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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/31100?offset=630</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/42936/ancient-whole-genome-duplication-wgd-detection-tools</guid>
	<pubDate>Sun, 07 Mar 2021 00:32:44 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/42936/ancient-whole-genome-duplication-wgd-detection-tools</link>
	<title><![CDATA[Ancient whole genome duplication (WGD) detection tools !]]></title>
	<description><![CDATA[<p>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.</p><p>At present, some people have posted articles about the analysis process of WGD. I searched for the keyword "wgd pipeline" and found the following:</p><p><strong>GenoDup: https:// github.com/MaoYafei/GenoDup-Pipeline</strong><br /><strong>https://peerj.com/articles/6303/</strong><br /><strong>WGDdetector: https:// github.com/yongzhiyang2 012/WGDdetector</strong><br /><strong>https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-019-2670-3</strong><br /><strong>wgd: https:// github.com/arzwa/wgd</strong><br /><strong>https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-016-1142-2#Sec1</strong><br /><strong>https://bmcbiol.biomedcentral.com/articles/10.1186/s12915-017-0399-x</strong><br /><strong>GeNoGAP https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-016-1142-2</strong><br /><strong>https://bmcbiol.biomedcentral.com/articles/10.1186/s12915-017-0399-x</strong><br /><strong>https://github.com/dfguan/purge_dups</strong><br /><strong>https://www.biorxiv.org/content/10.1101/2020.01.24.917997v1</strong></p><p>This article introduces the usage of wgd.</p><p>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</p><p><strong>BLAST</strong><br /><strong>MCL</strong><br /><strong>MUSCLE/MAFFT/PRANK</strong><br /><strong>PAML</strong><br /><strong>PhyML/FastTree</strong><br /><strong>i-ADHoRe</strong></p><p>But the good news is that most of the software it depends on can be installed with bioconda</p><blockquote><p>conda create -n wgd python=3.5 blast mcl muscle mafft prank paml fasttree cmake libpng mpi=1.0=mpich<br />conda activate wgd</p></blockquote><p>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</p><p>After that, the installation is much simpler</p><blockquote><p>git clone https://github.com/arzwa/wgd.git<br />cd wgd<br />pip install .<br />pip install git+https://github.com/arzwa/wgd.git<br />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</p></blockquote><p>Since my miniconda3 installed ~/opt/, the installation path is so~/opt/miniconda3/envs/wgd/</p><blockquote><p>tar -zxvf i-adhore-3.0.01.tar.gz<br />cd i-adhore-3.0.01<br />mkdir -p build &amp;&amp; cd build<br />cmake .. -DCMAKE_INSTALL_PREFIX=~/opt/miniconda3/envs/wgd/<br />make -j 4 <br />make insatall</p></blockquote><p>Take the sugarcane genome Saccharum spontaneum L as an example. The genome is 8-ploid with 32 chromosomes (2n = 4x8 = 32)</p><p><strong>Download the tutorial for CDS and GFF annotation files</strong></p><blockquote><p><strong>mkdir -p wgd_tutorial &amp;&amp; cd wgd_tutorial</strong><br /><strong>wget http://www.life.illinois.edu/ming/downloads/Spontaneum_genome/Sspon.v20190103.cds.fasta.gz</strong><br /><strong>wget http://www.life.illinois.edu/ming/downloads/Spontaneum_genome/Sspon.v20190103.gff3.gz</strong><br /><strong>gunzip *.gz</strong></p></blockquote><p>First conda activate wgdstart our analysis environment, and then start the analysis</p><p>Step 1 : Use to wgd mclidentify homologous genes in the genome</p><blockquote><p>wgd mcl -n 20 --cds --mcl -s Sspon.v20190103.cds.fasta -o Sspon_cds.out</p></blockquote><p>Step 2 : Use to wgd ksdbuild Ks distribution</p><blockquote><p>wgd ksd --n_threads 80 Sspon_cds.out/Sspon.v20190103.cds.fasta.blast.tsv.mcl Sspon.v20190103.cds.fasta</p></blockquote><p>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</p><blockquote><p>wgd syn --feature gene --gene_attribute ID \<br /> -ks wgd_ksd/Sspon.v20190103.cds.fasta.ks.tsv \<br /> Sspon.v20190103.gff3 Sspon_cds.out/Sspon.v20190103.cds.fasta.blast.tsv.mcl</p></blockquote><p>&nbsp;For more reading - There are 9 sub-modules in WGD</p><ul>
<li><span>kde: KDE fitting to the Ks distribution</span></li>
<li><span>ksd: Ks distribution construction</span></li>
<li><span>mcl: BLASP comparison of All-vs-ALl + MCL classification analysis.</span></li>
<li><span><span>mix: Hybrid modeling of Ks distribution.</span></span></li>
<li><span>pre: preprocess the CDS file</span></li>
<li><span>syn: Call I-ADHoRe 3.0 to use GFF files for collinearity analysis</span></li>
<li><span>viz: draw histogram and density plot</span></li>
<li><span>wf1: Ks standard analysis procedure of the whole genome paranome (paranome), call mcl, ksd and syn</span></li>
<li><span>wf2: Ks standard analysis procedure of one-vs-one homologous gene (ortholog), call wcl and kSD</span></li>
</ul>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/6562/molecular-bioinformatics-lab-mbl</guid>
  <pubDate>Tue, 19 Nov 2013 18:23:27 -0600</pubDate>
  <link></link>
  <title><![CDATA[Molecular Bioinformatics Lab (MBL)]]></title>
  <description><![CDATA[
<p>The main subject of interest in our laboratory is the study of the relationship among sequence, structure, and function in proteins and nucleic acids. Our research can be divided in two major topics:</p>

