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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/36533?offset=170</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36478/the-marvel-assembler</guid>
	<pubDate>Fri, 04 May 2018 19:18:41 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36478/the-marvel-assembler</link>
	<title><![CDATA[The MARVEL assembler]]></title>
	<description><![CDATA[<p><span>MARVEL consists of a set of tools that facilitate the overlapping, patching, correction and assembly of noisy (not so noisy ones as well) long reads.</span></p>
<p>The assembly process can be summarized as follows:</p>
<ol>
<li>overlap</li>
<li>patch reads</li>
<li>overlap (again)</li>
<li>scrubbing</li>
<li>assembly graph construction and touring</li>
<li>optional read correction</li>
<li>fasta file creation</li>
</ol><p>Address of the bookmark: <a href="https://github.com/schloi/MARVEL" rel="nofollow">https://github.com/schloi/MARVEL</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37984/baum-%E2%80%93-improving-genome-assembly-by-adaptive-unique-mapping-and-local-overlap-layout-consensus</guid>
	<pubDate>Wed, 24 Oct 2018 23:35:09 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37984/baum-%E2%80%93-improving-genome-assembly-by-adaptive-unique-mapping-and-local-overlap-layout-consensus</link>
	<title><![CDATA[BAUM – Improving Genome Assembly by Adaptive Unique Mapping and Local Overlap-Layout-Consensus]]></title>
	<description><![CDATA[<p><span>BAUM, breaks the whole genome into regions by adaptive unique mapping; then the local OLC is used to assemble each region in parallel. BAUM can: (1) perform reference-assisted assembly based on the genome of a close species; (2) or improve the results of existing assemblies that are obtained based on short or long sequencing reads.&nbsp;</span></p><p>Address of the bookmark: <a href="http://www.zhanyuwang.xin/wordpress/index.php/2017/07/21/baum-improving-genome-assembly-by-adaptive-unique-mapping-and-local-overlap-layout-consensus/" rel="nofollow">http://www.zhanyuwang.xin/wordpress/index.php/2017/07/21/baum-improving-genome-assembly-by-adaptive-unique-mapping-and-local-overlap-layout-consensus/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40208/ragoo-fast-reference-guided-scaffolding-of-genome-assembly-contigs</guid>
	<pubDate>Sun, 27 Oct 2019 00:57:23 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40208/ragoo-fast-reference-guided-scaffolding-of-genome-assembly-contigs</link>
	<title><![CDATA[RaGOO: Fast Reference-Guided Scaffolding of Genome Assembly Contigs]]></title>
	<description><![CDATA[<p>Alonge M, Soyk S, Ramakrishnan S, Wang X, Goodwin S, Sedlazeck FJ, Lippman ZB, Schatz MC:&nbsp;<a href="https://www.biorxiv.org/content/early/2019/01/13/519637">Fast and accurate reference-guided scaffolding of draft genomes</a>.&nbsp;<em>bioRxiv</em>&nbsp;2019.</p>
<p>RaGOO is a tool for coalescing genome assembly contigs into pseudochromosomes via minimap2 alignments to a closely related reference genome. The focus of this tool is on practicality and therefore has the following features:</p>
<ol>
<li>Good performance. On a MacBook Pro using Arabidopsis data, pseudochromosome construction takes less than a minute and the whole pipeline with SV calling takes ~2 minutes.</li>
<li>Intact ordering and orienting of contigs.</li>
<li><a href="https://github.com/malonge/RaGOO/wiki/Misassembly-Correction">Misassembly correction</a></li>
<li><a href="https://github.com/malonge/RaGOO/wiki/GFF-File-Lift-Over">GFF lift-over</a></li>
<li><a href="https://github.com/malonge/RaGOO/wiki/Calling-Structural-Variants">Structural variant calling with and integrated version of Assemblytics</a></li>
<li>Confidence scores associated with the grouping, localization, and orientation for each contig.</li>
</ol><p>Address of the bookmark: <a href="https://github.com/malonge/RaGOO" rel="nofollow">https://github.com/malonge/RaGOO</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43110/quasimodo-quasispecies-metric-determination-on-omics</guid>
	<pubDate>Sat, 26 Jun 2021 15:22:56 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43110/quasimodo-quasispecies-metric-determination-on-omics</link>
	<title><![CDATA[QuasiModo - Quasispecies Metric Determination on Omics]]></title>
	<description><![CDATA[<p><span>This repository contains the scripts and pipeline that reproduces the results of the HCMV benchmarking study. In this study we evaluated genome assemblers and variant callers on 10 in vitro generated, mixed strain HCMV sequence samples, each consisting of two lab strains in different abundance ratios. This tool can also be used to evaluate assemblies and variant calling results on other similar datasets.</span></p>
<p><span>https://academic.oup.com/bib/article/22/3/bbaa123/5868070</span></p><p>Address of the bookmark: <a href="https://github.com/hzi-bifo/Quasimodo" rel="nofollow">https://github.com/hzi-bifo/Quasimodo</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44223/ale-assembly-likelihood-estimator</guid>
	<pubDate>Wed, 08 Mar 2023 01:39:33 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44223/ale-assembly-likelihood-estimator</link>
	<title><![CDATA[ALE: Assembly Likelihood Estimator]]></title>
	<description><![CDATA[<p>Just import the assembly, bam and ALE scores. You can convert the .ale file to a set of .wig files with ale2wiggle.py and IGV can read those directly.&nbsp; Depending on your genome size you may want to convert the .wig files to the BigWig format.</p><p>Address of the bookmark: <a href="https://github.com/sc932/ALE" rel="nofollow">https://github.com/sc932/ALE</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38224/novograph-building-whole-genome-graphs-from-long-read-based-de-novo-assemblies</guid>
