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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/31105?offset=40</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36594/fragscaff-genome-assembly-with-contiguity-preserving-transposition</guid>
	<pubDate>Mon, 14 May 2018 04:28:14 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36594/fragscaff-genome-assembly-with-contiguity-preserving-transposition</link>
	<title><![CDATA[fragScaff: Genome Assembly with Contiguity Preserving Transposition]]></title>
	<description><![CDATA[<p>Contiguity preserving transposition and sequencing (CPT-seq) is an entirely in vitro means of generating libraries comprised of 9216 indexed pools, each of which contains thousands of sparsely sequenced long fragments ranging from 5 kilobases to &gt;1 megabase. This software, fragScaff, leverages coincidences between the content of different pools as a source of contiguity information for scaffolding de novo genome assemblies. FragScaff is complementary to Lachesis, providing midrange contiguity to support robust, accurate chromosome-scale de novo genome assemblies without the need for laborious in vivo cloning steps.</p>
<p>Further information about fragScaff, including source code, is available at:<a href="https://sourceforge.net/projects/fragscaff/files/">https://sourceforge.net/projects/fragscaff/files</a>.</p>
<p>Manuscript describing fragScaff was published as: Adey A, Kitzman JO, Burton JN, Daza R, Kumar A, Christiansen L, Ronaghi M, Amini S, L Gunderson K, Steemers FJ, Shendure J#.&nbsp;<em>In vitro, long-range sequence information for de novo genome assembly via transposase contiguity.</em>&nbsp;Genome Research 2014 Dec;24(12):2041-9. doi:&nbsp;<a href="http://dx.doi.org/10.1101/gr.178319.114">10.1101/gr.178319.114</a>. PubMed PMID:&nbsp;<a href="http://www.ncbi.nlm.nih.gov/pubmed/25327137">25327137</a>.</p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="https://sourceforge.net/projects/fragscaff/files/" rel="nofollow">https://sourceforge.net/projects/fragscaff/files/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/28999/redundans</guid>
	<pubDate>Thu, 01 Sep 2016 08:28:11 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/28999/redundans</link>
	<title><![CDATA[Redundans]]></title>
	<description><![CDATA[<p>Redundans pipeline assists&nbsp;<span>an assembly of heterozygous genomes</span>.<br>Program takes as input&nbsp;<span>assembled contigs</span>,&nbsp;<span>paired-end and/or mate pairs sequencing libraries</span>&nbsp;and returns&nbsp;<span>scaffolded homozygous genome assembly</span>, that should be&nbsp;<span>less fragmented</span>&nbsp;and with total&nbsp;<span>size smaller</span>&nbsp;than the input contigs. In addition, Redundans will automatically&nbsp;<span>close the gaps</span>&nbsp;resulting from genome assembly or scaffolding&nbsp;<a href="https://github.com/Gabaldonlab/redundans/blob/master/test#redundans-pipeline">more details</a>.</p>
<p>The pipeline consists of three steps/modules:</p>
<ul>
<li><span>redundancy reduction</span>: detection and selectively removal of redundant contigs from an initial&nbsp;<em>de novo</em>&nbsp;assembly</li>
<li><span>scaffolding</span>: joining of genome fragments using paired-end and/or mate-pairs reads</li>
<li><span>gap closing</span></li>
</ul>
<p>Redundans is:</p>
<ul>
<li><span>fast</span>&nbsp;&amp;&nbsp;<span>lightweight</span>, multi-core support and memory-optimised, so it can be run even on the laptop for small-to-medium size genomes</li>
<li><span>flexible</span>&nbsp;toward many sequencing technologies (Illumina, 454 or Sanger) and library types (paired-end, mate pairs, fosmids)</li>
<li><span>modular</span>: every step can be ommited or replaced by another tools</li>
</ul><p>Address of the bookmark: <a href="https://github.com/Gabaldonlab/redundans" rel="nofollow">https://github.com/Gabaldonlab/redundans</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30074/minia</guid>
	<pubDate>Thu, 08 Dec 2016 05:07:00 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30074/minia</link>
	<title><![CDATA[Minia]]></title>
	<description><![CDATA[<p>Minia is a short-read assembler based on a de Bruijn graph, capable of assembling a human genome on a desktop computer in a day. The output of Minia is a set of contigs. Minia produces results of similar contiguity and accuracy to other de Bruijn assemblers (e.g. Velvet).</p>
<h3>Download</h3>
