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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/44373?offset=540</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42806/graphunzip-phases-an-assembly-graph-using-hi-c-data-andor-long-reads</guid>
	<pubDate>Fri, 05 Feb 2021 21:22:24 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42806/graphunzip-phases-an-assembly-graph-using-hi-c-data-andor-long-reads</link>
	<title><![CDATA[GraphUnzip: Phases an assembly graph using Hi-C data and/or long reads.]]></title>
	<description><![CDATA[<p>GraphUnzip, a fast, memory-efficient and accurate tool to unzip assembly graphs into their constituent haplotypes using long reads and/or Hi-C data. As GraphUnzip only connects sequences in the assembly graph that already had a potential link based on overlaps, it yields high-quality gap-less supercontigs. To demonstrate the efficiency of GraphUnzip, we tested it on a simulated diploid Escherichia coli genome, and on two real datasets for the genomes of the rotifer Adineta vaga and the potato Solanum tuberosum. In all cases, GraphUnzip yielded highly continuous phased assemblies.</p>
<p>https://www.biorxiv.org/content/biorxiv/early/2021/02/01/2021.01.29.428779.full.pdf</p><p>Address of the bookmark: <a href="https://github.com/nadegeguiglielmoni/GraphUnzip" rel="nofollow">https://github.com/nadegeguiglielmoni/GraphUnzip</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/file/view/43732/spades-tutorial-pdf</guid>
	<pubDate>Tue, 01 Feb 2022 04:56:43 -0600</pubDate>
	<link>https://bioinformaticsonline.com/file/view/43732/spades-tutorial-pdf</link>
	<title><![CDATA[Spades tutorial PDF]]></title>
	<description><![CDATA[<p>SPAdes&mdash;St. Petersburg genome Assembler&mdash;was originally developed for de novo assembly of genome sequencing data produced for cultivated microbial isolates and for single-cell genomic DNA sequencing. With time, the functionality of SPAdes was extended to enable assembly of IonTorrent data, as well as hybrid assembly from short and long reads (PacBio and Oxford Nanopore). In this article we present protocols for five different assembly pipelines that comprise the SPAdes package and that are used for assembly of metagenomes and transcriptomes as well as assembly of putative plasmids and biosynthetic gene clusters from whole-genome sequencing and metagenomic datasets.&nbsp;</p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
	<enclosure url="https://bioinformaticsonline.com/file/download/43732" length="268093" type="application/pdf" />
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44529/contigextender-a-new-approach-to-improving-de-novo-sequence-assembly-for-viral-metagenomics-data</guid>
	<pubDate>Wed, 08 May 2024 07:32:45 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44529/contigextender-a-new-approach-to-improving-de-novo-sequence-assembly-for-viral-metagenomics-data</link>
	<title><![CDATA[ContigExtender: a new approach to improving de novo sequence assembly for viral metagenomics data]]></title>
	<description><![CDATA[<p dir="auto">ContigExtender, was developed to extend contigs, complementing de novo assembly. ContigExtender employs a novel recursive Overlap Layout Candidates (r-OLC) strategy that explores multiple extending paths to achieve longer and highly accurate contigs. ContigExtender is effective for extending contigs significantly in in silico synthesized and real metagenomics datasets.</p>
<p dir="auto">More at&nbsp;https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7953547/</p>
<p dir="auto"><a href="https://camo.githubusercontent.com/72dc78177cd84dd0c667a2922a9fd984fb548b5ec94b11f9a547211a4adba3b1/68747470733a2f2f692e696d6775722e636f6d2f7734516944496a2e706e67" target="_blank"><img src="https://camo.githubusercontent.com/72dc78177cd84dd0c667a2922a9fd984fb548b5ec94b11f9a547211a4adba3b1/68747470733a2f2f692e696d6775722e636f6d2f7734516944496a2e706e67" alt="extension process" title="extension process" style="border: 0px;"></a></p><p>Address of the bookmark: <a href="https://github.com/dengzac/contig-extender" rel="nofollow">https://github.com/dengzac/contig-extender</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26325/crossmap</guid>
	<pubDate>Mon, 08 Feb 2016 15:47:00 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26325/crossmap</link>
	<title><![CDATA[CrossMap]]></title>
	<description><![CDATA[<p>CrossMap is a program for convenient conversion of genome coordinates (or annotation files) between <em>different assemblies</em> (such as Human <a href="http://www.ncbi.nlm.nih.gov/assembly/2928/">hg18 (NCBI36)</a> &lt;&gt; <a href="http://www.ncbi.nlm.nih.gov/assembly/2758/">hg19 (GRCh37)</a>, Mouse <a href="http://www.ncbi.nlm.nih.gov/assembly/165668/">mm9 (MGSCv37)</a> &lt;&gt; <a href="http://www.ncbi.nlm.nih.gov/assembly/327618/">mm10 (GRCm38)</a>).</p>
<p>It supports most commonly used file formats including SAM/BAM, Wiggle/BigWig, BED, GFF/GTF, VCF.</p>
<p>CrossMap is designed to liftover genome coordinates between assemblies. It&rsquo;s <em>not</em> a program for aligning sequences to reference genome.</p>
<p>We <em>do not</em> recommend using CrossMap to convert genome coordinates between species.</p>
<p>More at http://crossmap.sourceforge.net/</p><p>Address of the bookmark: <a href="http://crossmap.sourceforge.net/" rel="nofollow">http://crossmap.sourceforge.net/</a></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27110/easyfig</guid>
	<pubDate>Fri, 29 Apr 2016 05:49:39 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27110/easyfig</link>
	<title><![CDATA[Easyfig]]></title>
