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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/36478?offset=490</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38561/hawkeye-an-interactive-visual-analytics-tool-for-genome-assemblies</guid>
	<pubDate>Tue, 01 Jan 2019 11:56:17 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38561/hawkeye-an-interactive-visual-analytics-tool-for-genome-assemblies</link>
	<title><![CDATA[Hawkeye: an interactive visual analytics tool for genome assemblies]]></title>
	<description><![CDATA[<p><span>Genome sequencing remains an inexact science, and genome sequences can contain significant errors if they are not carefully examined. Hawkeye is our new visual analytics tool for genome assemblies, designed to aid in identifying and correcting assembly errors. Users can analyze all levels of an assembly along with summary statistics and assembly metrics, and are guided by a ranking component towards likely mis-assemblies. Hawkeye is freely available and released as part of the open source AMOS project&nbsp;</span><span><a href="http://amos.sourceforge.net/hawkeye"><span>http://amos.sourceforge.net/hawkeye</span></a></span><span>.</span></p>
<p>https://genomebiology.biomedcentral.com/articles/10.1186/gb-2007-8-3-r34</p><p>Address of the bookmark: <a href="http://amos.sourceforge.net/wiki/index.php?title=Hawkeye" rel="nofollow">http://amos.sourceforge.net/wiki/index.php?title=Hawkeye</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39236/causel-an-epigenome-and-genome-editing-pipeline-for-establishing-function-of-noncoding-gwas-variants</guid>
	<pubDate>Tue, 09 Apr 2019 07:23:37 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39236/causel-an-epigenome-and-genome-editing-pipeline-for-establishing-function-of-noncoding-gwas-variants</link>
	<title><![CDATA[CAUSEL: an epigenome- and genome-editing pipeline for establishing function of noncoding GWAS variants]]></title>
	<description><![CDATA[<p><span>Validated a widely accessible approach that can be used to establish functional causality for noncoding sequence variants identified by GWASs.</span></p>
<p><a href="https://www.nature.com/articles/nm.3975">https://www.nature.com/articles/nm.3975</a></p><p>Address of the bookmark: <a href="https://www.nature.com/articles/nm.3975" rel="nofollow">https://www.nature.com/articles/nm.3975</a></p>]]></description>
	<dc:creator>BioJoker</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40140/alf-a-simulation-framework-for-genome-evolution</guid>
	<pubDate>Tue, 22 Oct 2019 22:05:58 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40140/alf-a-simulation-framework-for-genome-evolution</link>
	<title><![CDATA[ALF--a simulation framework for genome evolution.]]></title>
	<description><![CDATA[<p style="color: #000000; font-size: small; font-style: normal; font-weight: 400; text-align: -webkit-left;"><span style="color: #4d4d4d; font-size: small; font-style: normal; font-weight: 400; text-align: left; background-color: #ffffff; float: none;">Artificial Life Framework (ALF)</span> simulates a root genome into a number of related genomes. Result files include the resulting gene sequences, true tree and true MSAs. A description of ALF can be found in the following article:</p>
<p style="color: #000000; font-size: small; font-style: normal; font-weight: 400; text-align: -webkit-left;">Daniel A Dalquen, Maria Anisimova, Gaston H Gonnet, Christophe Dessimoz: ALF - A Simulation Framework for Genome Evolution.<span>&nbsp;</span><em>Mol Biol Evol</em>, 29(4):1115-1123, April 2012.<br><a href="http://mbe.oxfordjournals.org/content/29/4/1115" target="_blank">http://mbe.oxfordjournals.org/content/29/4/1115</a></p><p>Address of the bookmark: <a href="http://alfsim.org/#index" rel="nofollow">http://alfsim.org/#index</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40715/mutatrix-a-population-genome-simulator-which-generates-simulated-genomes</guid>
