<?xml version='1.0'?><rss version="2.0" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:georss="http://www.georss.org/georss" xmlns:atom="http://www.w3.org/2005/Atom" >
<channel>
	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/37259?offset=20</link>
	<atom:link href="https://bioinformaticsonline.com/related/37259?offset=20" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42303/fqc-dashboard-integrates-fastqc-results-into-a-web-based-interactive-and-extensible-fastq-quality-control-tool</guid>
	<pubDate>Tue, 10 Nov 2020 01:30:22 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42303/fqc-dashboard-integrates-fastqc-results-into-a-web-based-interactive-and-extensible-fastq-quality-control-tool</link>
	<title><![CDATA[FQC Dashboard: Integrates FastQC results into a web-based, interactive, and extensible FASTQ quality control tool]]></title>
	<description><![CDATA[<p>FQC is software that facilitates quality control of FASTQ files by carrying out a QC protocol using FastQC, parsing results, and aggregating quality metrics into an interactive dashboard designed to richly summarize individual sequencing runs. The dashboard groups samples in dropdowns for navigation among the data sets, utilizes human-readable configuration files to manipulate the pages and tabs, and is extensible with CSV data.</p><p>Address of the bookmark: <a href="https://github.com/pnnl/fqc" rel="nofollow">https://github.com/pnnl/fqc</a></p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35896/phylographer-graph-visualization-tool</guid>
	<pubDate>Wed, 07 Mar 2018 18:11:25 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35896/phylographer-graph-visualization-tool</link>
	<title><![CDATA[PhyloGrapher - Graph Visualization Tool]]></title>
	<description><![CDATA[<p><strong>PhyloGrapher</strong><span>&nbsp;is a program designed to visualize and study evolutionary relationships within families of homologous genes or proteins (elements).&nbsp;</span><strong>PhyloGrapher</strong><span>&nbsp;is a drawing tool that generates custom graphs for a given set of elements. In general, it is possible to use&nbsp;</span><strong>PhyloGrapher</strong><span>&nbsp;to visualize any type of relations between elements.&nbsp;</span></p>
<p><span>https://www.youtube.com/watch?v=WgufqYMHCvM</span></p><p>Address of the bookmark: <a href="http://www.atgc.org/PhyloGrapher/PhyloGrapher_Welcome.html" rel="nofollow">http://www.atgc.org/PhyloGrapher/PhyloGrapher_Welcome.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/33693/circleator</guid>
	<pubDate>Sun, 25 Jun 2017 18:04:32 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/33693/circleator</link>
	<title><![CDATA[Circleator]]></title>
	<description><![CDATA[<p>The Charm City Circleator--or Circleator for short--is a Perl-based visualization tool developed at the&nbsp;<a href="http://igs.umaryland.edu/">Institute for Genome Sciences</a>&nbsp;in the University of Maryland's School of Medicine. Circleator produces circular plots of genome-associated data, like this one:</p>
<p><a href="https://camo.githubusercontent.com/0b414f050a7dcb672386932ee0cd83e5f42d2271/687474703a2f2f6a6f6e617468616e63726162747265652e6769746875622e696f2f436972636c6561746f722f696d616765732f43503030323732352d322d3432302e706e673f7261773d74727565" target="_blank"><img src="https://camo.githubusercontent.com/0b414f050a7dcb672386932ee0cd83e5f42d2271/687474703a2f2f6a6f6e617468616e63726162747265652e6769746875622e696f2f436972636c6561746f722f696d616765732f43503030323732352d322d3432302e706e673f7261773d74727565" alt="Sample Circleator image" title="Sample Circleator Image" style="border: 0px;"></a></p>
<p>Common uses of the tool include:</p>
<ul>
<li>Displaying the sequence and/or genes in a&nbsp;<a href="http://www.ncbi.nlm.nih.gov/genbank/">GenBank</a>&nbsp;flat file.</li>
<li>Highlighting differences and/or similarities in gene content between related organisms.</li>
<li>Comparing SNPs and indels between closely-related strains or serovars.</li>
<li>Comparing gene expression values across multiple samples or timepoints.</li>
<li>Visualizing coverage plots of RNA-Seq read alignments.</li>
</ul>
<h3><a href="https://github.com/jonathancrabtree/Circleator#key-features"></a>Key Features</h3>
<p>Circleator...</p>
<ul>
<li>Builds on&nbsp;<a href="http://www.bioperl.org/">BioPerl</a>&nbsp;and the input file formats that it supports, including:
<ul>
<li><a href="http://www.ncbi.nlm.nih.gov/genbank/">GenBank</a>&nbsp;flat files, GFF, FASTA</li>
</ul>
</li>
<li>Accepts a number of other commonly-used datatypes and file formats:
<ul>
<li><a href="http://bsr.igs.umaryland.edu/">BSR</a>&nbsp;and&nbsp;<a href="http://tandem.bu.edu/trf/trf.html">TRF</a>&nbsp;output,&nbsp;<a href="http://samtools.sourceforge.net/">SAM/BAM</a>&nbsp;files,&nbsp;<a href="http://vcftools.sourceforge.net/">VCF</a>-encoded SNPs, tab-delimited files</li>
</ul>
</li>
<li>Outputs publication-ready figures in the&nbsp;<a href="http://www.w3.org/Graphics/SVG/">SVG</a>&nbsp;(Scalable Vector Graphics) format.</li>
<li>Requires only a single configuration file whose layout mirrors that of the figure itself.
