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<channel>
	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/44722?offset=340</link>
	<atom:link href="https://bioinformaticsonline.com/related/44722?offset=340" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/45303/the-tree-that-learned-to-read-genomes</guid>
	<pubDate>Fri, 11 Sep 2026 00:51:02 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/45303/the-tree-that-learned-to-read-genomes</link>
	<title><![CDATA[The Tree That Learned to Read Genomes]]></title>
	<description><![CDATA[<p>Imagine trying to reconstruct a family tree when many family photographs are missing, some names are unclear, and different relatives remember the past differently. This is similar to the challenge scientists face when trying to understand how organisms are related. Their family records are genomes, and the family tree is a phylogenetic tree. With modern sequencing technologies, scientists now have access to thousands of genomes, but comparing them can be difficult, especially when genomes are incomplete or poorly annotated.</p><p>A recent study by Webster and Chapman introduces Buscogeny (https://github.com/Jwebster89/Buscogeny), an open-source bioinformatics pipeline designed to make this process easier. The tool uses BUSCO (Benchmarking Universal Single-Copy Orthologs), which identifies conserved genes that are expected to occur as single copies in particular groups of organisms. These genes act like evolutionary landmarks, allowing researchers to compare genomes and investigate their relationships.</p><p>Buscogeny brings several steps of phylogenomic analysis into one workflow. It identifies BUSCO genes, extracts and aligns their sequences, removes unreliable regions, combines information from multiple genes, and uses the resulting data to construct a phylogenetic tree. It also provides quality-control information, helping researchers identify genomes that may be too incomplete for reliable analysis.</p><p>The authors demonstrate the usefulness of Buscogeny with bacterial and fungal genomes, including Alternaria. This is particularly valuable because fungal genomes can vary greatly in quality and annotation. Ultimately, Buscogeny helps transform massive amounts of genomic data into an understandable evolutionary story. Each DNA sequence becomes a clue, each conserved gene becomes a landmark, and together these clues reveal a picture of how life is connected.</p><p>More at&nbsp;https://link.springer.com/article/10.1007/s10123-025-00752-6?</p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/view/1926</guid>
	<pubDate>Sun, 11 Aug 2013 11:42:32 -0500</pubDate>
	<link>https://bioinformaticsonline.com/view/1926</link>
	<title><![CDATA[Want to Know which genome assembler rule the world ?]]></title>
	<description><![CDATA[<p><span><strong>Assemblathon 2</strong>: evaluating de novo methods of genome assembly&nbsp;</span></p><p><span><a href="http://www.gigasciencejournal.com/content/2/1/10/abstract">http://www.gigasciencejournal.com/content/2/1/10/abstract</a></span></p><p><span><a href="http://blogs.nature.com/news/2013/07/genome-assembly-contest-prompts-soul-searching.html">http://blogs.nature.com/news/2013/07/genome-assembly-contest-prompts-soul-searching.html</a></span></p><p><a href="http://assemblathon.org/post/44431915644/feedback-and-analysis-of-the-assemblathon-2-p">http://assemblathon.org/post/44431915644/feedback-and-analysis-of-the-assemblathon-2-p</a></p><p>&nbsp;</p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/44002/interesting-bioinformatics-resources</guid>
	<pubDate>Fri, 11 Nov 2022 06:30:46 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44002/interesting-bioinformatics-resources</link>
	<title><![CDATA[Interesting Bioinformatics Resources !]]></title>
