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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/34711?offset=240</link>
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	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44659/figeno-tool-for-plotting-sequencing-data-along-genomic-coordinates</guid>
	<pubDate>Tue, 17 Sep 2024 02:28:15 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44659/figeno-tool-for-plotting-sequencing-data-along-genomic-coordinates</link>
	<title><![CDATA[Figeno: Tool for plotting sequencing data along genomic coordinates.]]></title>
	<description><![CDATA[<p><span>Tool for plotting sequencing data along genomic coordinates.</span></p>
<div>
<pre><code>FIGENO is a
  FIGure
    GENerator
for GENOmics</code></pre>
</div>
<p dir="auto">With figeno, you can plot various types of sequencing data along genomic coordinates. Video overview:&nbsp;<a href="https://www.youtube.com/watch?v=h1cBeXoSYTA">https://www.youtube.com/watch?v=h1cBeXoSYTA</a>.</p>
<p dir="auto"><a href="https://github.com/CompEpigen/figeno/blob/main/docs/content/images/figeno.png" target="_blank"><img src="https://github.com/CompEpigen/figeno/raw/main/docs/content/images/figeno.png" alt="figeno" style="border: 0px;"></a></p><p>Address of the bookmark: <a href="https://github.com/CompEpigen/figeno" rel="nofollow">https://github.com/CompEpigen/figeno</a></p>]]></description>
	<dc:creator>LEGE</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>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36755/minialign-fast-and-accurate-alignment-tool-for-pacbio-and-nanopore-long-reads</guid>
	<pubDate>Thu, 24 May 2018 08:33:26 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36755/minialign-fast-and-accurate-alignment-tool-for-pacbio-and-nanopore-long-reads</link>
	<title><![CDATA[minialign: fast and accurate alignment tool for PacBio and Nanopore long reads]]></title>
	<description><![CDATA[Minialign is a little bit fast and moderately accurate nucleotide sequence alignment tool designed for PacBio and Nanopore long reads. It is built on three key algorithms, minimizer-based index of the minimap overlapper, array-based seed chaining, and SIMD-parallel Smith-Waterman-Gotoh extension.<p>Address of the bookmark: <a href="https://github.com/ocxtal/minialign" rel="nofollow">https://github.com/ocxtal/minialign</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37962/wtdbg2-a-de-novo-sequence-assembler-for-long-noisy-reads-produced-by-pacbio-or-oxford-nanopore</guid>
	<pubDate>Fri, 19 Oct 2018 08:48:43 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37962/wtdbg2-a-de-novo-sequence-assembler-for-long-noisy-reads-produced-by-pacbio-or-oxford-nanopore</link>
	<title><![CDATA[Wtdbg2: a de novo sequence assembler for long noisy reads produced by PacBio or Oxford Nanopore]]></title>
	<description><![CDATA[<p><span>Wtdbg2 is a&nbsp;</span><em>de novo</em><span>&nbsp;sequence assembler for long noisy reads produced by PacBio or Oxford Nanopore Technologies (ONT). It assembles raw reads without error correction and then builds the consensus from intermediate assembly output. Wtdbg2 is able to assemble the human and even the 32Gb&nbsp;</span><a href="https://www.nature.com/articles/nature25458">Axolotl</a><span>&nbsp;genome at a speed tens of times faster than&nbsp;</span><a href="https://github.com/marbl/canu">CANU</a><span>&nbsp;and&nbsp;</span><a href="https://github.com/PacificBiosciences/FALCON">FALCON</a><span>while producing contigs of comparable base accuracy.</span></p><p>Address of the bookmark: <a href="https://github.com/ruanjue/wtdbg2" rel="nofollow">https://github.com/ruanjue/wtdbg2</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40871/nanopore-adaptor</guid>
	<pubDate>Mon, 03 Feb 2020 00:10:29 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40871/nanopore-adaptor</link>
	<title><![CDATA[Nanopore adaptor !]]></title>
	<description><![CDATA[<p>Porechop is a tool for finding and removing adapters from&nbsp;<a href="https://nanoporetech.com/">Oxford Nanopore</a>&nbsp;reads. Adapters on the ends of reads are trimmed off, and when a read has an adapter in its middle, it is treated as chimeric and chopped into separate reads. Porechop performs thorough alignments to effectively find adapters, even at low sequence identity.</p>