	<description><![CDATA[<p>Easyfig has moved to github, for newer releases of Easyfig please visit our new webpage - https://mjsull.github.io/Easyfig.&nbsp; Easyfig is a Python application for creating linear comparison figures of multiple genomic loci with an easy-to-use graphical user interface (GUI).</p>
<p>More at http://easyfig.sourceforge.net/</p><p>Address of the bookmark: <a href="http://easyfig.sourceforge.net/" rel="nofollow">http://easyfig.sourceforge.net/</a></p>]]></description>
	<dc:creator>Poonam Mahapatra</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26923/quast-quality-assessment-tool-for-genome-assemblies</guid>
	<pubDate>Wed, 06 Apr 2016 18:23:33 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26923/quast-quality-assessment-tool-for-genome-assemblies</link>
	<title><![CDATA[QUAST: quality assessment tool for genome assemblies]]></title>
	<description><![CDATA[<p><span>QUAST evaluates genome assemblies. For metagenomes, please see&nbsp;<a href="http://bioinf.spbau.ru/metaquast">MetaQUAST</a>&nbsp;project.</span><br><span>It can works both with and without a given reference genome.</span><br><span>The tool accepts multiple assemblies, thus is suitable for comparison.</span></p>
<p><span>More at&nbsp;http://bioinf.spbau.ru/quast</span></p>
<p><span>http://bioinformatics.oxfordjournals.org/content/early/2013/03/09/bioinformatics.btt086.long</span></p><p>Address of the bookmark: <a href="http://bioinformatics.oxfordjournals.org/content/early/2013/03/09/bioinformatics.btt086.long" rel="nofollow">http://bioinformatics.oxfordjournals.org/content/early/2013/03/09/bioinformatics.btt086.long</a></p>]]></description>
	<dc:creator>Jitendra Prajapati</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27104/gatb-genome-analysis-toolbox-with-de-bruijn-graph</guid>
	<pubDate>Thu, 28 Apr 2016 11:16:51 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27104/gatb-genome-analysis-toolbox-with-de-bruijn-graph</link>
	<title><![CDATA[GATB : Genome Analysis Toolbox with de-Bruijn graph]]></title>
	<description><![CDATA[<p>The&nbsp;<strong><strong>Genome Analysis Toolbox with de-Bruijn graph</strong> (GATB)</strong> provides a set of <a href="https://gatb.inria.fr/gatb-global-architecture/">highly efficient algorithms to analyse NGS data sets</a>. These methods enable the analysis of data sets of any size on multi-core desktop computers, including very huge amount of reads data coming from any kind of organisms such as bacteria, plants, animals and even complex samples (<em>e.g.</em> metagenomes).</p>
<p>More at https://gatb.inria.fr/</p><p>Address of the bookmark: <a href="https://gatb.inria.fr/" rel="nofollow">https://gatb.inria.fr/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27818/gaemr</guid>
	<pubDate>Tue, 14 Jun 2016 06:18:37 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27818/gaemr</link>
	<title><![CDATA[GAEMR]]></title>
	<description><![CDATA[<p>The&nbsp;<span>G</span>enome&nbsp;<span>A</span>ssembly&nbsp;<span>E</span>valuation&nbsp;<span>M</span>etrics and&nbsp;<span>R</span>eporting (GAEMR) package is an assembly analysis framework composed a number of integrated modules. These modules can be executed as a single program to generate a complete analysis report, or executed individually to generate specific charts and tables. GAEMR standardizes input by converting a variety of read types to Binary Alignment Map (BAM) format, allowing a single input format to be entered into GAEMR&rsquo;s analysis pipeline, hence enabling the generation of standard reports.</p>
<p>GAEMR&rsquo;s analysis philosophy is centered on contiguity, correctness, and completeness -- how many pieces in an assembly composed of, how well those pieces accurately represent the genome sequenced, and how much of that genome is represented by those pieces. By performing over twenty different analyses based on these principles, GAEMR gives a clear picture of the condition of a genome assembly.&nbsp;</p><p>Address of the bookmark: <a href="https://www.broadinstitute.org/software/gaemr/" rel="nofollow">https://www.broadinstitute.org/software/gaemr/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30012/swalo</guid>
	<pubDate>Wed, 30 Nov 2016 05:06:05 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30012/swalo</link>
	<title><![CDATA[SWALO]]></title>
	<description><![CDATA[<p>SWALO (scaffolding with assembly likelihood optimization) is a method for scaffolding based on likelihood of genome assemblies computed using generative models for sequencing.</p>
<p><a href="https://atifrahman.github.io/SWALO/swalo-0.9.7-beta.tar.gz"><strong>Download</strong></a></p>
<p><strong>Git repository of SWALO is at <a href="https://github.com/atifrahman/SWALO">https://github.com/atifrahman/SWALO</a>.</strong></p><p>Address of the bookmark: <a href="https://atifrahman.github.io/SWALO/" rel="nofollow">https://atifrahman.github.io/SWALO/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/33856/assembly-course</guid>
	<pubDate>Mon, 10 Jul 2017 09:38:05 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/33856/assembly-course</link>
	<title><![CDATA[Assembly Course]]></title>
	<description><![CDATA[<p>https://ocw.mit.edu/courses/biology/7-91j-foundations-of-computational-and-systems-biology-spring-2014/lecture-slides/MIT7_91JS14_Lecture6.pdf</p><p>Address of the bookmark: <a href="https://ocw.mit.edu/courses/biology/7-91j-foundations-of-computational-and-systems-biology-spring-2014/lecture-slides/MIT7_91JS14_Lecture6.pdf" rel="nofollow">https://ocw.mit.edu/courses/biology/7-91j-foundations-of-computational-and-systems-biology-spring-2014/lecture-slides/MIT7_91JS14_Lecture6.pdf</a></p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
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