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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/41046?offset=20</link>
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	<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/40707/vt-a-variant-tool-set-that-discovers-short-variants-from-next-generation-sequencing-data</guid>
	<pubDate>Tue, 28 Jan 2020 03:44:43 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40707/vt-a-variant-tool-set-that-discovers-short-variants-from-next-generation-sequencing-data</link>
	<title><![CDATA[vt: a variant tool set that discovers short variants from Next Generation Sequencing data.]]></title>
	<description><![CDATA[<p><span>vt is a variant tool set that discovers short variants from Next Generation Sequencing data.</span></p>
<p><span><a href="https://genome.sph.umich.edu/wiki/Vt">https://genome.sph.umich.edu/wiki/Vt</a></span></p>
<p><a href="https://github.com/atks/vt">https://github.com/atks/vt</a></p><p>Address of the bookmark: <a href="https://genome.sph.umich.edu/wiki/Vt" rel="nofollow">https://genome.sph.umich.edu/wiki/Vt</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37643/lorma-a-tool-for-correcting-sequencing-errors-in-long-reads</guid>
	<pubDate>Thu, 06 Sep 2018 16:21:01 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37643/lorma-a-tool-for-correcting-sequencing-errors-in-long-reads</link>
	<title><![CDATA[LoRMA: A tool for correcting sequencing errors in long reads]]></title>
	<description><![CDATA[<p><span>An error correction method that uses long reads only. The method consists of two phases: first, we use an iterative alignment-free correction method based on de Bruijn graphs with increasing length of&nbsp;</span><em>k</em><span>-mers, and second, the corrected reads are further polished using long-distance dependencies that are found using multiple alignments. According to our experiments, the proposed method is the most accurate one relying on long reads only for read sets with high coverage. Furthermore, when the coverage of the read set is at least 75&times;, the throughput of the new method is at least 20% higher.</span></p>
<blockquote>
<p><span>conda install -c atgc-montpellier lorma</span></p>
</blockquote><p>Address of the bookmark: <a href="https://gite.lirmm.fr/lorma/lorma-releases/wikis/home" rel="nofollow">https://gite.lirmm.fr/lorma/lorma-releases/wikis/home</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44659/figeno-tool-for-plotting-sequencing-data-along-genomic-coordinates</guid>
	<pubDate>Tue, 17 Sep 2024 02:28:15 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44659/figeno-tool-for-plotting-sequencing-data-along-genomic-coordinates</link>
	<title><![CDATA[Figeno: Tool for plotting sequencing data along genomic coordinates.]]></title>
	<description><![CDATA[<p><span>Tool for plotting sequencing data along genomic coordinates.</span></p>
<div>
<pre><code>FIGENO is a
  FIGure
    GENerator
for GENOmics</code></pre>
</div>
<p dir="auto">With figeno, you can plot various types of sequencing data along genomic coordinates. Video overview:&nbsp;<a href="https://www.youtube.com/watch?v=h1cBeXoSYTA">https://www.youtube.com/watch?v=h1cBeXoSYTA</a>.</p>
<p dir="auto"><a href="https://github.com/CompEpigen/figeno/blob/main/docs/content/images/figeno.png" target="_blank"><img src="https://github.com/CompEpigen/figeno/raw/main/docs/content/images/figeno.png" alt="figeno" style="border: 0px;"></a></p><p>Address of the bookmark: <a href="https://github.com/CompEpigen/figeno" rel="nofollow">https://github.com/CompEpigen/figeno</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43867/genomeqc-a-quality-assessment-tool-for-genome-assemblies-and-gene-structure-annotations</guid>
	<pubDate>Thu, 19 May 2022 04:29:05 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43867/genomeqc-a-quality-assessment-tool-for-genome-assemblies-and-gene-structure-annotations</link>
	<title><![CDATA[GenomeQC: a quality assessment tool for genome assemblies and gene structure annotations]]></title>