	<description><![CDATA[<p>1. a reproducible workflow.&nbsp;<a href="https://www.youtube.com/watch?v=s3JldKoA0zw">https://www.youtube.com/watch?v=s3JldKoA0zw</a>&nbsp;This two minute video will change your mind on reproducible research&nbsp;</p><p>2. Parallel sequencing lives, or what makes large sequencing projects successful&nbsp;<a href="https://academic.oup.com/gigascience/article/6/11/gix100/4557140?login=false">https://academic.oup.com/gigascience/article/6/11/gix100/4557140?login=false</a></p><p>3. Common-sense approaches to sharing tabular data alongside publication&nbsp;<a href="https://www.sciencedirect.com/science/article/pii/S2666389921002300">https://www.sciencedirect.com/science/article/pii/S2666389921002300</a></p><p>4. A Reproducible Data Analysis Workflow with R Markdown, Git, Make, and Docker&nbsp;<a href="https://psyarxiv.com/8xzqy/">https://psyarxiv.com/8xzqy/</a></p><p>5. Practical Computational Reproducibility in the Life Sciences&nbsp;<a href="https://www.cell.com/cell-systems/fulltext/S2405-4712(18)30140-6">https://www.cell.com/cell-systems/fulltext/S2405-4712(18)30140-6</a></p><p>6. A video by Dr.Keith A. Baggerly from MD Anderson [The Importance of Reproducible Research in High-Throughput Biology](<a href="https://www.youtube.com/watch?v=7gYIs7uYbMo">https://www.youtube.com/watch?v=7gYIs7uYbMo</a>) highly recommended.</p><p>7. Ten Simple Rules for Reproducible Computational Research&nbsp;<a href="http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1003285">http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1003285</a>)</p><p>8. Good Enough Practices in Scientific Computing&nbsp;<a href="http://arxiv.org/abs/1609.00037">http://arxiv.org/abs/1609.00037</a>&nbsp;</p><p>9. Best Practices for Scientific Computing&nbsp;<a href="https://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.1001745">https://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.1001745</a></p><p>10. A Quick Guide to Organizing Computational Biology Projects&nbsp;<a href="http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.100042">http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.100042</a>&nbsp; A must read for computational biologists!</p><p>11. Reproducibility of computational workflows is automated using continuous analysis&nbsp;<a href="https://www.nature.com/articles/nbt.3780">https://www.nature.com/articles/nbt.3780</a></p><p>12. Five selfish reasons to work reproducibly&nbsp;<a href="https://genomebiology.biomedcentral.com/articles/10.1186/s13059-015-0850-7">https://genomebiology.biomedcentral.com/articles/10.1186/s13059-015-0850-7</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/40395/forbio-and-uib-course-introduction-to-phylogenetic-methods</guid>
	<pubDate>Mon, 16 Dec 2019 09:39:12 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/40395/forbio-and-uib-course-introduction-to-phylogenetic-methods</link>
	<title><![CDATA[ForBio and UiB course: Introduction to phylogenetic methods]]></title>
	<description><![CDATA[<p>The is an introductory course that is aimed at students who will need to preform phylogenetic analyses in their work, but who have little or no experience with phylogenetic analyses. The ForBio component of the course is focused on the practical aspects of phylogenetic analyses and students that have not attended the theoretical part of the course are expected to have read the relevant literature. The course will cover all basic aspects of phylogenetic analyses with emphasis on use of DNA data. Students will learn how to prepare their data, explore its properties and how to analyze it using distance, parsimony, likelihood and Bayesian methods. In the last two days students will also get an introduction to molecular dating with focus on the use of BEAST and to comparative methods used to study the evolution of discrete and continuous traits.</p><p><a href="https://www.forbio.uio.no/events/courses/2020/Bergen_Phylogenetics_2020.html">https://www.forbio.uio.no/events/courses/2020/Bergen_Phylogenetics_2020.html</a></p><p><a href="https://uio.us13.list-manage.com/track/click?u=12ea100a4bd384fb9ba660c5e&amp;id=527fe56cca&amp;e=fe181c3ca8" target="_blank">ForBio travel grants</a><br />We have changed our travel grants rules. ForBio offers both incoming and outgoing travel grants to fund collaborations between<strong>&nbsp;ForBio members based in Norway</strong>&nbsp;and taxonomic experts up to<strong>&nbsp;NOK 14,000</strong>. Grants are given for taxonomic training with relevance to the main research project of the applicant, and aim to allow the student to do taxonomic research with specific experts, work with particular collections, or learn new preparation techniques directly from experts.&nbsp; Participation in external courses, conferences, fieldwork or other kinds of activities which are not&nbsp;classified as expert-in-training visits are no longer eligible for support.&nbsp; There are two application deadlines:&nbsp;<strong>March 1st</strong><strong>&nbsp;</strong>2020.</p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/34702/run-miniasm-assembler-on-nanopore-reads</guid>