<p>the study of the sequence-structure relationship<br />(application -&gt; structure prediction)<br />the study of the structure-function relationship<br />(application -&gt; function prediction)</p>

<p>Therefore, anything related to the configuration (sequence) and conformation (structure) in atomic systems of proteins and nucleic acids, and the interaction of these with other elements (function) is of our major interest.</p>

<p>Lab page @ http://melolab.org/mbl/</p>
]]></description>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/43293/josefa-gonzalez-lab</guid>
  <pubDate>Thu, 19 Aug 2021 08:52:56 -0500</pubDate>
  <link></link>
  <title><![CDATA[Josefa González Lab]]></title>
  <description><![CDATA[
<p>Lab focus on understanding how organisms adapt to their environments. They combine omics approaches with detailed molecular and phenotypic analyses to get a comprehensive picture of adaptation. Our aim at being internationally recognized as a leading lab in the field of environmental adaptation.<br />Lab share our passion for science with the general public by leading outreach projects aimed at increasing science awareness.</p>

<p>More at https://www.biologiaevolutiva.org/gonzalez_lab/</p>
]]></description>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/6818/scientist-positions-gujarat-state-biotechnology-mission</guid>
  <pubDate>Mon, 25 Nov 2013 10:26:39 -0600</pubDate>
  <link></link>
  <title><![CDATA[Scientist Positions @ Gujarat State Biotechnology Mission]]></title>
  <description><![CDATA[
<p>Gujarat State Biotechnology Mission invite applications [Online Only] under various projects* namely Gujarat Biodiversity Gene Bank (BioGene), Gujarat Institute of Genomics (GIG), Gujarat Institute of Bioinformatics [GIBS] and Gujarat Institute of Marine Biotechnology. Eligible candidates can Apply through online application portal.</p>

<p>1 Scientist E 3</p>

<p>50,000/-</p>

<p>M.Sc. in Life sciences or Plant Sciences or Biotechnology or Microbiology or Bioinformatics or Ph.D. from a recognized university in any of above subject.</p>

<p>Minimum 8 Yrs. of experience after M.Sc. or 5 Yrs. of experience after Ph.D. in responsible position of work in R &amp; D in the area of genomics/ conservation biotechnology/bioinformatics/Planning/Scientific Administration in Science and technology organization. Highly qualified in the area of modern biology, as evidenced through research experience and proven ability to carry out work in the area of conservation biotechnology. Age limit not exceeding 40yrs.</p>

