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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/34172?offset=10</link>
	<atom:link href="https://bioinformaticsonline.com/related/34172?offset=10" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/33720/deschrambler</guid>
	<pubDate>Thu, 29 Jun 2017 11:54:59 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/33720/deschrambler</link>
	<title><![CDATA[DESCHRAMBLER]]></title>
	<description><![CDATA[<p>DESCHRAMBLER is shown to produce highly accurate reconstructions using data simulation and by benchmarking it against other reconstruction tools</p>
<p>You can find the detail of reconstructed data at http://bioinfo.konkuk.ac.kr/DESCHRAMBLER/</p><p>Address of the bookmark: <a href="https://github.com/jkimlab/DESCHRAMBLER" rel="nofollow">https://github.com/jkimlab/DESCHRAMBLER</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41604/synteny-and-rearrangement-identifier-syri</guid>
	<pubDate>Tue, 05 May 2020 10:37:10 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41604/synteny-and-rearrangement-identifier-syri</link>
	<title><![CDATA[Synteny and Rearrangement Identifier (SyRI)]]></title>
	<description><![CDATA[<p>SyRI is a comprehensive tool for predicting genomic differences between related genomes using whole-genome assemblies (WGA). The assemblies are aligned using whole-genome alignment tools, and these alignments are then used as input to SyRI. SyRI identifies syntenic path (longest set of co-linear regions), structural rearrangements (inversions, translocations, and duplications), local variations (SNPs, indels, CNVs etc) within syntenic and structural rearrangements, and un-aligned regions.</p><p>Address of the bookmark: <a href="https://schneebergerlab.github.io/syri/" rel="nofollow">https://schneebergerlab.github.io/syri/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34920/xmatchview-smith-waterman-alignment-visualization</guid>
	<pubDate>Thu, 28 Dec 2017 09:00:58 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34920/xmatchview-smith-waterman-alignment-visualization</link>
	<title><![CDATA[xmatchview: smith-waterman alignment visualization]]></title>
	<description><![CDATA[<p><span>xmatchview and xmatchview-conifer are imaging tools for comparing the synteny between DNA sequences. It allows users to align 2 DNA sequences in fasta format using cross_match and displays the alignment in a variety of image formats. xmatchview and xmatchview-conifer are written in python and run on linux and windows. They serve as visual tools for analyzing cross_match alignments. Cross_match (Green, P. (1994)&nbsp;</span><a href="http://www.phrap.org/">http://www.phrap.org</a><span>) uses an implementation of the Smith-Waterman algorithm for comparing DNA sequences that is sensitive.</span></p>
<p><span>http://www.bcgsc.ca/platform/bioinfo/software/xmatchview</span></p><p>Address of the bookmark: <a href="https://github.com/warrenlr/xmatchview" rel="nofollow">https://github.com/warrenlr/xmatchview</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42143/sibelia-a-comparative-genomics-tool</guid>
	<pubDate>Sat, 22 Aug 2020 02:49:00 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42143/sibelia-a-comparative-genomics-tool</link>
	<title><![CDATA[Sibelia: A comparative genomics tool]]></title>
	<description><![CDATA[<p><strong>Sibelia</strong>: A comparative genomics tool: It assists biologists in analysing the genomic variations that correlate with pathogens, or the genomic changes that help microorganisms adapt in different environments. Sibelia will also be helpful for the evolutionary and genome rearrangement studies for multiple strains of microorganisms.&nbsp;</p>
