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<channel>
	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/29679?offset=900</link>
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	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/4574/tools-to-detect-synteny-blocks-regions-among-multiple-genomes</guid>
	<pubDate>Mon, 16 Sep 2013 17:12:02 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/4574/tools-to-detect-synteny-blocks-regions-among-multiple-genomes</link>
	<title><![CDATA[Tools to detect synteny blocks regions among multiple genomes]]></title>
	<description><![CDATA[<p>The synteny block (which etymologically means &ldquo;on the same ribbon&rdquo;) is a collection of contiguous genes located on the same chromosome. These block regions have mostly been preserved by genome rearrangements, and so synteny blocks from two related species (e.g., humans and mice) will be roughly similar but flipped around on the respective genomes. Ovcharenko et. al. define it as &lsquo;any conserved sequence blocks, regardless of whether it encompasses multiple genes, an area containing single genes, or areas devoid of known genes to be considers as synteny block as long as there is conservation at the sequence level. Today, however, biologists usually refer to synteny as the conservation of blocks of order within two sets of chromosomes that are being compared with each other. This concept can also be referred to as shared synteny. The NHBLI/NCBI Glossary define synteny as &ldquo;Two genes which occur on the same chromosome are syntenic; however, syntenic genes may or may not be "linked."</p><p>Now a day, geneticists have developed a language of their own. They are pouring lots of money and energy to read the entire genomic text and understand the gods own code ATGC. It is somewhat fascinating, not only for geneticist but also for non-biologist to know that there are several conserved blocks in genome which remain conserved over hundreds of millions of years. There have been several researches on conserved blocks and non-conserved regions to understand the mechanism and importance of all these regions (http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2675965/). The finding indicates conservation and rearrangements of certain evolutionary important genes play an important role in evolution/adaptive changes (http://www.nature.com/nature/journal/v491/n7424/abs/nature11622.html https://academic.oup.com/gbe/article/8/8/2442/2198198/Novel-Insights-into-Chromosome-Evolution-in-Birds , http://science.sciencemag.org/content/346/6215/1311).</p><p>But the puzzle remains open, how to correctly define the synteny (presence of two or more genes on the same chromosome) and conserved synteny (presence of two or more genes on chromosome of each of the two species) on several genomes.</p><p><img src="http://bioinformaticsonline.com/mod/photo/syntenyImg.jpg" alt="image" width="720" height="179" style="border: 0px; border: 0px;"></p><p>Figure: Image generated with Evolution Highway (EH) tool http://eh-demo.ncsa.illinois.edu/&nbsp;</p><p>Keeping the new approach to define conserved synteny in mind there have been various algorithms developed to identify the conserved homologous synteny blocks (HSB) amongst species. Some of them which were commonly used for synteny detections are:</p><p>SyntenyTracker ( http://www-app.igb.uiuc.edu/labs/lewin/donthu/Synteny_assign/html/),</p><p>SyntenyTracker was shown to be an efficient and accurate automated tool for defining HSBs using datasets that may contain minor errors resulting from limitations in map construction methodologies.</p><p>CoGe (http://genomevolution.org/CoGe/SynFind.pl )</p><p>Satsuma (http://evomics.org/learning/genomics/satsuma/)</p><p>Cinteny (http://cinteny.cchmc.org/) ,</p><p>Cinteny server can be used for finding regions syntenic across multiple genomes and measuring the extent of genome rearrangement using reversal distance as a measure.</p><p>OrthoCluster (http://krono.act.uji.es/noticias/orthocluster-a-new-tool-for-mining-syntenic-blocks)</p><p>A new tool for mining syntenic blocks in comparative genomics</p><p>SynMap (http://genomevolution.org/wiki/index.php/SynMap),</p><p>SyMAP (http://www.symapdb.org/)</p><p>SyMAP (Synteny Mapping and Analysis Program) v4.0 is an automated system for identifying and displaying genome synteny alignments. The genomes may be represented by sequenced chromosomes (pseudomolecules), by draft sequence contigs, or by FPC physical maps (with BAC-end or marker sequence).</p><p>http://genomevolution.org/CoGe/SynMap.pl</p><p>RegionMiner (http://www.genomatix.de/online_help/help_regionminer/orthologous.html)</p><p>SyntenyMiner is being developed as an application to visualize and interrogate comparisons among multiple complete genome sequences. http://syntenyminer.sourceforge.net/</p><p>AutoGRAPH ( http://autograph.genouest.org/),</p><p>AutoGRAPH is an integrated web server for multi-species comparative genomic analysis. It is designed for constructing and visualizing synteny maps between two or three species, determination and display of macrosynteny and microsynteny relationships among species, and for highlighting evolutionary breakpoints.