<p>2 Scientist B 6</p>

<p>30,000/-</p>

<p>M.Sc. in Life sciences or Plant Sciences or Biotechnology or Microbiology or Bioinformatics or Ph.D. from a recognized university in any of above subject shall be preferred.</p>

<p>Minimum 3 Yrs. of experience after M.Sc. in responsible position of work in R &amp; D in the area of genomics/ conservation biotechnology/ bioinformatics /Planning/Scientific Administration in Science and technology organization. Highly qualified in the area of modern biology, as evidenced through research experience and proven ability to carry out work in the area of conservation biotechnology. Age limit not exceeding 35yrs.</p>

<p>The positions are purely on contractual basis for 11 months. Interested candidates can apply online in specified format available at "http://leogen.in/recruit/" The last date of applying is 24th December, 2013. Applications must be submitted online only. Applications submitted in any other format except online prescribed performa will be rejected. Candidates in service must apply through proper channel. Candidates will be required to provide original documents along with duly filled and signed application Performa, as and when called for interview.</p>

<p>For more details please visit the website URL : http://leogen.in/recruit</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43661/maftools</guid>
	<pubDate>Fri, 17 Dec 2021 03:18:28 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43661/maftools</link>
	<title><![CDATA[maftools]]></title>
	<description><![CDATA[<p>With advances in Cancer Genomics, <a href="https://docs.gdc.cancer.gov/Data/File_Formats/MAF_Format/">Mutation Annotation Format</a> (MAF) is being widely accepted and used to store somatic variants detected. <a href="http://cancergenome.nih.gov">The Cancer Genome Atlas</a> Project has sequenced over 30 different cancers with sample size of each cancer type being over 200. <a href="https://wiki.nci.nih.gov/display/TCGA/TCGA+MAF+Files">Resulting data</a> consisting of somatic variants are stored in the form of <a href="https://docs.gdc.cancer.gov/Data/File_Formats/MAF_Format/">Mutation Annotation Format</a>. This package attempts to summarize, analyze, annotate and visualize MAF files in an efficient manner from either TCGA sources or any in-house studies as long as the data is in MAF format.</p>
<p>https://www.bioconductor.org/packages/devel/bioc/vignettes/maftools/inst/doc/maftools.html</p><p>Address of the bookmark: <a href="https://github.com/PoisonAlien/maftools" rel="nofollow">https://github.com/PoisonAlien/maftools</a></p>]]></description>
	<dc:creator>Surabhi Chaudhary</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/7088/gabi</guid>
  <pubDate>Fri, 06 Dec 2013 16:43:01 -0600</pubDate>
  <link></link>
  <title><![CDATA[GABi]]></title>
  <description><![CDATA[
<p>GABi Research<br />The major researching fields defined as the GABi scope are described next:<br />    Sequence Analysis<br />    Protein Structure Prediction<br />    Comparative Genomics<br />    Functional Analysis of Residues on Protein Families<br />    Gene/Protein Networks<br />    Genome structure &amp; base composition<br />    Highthroughput data analysis from NGS</p>

