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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/26999?offset=1370</link>
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	<description><![CDATA[]]></description>
	
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38892/wtdbg2-a-fuzzy-bruijn-graph-approach-to-long-noisy-reads-assembly</guid>
	<pubDate>Mon, 04 Feb 2019 04:53:47 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38892/wtdbg2-a-fuzzy-bruijn-graph-approach-to-long-noisy-reads-assembly</link>
	<title><![CDATA[wtdbg2: A fuzzy Bruijn graph approach to long noisy reads assembly]]></title>
	<description><![CDATA[<p><span>Wtdbg2 is a&nbsp;</span><em>de novo</em><span>&nbsp;sequence assembler for long noisy reads produced by PacBio or Oxford Nanopore Technologies (ONT). It assembles raw reads without error correction and then builds the consensus from intermediate assembly output.&nbsp;</span></p>
<pre>./wtdbg2 -x rs -g 4.6m -t 16 -i reads.fa.gz -fo prefix
./wtpoa-cns -t 16 -i prefix.ctg.lay.gz -fo prefix.ctg.fa</pre><p>Address of the bookmark: <a href="https://github.com/ruanjue/wtdbg2" rel="nofollow">https://github.com/ruanjue/wtdbg2</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39856/tritex-sequence-assembly-pipeline-for-triticeae-genomes</guid>
	<pubDate>Tue, 20 Aug 2019 09:47:14 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39856/tritex-sequence-assembly-pipeline-for-triticeae-genomes</link>
	<title><![CDATA[TRITEX sequence assembly pipeline for Triticeae genomes]]></title>
	<description><![CDATA[<div>
<p>The pipeline is open-source and hosted in a public Bitbucket&nbsp;<a href="https://bitbucket.org/tritexassembly/tritexassembly.bitbucket.io/src/master/">repository</a>.</p>
</div>
<div>
<p>TRITEX has been run on highly inbred genotypes of barley (<em>Hordeum vulgare</em>), tetraploid wheat (<em>Triticum turgidum</em>) and hexaploid wheat (<em>T. aestivum</em>) with reasonable results: super-scaffold N50 values in the range of dozens of Mb and pseudomolecules with better gene space representation than a BAC-by-BAC assembly. It has never been tested and is not expected to work on heterozygous or autopolyploid genomes.</p>
</div>
<div>
<p>A protocol for generating chromosome-conformation capture sequencing (Hi-C) data suitable for use with the pipeline is described in&nbsp;<a href="https://bio-protocol.org/e2955">Himmelbach et al. 2018</a>. Refer to the&nbsp;<a href="https://www.10xgenomics.com/resources/technical-notes/">technical notes</a>&nbsp;of 10X Genomics on how to generate Chromium data.</p>
</div><p>Address of the bookmark: <a href="https://tritexassembly.bitbucket.io/" rel="nofollow">https://tritexassembly.bitbucket.io/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/29479/how-to-install-perl-modules-on-mac-os-x-in-easy-steps</guid>
	<pubDate>Thu, 20 Oct 2016 07:26:29 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/29479/how-to-install-perl-modules-on-mac-os-x-in-easy-steps</link>
	<title><![CDATA[How to install Perl modules on Mac OS X in easy steps !!]]></title>
	<description><![CDATA[<p>Today at work, I learned how to install Perl modules using&nbsp;<a href="http://en.wikipedia.org/wiki/CPAN">CPAN</a>. It&rsquo;s a lot easier than I thought.</p><p>You see, for the past couple of years, I&rsquo;ve been a bit frustrated because OS X does not come with a whole lot of Perl modules pre-installed, and for all I googled, I couldn&rsquo;t find an &ldquo;idiot&rsquo;s&rdquo; guide for moderately-savvy-but-not-expert users like myself to install modules and dependencies on demand.</p><p>The only instructions I could find point to&nbsp;<a href="http://fink.sourceforge.net/">Fink</a>, which basically installs modules in a path that isn&rsquo;t included in the Perl @INC variable, meaning you have to manually specify the full path to the modules in every script &mdash; which is not a lot of fun if you&rsquo;re developing on OS X and deploying on Red Hat, for instance.</p><p>Moreover, Fink doesn&rsquo;t seem to make every module available, and it&rsquo;s not very easy to determine which Fink package you need to install if you need a particular module.</p><p>So, with a script that called on several apparently unavailable modules, and a deadline looming, I finally decided to suck it up and figure out how to use CPAN to install them:</p><h4>1) Make sure you have the Apple Developer Tools (XCode) installed.