	<description><![CDATA[<p><span>The GenomeQC web application is implemented in R/Shiny version 1.5.9 and Python 3.6 and is freely available at&nbsp;</span><a href="https://genomeqc.maizegdb.org/">https://genomeqc.maizegdb.org/</a><span>&nbsp;under the GPL license. All source code and a containerized version of the GenomeQC pipeline is available in the GitHub repository&nbsp;</span><a href="https://github.com/HuffordLab/GenomeQC">https://github.com/HuffordLab/GenomeQC</a><span>.</span></p>
<p>https://bmcgenomics.biomedcentral.com/articles/10.1186/s12864-020-6568-2</p><p>Address of the bookmark: <a href="https://github.com/HuffordLab/GenomeQC" rel="nofollow">https://github.com/HuffordLab/GenomeQC</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/2631/what-junk-dna-it%E2%80%99s-an-operating-system</guid>
	<pubDate>Mon, 19 Aug 2013 15:24:26 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/2631/what-junk-dna-it%E2%80%99s-an-operating-system</link>
	<title><![CDATA[What Junk DNA? It’s an Operating System]]></title>
	<description><![CDATA[<p>The report adds to growing experimental support for the idea that all that extra stuff in the human genes, once referred to as &ldquo;junk DNA,&rdquo; is more than functionless, space-filling material that happens to make up nearly 98% of the genome. The paper adds to a growing body of knowledge establishing a considerable role for this material in the regulation of gene expression and its potential role in human disease.</p><p>Address of the bookmark: <a href="http://www.genengnews.com/keywordsandtools/print/3/32115/" rel="nofollow">http://www.genengnews.com/keywordsandtools/print/3/32115/</a></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/17843/pathway-analysis</guid>
	<pubDate>Fri, 03 Oct 2014 08:51:13 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/17843/pathway-analysis</link>
	<title><![CDATA[Pathway Analysis]]></title>
	<description><![CDATA[<p>Pathway Analysis is usually performed with aim to enrich the genes with their functional information and reveal the underlying biological mechanisms pursue by genes. Pathway Analysis is not only limited to what biological pathways a particular set of expressed genes follow but also to disclose the relationships between these genes. With availability of more genomics, transcriptomics and proteomics data, interactions between genes involve in multiple pathways become more clear and also relationships between the genes, their transcripts, and their gene products. However, existing tools and dbs mainly based on knowledge driven approach in which pathways will be identified by finding the correlation between the&nbsp;<span>information in one of the pathway knowledge databases (KEGG,Reactome,Panther,BioCarta, Panther,GO,NCI,WikiPathways,etc) and gene expression result for a specific conditions for instance tumor, obesity , cold resistant crops/plants, etc.</span></p><p><span><strong>Introductory Articles/ppt/sources</strong>:</span></p><p><a href="http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.1002375"><span>http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.1002375</span></a></p><p><a href="http://bioinformatics.mdanderson.org/MicroarrayCourse/Lectures09/Pathway%20Analysis.pdf"><span>http://bioinformatics.mdanderson.org/MicroarrayCourse/Lectures09/Pathway%20Analysis.pdf</span></a></p><p><a href="http://gettinggeneticsdone.blogspot.de/2012/03/pathway-analysis-for-high-throughput.html"><span>http://gettinggeneticsdone.blogspot.de/2012/03/pathway-analysis-for-high-throughput.html</span></a></p><p><a href="http://davetang.org/muse/tag/pathway/"><span>http://davetang.org/muse/tag/pathway/</span></a></p><p><a href="https://www.biostars.org/p/42219/"><span>https://www.biostars.org/p/42219/</span></a></p><p><a href="http://bioinformatics.ca//files/public/Pathways_2014_Module4_v2.pdf"><span>http://bioinformatics.ca//files/public/Pathways_2014_Module4_v2.pdf</span></a></p><p><a href="http://bioinformatics.ca//files/public/Pathways_2014_Module2.pdf"><span>http://bioinformatics.ca//files/public/Pathways_2014_Module2.pdf</span></a></p><p><span><strong>Impotant Database and Tools</strong>:</span></p><p>GeneMANIA, Cytoscape,&nbsp;<a href="http://www.ingenuity.com/products/ipa">IPA</a>&nbsp;and <a