<p>Porechop also supports demultiplexing of Nanopore reads that were barcoded with the&nbsp;<a href="https://store.nanoporetech.com/native-barcoding-kit-1d.html">Native Barcoding Kit</a>,&nbsp;<a href="https://store.nanoporetech.com/pcr-barcoding-kit-96.html">PCR Barcoding Kit</a>&nbsp;or&nbsp;<a href="https://store.nanoporetech.com/rapid-barcoding-sequencing-kit.html">Rapid Barcoding Kit</a>.</p>
<p><span>The known Nanopore adapters that Porechop looks for are defined</span></p>
<p><a href="https://github.com/rrwick/Porechop/blob/master/porechop/adapters.py">https://github.com/rrwick/Porechop/blob/master/porechop/adapters.py</a></p>
<p>They are:</p>
<ul>
<li>Ligation kit adapters</li>
<li>Rapid kit adapters</li>
<li>PCR kit adapters</li>
<li>Barcodes</li>
<li>Native barcoding</li>
<li>Rapid barcoding</li>
</ul><p>Address of the bookmark: <a href="https://github.com/rrwick/Porechop/blob/master/porechop/adapters.py" rel="nofollow">https://github.com/rrwick/Porechop/blob/master/porechop/adapters.py</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/34702/run-miniasm-assembler-on-nanopore-reads</guid>
	<pubDate>Mon, 18 Dec 2017 04:07:50 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/34702/run-miniasm-assembler-on-nanopore-reads</link>
	<title><![CDATA[Run miniasm assembler on nanopore reads !]]></title>
	<description><![CDATA[<p>Miniasm is a very fast OLC-based&nbsp;<em>de novo</em>&nbsp;assembler for noisy long reads. It takes all-vs-all read self-mappings (typically by&nbsp;<a href="https://github.com/lh3/minimap">minimap</a>) as input and outputs an assembly graph in the&nbsp;<a href="https://github.com/pmelsted/GFA-spec/blob/master/GFA-spec.md">GFA</a>&nbsp;format. Different from mainstream assemblers, miniasm does not have a consensus step. It simply concatenates pieces of read sequences to generate the final&nbsp;<a href="http://wgs-assembler.sourceforge.net/wiki/index.php/Celera_Assembler_Terminology">unitig</a>&nbsp;sequences. Thus the per-base error rate is similar to the raw input reads.</p><p>Find the detail of the reads repeats:</p><blockquote><p>fq2fa ONT_A.fastq ONT_A.fasta&nbsp;<br /><br />minimap2 -xava-ont ONT_A.fasta ONT_A.fasta -t10 -X &gt; AONT.paf&nbsp;<br /><br />awk '{if($1==$6){print}}' AONT.paf &gt; AONTself.paf&nbsp;<br /><br />awk '$5=="-"' AONTself.paf | awk '{print $1}'| sort|uniq &gt; invertedrepeat.list</p></blockquote><p>Generated a few palindrome and repeats plots (highlighting only repeats largest than 10, 20 and 30 kb)</p><blockquote><p>minidot -f 5 -m 30000 AONTself.paf &gt; AONTself30000.eps&nbsp;<br />sed 's/_template_pass_FAH31515//' AONTself30000.eps &gt; AONTself30000final.eps&nbsp;<br /><br />minidot -f 5 -m 20000 AONTself.paf &gt; AONTself20000.eps&nbsp;<br />sed 's/_template_pass_FAH31515//' AONTself20000.eps &gt; AONTself20000final.eps&nbsp;<br /><br />minidot -f 5 -m 10000 AONTself.paf &gt; AONTself10000.eps&nbsp;<br />sed 's/_template_pass_FAH31515//' AONTself10000.eps &gt; AONTself10000final.eps&nbsp;</p></blockquote><p>Assemble with miniasm:</p><blockquote><p>miniasm -f ONT_A.fasta AONT.paf &gt; AONT.gfa&nbsp;</p><p>grep '^S' AONT.gfa |awk '{print "&gt;"$2"\n"$3}' &gt; AONT_miniasm.fasta&nbsp;<br /><br />minimap2 -xasm10 AONT_miniasm.fasta AONT_miniasm.fasta -t1 -X &gt; AONT_miniasm.paf&nbsp;<br /><br />awk '{if($1==$6){print}}' AONT_miniasm.paf &gt; AONT_miniasm_self.paf&nbsp;<br /><br />minidot -f 5 -m 10000 AONT_miniasm_self.paf &gt; AONT_miniasm_self10000.eps&nbsp;</p></blockquote><p>Njoy the assembly !</p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41689/medaka-sequence-correction-provided-by-ont-research</guid>
	<pubDate>Mon, 18 May 2020 16:28:00 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41689/medaka-sequence-correction-provided-by-ont-research</link>
	<title><![CDATA[medaka: Sequence correction provided by ONT Research]]></title>
	<description><![CDATA[<p><code>medaka</code><span>&nbsp;is a tool to create a consensus sequence from nanopore sequencing data. This task is performed using neural networks applied from a pileup of individual sequencing reads against a draft assembly. It outperforms graph-based methods operating on basecalled data, and can be competitive with state-of-the-art signal-based methods, whilst being much faster.</span></p><p>Address of the bookmark: <a href="https://github.com/nanoporetech/medaka" rel="nofollow">https://github.com/nanoporetech/medaka</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/3918/the-human-genome-project-video-3d-animation-introduction-low</guid>