</p><p>SynChro(http://www.lgm.upmc.fr/CHROnicle/SynChro.html)</p><p>SynChro is a tool designed to define conserved synteny blocks. It reconstructs synteny blocks between pairwise comparison of multiple genomes. The reconstructed synteny blocks may overlap each other, be included in one another or duplicated due to micro-rearrangements.</p><p>SyntenyView ( http://www.cbs.dtu.dk/dtucourse/cookbooks/nikob/exercises/gf1_output_5.html),</p><p>Ensembl 'SyntenyView' shows conservation of large-scale gene order between species pairs. A brief summary of the calculation method appears at the bottom of this help page.&nbsp; The left of a 'SyntenyView' page displays a diagram of chromosomes with blocks of conserved synteny. The right of a page shows homology matches between individual genes within syntenic blocks.</p><p>SynBrowse ( http://www.synbrowse.org/),</p><p>SynBrowse (Synteny Browser) is a generic sequence comparison tool for visualizing genome alignments both within and between species. It is intended to help scientists study and analyze synteny, homologous genes and other conserved elements between sequences. This software is useful in studying genome duplication and evolution. It can also aid in identifying uncharacterized genes, putative regulatory elements and novel structural features of study species by comparing to a well annotated reference sequence, thus enabling genome curators to refine and edit annotations of species that have incomplete genome annotations.</p><p>Sibelia (http://arxiv.org/abs/1307.7941).</p><p>A comparative genomic tool: It assists biologists in analysing the genomic variations that correlate with pathogens, or the genomic changes that help microorganisms adapt in different environments. Sibelia will also be helpful for the evolutionary and genome rearrangement studies for multiple strains of microorganisms.</p><p>GSV (http://cas-bioinfo.cas.unt.edu/gsv/homepage.php)</p><p>Genome Synteny Viewer allows users to upload files which contain synteny regions between two or more genomes and interactively visualize the synteny between them. GSV also allows users to upload annotation files to visualize annotated regions in addition to synteny regions.</p><p>MicroSyn (http://www.lgm.upmc.fr/CHROnicle/SynChro.html)</p><p>MicroSyn software as a means of detecting microsynteny in adjacent genomic regions surrounding genes in gene families. MicroSyn searches for conserved, flanking colinear homologous gene pairs between two genomic fragments to determine the relationship between two members in a gene family.</p><p>SynOrth (http://synorth.genereg.net/)</p><p>Synorth [s n &ocirc;rth], named in combination of "synteny" and "ortholog", is designed for the study of evolutionary changes of genomic regulatory blocks (GRBs) in vertebrate genomes, and especially the changes following the whole-genome duplication in teleost fish, by tracing the ortholog genes gain and loss in ancient synteny blocks.</p><p>SyDiG (http://www.ncbi.nlm.nih.gov/pubmed/21441096)</p><p>Uncovering Synteny in Distant Genomes.</p><p>MapSynteny&nbsp; (http://www.automatizacionysistemas.com/download.html)</p><p>MapSynteny is a macro in MS Excel&reg; able to create images to show the relationship between genetic maps and large sequences (scaffolds, chromosomes, BACs, etc.). Based on tab &ndash; delimited BLAST results and some formulas, a suitable image of syntenic relationships or physical mapping can be obtained. http://www.automatizacionysistemas.com/Poster_MapSynteny.pdf</p><p>One of the best synteny tutorial for beginer @&nbsp;http://www.nature.com/scitable/topicpage/synteny-inferring-ancestral-genomes-44022</p><p>Reference:</p><p><a href="http://www.nature.com/scitable/topicpage/synteny-inferring-ancestral-genomes-44022">http://www.nature.com/scitable/topicpage/synteny-inferring-ancestral-genomes-44022</a></p><p><a href="http://www.nature.com/nature/journal/v491/n7424/full/nature11622.html">http://www.nature.com/nature/journal/v491/n7424/full/nature11622.html</a></p><p><a href="http://en.wikipedia.org/wiki/Synteny">http://en.wikipedia.org/wiki/Synteny</a></p><p><a href="http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2675965/">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2675965/</a></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/19729/senior-scientist-agricultural-bio-informatics-one-post</guid>
  <pubDate>Wed, 24 Dec 2014 05:01:02 -0600</pubDate>
  <link></link>
  <title><![CDATA[Senior Scientist (Agricultural Bio-informatics) (One post)]]></title>
  <description><![CDATA[
<p>Agricultural Scientists Recruitment Board</p>