<p><a href="https://github.com/GATB/minia/releases/download/v2.0.7/minia-v2.0.7-bin-Linux.tar.gz">Minia 2.0.7 Linux 64-bits binaries</a>&nbsp;(<a href="https://github.com/GATB/minia/releases/download/v2.0.7/minia-v2.0.7-Source.tar.gz">Source code</a>)&nbsp;<span>(<a href="http://minia.genouest.org/files/minia-1.6906.tar.gz">Legacy codebase</a>)</span></p>
<h3>For the impatient</h3>
<p>A typical Minia command line looks like:</p>
<pre>./minia -in <span>reads.fa</span> -kmer-size <span>31</span> -abundance-min <span>3</span> -out <span>output_prefix</span></pre>
<p>Type</p>
<pre>./minia</pre>
<p><span>for a quick explanation of the parameters.</span></p>
<p>For more information, refer to the&nbsp;<a href="http://minia.genouest.org/files/minia.pdf">manual</a>.</p>
<p><a href="http://kmergenie.bx.psu.edu/">KmerGenie</a>&nbsp;can be used to determine the best k-mer size, minimum abundance of correct k-mers, and genome size estimation for your dataset.</p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="http://minia.genouest.org/" rel="nofollow">http://minia.genouest.org/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30093/velvet-tutorial</guid>
	<pubDate>Fri, 09 Dec 2016 04:19:07 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30093/velvet-tutorial</link>
	<title><![CDATA[Velvet tutorial]]></title>
	<description><![CDATA[<p><span>The objective of this activity is to help you understand how to run&nbsp;</span><a href="http://evomics.org/resources/software/genomics-software/assembly/velvet/" title="Velvet">Velvet</a><span>&nbsp;in general, how to accurately estimate the insert size of a paired-end library through the use of&nbsp;</span><a href="http://evomics.org/resources/software/genomics-software/assembly/bowtie/" title="Bowtie">Bowtie</a><span>, the primary parameters of velvet, and the process involved in producing a&nbsp;</span><em>de novo</em><span>&nbsp;assembly from Illumina reads.</span></p>
<p>http://evomics.org/learning/assembly-and-alignment/velvet/</p><p>Address of the bookmark: <a href="http://evomics.org/learning/assembly-and-alignment/velvet/" rel="nofollow">http://evomics.org/learning/assembly-and-alignment/velvet/</a></p>]]></description>
	<dc:creator>Poonam Mahapatra</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30212/pear</guid>
	<pubDate>Mon, 19 Dec 2016 09:28:30 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30212/pear</link>
	<title><![CDATA[PEAR]]></title>
	<description><![CDATA[<p><strong>PEAR</strong>&nbsp;is an ultrafast, memory-efficient and highly accurate pair-end read merger. It is fully parallelized and can run with as low as just a few kilobytes of memory.</p>
<p>PEAR evaluates all possible paired-end read overlaps and without requiring the target fragment size as input. In addition, it implements a statistical test for minimizing false-positive results. Together with a highly optimized implementation, it can merge millions of paired end reads within a couple of minutes on a standard desktop computer.</p><p>Address of the bookmark: <a href="http://sco.h-its.org/exelixis/web/software/pear/doc.html" rel="nofollow">http://sco.h-its.org/exelixis/web/software/pear/doc.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31087/bedtools</guid>
	<pubDate>Fri, 24 Feb 2017 04:50:44 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31087/bedtools</link>
	<title><![CDATA[bedtools]]></title>
	<description><![CDATA[<p>Collectively, the&nbsp;<strong>bedtools</strong>&nbsp;utilities are a swiss-army knife of tools for a wide-range of genomics analysis tasks. The most widely-used tools enable&nbsp;<em>genome arithmetic</em>: that is, set theory on the genome. For example,&nbsp;<strong>bedtools</strong>&nbsp;allows one to<em>intersect</em>,&nbsp;<em>merge</em>,&nbsp;<em>count</em>,&nbsp;<em>complement</em>, and&nbsp;<em>shuffle</em>&nbsp;genomic intervals from multiple files in widely-used genomic file formats such as BAM, BED, GFF/GTF, VCF. While each individual tool is designed to do a relatively simple task (e.g.,&nbsp;<em>intersect</em>&nbsp;two interval files), quite sophisticated analyses can be conducted by combining multiple bedtools operations on the UNIX command line.</p>
<p><strong>bedtools</strong>&nbsp;is developed in the&nbsp;<a href="http://quinlanlab.org/">Quinlan laboratory</a>&nbsp;at the&nbsp;<a href="http://www.utah.edu/">University of Utah</a>&nbsp;and benefits from fantastic contributions made by scientists worldwide.</p><p>Address of the bookmark: <a href="http://bedtools.readthedocs.io/en/latest/index.html" rel="nofollow">http://bedtools.readthedocs.io/en/latest/index.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31345/prokka-tool-for-the-rapid-annotation-of-prokaryotic-genomes</guid>
