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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/32719?offset=320</link>
	<atom:link href="https://bioinformaticsonline.com/related/32719?offset=320" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38526/versatile-genome-assembly-evaluation-with-quast-lg</guid>
	<pubDate>Fri, 21 Dec 2018 22:06:31 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38526/versatile-genome-assembly-evaluation-with-quast-lg</link>
	<title><![CDATA[Versatile genome assembly evaluation with QUAST-LG]]></title>
	<description><![CDATA[<p>QUAST-LG is an extension of&nbsp;<a href="http://cab.spbu.ru/software/quast/">QUAST</a>&nbsp;intended for evaluating large-scale genome assemblies (up to mammalian-size).</p>
<p>QUAST-LG&nbsp;is included in the QUAST&nbsp; package starting from version 5.0.0 (<a href="https://sourceforge.net/projects/quast/files/latest/download?source=files">download the latest release</a>). Run QUAST as usual and do not forget to add&nbsp;<span>‐‐large</span>&nbsp;option to your command!</p>
<p>A short list of the new features (see&nbsp;<a href="http://cab.spbu.ru/files/quast/latest-docs/CHANGES.txt">CHANGES</a>&nbsp;for all):</p>
<ul>
<li>Significant speedup achieved by both&nbsp;use of new fast aligner (<a href="https://github.com/lh3/minimap2">minimap2</a>) and the refactoring of alignment analyzing&nbsp;modules</li>
<li>New k-mer-based completeness and correctness metrics</li>
<li>BUSCO added for enhanced reference-free analysis</li>
<li>The concept of upper bound&nbsp;assembly (theoretical limits on the assembly&nbsp;completeness and&nbsp;contiguity for a given genome and set of reads)</li>
</ul><p>Address of the bookmark: <a href="http://cab.spbu.ru/software/quast-lg/" rel="nofollow">http://cab.spbu.ru/software/quast-lg/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/38765/list-of-tools-frequently-used-while-genome-assembly</guid>
	<pubDate>Tue, 22 Jan 2019 09:39:02 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/38765/list-of-tools-frequently-used-while-genome-assembly</link>
	<title><![CDATA[List of tools frequently used while genome assembly]]></title>
	<description><![CDATA[<h4>List of tools frequently used while genome assembly:</h4><p>I have used the following assemblers</p><ul>
<li><a href="http://bioinf.spbau.ru/spades">Spades</a>&nbsp;(v. 3.10.1)</li>
<li><a href="http://canu.readthedocs.io/en/stable/index.html">CANU</a>&nbsp;(v. 1.6)</li>
<li><a href="https://github.com/rrwick/Unicycler">Unicycler&nbsp;</a>(v. v0.4.1)</li>
<li><a href="https://github.com/lh3/miniasm">Miniasm</a>&nbsp;(v. 0.2-r137-dirty)</li>
</ul><p>I have used the following mappers</p><ul>
<li><a href="https://github.com/lh3/minimap2">minimap2</a>&nbsp;(v.&nbsp;2.0rc1-r232)</li>
<li><a href="https://github.com/lh3/minimap">minimap&nbsp;</a>(v. 0.2-r124-dirty)</li>
<li><a href="https://github.com/lh3/bwa">bwa</a>&nbsp;(v.&nbsp;0.7.12-r1039)</li>
</ul><p>I have used the following polishing tools</p><ul>
<li><a href="https://github.com/isovic/racon">Racon</a>&nbsp;(v. not available)</li>
<li><a href="https://github.com/broadinstitute/pilon">Pilon</a>&nbsp;(v. 1.18)</li>
<li><a href="https://github.com/jts/nanopolish">Nanopolish</a>&nbsp;(v. 0.8.3)</li>
</ul><p>I have used the following tools to assess genome assembly characteristics</p><ul>
<li><a href="https://github.com/chjp/ANI">ANI.pl</a>&nbsp;(https://github.com/chjp/ANI)</li>
<li><a href="http://ecogenomics.github.io/CheckM/">CheckM</a>&nbsp;(v. 1.0.7)</li>
<li><a href="https://github.com/tseemann/prokka">Prokka</a>&nbsp;(v. 1.12)</li>
<li><a href="http://bioinf.spbau.ru/en/quast">QUAST</a>&nbsp;(v. 2.3)</li>
<li><a href="http://mummer.sourceforge.net/">mummer&nbsp;</a>(v. not available)</li>
</ul><p>If you have any ideas or superior tools we have missed please let us know in the comments.</p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40792/haslr-a-tool-for-rapid-genome-assembly-of-long-sequencing-reads</guid>
	<pubDate>Fri, 31 Jan 2020 05:50:15 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40792/haslr-a-tool-for-rapid-genome-assembly-of-long-sequencing-reads</link>
	<title><![CDATA[HASLR: a tool for rapid genome assembly of long sequencing reads]]></title>
	<description><![CDATA[<p><span>HASLR is a tool for rapid genome assembly of long sequencing reads. HASLR is a hybrid tool which means it requires long reads generated by Third Generation Sequencing technologies (such as PacBio or Oxford Nanopore) together with Next Generation Sequencing reads (such as Illumina) from the same sample.&nbsp;</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>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44549/quartet-a-telomere-to-telomere-toolkit-for-gap-free-genome-assembly-and-centromeric-repeat-identification</guid>
	<pubDate>Sat, 08 Jun 2024 15:54:36 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44549/quartet-a-telomere-to-telomere-toolkit-for-gap-free-genome-assembly-and-centromeric-repeat-identification</link>
	<title><![CDATA[quarTeT: a telomere-to-telomere toolkit for gap-free genome assembly and centromeric repeat identification.]]></title>
	<description><![CDATA[<p><span>quarTeT is a collection of tools for T2T genome assembly and basic analysis in automatic workflow.</span><br><br><span>Task include:</span></p>
<ul>
<li><a href="http://www.atcgn.com:8080/quarTeT/docuWeb.html#AssemblyMapper">AssemblyMapper</a>&nbsp;: reference-guided genome assembly</li>
<li><a href="http://www.atcgn.com:8080/quarTeT/docuWeb.html#GapFiller">GapFiller</a>&nbsp;: long-reads based gap filling</li>
<li><a href="http://www.atcgn.com:8080/quarTeT/docuWeb.html#TeloExplorer">TeloExplorer</a>&nbsp;: telomere identification</li>
<li><a href="http://www.atcgn.com:8080/quarTeT/docuWeb.html#CentroMiner">CentroMiner</a>&nbsp;: centromere candidate prediction</li>
</ul>
<p>https://academic.oup.com/hr/article/10/8/uhad127/7197191?login=false&nbsp;</p><p>Address of the bookmark: <a href="http://www.atcgn.com:8080/quarTeT/home.html" rel="nofollow">http://www.atcgn.com:8080/quarTeT/home.html</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/13267/the-genome-10k-project</guid>
	<pubDate>Tue, 29 Jul 2014 09:11:04 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/13267/the-genome-10k-project</link>
	<title><![CDATA[The Genome 10K Project]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/B57xDIGtCT0" frameborder="0" allowfullscreen></iframe>https://genome10k.soe.ucsc.edu