<p>Qualifications Essential:<br />Doctoral degree in Bio-informatics/ Biotechnology/Molecular Biology and Biotechnology/Life Sciences/ Computer Sciences with specialization in Bio-informatics including relevant basic sciences with 8 years’ experience in the relevant subject as Scientist/Lecturer or in an equivalent position in the Pay Band- 3 of 15600-39100 with Grade Pay of 5400/6000/7000/8000 having made contribution to research/teachin/extension education as evidenced by published work/innovations and impact. </p>

<p>OR </p>

<p>Doctoral degree in the above subject(s) including relevant basic sciences with minimum 8 years’ experience of high quality post-doctoral research in an institution/organization as evidenced by at least 6 publications in journals with NAAS rating of 7.5 or above.</p>

<p>Desirable:<br />(i) Specialization and experience: Knowledge of software development and its application in crop bioinformatics, experience in handling ‘omies’data. <br />(ii) Teaching experience in relevant subject</p>

<p>The Secretary, Agricultural Scientists Recruitment Board, Indian Council of Agricultural Research Krishi Anusandhan Bhavan-I, Pusa New Delhi –110 012, India</p>

<p>Detailed eligibility criteria with how to apply information can be had at:<br />http://www.indiastudychannel.com/jobs/333467-Indian-Council-of-Agricultural-Research-looking-for-Assistant-Director-General.aspx</p>

