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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/40715?offset=320</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40505/decostar-reconstructing-the-ancestral-organization-of-genes-or-genomes-using-reconciled-phylogenies</guid>
	<pubDate>Fri, 03 Jan 2020 13:28:19 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40505/decostar-reconstructing-the-ancestral-organization-of-genes-or-genomes-using-reconciled-phylogenies</link>
	<title><![CDATA[DeCoSTAR: Reconstructing the Ancestral Organization of Genes or Genomes Using Reconciled Phylogenies]]></title>
	<description><![CDATA[<p>DeCoSTAR computes adjacency evolutionary scenarios using a scoring scheme based on a weighted sum of adjacency gains and breakages. Solutions, both optimal and near-optimal, are sampled according to the Boltzmann&ndash;Gibbs distribution centered around parsimonious solutions, and statistical supports on ancestral and extant adjacencies are provided. DeCoSTAR supports the features of previously contributed tools that reconstruct ancestral adjacencies, namely DeCo, DeCoLT, ART-DeCo, and DeClone. In a few minutes, DeCoSTAR can reconstruct the evolutionary history of domains inside genes, of gene fusion and fission events, or of gene order along chromosomes, for large data sets including dozens of whole genomes from all kingdoms of life.</p><p>Address of the bookmark: <a href="https://github.com/YoannAnselmetti/DeCoSTAR_pipeline" rel="nofollow">https://github.com/YoannAnselmetti/DeCoSTAR_pipeline</a></p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42530/shovill-assemble-bacterial-isolate-genomes-from-illumina-paired-end-reads</guid>
	<pubDate>Sat, 02 Jan 2021 07:05:36 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42530/shovill-assemble-bacterial-isolate-genomes-from-illumina-paired-end-reads</link>
	<title><![CDATA[shovill: Assemble bacterial isolate genomes from Illumina paired-end reads]]></title>
	<description><![CDATA[<p><span>Shovill is a pipeline which uses SPAdes at its core, but alters the steps before and after the primary assembly step to get similar results in less time. Shovill also supports other assemblers like SKESA, Velvet and Megahit, so you can take advantage of the pre- and post-processing the Shovill provides with those too.</span></p><p>Address of the bookmark: <a href="https://github.com/tseemann/shovill" rel="nofollow">https://github.com/tseemann/shovill</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34562/harvest-a-suite-of-core-genome-alignment-and-visualization-tools</guid>
	<pubDate>Fri, 08 Dec 2017 07:16:03 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34562/harvest-a-suite-of-core-genome-alignment-and-visualization-tools</link>
	<title><![CDATA[Harvest: a suite of core-genome alignment and visualization tools]]></title>
	<description><![CDATA[<p>Harvest is a suite of core-genome alignment and visualization tools for quickly analyzing thousands of intraspecific microbial genomes, including variant calls, recombination detection, and phylogenetic trees.</p>
<p><a href="https://harvest.readthedocs.io/en/latest/_images/screen.png"><img src="https://harvest.readthedocs.io/en/latest/_images/screen.png" alt="_images/screen.png" style="border: 0px;"></a><span></span></p>
<p><strong>Tools</strong></p>
<ul>
<li><a href="https://harvest.readthedocs.io/en/latest/content/parsnp.html">Parsnp</a>&nbsp;- Core-genome alignment and analysis</li>
<li><a href="https://harvest.readthedocs.io/en/latest/content/gingr.html">Gingr</a>&nbsp;- Interactive visualization of alignments, trees and variants</li>
<li><a href="https://harvest.readthedocs.io/en/latest/content/harvest-tools.html">HarvestTools</a>&nbsp;- Archiving and postprocessing</li>
<li></li>
</ul><p>Address of the bookmark: <a href="https://harvest.readthedocs.io/en/latest/" rel="nofollow">https://harvest.readthedocs.io/en/latest/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35619/tallymer-method-to-compute-k-mer-frequencies-and-its-application-to-annotate-large-repetitive-plant-genomes</guid>
	<pubDate>Thu, 15 Feb 2018 10:21:02 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35619/tallymer-method-to-compute-k-mer-frequencies-and-its-application-to-annotate-large-repetitive-plant-genomes</link>
