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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/37554?offset=50</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32190/dbg2olcefficient-assembly-of-large-genomes-using-long-erroneous-reads-of-the-third-generation-sequencing-technologies</guid>
	<pubDate>Wed, 19 Apr 2017 10:09:51 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32190/dbg2olcefficient-assembly-of-large-genomes-using-long-erroneous-reads-of-the-third-generation-sequencing-technologies</link>
	<title><![CDATA[DBG2OLC:Efficient Assembly of Large Genomes Using Long Erroneous Reads of the Third Generation Sequencing Technologies]]></title>
	<description><![CDATA[<p>DBG2OLC:Efficient Assembly of Large Genomes Using Long Erroneous Reads of the Third Generation Sequencing Technologies</p>
<p>Our work is published in Scientific Reports:</p>
<p>Ye, C. et al. DBG2OLC: Efficient Assembly of Large Genomes Using Long Erroneous Reads of the Third Generation Sequencing Technologies. Sci. Rep. 6, 31900; doi: 10.1038/srep31900 (2016).</p>
<p><a href="http://www.nature.com/articles/srep31900">http://www.nature.com/articles/srep31900</a></p>
<p>The manual can be downloaded from:</p>
<p><a href="https://github.com/yechengxi/DBG2OLC/raw/master/Manual.docx">https://github.com/yechengxi/DBG2OLC/raw/master/Manual.docx</a></p>
<p>To use precompiled versions,please go to:</p>
<p><a href="https://github.com/yechengxi/DBG2OLC/tree/master/compiled">https://github.com/yechengxi/DBG2OLC/tree/master/compiled</a></p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="https://github.com/yechengxi/DBG2OLC" rel="nofollow">https://github.com/yechengxi/DBG2OLC</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32948/simba-a-web-tool-for-managing-bacterial-genome-assembly-generated-by-ion-pgm-sequencing-technology</guid>
	<pubDate>Tue, 23 May 2017 05:28:56 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32948/simba-a-web-tool-for-managing-bacterial-genome-assembly-generated-by-ion-pgm-sequencing-technology</link>
	<title><![CDATA[SIMBA: a web tool for managing bacterial genome assembly generated by Ion PGM sequencing technology]]></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>https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-016-1344-7</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>Abhimanyu Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36592/lachesis-genome-assembly-with-hi-c-based-contact-probability-maps-lachesis</guid>
	<pubDate>Mon, 14 May 2018 04:26:30 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36592/lachesis-genome-assembly-with-hi-c-based-contact-probability-maps-lachesis</link>
	<title><![CDATA[LACHESIS: Genome Assembly with Hi-C-based Contact Probability Maps (LACHESIS)]]></title>
	<description><![CDATA[<p>LACHESIS is method that exploits contact probability map data (e.g. from Hi-C) for chromosome-scale&nbsp;<em>de novo</em>&nbsp;genome assembly.</p>
<p>Further information about LACHESIS, including source code, documentation and a user's guide are available at:&nbsp;<a href="http://shendurelab.github.io/LACHESIS/">http://shendurelab.github.io/LACHESIS</a>.</p>
<p>Manuscript describing LACHESIS was published as: Burton JN#, Adey A, Patwardhan RP, Qiu R, Kitzman JO, Shendure J#.&nbsp;<em>Chromosome-scale scaffolding of de novo genome assemblies based on chromatin interactions.</em>&nbsp;Nature Biotechnology 2013 Dec;31(12):1119-25. doi:&nbsp;<a href="http://dx.doi.org/10.1038/nbt.2727">10.1038/nbt.272</a>. PubMed PMID:&nbsp;<a href="http://www.ncbi.nlm.nih.gov/pubmed/24185095">24185095</a>.</p>
<p>&nbsp;</p>
<p>http://shendurelab.github.io/LACHESIS/</p><p>Address of the bookmark: <a href="http://shendurelab.github.io/LACHESIS/" rel="nofollow">http://shendurelab.github.io/LACHESIS/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37241/remilo-reference-assisted-misassembly-detection-algorithm-using-short-and-long-reads</guid>
	<pubDate>Fri, 06 Jul 2018 04:27:49 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37241/remilo-reference-assisted-misassembly-detection-algorithm-using-short-and-long-reads</link>
	<title><![CDATA[ReMILO: reference assisted misassembly detection algorithm using short and long reads.]]></title>
