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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/29280?offset=1230</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/opportunity/view/19086/postdoctoral-fellowship-in-bioinformatics</guid>
  <pubDate>Sat, 08 Nov 2014 14:41:14 -0600</pubDate>
  <link></link>
  <title><![CDATA[Postdoctoral fellowship in Bioinformatics]]></title>
  <description><![CDATA[
<p>A two-year post-doctoral position is available in the Biocomputing group of the Sapienza University led by Anna Tramontano to work on either genomics research or structural bioinformatics, focusing on the study of relevant biomedical problems.<br />The ideal candidate should be motivated and talented, hold a PhD degree, have good programming skills, a grasp of statistical methods and an understanding of biology.<br />Experience in the development of computational biology methods would be an added value.</p>

<p>Good communication skills and fluency in spoken and written English are required.<br />Please apply sending a curriculum vitae, the names of at least two referees and a letter of motivation describing past experience and future goals to anna.tramontano@uniroma1.it with subject: “Application for post-doctoral position November 2014 YOUR LAST NAME”</p>

<p>Deadline: No later than November 28th, 2014.<br />Duration: 2 years</p>

<p>Salary on grant: Commeasured to the experience of the candidate<br />Contact Person (Referent): Anna Tramontano<br />Ref. E-Mail: anna.tramontano@uniroma1.it<br />Group Web Page: http:/www.biocomputing.it</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43273/understanding-kmer</guid>
	<pubDate>Wed, 18 Aug 2021 04:27:51 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43273/understanding-kmer</link>
	<title><![CDATA[Understanding kmer !]]></title>
	<description><![CDATA[<p><a href="https://en.wikipedia.org/wiki/k-mer">What is a&nbsp;<em>k-mer</em>&nbsp;anyway?</a><span>&nbsp;A&nbsp;</span><em>k-mer</em><span>&nbsp;is just a sequence of&nbsp;</span><em>k</em><span>&nbsp;characters in a string (or nucleotides in a DNA sequence). Now, it is important to remember that to get&nbsp;</span><em>all k-mers</em><span>&nbsp;from a sequence you need to get the first&nbsp;</span><em>k</em><span>&nbsp;characters, then move just a single character for the start of the next&nbsp;</span><em>k-mer</em><span>&nbsp;and so on. Effectively, this will create sequences that overlap in&nbsp;</span><code>k-1</code><span>&nbsp;positions.</span></p><p>Address of the bookmark: <a href="https://bioinfologics.github.io/post/2018/09/17/k-mer-counting-part-i-introduction/" rel="nofollow">https://bioinfologics.github.io/post/2018/09/17/k-mer-counting-part-i-introduction/</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/19137/centre-for-systems-biology-bioinformatics-panjab-university-vacancy-of-research-fellow</guid>
  <pubDate>Wed, 12 Nov 2014 06:18:54 -0600</pubDate>
  <link></link>
  <title><![CDATA[Centre for Systems Biology &amp; Bioinformatics, Panjab University vacancy of Research Fellow]]></title>
  <description><![CDATA[
<p>Applications are invited along with complete bio-data and attested copies of certificates of qualifications, experience etc. for the one post of <br />Research Fellow and one post of Program Assistant under PURSE Grant of the University in Centre for Systems Biology &amp; Bioinformatics, UIEAST, Panjab University, Chandigarh which is tenable till the period of the project</p>

<p>Essential Qualification<br />For Research Fellow:-<br />M.Sc. in Systems Biology and Bioinformatics / Life<br />Sciences with minimum 55% marks.<br />Preference will be given to NET/GATE/ICMR qualified candidates without fellowship however, candidates who have cleared the Panjab University Ph.D. entrance test in Systems Biology &amp; Bioinformatics will also be eligible. </p>

<p>Applications should be reach on or before 19-11-2014 in the office of the undersigned. Interview will be held on 21-11-2014 in the office of the Coordinator, Centre for Systems Biology &amp; Bioinformatics, South Campus, Block-3, Sector-25, Panjab University, Chandigarh. No TA/DA will be paid. </p>