	<title><![CDATA[Tallymer: method to compute K-mer frequencies and its application to annotate large repetitive plant genomes]]></title>
	<description><![CDATA[<p>Tallymer is based on enhanced suffix arrays. This gives a much larger flexibility concerning the choice of the&nbsp;<span>k</span>-mer size. Tallymer can process large data sizes of several billion bases. We used it in a variety of applications to study the genomes of maize and other plant species. In particular, Tallymer was used to index a set whole genome shotgun sequences from maize (B73) (total size 10<sup>9</sup>&nbsp;bp).&nbsp;<br>Tallymer was effective in a variety of applications to aid genome annotation in maize, despite limitations imposed by the relatively low coverage of sequence available.</p>
<p>A manual can be found&nbsp;<a href="https://www.zbh.uni-hamburg.de/fileadmin/gi/tallymer/tallymer.pdf" target="_blank" title="tallymer.pdf (111 KB)">here</a>.</p><p>Address of the bookmark: <a href="https://www.zbh.uni-hamburg.de/forschung/arbeitsgruppe-genominformatik/software/tallymer.html" rel="nofollow">https://www.zbh.uni-hamburg.de/forschung/arbeitsgruppe-genominformatik/software/tallymer.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36800/genomemapper-simultaneous-alignment-of-short-reads-against-multiple-genomes</guid>
	<pubDate>Fri, 25 May 2018 09:29:44 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36800/genomemapper-simultaneous-alignment-of-short-reads-against-multiple-genomes</link>
	<title><![CDATA[GenomeMapper: Simultaneous alignment of short reads against multiple genomes]]></title>
	<description><![CDATA[GenomeMapper is a short read mapping tool designed for accurate read alignments. It quickly aligns millions of reads either with ungapped or gapped alignments. It can be used to align against multiple genomes simulanteously or against a single reference. If you are unsure which one is the appropriate GenomeMapper, you might want to use the latter

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2768987/<p>Address of the bookmark: <a href="http://1001genomes.org/software/genomemapper.html" rel="nofollow">http://1001genomes.org/software/genomemapper.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39867/gepard-allows-the-calculation-of-dotplots-even-for-large-sequences-like-chromosomes-or-bacterial-genomes</guid>
	<pubDate>Mon, 26 Aug 2019 11:38:30 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39867/gepard-allows-the-calculation-of-dotplots-even-for-large-sequences-like-chromosomes-or-bacterial-genomes</link>
	<title><![CDATA[Gepard: allows the calculation of dotplots even for large sequences like chromosomes or bacterial genomes]]></title>
	<description><![CDATA[<p>Gepard (German: "cheetah", Backronym for "GEnome PAir - Rapid Dotter") allows the calculation of dotplots even for large sequences like chromosomes or bacterial genomes. Reference: Krumsiek J, Arnold R, Rattei T. Gepard: A rapid and sensitive tool for creating dotplots on genome scale. Bioinformatics 2007; 23(8): 1026-8. PMID:&nbsp;<a href="http://www.ncbi.nlm.nih.gov/pubmed/17309896" target="_blank">17309896</a></p>
<p><a href="http://cube.univie.ac.at/gepard">http://cube.univie.ac.at/gepard</a></p><p>Address of the bookmark: <a href="https://github.com/univieCUBE/gepard" rel="nofollow">https://github.com/univieCUBE/gepard</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41125/chromonomer-a-tool-set-for-repairing-and-enhancing-assembled-genomes-through-integration-of-genetic-maps-and-conserved-synteny</guid>
	<pubDate>Mon, 17 Feb 2020 05:38:46 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41125/chromonomer-a-tool-set-for-repairing-and-enhancing-assembled-genomes-through-integration-of-genetic-maps-and-conserved-synteny</link>
	<title><![CDATA[Chromonomer: a tool set for repairing and enhancing assembled genomes through integration of genetic maps and conserved synteny]]></title>