</h4><p>These are on one of your install discs, or available as a huge but free download from the&nbsp;<a href="https://developer.apple.com/xcode/">Apple Developer Connection</a>&nbsp;[free registration required] or the Mac App Store. I thought I had them, but apparently when we upgraded that computer to Tiger, they went missing.</p><p>If you don&rsquo;t have this stuff installed, your installation will fail with errors about unavailable commands.</p><h4>1.5) Install Command Line Tools (Recent XCode versions only)</h4><p>(Thank you to Tom Marchioro for informing me about this step.)</p><p>Older versions of XCode installed the command line tools (which are required to properly install CPAN modules) by default, but apparently newer ones do not. To check whether you have the command line tools already installed, run the following from the Terminal:</p><p><code>$ which make</code></p><p>This command checks the system for the &ldquo;<code>make</code>&rdquo; tool. If it spits out something like&nbsp;<code>/usr/bin/make</code>&nbsp;you&rsquo;re golden and can skip ahead to Step 2. If you just get a new prompt and no output, you&rsquo;ll need to install the tools:</p><ol>
<li>Launch XCode and bring up the Preferences panel.</li>
<li>Click on the Downloads tab</li>
<li>Click to install the Command Line Tools</li>
</ol><p>If you like, you can run&nbsp;<code>which make</code>&nbsp;again to confirm that everything&rsquo;s installed correctly.</p><h4>2) Configure CPAN.</h4><p><code>$ sudo perl -MCPAN -e shell</code></p><p><code>perl&gt; o conf init</code></p><p>This will prompt you for some settings. You can accept the defaults for almost everything (just hit &ldquo;return&rdquo;). The two things you must fill in are the path to&nbsp;<code>make</code>&nbsp;(which should be&nbsp;<code>/usr/bin/make</code>&nbsp;or the value returned when you run&nbsp;<code>which make</code>&nbsp;from the command line) and your choice of CPAN mirrors (which you actually choose don&rsquo;t really matter, but it won&rsquo;t let you finish until you select at least one). If you use a proxy or a very restrictive firewall, you may have to configure those settings as well.</p><p>If you skip Step 2, you may get errors about&nbsp;<code>make</code>&nbsp;being unavailable.</p><h4>3) Upgrade CPAN</h4><p><code>$ sudo perl -MCPAN -e 'install Bundle::CPAN'</code></p><p>Don&rsquo;t forget the&nbsp;<code>sudo</code>, or it&rsquo;ll fail with permissions errors, probably when doing something relatively unimportant like installing&nbsp;<code>man</code>&nbsp;files.</p><p>This will spend a long time downloading, testing, and compiling various files and dependencies. Bear with it. It will prompt you a few times about dependencies. You probably want to enter &ldquo;yes&rdquo;. I agreed to everything it asked me, and everything turned out fine. YMMV of course. If everything installs properly, it&rsquo;ll give you an &ldquo;OK&rdquo; at the end.</p><h4>4) Install your modules. For each module&hellip;.</h4><p><code>$ sudo perl -MCPAN -e 'install Bundle::Name'</code></p><p>or</p><p><code>$ sudo perl -MCPAN -e 'install Module::Name'</code></p><p>This will install the module&nbsp;<em>and</em>&nbsp;its dependencies. Nice, eh? Again, don&rsquo;t forget the&nbsp;<code>sudo</code>.</p><p>The first time you run this after upgrading CPAN, it may prompt you to configure again (see Step 2). If you accept its offer to try to configure itself automatically, it may just run through everything without a problem.</p><p>There are a couple of potential pitfalls with specific modules (such as the<code>LWP::UserAgent</code>&nbsp;/&nbsp;<code>HEAD</code>&nbsp;issue), but most have workarounds, and I haven&rsquo;t run into anything that wasn&rsquo;t easily recoverable.</p><p>And that&rsquo;s it!</p><p>Did you find this useful? Is there anything I missed?</p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/29953/traineeship-at-jawaharlal-nehru-tropical-botanic-garden-and-research-institute</guid>
  <pubDate>Fri, 25 Nov 2016 08:07:59 -0600</pubDate>
  <link></link>
  <title><![CDATA[Traineeship at JAWAHARLAL NEHRU TROPICAL BOTANIC GARDEN AND RESEARCH INSTITUTE]]></title>
  <description><![CDATA[
<p>JAWAHARLAL NEHRU TROPICAL BOTANIC GARDEN AND RESEARCH INSTITUTE</p>