	<pubDate>Tue, 28 Jan 2020 04:06:58 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40715/mutatrix-a-population-genome-simulator-which-generates-simulated-genomes</link>
	<title><![CDATA[mutatrix: a population genome simulator which generates simulated genomes.]]></title>
	<description><![CDATA[<p><span>genome simulation across a population with zeta-distributed allele frequency, snps, insertions, deletions, and multi-nucleotide polymorphisms</span></p>
<p><span>More at&nbsp;<a href="https://github.com/ekg/mutatrix">https://github.com/ekg/mutatrix</a></span></p>
<pre>./mutatrix -S sample -P test/ -p 2 -n 10 reference.fasta</pre><p>Address of the bookmark: <a href="https://github.com/ekg/mutatrix" rel="nofollow">https://github.com/ekg/mutatrix</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41275/shinychromosomea-gui-for-the-interactive-creation-of-non-circular-whole-genome-diagrams</guid>
	<pubDate>Sat, 29 Feb 2020 00:39:50 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41275/shinychromosomea-gui-for-the-interactive-creation-of-non-circular-whole-genome-diagrams</link>
	<title><![CDATA[shinyChromosome:a GUI for the interactive creation of non-circular whole genome diagrams]]></title>
	<description><![CDATA[<p><code>shinyChromosome</code> is a graphical user interface for interactive creation of non-circular whole genome diagrams developed using the R <strong>Shiny</strong> package.</p>
<p>To create single-genome plot by aligning genome data along all chromosomes of a single genome, go to the <code>Single-genome plot</code> menu.</p>
<p>To cretae two-genome plot for comparison of data across two genomes, go to the <code>Two-genome plot</code> menu.</p>
<p>For the detail format of input data, check the <code>Input data format</code> submenu of the <code>Help</code> menu.</p>
<p>shinyChromosome is deployed at <a href="http://150.109.59.144:3838/shinyChromosome/" target="_blank">http://150.109.59.144:3838/shinyChromosome/</a>, <a href="http://shinyChromosome.ncpgr.cn" target="_blank">http://shinyChromosome.ncpgr.cn</a>, and <a href="https://yimingyu.shinyapps.io/shinyChromosome" target="_blank">https://yimingyu.shinyapps.io/shinyChromosome</a> for online use. The source code and manual of shinyChromosome are freely available at <a href="https://github.com/venyao/shinyChromosome" target="_blank">https://github.com/venyao/shinyChromosome</a>.</p>
<p>https://yimingyu.shinyapps.io/shinychromosome/</p>
<p>https://www.sciencedirect.com/science/article/pii/S1672022919301883</p><p>Address of the bookmark: <a href="https://yimingyu.shinyapps.io/shinychromosome/" rel="nofollow">https://yimingyu.shinyapps.io/shinychromosome/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41937/merqury-evaluate-genome-assemblies-with-k-mers</guid>
	<pubDate>Fri, 03 Jul 2020 19:29:34 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41937/merqury-evaluate-genome-assemblies-with-k-mers</link>
	<title><![CDATA[merqury: Evaluate genome assemblies with k-mers]]></title>
	<description><![CDATA[<p><span>Often, genome assembly projects have illumina whole genome sequencing reads available for the assembled individual. The k-mer spectrum of this read set can be used for independently evaluating assembly quality without the need of a high quality reference. Merqury provides a set of tools for this purpose.</span></p>
<p><span>More at&nbsp;<a href="https://www.biorxiv.org/content/10.1101/2020.03.15.992941v1.full">https://www.biorxiv.org/content/10.1101/2020.03.15.992941v1.full</a></span></p><p>Address of the bookmark: <a href="https://github.com/marbl/merqury" rel="nofollow">https://github.com/marbl/merqury</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42923/flanker</guid>
	<pubDate>Sat, 27 Feb 2021 22:04:53 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42923/flanker</link>