	<description><![CDATA[<p>Chromonomer is a program designed to integrate a genome assembly with a genetic map. Chromonomer tries very hard to identify and remove markers that are out of order in the genetic map, when considered against their local assembly order; and to identify scaffolds that have been incorrectly assembled according to the genetic map, and split those scaffolds.</p><p>Address of the bookmark: <a href="http://catchenlab.life.illinois.edu/chromonomer/" rel="nofollow">http://catchenlab.life.illinois.edu/chromonomer/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42038/pyparanoid-a-pipeline-for-rapid-identification-of-homologous-gene-families-in-a-set-of-genomes</guid>
	<pubDate>Thu, 13 Aug 2020 10:06:19 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42038/pyparanoid-a-pipeline-for-rapid-identification-of-homologous-gene-families-in-a-set-of-genomes</link>
	<title><![CDATA[PyParanoid: a pipeline for rapid identification of homologous gene families in a set of genomes]]></title>
	<description><![CDATA[<p>PyParanoid is a pipeline for rapid identification of homologous gene families in a set of genomes - a central task of any comparative genomics analysis. The "gold standard" for identifying homologs is to use reciprocal best hits (RBHs) which depends on performing a all-vs-all sequence comparison, usually using BLAST, to determine homology. However, these methods are computationally expensive, requiring&nbsp;O(n2)&nbsp;resources to identify RBHs. This is problematic, as the modern deluge of sequencing data means that comparative genomics analyses could be performed on datasets of thousands of strains.</p><p>Address of the bookmark: <a href="https://github.com/ryanmelnyk/PyParanoid" rel="nofollow">https://github.com/ryanmelnyk/PyParanoid</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44313/orthovenn3-an-integrated-platform-for-exploring-and-visualizing-orthologous-data-across-genomes</guid>
	<pubDate>Tue, 02 May 2023 00:48:28 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44313/orthovenn3-an-integrated-platform-for-exploring-and-visualizing-orthologous-data-across-genomes</link>
	<title><![CDATA[OrthoVenn3: an integrated platform for exploring and visualizing orthologous data across genomes]]></title>
	<description><![CDATA[<p><span>OrthoVenn3 is a powerful tool for comparative genomics analysis, used as a web server for full genome comparisons, annotation, and evolutionary analysis of orthologous clusters across multiple species. It has already been used by thousands of users from over 60 countries.</span></p><p>Address of the bookmark: <a href="https://orthovenn3.bioinfotoolkits.net/" rel="nofollow">https://orthovenn3.bioinfotoolkits.net/</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44655/ngenomesyn-an-easy-to-use-and-flexible-tool-for-publication-ready-visualization-of-syntenic-relationships-across-multiple-genomes</guid>
	<pubDate>Tue, 10 Sep 2024 04:54:55 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44655/ngenomesyn-an-easy-to-use-and-flexible-tool-for-publication-ready-visualization-of-syntenic-relationships-across-multiple-genomes</link>
	<title><![CDATA[NGenomeSyn: an easy-to-use and flexible tool for publication-ready visualization of syntenic relationships across multiple genomes]]></title>
	<description><![CDATA[<p>NGenomeSyn: an easy-to-use and flexible tool for publication-ready visualization of syntenic relationships across multiple genomes&nbsp;</p>
<p><img src="https://github.com/hewm2008/NGenomeSyn/raw/main/Example/example2/OUT3.png" alt="image" style="border: 0px;"></p>
<p><span>NGenomeSyn [multiple (N) Genome Synteny], for publication-ready visualization of syntenic relationships of the whole genome or local region and genomic features (e.g. repeats, structural variations, genes) across multiple genomes with a high customization. NGenomeSyn provides an easy way for its users to visualize a large amount of data with a rich layout by simply adjusting options for moving, scaling, and rotation of target genomes. Moreover, NGenomeSyn could be applied on the visualization of relationships on non-genomic data with similar input formats.</span></p>
<p>https://academic.oup.com/bioinformatics/article/39/3/btad121/7072460</p><p>Address of the bookmark: <a href="https://github.com/hewm2008/NGenomeSyn" rel="nofollow">https://github.com/hewm2008/NGenomeSyn</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
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