<p>Lab Page http://gabi.cidbio.org/index/</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43770/chromeister-an-ultra-fast-heuristic-approach-to-detect-conserved-signals-in-extremely-large-pairwise-genome-comparisons</guid>
	<pubDate>Thu, 03 Feb 2022 04:01:55 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43770/chromeister-an-ultra-fast-heuristic-approach-to-detect-conserved-signals-in-extremely-large-pairwise-genome-comparisons</link>
	<title><![CDATA[chromeister: An ultra fast, heuristic approach to detect conserved signals in extremely large pairwise genome comparisons.]]></title>
	<description><![CDATA[<p>chromeister: An ultra fast, heuristic approach to detect conserved signals in extremely large pairwise genome comparisons.</p>
<p dir="auto">USAGE:</p>
<ul dir="auto">
<li>-query: sequence A in fasta format</li>
<li>-db: sequence B in fasta format</li>
<li>-out: output matrix</li>
<li>-kmer Integer: k&gt;1 (default 32) Use 32 for chromosomes and genomes and 16 for small bacteria</li>
<li>-diffuse Integer: z&gt;0 (default 4) Use 4 for everything - if using large plant genomes you can try using 1</li>
<li>-dimension Size of the output matrix and plot. Integer: d&gt;0 (default 1000) Use 1000 for everything that is not full genome size, where 2000 is recommended</li>
</ul><p>Address of the bookmark: <a href="https://github.com/estebanpw/chromeister" rel="nofollow">https://github.com/estebanpw/chromeister</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/7214/lapti-lab</guid>
  <pubDate>Thu, 12 Dec 2013 18:19:12 -0600</pubDate>
  <link></link>
  <title><![CDATA[LAPTI Lab]]></title>
  <description><![CDATA[
<p>The main theme of our research is the understanding of how genetic information is decoded from DNA into RNA and proteins. Someone may find this topic a little strange and argue that we already know how this is happening.</p>

<p>Translational recoding. </p>

<p>RNA editing. </p>

<p>Evolution of the genetic code and translation.</p>

<p>More at http://lapti.ucc.ie/research.html</p>

<p>Lab page http://lapti.ucc.ie/index.html</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43846/the-complete-sequence-of-a-human-genome</guid>
	<pubDate>Thu, 31 Mar 2022 23:58:18 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43846/the-complete-sequence-of-a-human-genome</link>
	<title><![CDATA[The complete sequence of a human genome]]></title>
	<description><![CDATA[<p><span>The completed regions include all centromeric satellite arrays, recent segmental duplications, and the short arms of all five acrocentric chromosomes, unlocking these complex regions of the genome to variational and functional studies.</span></p><p>Address of the bookmark: <a href="https://www.science.org/doi/10.1126/science.abj6987" rel="nofollow">https://www.science.org/doi/10.1126/science.abj6987</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/7362/junior-research-fellow-jrf-project-fellow-kalasalingam-university</guid>
  <pubDate>Thu, 19 Dec 2013 13:23:39 -0600</pubDate>
  <link></link>
  <title><![CDATA[Junior Research Fellow (JRF) / Project Fellow @ Kalasalingam University]]></title>
  <description><![CDATA[
<p>Applications are invited from interested candidates for the post of one Junior Research Fellow / Project Fellow on a purely temporary basis in a time bound research project (3 years) sponsored by Science and Engineering Research Board, Government of India, New Delhi.</p>

<p>Name of the fellowship: Junior Research Fellow (JRF) / Project Fellow</p>

<p>Title of the project: Genome-wide Mapping of Murine Specific Dengue T-cell Epitopes: Computational Prediction, Identification and use as Candidate Vaccines</p>

<p>Duration: 3 years</p>

<p>Fellowship: Rs. 18,000 for first 2 years and Rs. 20,000 for 3rdyear (for M.Tech. candidates)</p>

<p>Rs. 16,000 for first 2 years and Rs. 18,000 for 3rdyear (for M.Sc. candidates with NET qualification)</p>

<p>Rs. 8,000 for first 2 years and Rs. 10,000 for 3rdyear (for M.Sc. candidates without NET qualification)</p>

<p>Qualifications: M.Tech. in Biotechnology / M.Sc. in any branch of Life Sciences</p>

<p>Desirable Experience: Minimum of two years research experience in any of the following areas: Immunology / Microbiology / Gene Manipulation / Bioinformatics</p>

<p>Interested and eligible candidates may apply with their resume along with relevant documents and a passport size photograph to the Principal Investigator by post (or e-mail) on or before December 31, 2013. Only short listed candidates will be called for written test and/or interview. Selected candidate may register for PhD in Kalasalingam University. No TA/DA will be paid for attending interview.</p>

<p>Dr. K. Sundar<br />Principal Investigator (SERB Project)<br />Department of Biotechnology<br />Kalasalingam University<br />Krishnankoil – 626126, Tamil Nadu<br />sundarkr@klu.ac.in</p>
]]></description>
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