The Genome 10K project aims to assemble a genomic zoo—a collection of DNA sequences representing the genomes of 10,000 vertebrate species, approximately one for every vertebrate genus. The trajectory of cost reduction in DNA sequencing suggests that this project will be feasible within a few years. Capturing the genetic diversity of vertebrate species would create an unprecedented resource for the life sciences and for worldwide conservation efforts.

The growing Genome 10K Community of Scientists (G10KCOS), made up of leading scientists representing major zoos, museums, research centers, and universities around the world, is dedicated to coordinating efforts in tissue specimen collection that will lay the groundwork for a large-scale sequencing and analysis project.]]></description>
	
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27113/picard</guid>
	<pubDate>Fri, 29 Apr 2016 08:21:54 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27113/picard</link>
	<title><![CDATA[Picard]]></title>
	<description><![CDATA[<p>Picard is a set of command line tools for manipulating high-throughput sequencing (HTS) data and formats such as SAM/BAM/CRAM and VCF. These file formats are defined in the <a href="http://samtools.github.io/hts-specs/">Hts-specs</a> repository. See especially the <a href="http://samtools.github.io/hts-specs/SAMv1.pdf">SAM specification</a> and the <a href="http://samtools.github.io/hts-specs/VCFv4.3.pdf">VCF specification</a>.</p>
<p>Note that the information on this page is targeted at end-users. For developers, the source code, building instructions and implementation/development resources are available on <a href="https://github.com/broadinstitute/picard">GitHub</a>.</p>
<p>The Picard toolkit is open-source under the <a href="https://tldrlegal.com/license/mit-license">MIT license</a> and free for all uses.</p>
<p>Enjoy!</p><p>Address of the bookmark: <a href="http://broadinstitute.github.io/picard/" rel="nofollow">http://broadinstitute.github.io/picard/</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26909/sequence-assembly-with-mira-4</guid>
	<pubDate>Wed, 06 Apr 2016 08:21:22 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26909/sequence-assembly-with-mira-4</link>
	<title><![CDATA[Sequence assembly with MIRA 4]]></title>
	<description><![CDATA[<p>MIRA is a multi-pass DNA sequence data assembler/mapper for whole genome and EST/RNASeq projects. MIRA assembles/maps reads gained by</p>
<div>
<ul>
<li>
<p>electrophoresis sequencing (aka Sanger sequencing)</p>
</li>
<li>
<p>454 pyro-sequencing (GS20, FLX or Titanium)</p>
</li>
<li>
<p>Ion Torrent</p>
</li>
<li>
<p>Solexa (Illumina) sequencing</p>
</li>
<li>
<p>(in development) Pacific Biosciences sequencing</p>
</li>
</ul>
</div>
<p>into contiguous sequences (called <span><em>contigs</em></span>). One can use the sequences of different sequencing technologies either in a single assembly run (a <span><em>true hybrid assembly</em></span>) or by mapping one type of data to an assembly of other sequencing type (a <span><em>semi-hybrid assembly (or mapping)</em></span>) or by mapping a data against consensus sequences of other assemblies (a <span><em>simple mapping</em></span>).</p>
<p>The MIRA acronym stands for <span><strong>M</strong></span>imicking <span><strong>I</strong></span>ntelligent <span><strong>R</strong></span>ead <span><strong>A</strong></span>ssembly and the program pretty well does what its acronym says (well, most of the time anyway). It is the Swiss army knife of sequence assembly that I've used and developed during the past 14 years to get assembly jobs I work on done efficiently - and especially accurately. That is, without me actually putting too much manual work into it.</p>
<p>More at http://mira-assembler.sourceforge.net/docs/DefinitiveGuideToMIRA.html</p><p>Address of the bookmark: <a href="http://mira-assembler.sourceforge.net/docs/DefinitiveGuideToMIRA.html" rel="nofollow">http://mira-assembler.sourceforge.net/docs/DefinitiveGuideToMIRA.html</a></p>]]></description>
	<dc:creator>Priya Singh</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/42206/pollard-lab</guid>
  <pubDate>Fri, 25 Sep 2020 20:20:50 -0500</pubDate>
  <link></link>
  <title><![CDATA[Pollard Lab]]></title>
  <description><![CDATA[
<p>We are a bioinformatics research lab focused on developing novel methods and using them to study genome evolution, organization, and regulation. Our mission is to decode biomedical knowledge that is missed without rigorous statistical approaches.</p>