	<title><![CDATA[Flanker]]></title>
	<description><![CDATA[<p><span>Flanker, a Python package which performs alignment-free clustering of gene flanking sequences in a consistent format, allowing investigation of&nbsp;<span>mobile genetic elements (</span>MGEs) without prior knowledge of their structure.&nbsp;<span>Flanker can be flexibly parameterised to finetune outputs by characterising upstream and downstream regions separately and investigating variable lengths of flanking sequence.</span></span></p>
<p><span><img src="https://github.com/wtmatlock/flanker/raw/main/docs/frontpage.png" alt="image" style="border: 0px;"></span></p><p>Address of the bookmark: <a href="https://github.com/wtmatlock/flanker" rel="nofollow">https://github.com/wtmatlock/flanker</a></p>]]></description>
	<dc:creator>Rahul Nayak</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>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43620/ncbi-datasets-cli-quickstart-command-line-tools</guid>
	<pubDate>Tue, 07 Dec 2021 02:51:26 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43620/ncbi-datasets-cli-quickstart-command-line-tools</link>
	<title><![CDATA[ncbi-datasets-cli -- Quickstart: command line tools !]]></title>
	<description><![CDATA[<p><span>Install and use the NCBI Datasets command line tools</span></p>
<p>The NCBI Datasets datasets command line tools are&nbsp;<a href="https://www.ncbi.nlm.nih.gov/datasets/docs/v1/reference-docs/command-line/datasets/">datasets</a>&nbsp;and&nbsp;<a href="https://www.ncbi.nlm.nih.gov/datasets/docs/v1/reference-docs/command-line/dataformat/">dataformat</a>&nbsp;.</p>
<p>Use&nbsp;<span>datasets</span>&nbsp;to download biological sequence data across all domains of life from NCBI.</p>
<p>Use&nbsp;<span>dataformat</span>&nbsp;to convert metadata from&nbsp;<a href="https://jsonlines.org/" target="_blank">JSON Lines</a>&nbsp;format to other formats.</p>
<p><strong>Conda download:</strong></p>
<p>https://anaconda.org/conda-forge/ncbi-datasets-cli</p>
<p><strong>Buld Download</strong></p>
<p>&nbsp;https://www.ncbi.nlm.nih.gov/datasets/builder/?tax_id=29979</p><p>Address of the bookmark: <a href="https://www.ncbi.nlm.nih.gov/datasets/docs/v1/quickstarts/command-line-tools/" rel="nofollow">https://www.ncbi.nlm.nih.gov/datasets/docs/v1/quickstarts/command-line-tools/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43801/smudgeplot-inference-of-ploidy-and-heterozygosity-structure-using-whole-genome-sequencing-data</guid>
	<pubDate>Fri, 25 Feb 2022 04:42:09 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43801/smudgeplot-inference-of-ploidy-and-heterozygosity-structure-using-whole-genome-sequencing-data</link>
	<title><![CDATA[Smudgeplot: Inference of ploidy and heterozygosity structure using whole genome sequencing data]]></title>
	<description><![CDATA[<p dir="auto">This tool extracts heterozygous kmer pairs from kmer count databases and performs gymnastics with them. We are able to disentangle genome structure by comparing the sum of kmer pair coverages (CovA + CovB) to their relative coverage (CovB / (CovA + CovB)). Such an approach also allows us to analyze obscure genomes with duplications, various ploidy levels, etc.</p>
<p dir="auto">Smudgeplots are computed from raw or even better from trimmed reads and show the haplotype structure using heterozygous kmer pairs. For example:</p>
<p dir="auto"><a href="https://user-images.githubusercontent.com/8181573/45959760-f1032d00-c01a-11e8-8576-ff0512c33da9.png" target="_blank"><img src="https://user-images.githubusercontent.com/8181573/45959760-f1032d00-c01a-11e8-8576-ff0512c33da9.png" alt="smudgeexample" style="border: 0px;"></a></p><p>Address of the bookmark: <a href="https://github.com/KamilSJaron/smudgeplot" rel="nofollow">https://github.com/KamilSJaron/smudgeplot</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
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