<p>more at http://jobs.puchd.ac.in/includes/jobs/2014/20141110143634-Advertisement.pdf</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43614/mitoz-a-toolkit-for-animal-mitochondrial-genome-assembly-annotation-and-visualization</guid>
	<pubDate>Tue, 30 Nov 2021 23:23:57 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43614/mitoz-a-toolkit-for-animal-mitochondrial-genome-assembly-annotation-and-visualization</link>
	<title><![CDATA[MitoZ: a toolkit for animal mitochondrial genome assembly, annotation and visualization]]></title>
	<description><![CDATA[<p>MitoZ, consisting of independent modules of <em>de novo</em> assembly, findMitoScaf (find Mitochondrial Scaffolds), annotation and visualization, that can generate mitogenome assembly together with annotation and visualization results from HTS raw reads.</p>
<p>https://academic.oup.com/nar/article/47/11/e63/5377471</p><p>Address of the bookmark: <a href="https://github.com/linzhi2013/MitoZ" rel="nofollow">https://github.com/linzhi2013/MitoZ</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/19248/bioinformatics-jrfrasrf-position-at-institute-of-cytology-and-preventive-oncology-icpo</guid>
  <pubDate>Wed, 19 Nov 2014 20:16:32 -0600</pubDate>
  <link></link>
  <title><![CDATA[Bioinformatics JRF/RA/SRF position at Institute of Cytology and Preventive Oncology (ICPO)]]></title>
  <description><![CDATA[
<p>Institute of Cytology and Preventive Oncology (ICPO) I-7, Sector-39, Noida-201301</p>

<p>Candidates having the below mentioned qualifications may appear for walk in interview at ICPO on 2nd December 2014 between 10.00 AM and 12:00 PM under the below time bound projects under Dr. Subhash M. Agarwal, Scientist C. The post is purely temporary and co-terminus with the project.</p>

<p>Research Assistant (One)<br />25650/- consolidated<br />Discovery of EGFR secondary mutant inhibitors using structure based screening approach (ICMR)<br />Duration: 7 months</p>

<p>Essential: M.Sc./ M.Tech in Bioinformatics or any other related subject with good academic record.</p>

<p>Desirable: Experience in scripting and molecular docking.<br />	<br />Below 30 years</p>

<p>Junior Research Fellow (One)</p>

<p>16,000 + 30% HRA = Rs. 20800/-</p>

<p>Identification of novel inhibitors targeting EGFR using an integrated ligand and structure based approach (DBT)</p>

<p>Duration: 9 months</p>

<p>Essential: M.Sc./ M.Tech in Bioinformatics or any other related subject with good academic record. Candidates with CSIR-UGC / ICMR, NET qualification will be preferred</p>

<p>Desirable: Experience in scripting, QSAR and molecular docking.<br />	<br />Below 28 years</p>

<p>Interested eligible candidates may send their applications with Bio-data by email at (smagarwal@gmail.com) or by post addressed to Dr. Subhash M Agarwal, Scientist C, Institute of Cytology and Preventive Oncology (ICPO) I-7, Sector-39, Noida-201301 so as to reach latest by 1st December, 2014. The candidates may appear for interview at ICPO along with 3 copies of CV, photo and relevant certificates of qualifications in original and reprints of publications at the time of interview. It should be noted that No TA/DA will be paid for the walk in Interview.</p>