<p><strong>Sibelia</strong>&nbsp;is useful in finding: (1) shared regions, (2) regions that present in one group of genomes but not in others, (3) rearrangements that transform one genome to other genomes.</p>
<p>More at&nbsp;<a href="http://bioinf.spbau.ru/sibelia">http://bioinf.spbau.ru/sibelia</a></p>
<p>Sibelia docs&nbsp;<a href="http://gensoft.pasteur.fr/docs/Sibelia/3.0.7/SIBELIA.md">http://gensoft.pasteur.fr/docs/Sibelia/3.0.7/SIBELIA.md</a></p><p>Address of the bookmark: <a href="https://github.com/bioinf/Sibelia" rel="nofollow">https://github.com/bioinf/Sibelia</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43888/syri-compares-alignments-between-two-chromosome-level-assemblies-and-identifies-synteny-and-structural-rearrangements</guid>
	<pubDate>Wed, 01 Jun 2022 02:01:13 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43888/syri-compares-alignments-between-two-chromosome-level-assemblies-and-identifies-synteny-and-structural-rearrangements</link>
	<title><![CDATA[Syri compares alignments between two chromosome-level assemblies and identifies synteny and structural rearrangements.]]></title>
	<description><![CDATA[<p><span>Syri compares alignments between two chromosome-level assemblies and identifies synteny and structural rearrangements.</span></p>
<p><span><img src="https://github.com/schneebergerlab/syri/raw/master/example/ampril_col0_chr3_6600000_10000000.png" alt="image" style="border: 0px;"></span></p><p>Address of the bookmark: <a href="https://github.com/schneebergerlab/syri" rel="nofollow">https://github.com/schneebergerlab/syri</a></p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/5379/interview-mark-sansom-u-oxford-simulations-of-membrane-proteins</guid>
	<pubDate>Mon, 07 Oct 2013 14:34:13 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/5379/interview-mark-sansom-u-oxford-simulations-of-membrane-proteins</link>
	<title><![CDATA[Interview Mark Sansom (U. Oxford): Simulations of Membrane Proteins]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/Fu8hiBu5V5Y" frameborder="0" allowfullscreen></iframe>Workshop in Bioinformatics, 4/June/2012
Campus Vida's Research Centers organize in Santiago de Compostela the Workshop in Bioinformatics. This event addressed issues such as structural bioinformatics, biological modelling and mining bioinformatics data.
Professor Mark Sansom (University of Oxford), belonging to the Structural Bioinformatics and Computational Biochemistr Unit, opened the sessions with the lecture "Multiscale Simulations of Membrane Proteins: Lipid Interactions and Signalling".]]></description>
	
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	<guid isPermaLink="true">https://bioinformaticsonline.com/poll/view/23590/will-minion-nanopore-sequencing-increase-the-number-of-next-generation-sequencing-projects</guid>
	<pubDate>Tue, 04 Aug 2015 05:14:07 -0500</pubDate>
	<link>https://bioinformaticsonline.com/poll/view/23590/will-minion-nanopore-sequencing-increase-the-number-of-next-generation-sequencing-projects</link>
	<title><![CDATA[Will MinION Nanopore sequencing increase the number of Next Generation Sequencing projects?]]></title>
	<description><![CDATA[<p>Will MinION Nanopore sequencing increase the number of Next Generation Sequencing projects?</p>]]></description>
	<dc:creator>Strand</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/34916/bioinformatics-tools-developed-for-oxford-nanopore-data-analysis</guid>
	<pubDate>Wed, 27 Dec 2017 20:47:30 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/34916/bioinformatics-tools-developed-for-oxford-nanopore-data-analysis</link>
	<title><![CDATA[Bioinformatics tools developed for Oxford Nanopore data analysis !]]></title>