	<pubDate>Thu, 15 Nov 2018 12:48:30 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38224/novograph-building-whole-genome-graphs-from-long-read-based-de-novo-assemblies</link>
	<title><![CDATA[NovoGraph: building whole genome graphs from long-read-based de novo assemblies]]></title>
	<description><![CDATA[<p><span>NovoGraph: building whole genome graphs from long-read-based de novo assemblies</span></p>
<p><span><span>An algorithmically novel approach to construct a genome graph representation of long-read-based&nbsp;</span><em>de novo</em><span>&nbsp;sequence assemblies. We then provide a proof of principle by creating a genome graph of seven ethnically-diverse human genomes.</span></span></p>
<p>&nbsp;</p>
<p>https://f1000research.com/articles/7-1391/v1</p><p>Address of the bookmark: <a href="https://github.com/NCBI-Hackathons/NovoGraph" rel="nofollow">https://github.com/NCBI-Hackathons/NovoGraph</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36954/mscaffolder-a-comparative-genome-scaffolding-tool</guid>
	<pubDate>Fri, 15 Jun 2018 04:48:01 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36954/mscaffolder-a-comparative-genome-scaffolding-tool</link>
	<title><![CDATA[mScaffolder: A comparative genome scaffolding tool]]></title>
	<description><![CDATA[<p>A comparative genome scaffolding tool based on MUMmer</p>
<p>mScaffolder scaffolds a genome using an existing high quality genome as the reference. It aligns the two genomes using nucmer utility from MUMmer and then orders and orients the contigs of the candidate genome guided by their alignments to the reference genome. Please send your questions and comments to&nbsp;<a href="mailto:mchakrab@uci.edu">mchakrab@uci.edu</a>.</p>
<p><span>Citation</span><span>&nbsp;</span><a href="https://www.nature.com/articles/s41588-017-0010-y">https://www.nature.com/articles/s41588-017-0010-y</a></p><p>Address of the bookmark: <a href="https://github.com/mahulchak/mscaffolder" rel="nofollow">https://github.com/mahulchak/mscaffolder</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37306/genome-u-plot-a-whole-genome-visualization</guid>
	<pubDate>Fri, 13 Jul 2018 19:50:41 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37306/genome-u-plot-a-whole-genome-visualization</link>
	<title><![CDATA[Genome U-Plot: a whole genome visualization]]></title>
	<description><![CDATA[<p><span>Genome U-Plot for producing clear and intuitive graphs that allows researchers to generate novel insights and hypotheses by visualizing SVs such as deletions, amplifications, and chromoanagenesis events. The main features of the Genome U-Plot are its layered layout, its high spatial resolution and its improved aesthetic qualities.&nbsp;</span></p>
<p><span>https://github.com/gaitat/GenomeUPlot</span></p><p>Address of the bookmark: <a href="https://github.com/gaitat/GenomeUPlot" rel="nofollow">https://github.com/gaitat/GenomeUPlot</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37796/grsr-a-tool-for-deriving-genome-rearrangement-scenarios-from-multiple-unichromosomal-genome-sequences</guid>
	<pubDate>Fri, 28 Sep 2018 09:35:10 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37796/grsr-a-tool-for-deriving-genome-rearrangement-scenarios-from-multiple-unichromosomal-genome-sequences</link>
	<title><![CDATA[GRSR: a tool for deriving genome rearrangement scenarios from multiple unichromosomal genome sequences]]></title>
	<description><![CDATA[<p>GRSR is a Tool for Deriving Genome Rearrangement Scenarios for Multiple Uni-chromosomal Genomes. This tool will do the following steps:</p>
<ul>
<li>Step 1. Run mugsy to get multiple sequence alignment results.</li>
<li>Step 2 &amp; 3. Extraction of the Coordinates of Core Blocks, Construction of Synteny Blocks and Generating Signed Permutations.</li>
<li>Step 4. Generate pairwise genome rearrangement scenarios and find repeats at the breakpoints of each rearrangement events.</li>
<li></li>
<li></li>
</ul>
<p>https://github.com/DanwangJessica/GRSR</p><p>Address of the bookmark: <a href="https://github.com/DanwangJessica/GRSR" rel="nofollow">https://github.com/DanwangJessica/GRSR</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43273/understanding-kmer</guid>
	<pubDate>Wed, 18 Aug 2021 04:27:51 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43273/understanding-kmer</link>
	<title><![CDATA[Understanding kmer !]]></title>
	<description><![CDATA[<p><a href="https://en.wikipedia.org/wiki/k-mer">What is a&nbsp;<em>k-mer</em>&nbsp;anyway?</a><span>&nbsp;A&nbsp;</span><em>k-mer</em><span>&nbsp;is just a sequence of&nbsp;</span><em>k</em><span>&nbsp;characters in a string (or nucleotides in a DNA sequence). Now, it is important to remember that to get&nbsp;</span><em>all k-mers</em><span>&nbsp;from a sequence you need to get the first&nbsp;</span><em>k</em><span>&nbsp;characters, then move just a single character for the start of the next&nbsp;</span><em>k-mer</em><span>&nbsp;and so on. Effectively, this will create sequences that overlap in&nbsp;</span><code>k-1</code><span>&nbsp;positions.</span></p><p>Address of the bookmark: <a href="https://bioinfologics.github.io/post/2018/09/17/k-mer-counting-part-i-introduction/" rel="nofollow">https://bioinfologics.github.io/post/2018/09/17/k-mer-counting-part-i-introduction/</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>

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