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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/41843?offset=140</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38755/svaba-genome-wide-detection-of-structural-variants-and-indels-by-local-assembly</guid>
	<pubDate>Mon, 21 Jan 2019 17:58:56 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38755/svaba-genome-wide-detection-of-structural-variants-and-indels-by-local-assembly</link>
	<title><![CDATA[SvABA: Genome-wide detection of structural variants and indels by local assembly]]></title>
	<description><![CDATA[<p><span>SvABA is a method for detecting structural variants in sequencing data using genome-wide local assembly. Under the hood, SvABA uses a custom implementation of&nbsp;</span><a href="https://github.com/jts/sga">SGA</a><span>&nbsp;(String Graph Assembler) by Jared Simpson, and&nbsp;</span><a href="https://github.com/lh3/bwa">BWA-MEM</a><span>&nbsp;by Heng Li. Contigs are assembled for every 25kb window (with some small overlap) for every region in the genome. The default is to use only clipped, discordant, unmapped and indel reads, although this can be customized to any set of reads at the command line using&nbsp;</span><a href="https://github.com/walaj/VariantBam">VariantBam</a><span>&nbsp;rules. These contigs are then immediately aligned to the reference with BWA-MEM and parsed to identify variants. Sequencing reads are then realigned to the contigs with BWA-MEM, and variants are scored by their read support.</span></p><p>Address of the bookmark: <a href="https://github.com/walaj/svaba" rel="nofollow">https://github.com/walaj/svaba</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/file/view/38886/evaluation-of-genome-assembly-software-based-on-long-reads</guid>
	<pubDate>Fri, 01 Feb 2019 11:55:54 -0600</pubDate>
	<link>https://bioinformaticsonline.com/file/view/38886/evaluation-of-genome-assembly-software-based-on-long-reads</link>
	<title><![CDATA[Evaluation of genome assembly software based on long reads]]></title>
	<description><![CDATA[<p>TGS technologies have been used to produce highly accurate de novo assemblies of hundreds of microbial genomes and highly contiguous reconstructions of many dozens of plant and animal genomes, enabling new insights into evolution and sequence diversity. They have also been applied to resequencing analyses, to create detailed maps of structural variations in many species. Also, these new technologies have been used to fill in many of the gaps in the human reference genome.</p><p>In this report, we compare and evaluate several genome assembly software based on TSG technology. The experimentation has been performed on 4 reference genomes and the results evaluated with the QUAST software. The 11 software that have been evaluated are: Celera Assembler , Falcon , Miniasm, Newbler , SGA Assembler, Smartdenovo, Abruijn, Ra, DBG2OLC, Spades and Cerulean. The first 8 software use only long reads, while the 3 last software can merge long and short reads</p>]]></description>
	<dc:creator>BioStar</dc:creator>
	<enclosure url="https://bioinformaticsonline.com/file/download/38886" length="382699" type="application/pdf" />
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39253/gmass-a-novel-measure-for-genomeassembly-structural-similarity</guid>
	<pubDate>Sun, 14 Apr 2019 20:35:40 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39253/gmass-a-novel-measure-for-genomeassembly-structural-similarity</link>
	<title><![CDATA[GMASS: a novel measure for genomeassembly structural similarity]]></title>
	<description><![CDATA[<div id="Abstract">
<div id="ASec3">
<p id="Par3">The GMASS score is a novel measure for representing structural similarity between two assemblies. It will contribute to the understanding of assembly output and developing de novo assemblers.</p>
<p><a href="https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-019-2710-z">https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-019-2710-z</a></p>
</div>
</div><p>Address of the bookmark: <a href="http://bioinfo.konkuk.ac.kr/GMASS/htdocs/syncircos.php" rel="nofollow">http://bioinfo.konkuk.ac.kr/GMASS/htdocs/syncircos.php</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40598/mitoz-a-toolkit-for-animal-mitochondrial-genome-assembly-annotation-and-visualization</guid>
	<pubDate>Fri, 24 Jan 2020 04:09:15 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40598/mitoz-a-toolkit-for-animal-mitochondrial-genome-assembly-annotation-and-visualization</link>
	<title><![CDATA[MitoZ: a toolkit for animal mitochondrial genome assembly, annotation and visualization]]></title>
	<description><![CDATA[<p><span>MitoZ is a Python3-based toolkit which aims to automatically filter pair-end raw data (fastq files), assemble genome, search for mitogenome sequences from the genome assembly result, annotate mitogenome (genbank file as result), and mitogenome visualization. MitoZ is available from&nbsp;</span><code>https://github.com/linzhi2013/MitoZ</code><span>.</span></p>
<p><span><a href="https://academic.oup.com/nar/article/47/11/e63/5377471">https://academic.oup.com/nar/article/47/11/e63/5377471</a></span></p><p>Address of the bookmark: <a href="https://github.com/linzhi2013/MitoZ" rel="nofollow">https://github.com/linzhi2013/MitoZ</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</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/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>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/42166/software-for-genome-assembly</guid>
	<pubDate>Sun, 30 Aug 2020 09:51:38 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/42166/software-for-genome-assembly</link>
	<title><![CDATA[Software for genome assembly !]]></title>
	<description><![CDATA[<p>List of bioinformatics tools/Software Website References for genome assembly:</p><p>1 Falcon&nbsp;https://github.com/PacificBiosciences/pb-assembly</p><p>2 Canu assembler http://canu.readthedocs.io/en/latest/index.html</p><p>3 Miniasm assembler https://github.com/lh3/miniasm</p><p>4 PBJelly scaffolding tool https://sourceforge.net/projects/pb-jelly/</p><p>5 ARCS scaffolding tool https://github.com/bcgsc/arcs</p><p>6 Redundans reduction and scaffolding tool https://github.com/Gabaldonlab/redundans</p><p>7 Arrow error correction https://github.com/PacificBiosciences/ GenomicConsensus</p><p>8 PILON error correction https://github.com/broadinstitute/pilon/wiki</p><p>9 BUSCO single copy gene markers http://busco.ezlab.org/</p><p>10 Bandage graph assembly viewer https://rrwick.github.io/Bandage/</p><p>11 Gepard dotter http://cube.univie.ac.at/gepard</p><p>12 MUMmer aligner and plotter http://mummer.sourceforge.net/</p>]]></description>
	<dc:creator>LEGE</dc:creator>
</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>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43614/mitoz-a-toolkit-for-animal-mitochondrial-genome-assembly-annotation-and-visualization</guid>
	<pubDate>Tue, 30 Nov 2021 23:23:57 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43614/mitoz-a-toolkit-for-animal-mitochondrial-genome-assembly-annotation-and-visualization</link>
	<title><![CDATA[MitoZ: a toolkit for animal mitochondrial genome assembly, annotation and visualization]]></title>
	<description><![CDATA[<p>MitoZ, consisting of independent modules of <em>de novo</em> assembly, findMitoScaf (find Mitochondrial Scaffolds), annotation and visualization, that can generate mitogenome assembly together with annotation and visualization results from HTS raw reads.</p>
<p>https://academic.oup.com/nar/article/47/11/e63/5377471</p><p>Address of the bookmark: <a href="https://github.com/linzhi2013/MitoZ" rel="nofollow">https://github.com/linzhi2013/MitoZ</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>

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