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<channel>
	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/36950?offset=20</link>
	<atom:link href="https://bioinformaticsonline.com/related/36950?offset=20" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43364/ragtag-a-collection-of-software-tools-for-scaffolding-and-improving-modern-genome-assemblies</guid>
	<pubDate>Sat, 11 Sep 2021 00:28:14 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43364/ragtag-a-collection-of-software-tools-for-scaffolding-and-improving-modern-genome-assemblies</link>
	<title><![CDATA[RagTag: a collection of software tools for scaffolding and improving modern genome assemblies]]></title>
	<description><![CDATA[<p>RagTag is a collection of software tools for scaffolding and improving modern genome assemblies. Tasks include:</p>
<ul>
<li>Homology-based misassembly&nbsp;<a href="https://github.com/malonge/RagTag/wiki/correct">correction</a></li>
<li>Homology-based assembly&nbsp;<a href="https://github.com/malonge/RagTag/wiki/scaffold">scaffolding</a>&nbsp;and&nbsp;<a href="https://github.com/malonge/RagTag/wiki/patch">patching</a></li>
<li>Scaffold&nbsp;<a href="https://github.com/malonge/RagTag/wiki/merge">merging</a></li>
</ul><p>Address of the bookmark: <a href="https://github.com/malonge/RagTag" rel="nofollow">https://github.com/malonge/RagTag</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34528/cope-an-accurate-k-mer-based-pair-end-reads-connection-tool-to-facilitate-genome-assembly</guid>
	<pubDate>Wed, 06 Dec 2017 02:08:14 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34528/cope-an-accurate-k-mer-based-pair-end-reads-connection-tool-to-facilitate-genome-assembly</link>
	<title><![CDATA[COPE: an accurate k-mer-based pair-end reads connection tool to facilitate genome assembly]]></title>
	<description><![CDATA[<p><span>An efficient tool called Connecting Overlapped Pair-End (COPE) reads, to connect overlapping pair-end reads using k-mer frequencies. We evaluated our tool on 30&times; simulated pair-end reads from Arabidopsis thaliana with 1% base error. COPE connected over 99% of reads with 98.8% accuracy, which is, respectively, 10 and 2% higher than the recently published tool FLASH. When COPE is applied to real reads for genome assembly, the resulting contigs are found to have fewer errors and give a 14-fold improvement in the N50 measurement when compared with the contigs produced using unconnected reads.</span></p><p>Address of the bookmark: <a href="ftp://ftp.genomics.org.cn/pub/cope" rel="nofollow">ftp://ftp.genomics.org.cn/pub/cope</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37650/p-rna-scaffolder-a-fast-and-accurate-genome-scaffolder-using-paired-end-rna-sequencing-reads</guid>
	<pubDate>Fri, 07 Sep 2018 05:19:06 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37650/p-rna-scaffolder-a-fast-and-accurate-genome-scaffolder-using-paired-end-rna-sequencing-reads</link>
	<title><![CDATA[P_RNA_scaffolder: a fast and accurate genome scaffolder using paired-end RNA-sequencing reads]]></title>
	<description><![CDATA[<p><span>P_RNA_scaffolder is a novel scaffolding tool using Pair-end RNA-seq to scaffold genome fragments. The method is suitable for most genomes. The program could utilize Illumina Paired-end RNA-sequencing reads from target speciesies. Our method provides another practical alternative to existing mate-pair_based approaches or other Protein-based approaches (for instance,&nbsp;</span><a href="http://www.fishbrowser.org/software/PEP_scaffolder/">PEP_scaffolder&nbsp;</a><span>) for scaffolding genome sequences. The most important feature of this method is to improve the completeness of gene regions and long-coding gene regions (for instance,&nbsp;</span><a href="http://circrna.org/">circRNA</a><span>).</span></p><p>Address of the bookmark: <a href="http://www.fishbrowser.org/software/P_RNA_scaffolder/#" rel="nofollow">http://www.fishbrowser.org/software/P_RNA_scaffolder/#</a></p>]]></description>
	<dc:creator>BioStar</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/40994/biological-databases</guid>
	<pubDate>Wed, 12 Feb 2020 01:16:29 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40994/biological-databases</link>
	<title><![CDATA[Biological databases !]]></title>
	<description><![CDATA[<p>Now a days there are a lots of genomics databases available around the world. This bookmark is created to provide all links in one place ...</p>
<p>ftp://ftp.ncbi.nih.gov/genomes/</p>
<p>https://hgdownload.soe.ucsc.edu/downloads.html</p><p>Address of the bookmark: <a href="ftp://ftp.ncbi.nih.gov/genomes/" rel="nofollow">ftp://ftp.ncbi.nih.gov/genomes/</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/19786/shrec3d</guid>
