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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/30147?offset=100</link>
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	<description><![CDATA[]]></description>
	
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	<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>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/31566/software-and-tools-to-detect-structure-variation-with-long-reads</guid>
	<pubDate>Wed, 15 Mar 2017 14:31:09 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/31566/software-and-tools-to-detect-structure-variation-with-long-reads</link>
	<title><![CDATA[Software and Tools to detect structure variation with long reads !!]]></title>
	<description><![CDATA[<p>Uncovering the connection between genetics and heritable diseases requires an approach that looks at all the variant bases and types in a genome. While a PacBio&nbsp;<em>de novo</em>&nbsp;assembly resolves the most novel SV variants. 8-10X PacBio coverage of single genomes or trios reveals triple the SVs detectable by short-read data.</p><p>With&nbsp;<span style="text-decoration: underline;"><a href="http://www.pacb.com/smrt-science/">Single Molecule, Real-Time (SMRT) Sequencing</a></span>, you can access structural variations having a broad range of sizes, types, and GC content with the ability to:</p><ul>
<li>Uncover missing heritability linked to structural variation</li>
<li>Unambiguously identify genomic context and variant breakpoints at the sequence level to unravel the genetic etiology of disease</li>
<li>Resolve structural variation across the complete size spectrum with basepair resolution</li>
</ul><p>Following are the SV tools, which can assist you to achieve your goal.</p><p><strong>Sniffles:</strong>&nbsp;Structural variation caller using third generation sequencing</p><p>Sniffles is a structural variation caller using third generation sequencing (PacBio or Oxford Nanopore). It detects all types of SVs using evidence from split-read alignments, high-mismatch regions, and coverage analysis. Please note the current version of Sniffles requires sorted output from BWA-MEM (use -M and -x parameter) or NGM-LR with the optional SAM attributes enabled!&nbsp;</p><p>More at&nbsp;https://github.com/fritzsedlazeck/Sniffles</p><p><strong style="font-size: 12.8px;"><br />MultiBreak-SV:</strong> It identifies structural variants from next-generation paired end data, third-generation long read data, or data from a combination of sequencing platforms.</p><p>There are two pieces of software in this release: (1) a pre-processor that takes machineformat (.m5) BLASR files, and (2) MultiBreak-SV. For installation and usage instructions, see doc/MultiBreakSV-Manual.txt.</p><p>More at&nbsp;https://github.com/raphael-group/multibreak-sv</p><p><strong style="font-size: 12.8px;"><br />Parliament:</strong>&nbsp;A Structural Variation Tool. Why ask a single sv-detection approach to find every variant when you can have a parliament of tools deciding?</p><p>Publication about the algorithm and &ldquo;&hellip;the first long-read characterization of structural variation in a diploid human personal genome&hellip;&rdquo; (HS1011) -&nbsp;<a href="http://www.biomedcentral.com/1471-2164/16/286">&ldquo;Assessing structural variation in a personal genome&mdash;towards a human reference diploid genome&rdquo;</a></p><p>More at&nbsp;https://sourceforge.net/projects/parliamentsv/</p><p>https://www.dnanexus.com/papers/Parliament_Info_Sheet.pdf</p><p><br /><strong>PBHoney:</strong>&nbsp;the structural variation discovery tool&nbsp;<br /><br />PBHoney is an implementation of two variant-identification approaches designed to exploit the high mappability of long reads (i.e., greater than 10,000 bp). PBHoney considers both intra-read discordance and soft-clipped tails of long reads to identify structural variants.</p><p>Read The Paper&nbsp;<a href="http://www.biomedcentral.com/1471-2105/15/180/abstract" target="_blank">http://www.biomedcentral.com/1471-2105/15/180/abstract</a></p><p>More at&nbsp;https://sourceforge.net/projects/pb-jelly/</p><p><strong><br />SMRT-SV:</strong> Structural variant and indel caller for PacBio reads</p><p>Structural variant (SV) and indel caller for PacBio reads based on methods from&nbsp;<a href="http://www.nature.com/nature/journal/vaop/ncurrent/full/nature13907.html">Chaisson et al. 2014</a>.</p><p>SMRT-SV provides an official software package for tools described in&nbsp;<a href="http://www.nature.com/nature/journal/vaop/ncurrent/full/nature13907.html">Chaisson et al. 2014</a>&nbsp;and adds several key features including the following.</p><ul>