	<pubDate>Mon, 18 Dec 2017 04:07:50 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/34702/run-miniasm-assembler-on-nanopore-reads</link>
	<title><![CDATA[Run miniasm assembler on nanopore reads !]]></title>
	<description><![CDATA[<p>Miniasm is a very fast OLC-based&nbsp;<em>de novo</em>&nbsp;assembler for noisy long reads. It takes all-vs-all read self-mappings (typically by&nbsp;<a href="https://github.com/lh3/minimap">minimap</a>) as input and outputs an assembly graph in the&nbsp;<a href="https://github.com/pmelsted/GFA-spec/blob/master/GFA-spec.md">GFA</a>&nbsp;format. Different from mainstream assemblers, miniasm does not have a consensus step. It simply concatenates pieces of read sequences to generate the final&nbsp;<a href="http://wgs-assembler.sourceforge.net/wiki/index.php/Celera_Assembler_Terminology">unitig</a>&nbsp;sequences. Thus the per-base error rate is similar to the raw input reads.</p><p>Find the detail of the reads repeats:</p><blockquote><p>fq2fa ONT_A.fastq ONT_A.fasta&nbsp;<br /><br />minimap2 -xava-ont ONT_A.fasta ONT_A.fasta -t10 -X &gt; AONT.paf&nbsp;<br /><br />awk '{if($1==$6){print}}' AONT.paf &gt; AONTself.paf&nbsp;<br /><br />awk '$5=="-"' AONTself.paf | awk '{print $1}'| sort|uniq &gt; invertedrepeat.list</p></blockquote><p>Generated a few palindrome and repeats plots (highlighting only repeats largest than 10, 20 and 30 kb)</p><blockquote><p>minidot -f 5 -m 30000 AONTself.paf &gt; AONTself30000.eps&nbsp;<br />sed 's/_template_pass_FAH31515//' AONTself30000.eps &gt; AONTself30000final.eps&nbsp;<br /><br />minidot -f 5 -m 20000 AONTself.paf &gt; AONTself20000.eps&nbsp;<br />sed 's/_template_pass_FAH31515//' AONTself20000.eps &gt; AONTself20000final.eps&nbsp;<br /><br />minidot -f 5 -m 10000 AONTself.paf &gt; AONTself10000.eps&nbsp;<br />sed 's/_template_pass_FAH31515//' AONTself10000.eps &gt; AONTself10000final.eps&nbsp;</p></blockquote><p>Assemble with miniasm:</p><blockquote><p>miniasm -f ONT_A.fasta AONT.paf &gt; AONT.gfa&nbsp;</p><p>grep '^S' AONT.gfa |awk '{print "&gt;"$2"\n"$3}' &gt; AONT_miniasm.fasta&nbsp;<br /><br />minimap2 -xasm10 AONT_miniasm.fasta AONT_miniasm.fasta -t1 -X &gt; AONT_miniasm.paf&nbsp;<br /><br />awk '{if($1==$6){print}}' AONT_miniasm.paf &gt; AONT_miniasm_self.paf&nbsp;<br /><br />minidot -f 5 -m 10000 AONT_miniasm_self.paf &gt; AONT_miniasm_self10000.eps&nbsp;</p></blockquote><p>Njoy the assembly !</p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/43954/elgg-installation-steps</guid>
	<pubDate>Wed, 07 Sep 2022 00:43:53 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/43954/elgg-installation-steps</link>
	<title><![CDATA[Elgg Installation steps !]]></title>
	<description><![CDATA[<p>Elgg is an open source social networking engine that allows the creation of social environments such as campus social networks and internal collaborative platforms for organizations. Elgg offers a number of social networking features including microblogging, messaging, file-sharing and groups. This tutorial will guide you through the process of installing Elgg on a Ubuntu 18.04 VPS.</p><h2 id="Prerequisites">Prerequisites</h2><ul>
<li>A fresh Vultr Cloud Compute instance with Ubuntu 18.04 and root access.</li>
</ul><h2 id="Step_1__Install_Apache__MySQL__and_PHP">Step 1: Install Apache, MySQL, and PHP</h2><p>Elgg requires MySQL, PHP, and a web server. Before you can install Elgg, you will need to install the Apache web server, MySQL, and PHP.</p><p>Update the repository list.</p><pre><code>apt-get update
</code></pre><p>Install the Apache web server.</p><pre><code>apt-get install apache2 -y
</code></pre><p>Install MySQL.</p><pre><code>apt-get install mysql-server -y
</code></pre><p>Complete the MySQL installation by executing the following command.</p><pre><code>/usr/bin/mysql_secure_installation