<p>http://docpollard.org/</p>

<p>Tools</p>

<p>http://docpollard.org/resources/software/</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26972/understanding-fastqc-output</guid>
	<pubDate>Fri, 15 Apr 2016 05:47:40 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26972/understanding-fastqc-output</link>
	<title><![CDATA[Understanding Fastqc Output]]></title>
	<description><![CDATA[<p>Understanding Following table and graphs</p>
<ol>
<li>Duplication level</li>
<li>kmer profile</li>
<li>per base GC content</li>
<li>per base N content</li>
<li>per base quality</li>
<li>per base sequence content</li>
<li>per sequence GC content</li>
<li>per sequence quality</li>
<li>sequence length distribution</li>
</ol>
<p>More at http://www.bioinformatics.babraham.ac.uk/projects/fastqc/Help/3%20Analysis%20Modules/</p><p>Address of the bookmark: <a href="http://www.bioinformatics.babraham.ac.uk/projects/fastqc/Help/3%20Analysis%20Modules/" rel="nofollow">http://www.bioinformatics.babraham.ac.uk/projects/fastqc/Help/3%20Analysis%20Modules/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27076/ale-a-generic-assembly-likelihood-evaluation-framework-for-assessing-the-accuracy-of-genome-and-metagenome-assemblies</guid>
	<pubDate>Tue, 26 Apr 2016 03:38:43 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27076/ale-a-generic-assembly-likelihood-evaluation-framework-for-assessing-the-accuracy-of-genome-and-metagenome-assemblies</link>
	<title><![CDATA[ALE: a Generic Assembly Likelihood Evaluation Framework for Assessing the Accuracy of Genome and Metagenome Assemblies]]></title>
	<description><![CDATA[<p>Assembly Likelihood Evaluation (ALE) framework that overcomes these limitations, systematically evaluating the accuracy of an assembly in a reference-independent manner using rigorous statistical methods. This framework is comprehensive, and integrates read quality, mate pair orientation and insert length (for paired-end reads), sequencing coverage, read alignment and k-mer frequency. ALE pinpoints synthetic errors in both single and metagenomic assemblies, including single-base errors, insertions/deletions, genome rearrangements and chimeric assemblies presented in metagenomes. At the genome level with real-world data, ALE identifies three large misassemblies from the Spirochaeta smaragdinae finished genome, which were all independently validated by Pacific Biosciences sequencing. At the single-base level with Illumina data, ALE recovers 215 of 222 (97%) single nucleotide variants in a training set from a GC-rich Rhodobacter sphaeroides genome. Using real Pacific Biosciences data, ALE identifies 12 of 12 synthetic errors in a Lambda Phage genome, surpassing even Pacific Biosciences' own variant caller, EviCons. In summary, the ALE framework provides a comprehensive, reference-independent and statistically rigorous measure of single genome and metagenome assembly accuracy, which can be used to identify misassemblies or to optimize the assembly process.</p>
<p>More at&nbsp;http://www.ncbi.nlm.nih.gov/pubmed/23303509</p><p>Address of the bookmark: <a href="http://sc932.github.io/ALE/about.html" rel="nofollow">http://sc932.github.io/ALE/about.html</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>

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