<p>THIRUVANANTHAPURAM - 695 562</p>

<p>Traineeship on Bioinformatics(2)</p>

<p>First class M.Sc. Bioinformatics/ Agriculture/ Botany/ Biotechnology @ Rs.8000</p>

<p>Those candidates who fulfill the above criteria may attend a walk PCC Coordinator in-interview on 28th November 2016 at Saraswathy Thangavelu center, JNTBGRI, Puthenthope, Thiruvananthapuram between at 10.00 am and 2.00 pm with all the relevant document and testimonials.</p>

<p>No TA/DA will be given to candidates for attending the interview.</p>

<p>More Info : http://jntbgri.res.in/downloads/traineeship_notification.pdf</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40946/free-genomics-data</guid>
	<pubDate>Fri, 07 Feb 2020 14:08:31 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40946/free-genomics-data</link>
	<title><![CDATA[Free Genomics data !]]></title>
	<description><![CDATA[<p><span>The specimens were collected by the Oxford Wytham Woods and Edinburgh Lohse lab teams. DNA extraction and sequencing was carried out by the Sanger Institute Scientific Operations teams. Assemblies were carried out by the Tree of Life team (Shane McCarthy) and colleagues in Pacific Biosciences (Jonas Korlach).</span></p>
<p><a href="https://www.darwintreeoflife.org/an-initial-set-of-raw-genome-assemblies-from-the-darwin-tree-of-life-project/">https://www.darwintreeoflife.org/an-initial-set-of-raw-genome-assemblies-from-the-darwin-tree-of-life-project/</a></p><p>Address of the bookmark: <a href="https://www.darwintreeoflife.org/an-initial-set-of-raw-genome-assemblies-from-the-darwin-tree-of-life-project/" rel="nofollow">https://www.darwintreeoflife.org/an-initial-set-of-raw-genome-assemblies-from-the-darwin-tree-of-life-project/</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41459/jcvipython-utility-libraries-on-genome-assembly-annotation-and-comparative-genomics</guid>
	<pubDate>Tue, 17 Mar 2020 06:19:06 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41459/jcvipython-utility-libraries-on-genome-assembly-annotation-and-comparative-genomics</link>
	<title><![CDATA[JCVI:Python utility libraries on genome assembly, annotation and comparative genomics]]></title>
	<description><![CDATA[<p>Collection of Python libraries to parse bioinformatics files, or perform computation related to assembly, annotation, and comparative genomics.</p>
<p>https://github.com/tanghaibao/jcvi</p>
<p>More at https://github.com/tanghaibao/jcvi/wiki</p><p>Address of the bookmark: <a href="https://github.com/tanghaibao/jcvi" rel="nofollow">https://github.com/tanghaibao/jcvi</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29603/statistical-for-biological-research</guid>
	<pubDate>Thu, 03 Nov 2016 04:59:48 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29603/statistical-for-biological-research</link>
	<title><![CDATA[Statistical for biological research]]></title>
	<description><![CDATA[<p>There is no disputing the importance of statistical analysis in biological research, but too often it is considered only after an experiment is completed, when it may be too late.</p>
<p>This collection highlights important statistical issues that biologists should be aware of and provides practical advice to help them improve the rigor of their work.</p>
<p><em>Nature Methods</em>' <strong><a href="http://www.nature.com/collections/qghhqm/pointsofsignificance">Points of Significance</a></strong> column on statistics explains many key statistical and experimental design concepts. <strong><a href="http://www.nature.com/collections/qghhqm/resources">Other resources</a></strong> include an online plotting tool and links to statistics guides from other publishers.</p><p>Address of the bookmark: <a href="http://www.nature.com/collections/qghhqm" rel="nofollow">http://www.nature.com/collections/qghhqm</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41599/haslr-a-hybrid-assembler-which-uses-both-second-and-third-generation-sequencing-reads</guid>