</code></pre><p>During the installation, you will be asked to enter a root password. Enter a secure password. This will be the MySQL root password.</p><pre><code>Would you like to setup VALIDATE PASSWORD plugin? [Y/N] N
New password: password
Re-enter new password: password
Remove anonymous users? [Y/N] Y
Disallow root login remotely? [Y/N] Y
Remove test database and access to it? [Y/N] Y
Reload privilege tables now? [Y/N] Y
</code></pre><p>Install PHP 7.2, as well as the PHP modules required by Elgg.</p><pre><code>apt-get install php7.2 libapache2-mod-php7.2 php7.2-common php7.2-sqlite3 php7.2-curl php7.2-intl php7.2-mbstring php7.2-xmlrpc php7.2-mysql php7.2-gd php7.2-xml php7.2-cli php7.2-zip -y
</code></pre><h2 id="Step_2__Create_a_MySQL_database_for_Elgg">Step 2: Create a MySQL database for Elgg</h2><p>Elgg will require a MySQL database. Log into the MySQL console.</p><pre><code>mysql -u root -p
</code></pre><p>When prompted for a password, enter the MySQL root password you set in step 1. Once you are logged in to the MySQL console, create a new database.</p><pre><code>CREATE DATABASE elgg;
</code></pre><p>Create a new MySQL user and grant it privileges to the newly created database. You can replace&nbsp;<code>username</code>&nbsp;and&nbsp;<code>password</code>&nbsp;with the username and password of your choice.</p><pre><code>GRANT ALL PRIVILEGES on elgg.* to 'username'@'localhost' identified by 'password';
FLUSH PRIVILEGES;
</code></pre><p>Exit the MySQL console.</p><pre><code>exit
</code></pre><h2 id="Step_3__Download_and_Install_Elgg">Step 3: Download and Install Elgg</h2><p>Download the latest version of Elgg.</p><pre><code>cd /var/www/html
rm -r index.html
wget https://elgg.org/download/elgg-2.3.7.zip
</code></pre><p>Unzip the downloaded archive and move the files to the root of the Apache web server.</p><pre><code>apt install unzip
unzip elgg-2.3.7.zip
mv ./elgg-2.3.7/* . &amp;&amp; rm elgg-2.3.7.zip &amp;&amp; rm -r elgg-2.3.7
</code></pre><p>Create a data directory for Elgg.</p><pre><code>sudo mkdir -p /var/www/html/data
</code></pre><p>Set the appropriate file permissions.</p><pre><code>sudo chown -R www-data:www-data /var/www/html/
sudo chmod -R 755 /var/www/html/
</code></pre><h2 id="Step_4__Configure_Apache_for_Elgg">Step 4: Configure Apache for Elgg</h2><p>Elgg requires the Apache rewrite module. Enable the Apache rewrite module.</p><pre><code>sudo a2enmod rewrite
</code></pre><p>Create an Apache configuration file for the Elgg installation.</p><pre><code>sudo nano /etc/apache2/sites-available/elgg.conf
</code></pre><p>Paste the following snippet to the file, replacing&nbsp;<code>example.com</code>&nbsp;with your own domain name.</p><pre><code>&lt;VirtualHost *:80&gt;
     DocumentRoot /var/www/html/
     ServerName example.com
     &lt;Directory /var/www/html/&gt;
          Options FollowSymlinks
          AllowOverride All
          Require all granted
     &lt;/Directory&gt;
     ErrorLog ${APACHE_LOG_DIR}/error.log
     CustomLog ${APACHE_LOG_DIR}/access.log combined
&lt;/VirtualHost&gt;
</code></pre><p>Enable the configuration and restart the Apache server.</p><pre><code> sudo a2ensite elgg.conf
 sudo systemctl restart apache2.service</code></pre>]]></description>
	<dc:creator>Abhi</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34246/unicycler-hybrid-assembly-pipeline-for-bacterial-genomes</guid>
	<pubDate>Fri, 10 Nov 2017 03:58:27 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34246/unicycler-hybrid-assembly-pipeline-for-bacterial-genomes</link>
	<title><![CDATA[Unicycler: Hybrid assembly pipeline for bacterial genomes]]></title>
	<description><![CDATA[<p><span>Unicycler is an assembly pipeline for bacterial genomes. It can assemble&nbsp;</span><a href="http://www.illumina.com/">Illumina</a><span>-only read sets where it functions as a&nbsp;</span><a href="http://cab.spbu.ru/software/spades/">SPAdes</a><span>-optimiser. It can also assembly long-read-only sets (</span><a href="http://www.pacb.com/">PacBio</a><span>&nbsp;or&nbsp;</span><a href="https://nanoporetech.com/">Nanopore</a><span>) where it runs a&nbsp;</span><a href="https://github.com/lh3/miniasm">miniasm</a><span>+</span><a href="https://github.com/isovic/racon">Racon</a><span>&nbsp;pipeline. For the best possible assemblies, give it both Illumina reads&nbsp;</span><em>and</em><span>&nbsp;long reads, and it will conduct a hybrid assembly.</span></p><p>Address of the bookmark: <a href="https://github.com/rrwick/Unicycler" rel="nofollow">https://github.com/rrwick/Unicycler</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36621/hapcut2-robust-and-accurate-haplotype-assembly-for-diverse-sequencing-technologies</guid>