	<description><![CDATA[<p><span>MinION is the only portable real-time device for DNA and RNA&nbsp;</span><span>sequencing</span><span>. Each consumable flow cell can now generate 10&ndash;20 Gb of DNA&nbsp;</span><span>sequence</span><span>&nbsp;data. Ultra-</span><span>long read lengths are possible (hundreds of kb) as you can choose your fragment length.&nbsp;</span>One of the technical advantages of ONT data is the read length, which offers great prospects for genome assembly. Generally, assemblers are based on several different types of algorithms, such as greedy, overlap-layout-consensus (OLC), de Bruijn graph (DBG), and string graph.</p><p><span>List of analysis tools developed for Oxford Nanopore data</span></p><p>BWA <br />Fast nanopore data tuned alignment tool <br />https://github.com/lh3/bwa</p><p>GraphMap<br />Mapper for long and error-prone reads<br />https://github.com/isovic/graphmap</p><p>LAST<br />Nanopore tuned alignment tool<br />http://last.cbrc.jp/</p><p>LINKS<br />Software tool for long read scaffolding <br />https://github.com/warrenlr/LINKS/</p><p>marginAlign<br />Tools to align nanopore reads to a reference<br />https://github.com/benedictpaten/marginAlign</p><p>minoTour<br />Real time analysis tools<br />http://minotour.nottingham.ac.uk/</p><p>nanoCORR<br />Error-correction tool for nanopore sequence data<br />https://github.com/jgurtowski/nanocorr</p><p>NanoOK<br />Software for nanopore data, quality and error profiles<br />https://documentation.tgac.ac.uk/display/NANOOK/NanoOK</p><p>Nanopolish<br />Nanopore analysis and genome assembly software<br />https://github.com/jts/nanopolish</p><p>nanopore<br />Variant-detection tool for nanopore sequence data<br />https://github.com/mitenjain/nanopore</p><p>Nanocorrect<br />Error-correction tool for nanopore sequence data<br />https://github.com/jts/nanocorrect/</p><p>npReader<br />Real-time conversion and analysis of nanopore reads<br />https://github.com/mdcao/npReader</p><p>poRe<br />Tool for analyzing and visualizing nanopore data<br />https://sourceforge.net/p/rpore/wiki/Home/</p><p>PoreSeq<br />Error-correction and variant-calling software<br />https://github.com/tszalay/poreseq</p><p>Poretools<br />Nanopore sequence analysis and visualization software <br />https://github.com/arq5x/poretools</p><p>SSPACE-LongRead<br />Genome scaffolding tool <br />http://www.baseclear.com/genomics/bioinformatics/basetools/SSPACE-longread</p><p>SMIS<br />Genome scaffolding tool <br />https://sourceforge.net/projects/phusion2/files/smis/</p><p>&nbsp;</p><p>List of assemblers for Oxford Nanopore MinION long reads</p><p>LQS<br />DALIGNER, Celera OLC Nanocorrect, <br />Nanopolish corrector<br />https://github.com/jts/nanopolish</p><p>PBcR<br />HGAP or BLASR, Celera OLC <br />PBcR corrector<br />http://wgs-assembler.sourceforge.net/wiki/index.php/PBcR<br /> &ndash;<br />Canu<br />MHAP, Celera OLC <br />Canu corrector<br />https://github.com/marbl/canu</p><p>Falcon<br />String graph, Celera OLC <br />Falcon corrector<br />https://github.com/PacificBiosciences/falcon</p><p>Miniasm <br />OLC<br />https://github.com/lh3/miniasm</p><p>ra-integrate<br />OLC<br />https://github.com/mariokostelac/ra-integrate/</p><p>ALLPATHS-LG<br />de Bruijn graph <br />ALLPATHS-L corrector<br />https://www.broadinstitute.org/software/allpaths-lg/blog/?page_id=12</p><p>SPAdes <br />de Bruijn graph <br />SPAdes corrector<br />http://bioinf.spbau.ru/spades</p>]]></description>
	<dc:creator>biogeek</dc:creator>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38299/deepbinner-a-signal-level-demultiplexer-for-oxford-nanopore-reads</guid>
	<pubDate>Tue, 27 Nov 2018 03:38:49 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38299/deepbinner-a-signal-level-demultiplexer-for-oxford-nanopore-reads</link>