href="http://thomsonreuters.com/metacore/">Metacore</a> (Commerical ),&nbsp;<span>Pathway Commons, Reactome ,Panther, BioCyc, WikiPathways, Pathvisio, KEGG, NCI, Stringdb, Amigo,&nbsp;<span>WebGestalt ,<span>ConsensusPathDB ,GSEA,Blast2go</span></span></span></p><p><span><strong>Popular R based tools</strong>:</span></p><p><span>Reactome.db, ReactomePA, ClusterProfiler, Gage, SPIA, topGO, Pathview,DOSE,GOStat</span></p><p><span><strong>More</strong>:</span></p><p><a href="http://www.bioconductor.org/help/search/index.html?q=Enrichment+analysis+"><span>http://www.bioconductor.org/help/search/index.html?q=Enrichment+analysis+</span></a></p><p>&nbsp;</p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37650/p-rna-scaffolder-a-fast-and-accurate-genome-scaffolder-using-paired-end-rna-sequencing-reads</guid>
	<pubDate>Fri, 07 Sep 2018 05:19:06 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37650/p-rna-scaffolder-a-fast-and-accurate-genome-scaffolder-using-paired-end-rna-sequencing-reads</link>
	<title><![CDATA[P_RNA_scaffolder: a fast and accurate genome scaffolder using paired-end RNA-sequencing reads]]></title>
	<description><![CDATA[<p><span>P_RNA_scaffolder is a novel scaffolding tool using Pair-end RNA-seq to scaffold genome fragments. The method is suitable for most genomes. The program could utilize Illumina Paired-end RNA-sequencing reads from target speciesies. Our method provides another practical alternative to existing mate-pair_based approaches or other Protein-based approaches (for instance,&nbsp;</span><a href="http://www.fishbrowser.org/software/PEP_scaffolder/">PEP_scaffolder&nbsp;</a><span>) for scaffolding genome sequences. The most important feature of this method is to improve the completeness of gene regions and long-coding gene regions (for instance,&nbsp;</span><a href="http://circrna.org/">circRNA</a><span>).</span></p><p>Address of the bookmark: <a href="http://www.fishbrowser.org/software/P_RNA_scaffolder/#" rel="nofollow">http://www.fishbrowser.org/software/P_RNA_scaffolder/#</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35420/telomerehunter</guid>
	<pubDate>Fri, 02 Feb 2018 04:23:59 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35420/telomerehunter</link>
	<title><![CDATA[TelomereHunter]]></title>
	<description><![CDATA[<p><span>TelomereHunter is a tool for estimating telomere content from human whole-genome sequencing data. It is designed to take BAM files from a tumor and a matching control sample as input. However, it is also possible to run TelomereHunter with one input file. TelomereHunter extracts and sorts telomeric reads from the input sample(s). For the estimation of telomere content, GC biases are taken into account. Finally, the results of TelomereHunter are visualized in several diagrams.</span><br><br><span>TelomereHunter is available for download at the following address:&nbsp;</span><a href="https://pypi.python.org/pypi/telomerehunter/" target="_blank">https://pypi.python.org/pypi/telomerehunter/</a></p><p>Address of the bookmark: <a href="http://www.dkfz.de/en/applied-bioinformatics/telomerehunter/telomerehunter.html" rel="nofollow">http://www.dkfz.de/en/applied-bioinformatics/telomerehunter/telomerehunter.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40792/haslr-a-tool-for-rapid-genome-assembly-of-long-sequencing-reads</guid>
	<pubDate>Fri, 31 Jan 2020 05:50:15 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40792/haslr-a-tool-for-rapid-genome-assembly-of-long-sequencing-reads</link>
	<title><![CDATA[HASLR: a tool for rapid genome assembly of long sequencing reads]]></title>
	<description><![CDATA[<p><span>HASLR is a tool for rapid genome assembly of long sequencing reads. HASLR is a hybrid tool which means it requires long reads generated by Third Generation Sequencing technologies (such as PacBio or Oxford Nanopore) together with Next Generation Sequencing reads (such as Illumina) from the same sample.&nbsp;</span></p><p>Address of the bookmark: <a href="https://github.com/vpc-ccg/haslr" rel="nofollow">https://github.com/vpc-ccg/haslr</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>

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