	<pubDate>Mon, 04 May 2020 02:04:03 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41599/haslr-a-hybrid-assembler-which-uses-both-second-and-third-generation-sequencing-reads</link>
	<title><![CDATA[HASLR: a hybrid assembler which uses both second and third generation sequencing reads]]></title>
	<description><![CDATA[<p><span>HASLR, a hybrid assembler which uses both second and third generation sequencing reads to efficiently generate accurate genome assemblies. Our experiments show that HASLR is not only the fastest assembler but also the one with the lowest number of misassemblies on all the samples compared to other tested assemblers. Furthermore, the generated assemblies in terms of contiguity and accuracy are on par with the other tools on most of the samples. Availability. HASLR is an open source tool available at https://github.com/vpc-ccg/haslr.</span></p><p>Address of the bookmark: <a href="https://github.com/vpc-ccg/haslr" rel="nofollow">https://github.com/vpc-ccg/haslr</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/file/view/29652/bioistats-ppt</guid>
	<pubDate>Tue, 08 Nov 2016 07:09:01 -0600</pubDate>
	<link>https://bioinformaticsonline.com/file/view/29652/bioistats-ppt</link>
	<title><![CDATA[Bioistats PPT]]></title>
	<description><![CDATA[<p>Basics concepts of&nbsp;Probability: The Study of Randomness</p><p>Biostatistics is the application of statistics to a wide range of topics in biology. The science of biostatistics encompasses the design of biological experiments, especially in medicine, pharmacy, agriculture and fishery; the collection, summarization, and analysis of data from those experiments; and the interpretation of, and inference from, the results. A major branch of this is medical biostatistics, which is exclusively concerned with medicine and health.</p>]]></description>
	<dc:creator>Jit</dc:creator>
	<enclosure url="https://bioinformaticsonline.com/file/download/29652" length="1663809" type="application/pdf" />
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42941/csa-a-high-throughput-chromosome-scale-assembly-pipeline-for-vertebrate-genomes</guid>
	<pubDate>Wed, 10 Mar 2021 06:13:49 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42941/csa-a-high-throughput-chromosome-scale-assembly-pipeline-for-vertebrate-genomes</link>
	<title><![CDATA[CSA: A high-throughput chromosome-scale assembly pipeline for vertebrate genomes]]></title>
	<description><![CDATA[<p>The pipeline can use information from scaffolded assemblies (for example from HiC or 10X Genomics), or even from diverged (~65-100 Mya) reference genomes for ordering the contigs and thus support the assembly process. This typically results in improved contig N50 when compared to current state of the art methods.</p>
<p><img src="https://github.com/HMPNK/CSA2.6/raw/master/Fig1.png" alt="image" style="border: 0px;"></p>
<p>For smaller vertebrate genomes (~1 Gbp) chromosome scale assemblies can be achieved within 12h on high-end Desktop computers (Intel i7, 12 CPU threads, 128 GB RAM). Larger mammalian genomes (~3Gbp) can be processed within 15-18 h on server equipment (Xeon, 96 CPU threads, 1TB RAM).</p><p>Address of the bookmark: <a href="https://github.com/HMPNK/CSA2.6" rel="nofollow">https://github.com/HMPNK/CSA2.6</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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