<p>More at http://asrb.org.in/administrator/uploads_dir/1418978057english.pdf</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34172/orthodotter-synteny-plots-oxford-grid</guid>
	<pubDate>Wed, 09 Aug 2017 07:16:16 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34172/orthodotter-synteny-plots-oxford-grid</link>
	<title><![CDATA[orthodotter: Synteny plots (oxford grid)]]></title>
	<description><![CDATA[<pre><code>orthodotter -h
--------------------------------------------------------------------------------
orthodotter - Plot orthologous genes on an oxford grid.
       -f &lt;file&gt;     : input file, containing orthologous genes, default is stdin
                       species chr-name start end species chr-name start end
       -toPlot &lt;arg&gt; : give the x and y sets and the color separated by double-dots,
                       for example set1:set2:red will plot set1 on x, set2 on y with
                       red points. Could give several -toPlot arguments.
                       To launch the clustering of dots, use extra-option 1=dist,min_nb_genes
                       where dist is the minimal distance (euclidian) between two points and min_nb_genes the minimal
                       number of genes in a cluster to be valid.
       -o &lt;file&gt;     : output file, default is stdout
       -x &lt;int&gt;      : resolution of x axis, default is 600
       -y &lt;int&gt;      : resolution on y axis, default is 600
       -r &lt;int&gt;      : radius of circle representing orthologous genes
       -format       : could be png, gif, jpg, pdf or ps. Default is png.
       -fg           : foreground color, default is black
       -bg           : background color, default is transparent
       -fSize &lt;int&gt;  : fontSize, default is 1
       -filter       : check chromosome names
       -h            : help
--------------------------------------------------------------------------------
orthodotter -f Vigne_Banane.ortho -toPlot Vigne:Banane:black:1=10,5 -x 1200 -y 1200 -bg white -o Vigne_vs_Banane.png &gt; Vigne_vs_Banane.clusters
--------------------------------------------------------------------------------</code></pre><p>Address of the bookmark: <a href="https://github.com/institut-de-genomique/orthodotter" rel="nofollow">https://github.com/institut-de-genomique/orthodotter</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/19820/rstudio</guid>
	<pubDate>Sat, 27 Dec 2014 06:50:58 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/19820/rstudio</link>
	<title><![CDATA[RStudio]]></title>
	<description><![CDATA[<p>RStudio IDE is a powerful and productive user interface for R. It&rsquo;s free and open source, and works great on Windows, Mac, and Linux.</p>
<p>The developers and expert trainers are the authors of several popular R packages, including ggplot2, plyr, lubridate, and others.</p>
<p>More at http://www.rstudio.com/</p>
<p>http://www.rstudio.com/products/RStudio/</p><p>Address of the bookmark: <a href="http://www.rstudio.com/" rel="nofollow">http://www.rstudio.com/</a></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41694/mercator-multiple-whole-genome-orthology-map-construction</guid>
	<pubDate>Tue, 19 May 2020 16:46:22 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41694/mercator-multiple-whole-genome-orthology-map-construction</link>
	<title><![CDATA[Mercator: Multiple Whole-Genome Orthology Map Construction]]></title>
	<description><![CDATA[<p><span>Whole-genome homology maps attempt to identify the evolutionary relationships between and within multiple genomes. The term "syntenic" is often used to describe regions of multiple genomes that are believed to have evolved from the same region in an ancestral genome. However, it has been pointed out that this use of the term is incorrect (</span><a href="https://www.biostat.wisc.edu/~cdewey/mercator/#refSynteny">Passarge et al. 1999</a><span>) and thus we will use the terms "homologous", "orthologous", and "paralogous" instead. Ideally, given K genomes, we would like to identify all orthologous genomic regions as well as paralogous regions within each genome and hypothetical ancestral genome. Maps listing these relationships are extremely valuable to researchers performing comparative analyses of genomic sequence. Here we present our initial work in the form a program called&nbsp;</span><em>Mercator</em><span>&nbsp;that constructs orthology maps between multiple whole genomes.</span></p><p>Address of the bookmark: <a href="https://www.biostat.wisc.edu/~cdewey/mercator/" rel="nofollow">https://www.biostat.wisc.edu/~cdewey/mercator/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/19980/seqloc-06</guid>
	<pubDate>Sun, 28 Dec 2014 12:51:29 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/19980/seqloc-06</link>
	<title><![CDATA[seqloc 0.6]]></title>
	<description><![CDATA[<p>The <code>Bio.SeqLoc</code> modules in <code>seqloc</code> are designed to represent positions and locations (ranges of positions) on sequences, particularly nucleotide sequences. My original motivation for writing these packages was handing the locations of genes in eukaryotic genomes.</p>
<p>Handle sequence locations for bioinformatics http://www.ingolia-lab.org/seqloc-tutorial.html</p><p>Address of the bookmark: <a href="http://www.stackage.org/snapshot/nightly-2014-12-28/package/seqloc-0.6" rel="nofollow">http://www.stackage.org/snapshot/nightly-2014-12-28/package/seqloc-0.6</a></p>]]></description>
	<dc:creator>Gudiya Pal</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39881/apollo-a-sequence-annotation-editor</guid>
	<pubDate>Tue, 27 Aug 2019 08:08:47 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39881/apollo-a-sequence-annotation-editor</link>
	<title><![CDATA[Apollo: a sequence annotation editor]]></title>
	<description><![CDATA[<p><span>The well-established inaccuracy of purely computational methods for annotating genome sequences necessitates an interactive tool to allow biological experts to refine these approximations by viewing and independently evaluating the data supporting each annotation. Apollo was developed to meet this need, enabling curators to inspect genome annotations closely and edit them</span></p><p>Address of the bookmark: <a href="https://genomebiology.biomedcentral.com/articles/10.1186/gb-2002-3-12-research0082" rel="nofollow">https://genomebiology.biomedcentral.com/articles/10.1186/gb-2002-3-12-research0082</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/20271/research-associate-tata-memorial-centre-advanced-centre-for-treatment-research-and-education-in-cancer-kharghar-navi-mumbai</guid>
  <pubDate>Thu, 08 Jan 2015 20:53:57 -0600</pubDate>
  <link></link>
  <title><![CDATA[Research Associate	@ TATA MEMORIAL CENTRE ADVANCED CENTRE FOR TREATMENT, RESEARCH AND EDUCATION IN CANCER KHARGHAR, NAVI MUMBAI]]></title>
  <description><![CDATA[
<p>TATA MEMORIAL CENTRE ADVANCED CENTRE FOR TREATMENT, RESEARCH AND EDUCATION IN CANCER KHARGHAR, NAVI MUMBAI – 410210</p>

