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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/36012?offset=40</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38041/synima-a-synteny-imaging-tool-for-annotated-genome-assemblies</guid>
	<pubDate>Tue, 30 Oct 2018 10:49:13 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38041/synima-a-synteny-imaging-tool-for-annotated-genome-assemblies</link>
	<title><![CDATA[Synima: a Synteny imaging tool for annotated genome assemblies]]></title>
	<description><![CDATA[<p><span>Synima written in Perl, which uses the graphical features of R. Synima takes orthologues computed from reciprocal best BLAST hits or OrthoMCL, and DAGchainer, and outputs an overview of genome-wide synteny in PDF. Each of these programs are included with the Synima package, and a pipeline for their use. Synima has a range of graphical parameters including size, colours, order, and labels, which are specified in a config file generated by the first run of Synima &ndash; and can be subsequently edited. Synima runs quickly on a command line to generate informative and publication quality figures. Synima is open source and freely available from&nbsp;</span><a href="https://github.com/rhysf/Synima" target="_blank">https://github.com/rhysf/Synima</a><span>&nbsp;under the MIT License.</span></p><p>Address of the bookmark: <a href="https://github.com/rhysf/Synima" rel="nofollow">https://github.com/rhysf/Synima</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38208/anitools-web-a-web-tool-for-fast-genome-comparison-within-multiple-bacterial-strains</guid>
	<pubDate>Wed, 14 Nov 2018 04:34:23 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38208/anitools-web-a-web-tool-for-fast-genome-comparison-within-multiple-bacterial-strains</link>
	<title><![CDATA[ANItools web: a web tool for fast genome comparison within multiple bacterial strains]]></title>
	<description><![CDATA[<p><span>ANItools is a software package written by PERL scripts that can be run in a Linux/Unix system. If you want to compare bacterial genomes and calculate their average nucleotide identity (ANI), you could download and run this program directly. Or you could send us the genome sequence by email. Then we will do the analysis work for you.</span></p>
<p><span>https://academic.oup.com/database/article/doi/10.1093/database/baw084/2630454</span></p><p>Address of the bookmark: <a href="http://ani.mypathogen.cn/" rel="nofollow">http://ani.mypathogen.cn/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</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/43614/mitoz-a-toolkit-for-animal-mitochondrial-genome-assembly-annotation-and-visualization</guid>
	<pubDate>Tue, 30 Nov 2021 23:23:57 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43614/mitoz-a-toolkit-for-animal-mitochondrial-genome-assembly-annotation-and-visualization</link>
	<title><![CDATA[MitoZ: a toolkit for animal mitochondrial genome assembly, annotation and visualization]]></title>
	<description><![CDATA[<p>MitoZ, consisting of independent modules of <em>de novo</em> assembly, findMitoScaf (find Mitochondrial Scaffolds), annotation and visualization, that can generate mitogenome assembly together with annotation and visualization results from HTS raw reads.</p>
<p>https://academic.oup.com/nar/article/47/11/e63/5377471</p><p>Address of the bookmark: <a href="https://github.com/linzhi2013/MitoZ" rel="nofollow">https://github.com/linzhi2013/MitoZ</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<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>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44483/baclife-an-automated-genome-mining-tool-for-identification-of-lifestyle-associated-genes</guid>
	<pubDate>Fri, 15 Mar 2024 04:59:14 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44483/baclife-an-automated-genome-mining-tool-for-identification-of-lifestyle-associated-genes</link>
	<title><![CDATA[bacLIFE: an automated genome mining tool for identification of lifestyle associated genes]]></title>
	<description><![CDATA[<p style="margin-top: 0px; margin-bottom: 16px; color: #1f2328; font-size: 16px; font-style: normal; font-weight: 400; text-align: start; background-color: #ffffff;" dir="auto">bacLIFE is a streamlined computational workflow that annotates bacterial genomes and performs large-scale comparative genomics to predict bacterial lifestyles and to pinpoint candidate genes, denominated<span>&nbsp;</span><strong style="font-weight: var(--base-text-weight-semibold, 600);">lifestyle-associated genes (LAGs)</strong>, and biosynthetic gene clusters associated with each lifestyle detected. This whole process is divided into different modules:</p>
<ul style="margin-top: 0px; margin-bottom: 16px; color: #1f2328; font-size: 16px; font-style: normal; font-weight: 400; text-align: start; background-color: #ffffff;" dir="auto">
<li><strong style="font-weight: var(--base-text-weight-semibold, 600);">Clustering module</strong><span>&nbsp;</span>Predicts, clusters and annotates the genes of every input genome</li>
<li style="margin-top: 0.25em;"><strong style="font-weight: var(--base-text-weight-semibold, 600);">Lifestyle prediction</strong><span>&nbsp;</span>Employs a machine learning model to forecast bacterial lifestyle or other specified metadata</li>
<li style="margin-top: 0.25em;"><strong style="font-weight: var(--base-text-weight-semibold, 600);">Analitical module (Shiny app)</strong><span>&nbsp;</span>Results from the previous modules are embedded in a user-friendly interface for comprehensive and interactive comparative genomics.</li>
</ul>
<p style="margin-top: 0px; margin-bottom: 16px; color: #1f2328; font-size: 16px; font-style: normal; font-weight: 400; text-align: start; background-color: #ffffff;" dir="auto">You can find the complete wiki here [<a href="https://github.com/Carrion-lab/bacLIFE/wiki/bacLIFE-wiki">https://github.com/Carrion-lab/bacLIFE/wiki/bacLIFE-wiki</a>]</p><p>Address of the bookmark: <a href="https://github.com/Carrion-lab/bacLIFE" rel="nofollow">https://github.com/Carrion-lab/bacLIFE</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27427/rcircos-an-r-package-for-circos-2d-track-plots</guid>
	<pubDate>Fri, 20 May 2016 11:01:13 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27427/rcircos-an-r-package-for-circos-2d-track-plots</link>
	<title><![CDATA[RCircos: an R package for Circos 2D track plots]]></title>
	<description><![CDATA[<p>RCircos package provides a simple and flexible way to make Circos 2D track plots with R and could be easily integrated into other R data processing and graphic manipulation pipelines for presenting large-scale multi-sample genomic research data. It can also serve as a base tool to generate complex Circos images.</p>
<p>More at https://bitbucket.org/henryhzhang/rcircos/src</p><p>Address of the bookmark: <a href="https://bitbucket.org/henryhzhang/rcircos/src" rel="nofollow">https://bitbucket.org/henryhzhang/rcircos/src</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/file/view/29110/structural-variants-ppt</guid>
	<pubDate>Wed, 07 Sep 2016 03:16:09 -0500</pubDate>
	<link>https://bioinformaticsonline.com/file/view/29110/structural-variants-ppt</link>
	<title><![CDATA[Structural variants PPT]]></title>
	<description><![CDATA[<p>1000 Genomes data tutorial at ASHG</p><p>Structural variants presentation by</p><p>Jan Korbel</p><p>European Molecular Biology Laboratory (EMBL) Heidelberg Genome Biology Research Unit</p><p>Reference:&nbsp;</p><p>https://www.genome.gov/pages/research/der/1000genomesprojecttutorials/structuralvariants-jankorbel.pdf</p>]]></description>
	<dc:creator>Jit</dc:creator>
	<enclosure url="https://bioinformaticsonline.com/file/download/29110" length="1090837" type="application/pdf" />
</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>

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