	<description><![CDATA[ReMILO, a reference assisted misassembly detection algorithm that uses both short reads and PacBio SMRT long reads. ReMILO aligns the initial short reads to both the contigs and reference genome, and then constructs a novel data structure called red-black multipositional de Bruijn graph to detect misassemblies. In addition, ReMILO also aligns the contigs to long reads and find their differences from the long reads to detect more misassemblies.<p>Address of the bookmark: <a href="https://github.com/songc001/remilo" rel="nofollow">https://github.com/songc001/remilo</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42946/aligngraph2-similar-genome-assisted-reassembly-pipeline-for-pacbio-long-reads</guid>
	<pubDate>Sun, 14 Mar 2021 09:42:47 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42946/aligngraph2-similar-genome-assisted-reassembly-pipeline-for-pacbio-long-reads</link>
	<title><![CDATA[AlignGraph2: similar genome-assisted reassembly pipeline for PacBio long reads]]></title>
	<description><![CDATA[<p><span>AlignGraph2 is the second version of&nbsp;</span><a href="https://github.com/baoe/AlignGraph">AlignGraph</a><span>&nbsp;for PacBio long reads. It extends and refines contigs assembled from the long reads with a published genome similar to the sequencing genome.</span></p>
<p><span>More at&nbsp;https://academic.oup.com/bib/advance-article-abstract/doi/10.1093/bib/bbab022/6146772</span></p><p>Address of the bookmark: <a href="https://github.com/huangs001/AlignGraph2" rel="nofollow">https://github.com/huangs001/AlignGraph2</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32129/lordec-a-hybrid-error-correction-program-for-long-pacbio-reads</guid>
	<pubDate>Mon, 10 Apr 2017 04:16:09 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32129/lordec-a-hybrid-error-correction-program-for-long-pacbio-reads</link>
	<title><![CDATA[LoRDEC: a hybrid error correction program for long, PacBio reads]]></title>
	<description><![CDATA[<p>LoRDEC is a program to correct sequencing errors in long reads from 3rd generation sequencing with high error rate, and is especially intended for PacBio reads. It uses a hybrid strategy, meaning that it uses two sets of reads: the reference read set, whose error rate is assumed to be small, and the PacBio read set, which is then corrected using the reference set. Typically, the reference set contains Illumina reads.</p>
<p><br> Usually, errors in PacBio reads include many insertions and deletions, and comparatively less substitutions. LoRDEC can correct errors of all these types.<br> After correction, a larger portion of the sequence of PacBio reads is usable for detection of region of similarity with other sequences, for aligning them to the contigs of an assembly, etc.</p>
<p>Why is LoRDEC different?</p>
<ul>
<li>It is efficient and can process large read data sets, included from eukaryotic or vertebrate species, on a usual computing server, and even works on desktop/laptop computers.</li>
<li>It adopts a novel graph based approach: it builds a succinct De Bruijn Graph (DBG) representing the short reads, and seeks a corrective sequence for each erroneous region of a long read by traversing chosen paths in the graph.</li>
</ul><p>Address of the bookmark: <a href="http://www.atgc-montpellier.fr/lordec/" rel="nofollow">http://www.atgc-montpellier.fr/lordec/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37502/alignqc-a-tool-for-assessing-an-alignment-and-generating-reports-that-are-easy-to-share</guid>
	<pubDate>Tue, 07 Aug 2018 04:41:07 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37502/alignqc-a-tool-for-assessing-an-alignment-and-generating-reports-that-are-easy-to-share</link>
	<title><![CDATA[AlignQC: A tool for assessing an alignment, and generating reports that are easy to share]]></title>
	<description><![CDATA[<p><span>Long read alignment analysis. Generate a reports on sequence alignments for mappability vs read sizes, error patterns, annotations and rarefraction curve analysis. The most basic analysis only requires a BAM file, and outputs a web browser compatible xhtml to visualize/share/store/extract analysis results.</span></p>
<p>https://f1000research.com/articles/6-100/</p>
<p>https://github.com/jason-weirather/AlignQC</p><p>Address of the bookmark: <a href="https://www.healthcare.uiowa.edu/labs/au/AlignQC/" rel="nofollow">https://www.healthcare.uiowa.edu/labs/au/AlignQC/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42160/vicuna-a-software-tool-that-enables-consensus-assembly-of-ultra-deep-sequence-derived-from-diverse-viral-or-other-heterogeneous-populations</guid>