	<pubDate>Tue, 15 May 2018 07:35:26 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36621/hapcut2-robust-and-accurate-haplotype-assembly-for-diverse-sequencing-technologies</link>
	<title><![CDATA[HapCUT2: robust and accurate haplotype assembly for diverse sequencing technologies]]></title>
	<description><![CDATA[HapCUT2 is a maximum-likelihood-based tool for assembling haplotypes from DNA sequence reads, designed to "just work" with excellent speed and accuracy. We found that previously described haplotype assembly methods are specialized for specific read technologies or protocols, with slow or inaccurate performance on others. With this in mind, HapCUT2 is designed for speed and accuracy across diverse sequencing technologies, including but not limited to:

NGS short reads (Illumina HiSeq)
clone-based sequencing (Fosmid or BAC clones)
SMRT reads (PacBio)
Oxford Nanopore reads
10X Genomics Linked-Reads
proximity-ligation (Hi-C) reads
high-coverage sequencing (&gt;40x coverage-per-SNP) using above technologies
combinations of the above technologies (e.g. scaffold long reads with Hi-C reads)
See below for specific examples of command line options and best practices for some of these technologies.

NOTE: At this time HapCUT2 is for diploid organisms only. VCF input should contain diploid variants.

If you use HapCUT2 in your research, please cite:

Edge, P., Bafna, V. &amp; Bansal, V. HapCUT2: robust and accurate haplotype assembly for diverse sequencing technologies. Genome Res. gr.213462.116 (2016). doi:10.1101/gr.213462.116<p>Address of the bookmark: <a href="https://github.com/vibansal/HapCUT2" rel="nofollow">https://github.com/vibansal/HapCUT2</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37291/transrate-understanding-your-transcriptome-assembly</guid>
	<pubDate>Fri, 13 Jul 2018 07:49:26 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37291/transrate-understanding-your-transcriptome-assembly</link>
	<title><![CDATA[transrate: Understanding your transcriptome assembly]]></title>
	<description><![CDATA[<p><span>Transrate is software for&nbsp;</span><em>de-novo</em><span>&nbsp;transcriptome assembly quality analysis. It examines your assembly in detail and compares it to experimental evidence such as the sequencing reads, reporting quality scores for contigs and assemblies. This allows you to choose between assemblers and parameters, filter out the bad contigs from an assembly, and help decide when to stop trying to improve the assembly.</span></p><p>Address of the bookmark: <a href="http://hibberdlab.com/transrate/index.html" rel="nofollow">http://hibberdlab.com/transrate/index.html</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38505/allhic-phasing-and-scaffolding-polyploid-genomes-based-on-hi-c-data</guid>
	<pubDate>Thu, 20 Dec 2018 12:03:32 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38505/allhic-phasing-and-scaffolding-polyploid-genomes-based-on-hi-c-data</link>
	<title><![CDATA[ALLHiC: Phasing and scaffolding polyploid genomes based on Hi-C data]]></title>
	<description><![CDATA[<p><span>The major problem of scaffolding polyploid genome is that Hi-C signals are frequently detected between allelic haplotypes and any existing stat of art Hi-C scaffolding program links the allelic haplotypes together. To solve the problem, we developed a new Hi-C scaffolding pipeline, called ALLHIC, specifically tailored to the polyploid genomes. ALLHIC pipeline contains a total of 5 steps:&nbsp;</span><em>prune</em><span>,&nbsp;</span><em>partition</em><span>,&nbsp;</span><em>rescue</em><span>,&nbsp;</span><em>optimize</em><span>&nbsp;and&nbsp;</span><em>build</em><span>.</span></p><p>Address of the bookmark: <a href="https://github.com/tangerzhang/ALLHiC/wiki" rel="nofollow">https://github.com/tangerzhang/ALLHiC/wiki</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>

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