<p>Website: www.actrec.gov.in; Ph: 27405000</p>

<p>No. ACTREC/Advt./ 66 /2014 23rd December, 2014<br />Research Associate	</p>

<p>International Cancer Genome Consortium (ICGC) - India Project (IRB Project No. 3 A/c. No. 2408)</p>

<p>Dr. Rajiv Sarin</p>

<p>Duration of the Project: One year Extendable up to Three years.</p>

<p>Consolidated Salary: Rs. 42,000/- p.m.</p>

<p>Application last date: 8th January, 2015.</p>

<p>Interview Date &amp; Time: 21st January, 2015, at 11.00 a.m.</p>

<p>Venue: Conference Room, 3rd floor, Khanolkar Shodhika, ACTREC.</p>

<p>Essential Qualifications and Experience:</p>

<p>Ph.D (any branch of Life Sciences)</p>

<p>The candidate must have at least one year experience after Ph.D., preferably in Genomics and Molecular Biology.</p>

<p>Candidates fulfilling these requirements should pre register themselves by sending their application in the prescribed format with recent CV and contact details of 2 referees by e-mail to icgc@actrec.gov.in latest 8th January, 2015 by 10.00 a.m.</p>

<p>Candidates shortlisted for the interview will be intimated by email on or before 9th January, 2015.</p>

<p>The interviews would be held on 21st January 2015 and will be only for the pre registered candidates who have been shortlisted.<br />No T.A./D.A. will be admissible for attending the interview.</p>

<p>At the time of Interview the candidate should bring original certificates along with CV with contact details of 2 referees and submit the photocopies (attested) of the certificates, with a recent passport size photograph.</p>

<p>Advertisement: www.actrec.gov.in/data%20files/2014/Walk-in-Research-Fellow-26-12-14.doc</p>
]]></description>
</item>
<item>
	<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/bookmarks/view/20471/bioinformatics-scripts</guid>
	<pubDate>Thu, 22 Jan 2015 22:29:39 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/20471/bioinformatics-scripts</link>
	<title><![CDATA[Bioinformatics Scripts]]></title>
	<description><![CDATA[<p>Some of the useful bioinformatics scripts.</p>
<p>For example ... contig-stats.pl is a Perl script that will automatically describe features of a sequence assembly.</p>
<p>http://milkweedgenome.org/?q=scripts</p><p>Address of the bookmark: <a href="http://milkweedgenome.org/?q=scripts" rel="nofollow">http://milkweedgenome.org/?q=scripts</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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