	<pubDate>Thu, 25 Dec 2014 23:14:52 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/19786/shrec3d</link>
	<title><![CDATA[ShRec3D]]></title>
	<description><![CDATA[<p><strong>ShRec3D</strong> is a program that aims at reconstructing a genome 3D structure (b) from the sole knowledge of the contacts between different genomic regions (a) as determined by Hi-C (http://www.ncbi.nlm.nih.gov/pubmed/19815776).</p>
<p>There are two options to run ShRec3D (on linuX only so far): the first one uses the Matlab complier runtime environment (MCR), the second one doesn't need any other library to be installed but only works with the latest versions of Linux (equivalent to Fedora 19 and above).</p><p>Address of the bookmark: <a href="https://sites.google.com/site/julienmozziconacci/#TOC-Downloads" rel="nofollow">https://sites.google.com/site/julienmozziconacci/#TOC-Downloads</a></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>
<item>
	<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>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44491/cgviewjs-is-a-circular-genome-viewing-tool</guid>
	<pubDate>Wed, 27 Mar 2024 11:16:24 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44491/cgviewjs-is-a-circular-genome-viewing-tool</link>
	<title><![CDATA[CGView.js is a Circular Genome Viewing tool]]></title>
	<description><![CDATA[<p>CGView.js is a&nbsp;<span>C</span>ircular&nbsp;<span>G</span>enome&nbsp;<span>View</span>ing tool for visualizing and interacting with small genomes. This software is an adaptation of the Java program&nbsp;<a href="https://paulstothard.github.io/cgview/">CGView</a>.</p>
<div>
<p>CGView.js is the genome viewer of Proksee, an expert system for genome assembly, annotation and visualization.</p>
<a href="https://proksee.ca/"></a></div>
<h1 id="features">Features</h1>
<ul>
<li>
<p>Circular and linear views of genomes</p>
</li>
<li>
<p>Capable of drawing genomes up to 10 Mbp with 1000's of features and 100's contigs</p>
</li>
<li>
<p>Smooth zooming down to the sequence level</p>
</li>
<li>
<p>Easily generate features and plots directly form the sequence (e.g. ORFs, GC-content and GC-Skew)</p>
</li>
<li>
<p>Save high resolution PNG maps up to 8000x8000px</p>
</li>
<li>
<p>Fully documented API for interacting with CGView.js maps</p>
</li>
</ul><p>Address of the bookmark: <a href="https://js.cgview.ca/" rel="nofollow">https://js.cgview.ca/</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37643/lorma-a-tool-for-correcting-sequencing-errors-in-long-reads</guid>
	<pubDate>Thu, 06 Sep 2018 16:21:01 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37643/lorma-a-tool-for-correcting-sequencing-errors-in-long-reads</link>
	<title><![CDATA[LoRMA: A tool for correcting sequencing errors in long reads]]></title>
	<description><![CDATA[<p><span>An error correction method that uses long reads only. The method consists of two phases: first, we use an iterative alignment-free correction method based on de Bruijn graphs with increasing length of&nbsp;</span><em>k</em><span>-mers, and second, the corrected reads are further polished using long-distance dependencies that are found using multiple alignments. According to our experiments, the proposed method is the most accurate one relying on long reads only for read sets with high coverage. Furthermore, when the coverage of the read set is at least 75&times;, the throughput of the new method is at least 20% higher.</span></p>
<blockquote>
<p><span>conda install -c atgc-montpellier lorma</span></p>
</blockquote><p>Address of the bookmark: <a href="https://gite.lirmm.fr/lorma/lorma-releases/wikis/home" rel="nofollow">https://gite.lirmm.fr/lorma/lorma-releases/wikis/home</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41669/filtlong-quality-filtering-tool-for-long-reads</guid>
	<pubDate>Wed, 13 May 2020 10:23:55 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41669/filtlong-quality-filtering-tool-for-long-reads</link>
	<title><![CDATA[Filtlong: quality filtering tool for long reads]]></title>
	<description><![CDATA[<p>Filtlong is a tool for filtering long reads by quality. It can take a set of long reads and produce a smaller, better subset. It uses both read length (longer is better) and read identity (higher is better) when choosing which reads pass the filter.</p>
<p>Filtlong builds into a stand-alone executable:</p>
<pre><code>git clone https://github.com/rrwick/Filtlong.git
cd Filtlong
make -j
bin/filtlong -h
</code></pre><p>Address of the bookmark: <a href="https://github.com/rrwick/Filtlong" rel="nofollow">https://github.com/rrwick/Filtlong</a></p>]]></description>
	<dc:creator>Radha Agarkar</dc:creator>
</item>

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