict protein binding sites in a protein sequence based on geometrical analysis of protein tertiary substructures.

Search for evolutionarily conserved motif-like patterns in protein sequences.

Web-based server for analyzing and predicting RNA binding sites in proteins.

Search for similarities between proteins by simultaneous matching of multiple motifs.

Predict residues in protein sequences that determine the proteins' functional specificity.

Predict specificity-determining residues in protein families.

Find shared motifs in proteins with a common attribute.

Conduct in silico sumoylation sites prediction.

Search for motifs and patterns within protein sequences.

Search for motifs within proteins that are likely to be phosphorylated by specific protein kinases or bind to domains such as SH2 domains, 14-3-3 domains or PDZ domains.

Find information about populations carrying polymorphisms within protein binding pockets that make them susceptible to serious adverse drug reaction (SADR).

Search the presence of a motif in either amino acid sequence or nucleotide sequence.

Predict the presence of tyrosine sulfation sites in protein sequences

Look at protein structure from a ligand and binding site perspective.

Use a collection of bioinformatics tools at this portal site.

Find information about tandem repeats in proteins that carry fundamental biological functions and are related to a number of human diseases.

Find information about functional residues in alpha-helical and beta-barrel membrane proteins.

Database of domains and motifs with conservative location in transmembrane proteins.

Search for highly conserved and specific protein sequence motifs.

Predict functional sites in protein sequence alignments use different methodologies.

Find de novo protein motifs from chromatin immunoprecipitation data.

Scan query structures for functional sites in both proteins and nucleic acids.

Analyze quantitative structure-activity relationship of related protein families.

Search for ungapped alignments of highly conserved regions among a protein family or superfamily.

An expert system for predicting ligand-binding residues in protein structures.

Automatically identify spatially interacting motifs among distantly related proteins sharing similar folds and possessing common ancestral lineage.

]]> Neel https://bioinformaticsonline.com/opportunity/view/16313/project-assistant-position-at-jmi Fri, 12 Sep 2014 00:37:44 -0500 <![CDATA[Project Assistant Position at JMI]]> Project Assistant Position (@ Rs.10,000/pm Fixed) is available for one year ina research project funded by the Department of Science and Technology entitled, "Folding and stability of naturally truncated photosynthetic pigment,C- phycoerythrin from cyanobacterium Phormidium tenue", at Centre forInterdisciplinary Research in Basic Sciences, lamia Millia Islamia, New Delhi-110025 under' the supervision of Dr. Md. Imtaiyaz Hassan (PrincipalInvestigator).

Eligibility:
M.Sc. in any stream of Life Sciences with minimum 55% marks.

Desirable:
Candidates having experience in Molecular Spectroscopy, Protein Folding and Bioinformatics will be preferred.

Interested candidate may appear in the walk in Interview conducted on September 16, 2014 (Tuesday) 11:00 AM in the Director's Office, Centre for Interdisciplinary Research in Basic Sciences, lamia Millia Islamia, New Delhi-110025.
Candidates are required to bring a set of Xerox copy of their recent CV and qualifying degree (certificate/mark sheet) along with original documents. NoTA/DA will be paid.

For any further information you may e-mail to: mihassan@jmLac.in

Read more at http://jmi.ac.in/upload/advertisement/jobs_cirbs_2014september8.pdf

]]> https://bioinformaticsonline.com/bookmarks/view/41559/dahak-benchmarking-and-containerization-of-tools-for-analysis-of-complex-non-clinical-metagenomes Thu, 09 Apr 2020 04:56:09 -0500 https://bioinformaticsonline.com/bookmarks/view/41559/dahak-benchmarking-and-containerization-of-tools-for-analysis-of-complex-non-clinical-metagenomes <![CDATA[Dahak: benchmarking and containerization of tools for analysis of complex non-clinical metagenomes.]]> Dahak is a software suite that integrates state-of-the-art open source tools for metagenomic analyses. Tools in the dahak software suite will perform various steps in metagenomic analysis workflows including data pre-processing, metagenome assembly, taxonomic and functional classification, genome binning, and gene assignment. We aim to deliver the analytical framework as a robust and reliable containerized workflow system, which will be free from dependency, installation, and execution problems typically associated with other open-source bioinformatics solutions. This will maximize the transparency, data provenance (i.e., the process of tracing the origins of data and its movement through the workflow), and reproducibility.