<li>Unified variant calling user interface with built-in cluster compute support</li>
<li>Small indel calling (2-49 bp)</li>
<li>Improved inversion calling (<code>screenInversions</code>)</li>
<li>Quality metric for SV calls based on number of local assemblies supporting each call</li>
<li>Higher sensitivity for SV calls using tiled local assemblies across the entire genome instead of "signature" regions</li>
<li>Genotyping of SVs with Illumina paired-end reads from WGS samples</li>
</ul><p>More at&nbsp;https://github.com/EichlerLab/pacbio_variant_caller</p>]]></description>
	<dc:creator>Archana Malhotra</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32633/a-post-assembly-genome-improvement-toolkit-pagit-to-obtain-annotated-genomes-from-contigs</guid>
	<pubDate>Fri, 12 May 2017 10:50:29 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32633/a-post-assembly-genome-improvement-toolkit-pagit-to-obtain-annotated-genomes-from-contigs</link>
	<title><![CDATA[A Post-assembly genome-improvement toolkit (PAGIT) to obtain annotated genomes from contigs]]></title>
	<description><![CDATA[<p>PAGIT addresses the need for software to generate high quality draft genomes. It is based on a series of programs that we developed:</p>
<p><a href="https://sourceforge.net/projects/abacas/files/">ABACAS</a>, that is able to contiguate contigs from a de novo assembly against a closely related reference.</p>
<p><a href="https://sourceforge.net/projects/image2/files/">IMAGE</a>, an iterative approach for closing gaps in assembled genomes using mate pair information. It is able to close gaps left open by the assembler in a draft genome, even when using the same data sets as used by the original assembler.</p>
<p><a href="http://icorn.sourceforge.net/">iCORN</a>, that enables errors in the consensus sequence to be corrected by iteratively mapping reads to the current assembly. An improved version, especially correction Pacfic Bioscience assemblies (PacBio) can be found&nbsp;<a href="ftp://ftp.sanger.ac.uk/pub4/resources/software/pagit/ICORN2/icorn2.V0.95.tgz">here</a>.</p>
<p><a href="https://ratt.svn.sourceforge.net/svnroot/ratt">RATT</a>, a tool to transfer the annotation from a reference genome, or an earlier assembly, onto the latest assembly.</p>
<p>PAGIT bundles these software and makes them more accessible for users.</p><p>Address of the bookmark: <a href="http://www.sanger.ac.uk/science/tools/pagit" rel="nofollow">http://www.sanger.ac.uk/science/tools/pagit</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34216/meraculous-de-novo-genome-assembly-with-short-paired-end-reads</guid>
	<pubDate>Tue, 07 Nov 2017 04:36:10 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34216/meraculous-de-novo-genome-assembly-with-short-paired-end-reads</link>
	<title><![CDATA[Meraculous: De Novo Genome Assembly with Short Paired-End Reads]]></title>
	<description><![CDATA[<p><span>We describe a new algorithm, meraculous, for whole genome assembly of deep paired-end short reads, and apply it to the assembly of a dataset of paired 75-bp Illumina reads derived from the 15.4 megabase genome of the haploid yeast&nbsp;</span><em>Pichia stipitis</em><span>. More than 95% of the genome is recovered, with no errors; half the assembled sequence is in contigs longer than 101 kilobases and in scaffolds longer than 269 kilobases. Incorporating fosmid ends recovers entire chromosomes. Meraculous relies on an efficient and conservative traversal of the subgraph of the&nbsp;</span><em>k</em><span>-mer (deBruijn) graph of oligonucleotides with unique high quality extensions in the dataset, avoiding an explicit error correction step as used in other short-read assemblers. A novel memory-efficient hashing scheme is introduced. The resulting contigs are ordered and oriented using paired reads separated by &sim;280 bp or &sim;3.2 kbp, and many gaps between contigs can be closed using paired-end placements. Practical issues with the dataset are described, and prospects for assembling larger genomes are discussed.</span></p><p>Address of the bookmark: <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3158087/" rel="nofollow">https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3158087/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36597/gappadder-a-sensitive-approach-for-closing-gaps-on-draft-genomes-with-short-sequence-reads</guid>