<p>Advertisement: www.icpo.org.in/advt-walk-in-interview.docx</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/news/view/19556/genome-origami</guid>
	<pubDate>Fri, 12 Dec 2014 22:48:17 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/19556/genome-origami</link>
	<title><![CDATA[Genome Origami]]></title>
	<description><![CDATA[<p>There are several interesting factoid about our genomes, one of them is their folding. If we stretched out the DNA in a single cell, which is only a few millionths of an inch wide, it would span more than six feet. In other word, the size of six feet DNA fold themself to fit in a few millionths of an inch wide space. These DNA folding is a dynamic process that changes over time (!!). Researchers around the world have been trying to understand how DNA folds itself up so efficiently, and a recent post on the NIH Director&rsquo;s Blog highlights new research illustrating how the human genome folds inside the cell&rsquo;s nucleus, as well as how DNA folding affects gene regulation. The research team created this delightful video that demonstrates the principles involved using origami art.</p><p>http://bioinformaticsonline.com/videolist/watch/19555/a-3d-map-of-the-human-genome<br /><br />Researchers have been working to determine how cells regulate gene expression for nearly as long as we&rsquo;ve known about DNA. How, for example, do nerve cells know to turn off only nerve cell genes and turn off bone cell genes? DNA folding loops are part of the answer. This research team, which published their findings in a paper in Cell http://www.cell.com/cell/abstract/S0092-8674%2814%2901497-4 , found that the number of loops is much lower than expected. There are only 10,000 loops instead of the predicted millions, and they form on/off switches in DNA.<br /><br /></p><p>More at http://www.eurekalert.org/pub_releases/2014-12/ru-3mr121114.php</p><p>Reference http://www.cell.com/cell/abstract/S0092-8674%2814%2901497-4</p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/43728/short-read-assembly-using-spades</guid>
	<pubDate>Mon, 31 Jan 2022 07:18:16 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/43728/short-read-assembly-using-spades</link>
	<title><![CDATA[Short-read assembly using Spades !]]></title>
	<description><![CDATA[<h2 id="short-read-assembly-a-comparison">If we only had Illumina reads, we could also assemble these using the tool Spades.</h2><p>You can try this here, or try it later on your own data.</p><h2 id="get-data">Get data</h2><p>We will use the same Illumina data as we used above:</p><ul>
<li>illumina_R1.fastq.gz: the Illumina forward reads</li>
<li>illumina_R2.fastq.gz: the Illumina reverse reads</li>
</ul><h2 id="assemble">Assemble</h2><p>Run Spades:</p><div><pre>spades.py -1 illumina_R1.fastq.gz -2 illumina_R2.fastq.gz --careful --cov-cutoff auto -o spades_assembly_all_illumina
</pre></div><ul>
<li><code>-1</code>&nbsp;is input file of forward reads</li>
<li><code>-2</code>&nbsp;is input file of reverse reads</li>
<li><code>--careful</code>&nbsp;minimizes mismatches and short indels</li>
<li><code>--cov-cutoff auto</code>&nbsp;computes the coverage threshold (rather than the default setting, &ldquo;off&rdquo;)</li>
<li><code>-o</code>&nbsp;is the output directory</li>
</ul><h2 id="results">Results</h2><p>Move into the output directory and look at the contigs:</p><div><pre>infoseq contigs.fasta</pre></div>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/19545/walk-%E2%80%93-in-%E2%80%93-interview-agricultural-knowledge-management-unit-indian-agricultural-research-institute-new-delhi-110012</guid>
  <pubDate>Fri, 12 Dec 2014 21:33:02 -0600</pubDate>
  <link></link>
  <title><![CDATA[WALK – IN – INTERVIEW @ Agricultural Knowledge Management Unit Indian Agricultural Research Institute, New Delhi-110012]]></title>
  <description><![CDATA[
<p>Walk-in-interview for the following temporary positions will be conducted on 20th December 2014 (between 10:00 AM to 01:00 PM) at Agricultural Knowledge Management Unit, A0 block (Ground Floor), LBS Building, Indian Agricultural Research Institute, New Delhi-110012:</p>

<p>1 Dr. A.K.Mishra Coordinator &amp; PI (BTISnet)</p>

<p>Traineeship (two) for one year</p>

<p>Rs. 5000/- (consolidated)</p>

<p>M.Sc. (Bioinformatics) with 60 % marks from a recognized University</p>

<p>20-12-2014 (10:00 AM -11:00 AM)</p>

<p>Studentship (four) for one year</p>

<p>Rs. 2500/- (consolidated)</p>

<p>Final year M.Sc./ M.Tech (Bioinformatics) Students from a recognized University</p>

<p>20-12-2014 (11:00 AM- 1:00 PM)</p>

<p>The positions are purely temporary and co-terminus with the DBT Programme. Eligible candidates are requested to submit the application form in the prescribed format along with original certificates/ documents (Degree, Marks sheets, Work experience, if any) at the time of interview. No TA/DA will be paid. Maximum age limit is 28 years for all positions. Age relaxation of 5 yrs for SC/ST and woman candidates and 3 years for OBC candidates will be given. Canvassing in any form invites disqualification.</p>

<p>Advertisement: http://www.iari.res.in/files/BIC-08122014-20141208-172344.pdf</p>
]]></description>
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