More at https://dahak-metagenomics.github.io/dahak/

Address of the bookmark: https://github.com/dahak-metagenomics/dahak

]]> BioStar https://bioinformaticsonline.com/opportunity/view/17188/jamia-hamdard-bioinformatics-faculty-jobs-2014 Sat, 20 Sep 2014 21:00:05 -0500 <![CDATA[JAMIA HAMDARD Bioinformatics Faculty Jobs 2014]]> JAMIA HAMDARD

(Deemed University)

Hamdard Nagar, New Delhi – 110 062

R E C R U I T M E N T

(Advertisement No. 5/2014)

Applications on prescribed form are invited for filling up the following teaching positions in the Department of Biotechnology, Faculty of Science in the university. Eligible candidates may apply on or before 30.09.2014.

1. Professor/Associate Professor - One in Pay Band of Rs. 37400-67000+ AGP Rs.10000/9000

2. Assistant Professor - Two in Pay Band of Rs. 15600-39100+ AGP Rs. 6000/-

ASSISTANT PROFESSOR – 02 (including 01 SFS)

Specialization : Bioinformatics

Qualification and Experience :

Ph.D. in Biotechnology or an allied discipline with M.Sc. in Biotechnology/ Biochemistry in the First division or equivalent grade from a recognized University/ Institute.

NET in Life Science or allied discipline in addition to the above qualification.

Experience : At least two years of Post-doctoral teaching and/or research experience in Bioinformatics or relevant field in a UGC recognized Institution of repute or international research institute/ University. Proof of research to be evidenced by publications in SCI-indexed journals of high impact factor as the first or corresponding author.

Note : University may consider exempting candidates from NET, who has been awarded Ph.D. degree from ‘A’ Grade accredited University following the procedure as notified by the UGC in its Regulations of 2009 and adopted by Jamia Hamdard.

For more information: http://www.jamiahamdard.ac.in/PDF/Online%20application%20form%20_Teaching_1.pdf
http://www.jamiahamdard.ac.in/PDF/PBAS.pdf

]]> https://bioinformaticsonline.com/blog/view/42936/ancient-whole-genome-duplication-wgd-detection-tools Sun, 07 Mar 2021 00:32:44 -0600 https://bioinformaticsonline.com/blog/view/42936/ancient-whole-genome-duplication-wgd-detection-tools <![CDATA[Ancient whole genome duplication (WGD) detection tools !]]> There are two methods for ancient WGD detection, one is collinearity analysis, and the other is based on the Ks distribution map. Among them, Ks is defined as the average number of synonymous substitutions at each synonymous site, and there is also a Ka corresponding to it, which refers to the average number of non-synonymous substitutions at each non-synonymous site.

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
]]> Rahul Nayak https://bioinformaticsonline.com/researchlabs/view/17500/joao-pedro-de-magalhaes-lab Fri, 26 Sep 2014 19:08:34 -0500 <![CDATA[Joao Pedro de Magalhaes Lab]]> Ageing has a profound impact on human society and modern medicine, yet it remains a major puzzle of biology. The goal of my work is to help understand the genetic, cellular, and molecular mechanisms of ageing. In the long term, I would like my work to help ameliorate age-related diseases and preserve health. No other biomedical field has so much potential to improve human health as research on the basic mechanisms of ageing. Please see our lab website for further details about our work and publications.

Functional and Comparative Genomics

http://jp.senescence.info/
http://www.senescence.info/
http://www.liv.ac.uk/integrative-biology/staff/joao-de-magalhaes/

]]>