	<pubDate>Mon, 06 Mar 2017 03:49:57 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31345/prokka-tool-for-the-rapid-annotation-of-prokaryotic-genomes</link>
	<title><![CDATA[Prokka: tool for the rapid annotation of prokaryotic genomes]]></title>
	<description><![CDATA[<p>Prokka is a software tool for the rapid annotation of prokaryotic genomes. A typical 4 Mbp genome can be fully annotated in less than 10 minutes on a quad-core computer, and scales well to 32 core SMP systems. It produces GFF3, GBK and SQN files that are ready for editing in Sequin and ultimately submitted to Genbank/DDJB/ENA.</p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="http://www.vicbioinformatics.com/software.prokka.shtml" rel="nofollow">http://www.vicbioinformatics.com/software.prokka.shtml</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31375/cocacola-binning-metagenomic-contigs-using-sequence-composition-read-coverage-co-alignment-and-paired-end-read-linkage</guid>
	<pubDate>Tue, 07 Mar 2017 08:50:57 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31375/cocacola-binning-metagenomic-contigs-using-sequence-composition-read-coverage-co-alignment-and-paired-end-read-linkage</link>
	<title><![CDATA[COCACOLA (binning metagenomic contigs using sequence COmposition, read CoverAge, CO-alignment, and paired-end read LinkAge)]]></title>
	<description><![CDATA[<p>COCACOLA is a general framework that combines different types of information: sequence COmposition, CoverAge across multiple samples, CO-alignment to reference genomes and paired-end reads LinkAge to automatically bin contigs into OTUs. Furthermore, COCACOLA seamlessly embraces customized prior knowledge to facilitate binning accuracy.</p>
<p>News: Python version of COCACOLA is available now!</p><p>Address of the bookmark: <a href="https://github.com/younglululu/COCACOLA" rel="nofollow">https://github.com/younglululu/COCACOLA</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31552/multigenome-assembly</guid>
	<pubDate>Tue, 14 Mar 2017 04:41:23 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31552/multigenome-assembly</link>
	<title><![CDATA[Multigenome assembly]]></title>
	<description><![CDATA[<p>This project contains scripts and tutorials on how to assemble individual microbial genomes from metagenomes, as described in:</p>
<p>Genome sequences of rare, uncultured bacteria obtained by differential coverage binning of multiple metagenomes</p>
<p>Mads Albertsen, Philip Hugenholtz, Adam Skarshewski, Gene W. Tyson, K&aring;re L. Nielsen and Per .H. Nielsen</p>
<p>Nature Biotechnology 2013, doi:&nbsp;<a href="http://www.nature.com/nbt/journal/vaop/ncurrent/abs/nbt.2579.html">10.1038/nbt.2579</a></p>
<p>See the associated&nbsp;<a href="http://madsalbertsen.github.io/multi-metagenome/">online guide</a>&nbsp;for detailed information.</p>
<p>https://github.com/MadsAlbertsen/multi-metagenome</p><p>Address of the bookmark: <a href="https://github.com/MadsAlbertsen/multi-metagenome" rel="nofollow">https://github.com/MadsAlbertsen/multi-metagenome</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/32719/download-assemblies-from-ncbi</guid>
	<pubDate>Mon, 15 May 2017 06:02:32 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/32719/download-assemblies-from-ncbi</link>
	<title><![CDATA[Download assemblies from NCBI]]></title>
	<description><![CDATA[<p>A new &ldquo;Download assemblies&rdquo; button is now available in the&nbsp;<a href="https://www.ncbi.nlm.nih.gov/assembly" target="_blank">Assembly</a>&nbsp;database. This makes it easy to download data for multiple genomes without having to write scripts.</p><p>For example, you can run a search in Assembly and use check boxes (see left side of screenshot below) to refine the set of genome assemblies of interest. Then, just open the &ldquo;Download assemblies&rdquo; menu, choose the source database (<a href="https://www.ncbi.nlm.nih.gov/genbank/" target="_blank">GenBank</a>&nbsp;or&nbsp;<a href="https://www.ncbi.nlm.nih.gov/refseq/" target="_blank">RefSeq</a>), choose the file type, and start the download. An archive file will be saved to your computer that can be expanded into a folder containing your selected genome data files.</p><p><img src="https://ncbiinsights.files.wordpress.com/2017/05/download_button.jpg?w=584" alt="image" width="584" height="444" style="border: 0px; border: 0px;"></p><p>&nbsp;</p><p>More at&nbsp;https://ncbiinsights.ncbi.nlm.nih.gov/2017/05/08/genome-data-download-made-easy/</p>]]></description>
	<dc:creator>Bulbul</dc:creator>
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