	<pubDate>Tue, 25 Aug 2020 03:40:17 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42160/vicuna-a-software-tool-that-enables-consensus-assembly-of-ultra-deep-sequence-derived-from-diverse-viral-or-other-heterogeneous-populations</link>
	<title><![CDATA[VICUNA: a software tool that enables consensus assembly of ultra-deep sequence derived from diverse viral or other heterogeneous populations.]]></title>
	<description><![CDATA[<p><span>VICUNA</span><span>&nbsp;is a&nbsp;</span><em>de novo</em><span>&nbsp;assembly program targeting populations with high mutation rates. It creates a single linear representation of the mixed population on which intra-host variants can be mapped. For clinical samples rich in contamination (e.g., &gt;95%), VICUNA can leverage existing genomes, if available, to assemble only target-alike reads. After initial assembly, it can also use existing genomes to perform guided merging of contigs. For each data set (e.g., Illumina paired read, 454), VICUNA outputs consensus sequence(s) and the corresponding multiple sequence alignment of constituent reads. VICUNA efficiently handles ultra-deep sequence data with tens of thousands fold coverage.</span></p>
<p><a href="http://software.broadinstitute.org/viral/docs/vicuna_v1.0.pdf">http://software.broadinstitute.org/viral/docs/vicuna_v1.0.pdf</a></p><p>Address of the bookmark: <a href="https://www.broadinstitute.org/viral-genomics/vicuna" rel="nofollow">https://www.broadinstitute.org/viral-genomics/vicuna</a></p>]]></description>
	<dc:creator>biogeek</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43090/loretta-a-user-friendly-tool-for-assembling-viral-genomes-from-pacbio-sequence-data</guid>
	<pubDate>Wed, 23 Jun 2021 07:54:53 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43090/loretta-a-user-friendly-tool-for-assembling-viral-genomes-from-pacbio-sequence-data</link>
	<title><![CDATA[LoReTTA, a user-friendly tool for assembling viral genomes from PacBio sequence data]]></title>
	<description><![CDATA[<p>LoReTTA (Long Read Template-Targeted Assembler), a tool designed for performing <em>de novo</em> assembly of long reads generated from viral genomes on the PacBio platform. LoReTTA exploits a reference genome to guide the assembly process, an approach that has been successful with short reads.</p>
<p>https://academic.oup.com/ve/article/7/1/veab042/6248116</p><p>Address of the bookmark: <a href="https://academic.oup.com/ve/article/7/1/veab042/6248116" rel="nofollow">https://academic.oup.com/ve/article/7/1/veab042/6248116</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44529/contigextender-a-new-approach-to-improving-de-novo-sequence-assembly-for-viral-metagenomics-data</guid>
	<pubDate>Wed, 08 May 2024 07:32:45 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44529/contigextender-a-new-approach-to-improving-de-novo-sequence-assembly-for-viral-metagenomics-data</link>
	<title><![CDATA[ContigExtender: a new approach to improving de novo sequence assembly for viral metagenomics data]]></title>
	<description><![CDATA[<p dir="auto">ContigExtender, was developed to extend contigs, complementing de novo assembly. ContigExtender employs a novel recursive Overlap Layout Candidates (r-OLC) strategy that explores multiple extending paths to achieve longer and highly accurate contigs. ContigExtender is effective for extending contigs significantly in in silico synthesized and real metagenomics datasets.</p>
<p dir="auto">More at&nbsp;https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7953547/</p>
<p dir="auto"><a href="https://camo.githubusercontent.com/72dc78177cd84dd0c667a2922a9fd984fb548b5ec94b11f9a547211a4adba3b1/68747470733a2f2f692e696d6775722e636f6d2f7734516944496a2e706e67" target="_blank"><img src="https://camo.githubusercontent.com/72dc78177cd84dd0c667a2922a9fd984fb548b5ec94b11f9a547211a4adba3b1/68747470733a2f2f692e696d6775722e636f6d2f7734516944496a2e706e67" alt="extension process" title="extension process" style="border: 0px;"></a></p><p>Address of the bookmark: <a href="https://github.com/dengzac/contig-extender" rel="nofollow">https://github.com/dengzac/contig-extender</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
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