	<title><![CDATA[Deepbinner: a signal-level demultiplexer for Oxford Nanopore reads]]></title>
	<description><![CDATA[<p>Deepbinner is a tool for demultiplexing barcoded&nbsp;<a href="https://nanoporetech.com/">Oxford Nanopore</a>&nbsp;sequencing reads. It does this with a deep&nbsp;<a href="https://adeshpande3.github.io/adeshpande3.github.io/A-Beginner's-Guide-To-Understanding-Convolutional-Neural-Networks/">convolutional neural network</a>&nbsp;classifier, using many of the&nbsp;<a href="https://towardsdatascience.com/neural-network-architectures-156e5bad51ba">architectural advances</a>&nbsp;that have proven successful in image classification. Unlike other demultiplexers (e.g. Albacore and&nbsp;<a href="https://github.com/rrwick/Porechop">Porechop</a>), Deepbinner identifies barcodes from the raw signal (a.k.a. squiggle) which gives it greater sensitivity and fewer unclassified reads.</p>
<ul>
<li><span>Reasons to use Deepbinner</span>:
<ul>
<li>To minimise the number of unclassified reads (use Deepbinner by itself).</li>
<li>To minimise the number of misclassified reads (use Deepbinner in conjunction with Albacore demultiplexing).</li>
<li>You plan on running signal-level downstream analyses, like&nbsp;<a href="https://github.com/jts/nanopolish">Nanopolish</a>. Deepbinner can&nbsp;<a href="https://github.com/rrwick/Deepbinner#using-deepbinner-before-basecalling">demultiplex the fast5 files</a>which makes this easier.</li>
</ul>
</li>
<li><span>Reasons to&nbsp;<em>not</em>&nbsp;use Deepbinner</span>:
<ul>
<li>You only have basecalled reads not the raw fast5 files (which Deepbinner requires).</li>
<li>You have a small/slow computer. Deepbinner is more computationally intensive than&nbsp;<a href="https://github.com/rrwick/Porechop">Porechop</a>.</li>
<li>You used a sequencing/barcoding kit other than&nbsp;<a href="https://github.com/rrwick/Deepbinner/blob/master/models">the ones Deepbinner was trained on</a>.</li>
</ul>
</li>
</ul><p>Address of the bookmark: <a href="https://github.com/rrwick/Deepbinner" rel="nofollow">https://github.com/rrwick/Deepbinner</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27438/hagfish-assess-an-assembly-through-creative-use-of-coverage-plots</guid>
	<pubDate>Fri, 20 May 2016 19:08:17 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27438/hagfish-assess-an-assembly-through-creative-use-of-coverage-plots</link>
	<title><![CDATA[Hagfish - assess an assembly through creative use of coverage plots]]></title>
	<description><![CDATA[<p>Hagfish is a tool that is to be used in data analysis of Next Generation Sequencing (NGS) experiments. Hagfish builds on the concept of coverage plots and aims to assist (amongst others) in quality control of&nbsp;<em style="font-size: 12.8px;">de novo</em>&nbsp;genome assembly or identification of structural variation in a genome re-sequencing experiment.</p>
<p>Hagfish requires a reference sequence and a&nbsp;<span>paired end</span>&nbsp;re-sequencing data set. Hagfish has more power the larger the insert size of the paired end library is.</p>
<p>Quick links:&nbsp;<a href="https://github.com/mfiers/hagfish/wiki/Install">Installation</a>,<a href="https://github.com/mfiers/hagfish/wiki/Operation">Operation</a>,&nbsp;<a href="https://github.com/mfiers/hagfish/wiki/ReadMappers">Read mappers</a>,&nbsp;<a href="https://github.com/mfiers/hagfish/wiki/Scripts">Hagfish scripts</a>,&nbsp;<a href="https://github.com/mfiers/hagfish/wiki/Plots">Hagfish plots</a></p><p>Address of the bookmark: <a href="https://github.com/mfiers/hagfish" rel="nofollow">https://github.com/mfiers/hagfish</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
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