	<pubDate>Mon, 14 May 2018 05:25:48 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36597/gappadder-a-sensitive-approach-for-closing-gaps-on-draft-genomes-with-short-sequence-reads</link>
	<title><![CDATA[GAPPadder: A Sensitive Approach for Closing Gaps on Draft Genomes with Short Sequence Reads]]></title>
	<description><![CDATA[<p><span>This software is provided ``as is&rdquo; without warranty of any kind. In no event shall the author be held responsible for any damage resulting from the use of this software. The program package, including source codes, executables, and this documentation, is distributed free of charge. If you use this program in a publication, please cite the following reference:</span><br><span>Chong Chu, Xin Li, and Yufeng Wu. "GAPPadder: A Sensitive Approach for Closing Gaps on Draft Genomes with Short Sequence Reads." bioRxiv (2017): 125534.</span></p><p>Address of the bookmark: <a href="https://github.com/Reedwarbler/GAPPadder" rel="nofollow">https://github.com/Reedwarbler/GAPPadder</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36897/gmcloser-closing-gaps-in-assemblies-accurately-with-a-likelihood-based-selection-of-contig-or-long-read-alignments</guid>
	<pubDate>Mon, 11 Jun 2018 05:43:44 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36897/gmcloser-closing-gaps-in-assemblies-accurately-with-a-likelihood-based-selection-of-contig-or-long-read-alignments</link>
	<title><![CDATA[GMcloser: closing gaps in assemblies accurately with a likelihood-based selection of contig or long-read alignments]]></title>
	<description><![CDATA[GMcloser uses likelihood-based classifiers calculated from the alignment statistics between scaffolds, contigs and paired-end reads to correctly assign contigs or long reads to gap regions of scaffolds, thereby achieving accurate and efficient gap closure. We demonstrate with sequencing data from various organisms that the gap-closing accuracy of GMcloser is 3–100-fold higher than those of other available tools, with similar efficiency.

https://academic.oup.com/bioinformatics/article/31/23/3733/209212<p>Address of the bookmark: <a href="https://academic.oup.com/bioinformatics/article/31/23/3733/209212" rel="nofollow">https://academic.oup.com/bioinformatics/article/31/23/3733/209212</a></p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38316/simba-a-genome-assembly-project-management-system</guid>
	<pubDate>Thu, 29 Nov 2018 08:52:25 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38316/simba-a-genome-assembly-project-management-system</link>
	<title><![CDATA[SIMBA: a Genome Assembly Project Management System]]></title>
	<description><![CDATA[<p><span>SIMBA</span><span>, SImple Manager for Bacterial Assemblies, is a Web interface for managing assembly projects of bacterial genomes. SIMBA was created to assist bioinformaticians to assemble bacterial genomes sequenced with NextGeneration Sequencing (NGS) platforms quickly, easily and effectively. SIMBA also is open source tool, i.e., can be freely downloaded, shared and modified.</span></p><p>Address of the bookmark: <a href="http://ufmg-simba.sourceforge.net/" rel="nofollow">http://ufmg-simba.sourceforge.net/</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40573/de-novo-genome-assembly-for-illumina-data</guid>
	<pubDate>Mon, 20 Jan 2020 05:13:29 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40573/de-novo-genome-assembly-for-illumina-data</link>
	<title><![CDATA[De novo Genome Assembly for Illumina Data]]></title>
	<description><![CDATA[<p>Written and maintained by <a href="mailto:simon.gladman@unimelb.edu.au">Simon Gladman</a> - Melbourne Bioinformatics (formerly VLSCI)</p>
<p>Protocol Overview / Introduction</p>
<p>In this protocol we discuss and outline the process of de novo assembly for small to medium sized genomes.</p>