	<pubDate>Sat, 24 Aug 2013 19:01:19 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/3918/the-human-genome-project-video-3d-animation-introduction-low</link>
	<title><![CDATA[The Human Genome Project Video   3D Animation Introduction Low)]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/YxoQFSBwyms" frameborder="0" allowfullscreen></iframe>]]></description>
	
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/7913/the-genome-factory</guid>
	<pubDate>Thu, 16 Jan 2014 02:09:31 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/7913/the-genome-factory</link>
	<title><![CDATA[The genome factory !!!]]></title>
	<description><![CDATA[<p>Illumina, Inc. announced Tuesday that its new HiSeq X Ten Sequencing System has broken the &ldquo;sound barrier&rdquo; of human genomics by enabling the $1,000 genome. &ldquo;This platform includes dramatic technology breakthroughs that enable researchers to undertake studies of unprecedented scale by providing the throughput to sequence tens of thousands of human whole genomes in a single year in a single lab,&rdquo; Illumina stated.</p><p>Initial customers for the HiSeq X Ten System, which will ship in Q1 2014, include Macrogen, based in Seoul, South Korea and its CLIA laboratory in Rockville, Maryland, the Broad Institute in Cambridge, Massachusetts, and the Garvan Institute of Medical Research in Sydney, Australia.</p><p>&ldquo;For the first time, it looks like it will be possible to deliver the $1,000 genome, which is tremendously exciting,&rdquo; said Eric Lander, founding director of the Broad Institute and a professor of biology at MIT. &ldquo;The HiSeq X Ten should give us the ability to analyze complete genomic information from huge sample populations. Over the next few years, we have an opportunity to learn as much about the genetics of human disease as we have learned in the history of medicine.&rdquo;</p><p>&ldquo;The HiSeq X Ten is an ideal platform for scientists and institutions focused on the discovery of genotypic variation to enable a deeper understanding of human biology and genetic disease,&rdquo; Illumina stated. &ldquo;It can sequence tens of thousands of samples annually with high-quality, high-coverage sequencing, delivering a comprehensive catalog of human variation within and outside coding regions.&rdquo;</p><p>HiSeq X Ten utilizes a number of advanced design features to generate massive throughput. Patterned flow cells, which contain billions of nanowells at fixed locations, combined with a new clustering chemistry deliver a significant increase in data density (6 billion clusters per run). Using state-of-the art optics and faster chemistry, HiSeq X Ten can process sequencing flow cells more quickly than ever before &mdash; generating a 10x increase in daily throughput when compared to current HiSeq 2500 performance.</p><p>The HiSeq X Ten is sold as a set of 10 or more ultra-high throughput sequencing systems, each generating up to 1.8 terabases (Tb) of sequencing data in less than three days or up to 600 gigabases (Gb) per day, per system, providing the throughput to sequence tens of thousands of high-quality, high-coverage genomes per year. Illumina says the $1,000 includes typical instrument depreciation, DNA extraction, library preparation, and estimated labor.</p>]]></description>
	<dc:creator>Madhvan Reddy</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/11175/next-generation-sequencingngs-books</guid>
	<pubDate>Fri, 30 May 2014 04:48:04 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/11175/next-generation-sequencingngs-books</link>
	<title><![CDATA[Next generation sequencing(NGS) books]]></title>
	<description><![CDATA[<p>Employing different technologies, the purpose of NGS platform is to decode the identity or modification on the nucleotides. NGS platforms evolve quickly and capture the main stream.</p>
<p>This bookmark is created to provide NGS online books links.</p><p>Address of the bookmark: <a href="http://en.wikibooks.org/wiki/Next_Generation_Sequencing_%28NGS%29/Print_version" rel="nofollow">http://en.wikibooks.org/wiki/Next_Generation_Sequencing_%28NGS%29/Print_version</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>

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