<p>https://www.melbournebioinformatics.org.au/tutorials/tutorials/assembly/assembly-protocol/</p><p>Address of the bookmark: <a href="https://www.melbournebioinformatics.org.au/tutorials/tutorials/assembly/assembly-protocol/" rel="nofollow">https://www.melbournebioinformatics.org.au/tutorials/tutorials/assembly/assembly-protocol/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43315/genome-assembly-workshop-2020</guid>
	<pubDate>Wed, 25 Aug 2021 04:30:32 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43315/genome-assembly-workshop-2020</link>
	<title><![CDATA[Genome Assembly Workshop 2020]]></title>
	<description><![CDATA[<p><span>Our team offers custom bioinformatics services to academic and private organizations. We have a strong academic background with a focus on cutting edge, open source software. We replicate standard analysis pipelines (best practices) when appropriate, and/or develop novel applications and pipelines when needed, however we always emphasize biological interpretation of the data.</span></p>
<p><span>More at&nbsp;https://ucdavis-bioinformatics-training.github.io/</span></p><p>Address of the bookmark: <a href="https://ucdavis-bioinformatics-training.github.io/2020-Genome_Assembly_Workshop/snakemake/snakemake_intro" rel="nofollow">https://ucdavis-bioinformatics-training.github.io/2020-Genome_Assembly_Workshop/snakemake/snakemake_intro</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/44342/ncbi-datasets%E2%80%AFpages</guid>
	<pubDate>Wed, 12 Jul 2023 06:29:31 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/44342/ncbi-datasets%E2%80%AFpages</link>
	<title><![CDATA[NCBI Datasets pages]]></title>
	<description><![CDATA[<p>Update! Assembly and Genome record pages now redirect to new NCBI Datasets pages. NCBI Datasets is a new resource that makes it easier to find and download genome data. Learn more: https://ncbiinsights.ncbi.nlm.nih.gov/2023/07/11/ncbi-datasets-genome-assembly-pages/&nbsp;<a href="https://ow.ly/GU3o50P8QH4"></a><a href="https://www.linkedin.com/feed/hashtag/?keywords=ncbicgr&amp;highlightedUpdateUrns=urn%3Ali%3Aactivity%3A7084592728260386816">#NCBICGR</a></p><p><span>Effective July 10, 2023, NCBI&rsquo;s Assembly and Genome record pages now redirect to&nbsp;</span>new<a href="https://www.ncbi.nlm.nih.gov/datasets/?utm_source=ncbi_insights&amp;utm_medium=referral&amp;utm_campaign=datasets-genome-assembly-redirect-20230711"> NCBI Datasets </a><span>pages. As&nbsp;</span><a href="https://ncbiinsights.ncbi.nlm.nih.gov/2023/03/07/ncbi-datasets-genome-taxonomy-pages/?utm_source=ncbi_insights&amp;utm_medium=referral&amp;utm_campaign=datasets-genome-assembly-redirect-20230711">previously announced</a><span>, these updates are part of our ongoing effort to modernize and improve your user experience. NCBI Datasets is a new resource that makes it easier to find and download genome data.  </span><span>&nbsp;</span></p><h5>The following pages have been updated:</h5><ul>
<li><span>The NCBI Assembly record pages now redirect to the new </span><a href="https://www.ncbi.nlm.nih.gov/datasets/genome/GCF_023065955.2/?utm_source=ncbi_insights&amp;utm_medium=referral&amp;utm_campaign=datasets-genome-assembly-redirect-20230711"><span>NCBI Datasets</span><strong><span> </span></strong><span>Genome</span></a><span> </span><span>record pages that describe assembled genomes and provide links to related NCBI tools such as Genome Data Viewer and BLAST. </span><span>&nbsp;</span></li>
<li><span>The NCBI</span><strong> </strong><span>Genome record pages now redirect to the </span><a href="https://www.ncbi.nlm.nih.gov/datasets/taxonomy/9644/?utm_source=ncbi_insights&amp;utm_medium=referral&amp;utm_campaign=datasets-genome-assembly-redirect-20230711"><span>NCBI Datasets</span><strong><span> </span></strong><span>Taxonomy</span></a><span> </span><span>record pages that provide a taxonomy-focused portal to genes, genomes, and additional NCBI resources.  </span><span>&nbsp;</span></li>
</ul><p><span>During this transition, you will have the option to return to the legacy Genome and Assembly record pages. We will remove the legacy pages in early 2024. </span><span>&nbsp;</span></p>]]></description>
	<dc:creator>BioStar</dc:creator>
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