<ul>
<li>Predefined configuration files and "track" types are supplied for common datasets.</li>
<li>Advanced features allow limited analyses to be performed as a figure is drawn.</li>
</ul>
</li>
<li>Includes an extensive set of regression tests.</li>
<li>Offers a prototype web-based GUI (under the "Ringmaster" project.)</li>
</ul>
<p>https://github.com/jonathancrabtree/Circleator</p><p>Address of the bookmark: <a href="https://github.com/jonathancrabtree/Circleator" rel="nofollow">https://github.com/jonathancrabtree/Circleator</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36907/higlass-a-tool-for-exploring-genomic-contact-matrices-and-tracks</guid>
	<pubDate>Mon, 11 Jun 2018 09:44:49 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36907/higlass-a-tool-for-exploring-genomic-contact-matrices-and-tracks</link>
	<title><![CDATA[HiGlass: a tool for exploring genomic contact matrices and tracks.]]></title>
	<description><![CDATA[HiGlass is a tool for exploring genomic contact matrices and tracks. Please take a look at the examples and documentation for a description of the ways that it can be configured to explore and compare contact matrices. To load private data, HiGlass can be run locally within a Docker container. The HiC data in the examples below is from Rao et al. (2014)

http://higlass.io/<p>Address of the bookmark: <a href="http://higlass.io/" rel="nofollow">http://higlass.io/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37527/nanopack-visualizing-and-processing-long-read-sequencing-data</guid>
	<pubDate>Fri, 10 Aug 2018 18:41:34 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37527/nanopack-visualizing-and-processing-long-read-sequencing-data</link>
	<title><![CDATA[NanoPack: visualizing and processing long-read sequencing data]]></title>
	<description><![CDATA[<p>The NanoPack tools are written in Python3 and released under the GNU GPL3.0 License. The source code can be found at&nbsp;<a href="https://github.com/wdecoster/nanopack" target="">https://github.com/wdecoster/nanopack</a>, together with links to separate scripts and their documentation. The scripts are compatible with Linux, Mac OS and the MS Windows 10 subsystem for Linux and are available as a graphical user interface, a web service at&nbsp;<a href="http://nanoplot.bioinf.be/" target="">http://nanoplot.bioinf.be</a>&nbsp;and command line tools.</p>
<p>&nbsp;https://academic.oup.com/bioinformatics/article/34/15/2666/4934939</p><p>Address of the bookmark: <a href="https://github.com/wdecoster/nanoQC" rel="nofollow">https://github.com/wdecoster/nanoQC</a></p>]]></description>
	<dc:creator>Jit</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/41209/juicebox-visualization-and-analysis-software-for-hi-c-data</guid>
	<pubDate>Fri, 21 Feb 2020 00:33:38 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41209/juicebox-visualization-and-analysis-software-for-hi-c-data</link>
	<title><![CDATA[Juicebox: Visualization and analysis software for Hi-C data]]></title>
	<description><![CDATA[<p>Juicebox is visualization software for Hi-C data. This distribution includes the source code for Juicebox,&nbsp;<a href="https://github.com/theaidenlab/juicer/wiki/Download">Juicer Tools</a>, and&nbsp;<a href="https://aidenlab.org/assembly/">Assembly Tools</a>.&nbsp;<a href="https://github.com/theaidenlab/juicebox/wiki/Download">Download Juicebox here</a>, or use&nbsp;<a href="https://aidenlab.org/juicebox">Juicebox on the web</a>. Detailed documentation is available&nbsp;<a href="https://github.com/theaidenlab/juicebox/wiki">on the wiki</a>. Instructions below pertain primarily to usage of command line tools and the Juicebox jar files.</p>
<p>Juicebox can now be used to visualize and interactively (re)assemble genomes. Check out the Juicebox Assembly Tools Module website&nbsp;<a href="https://aidenlab.org/assembly">https://aidenlab.org/assembly</a>&nbsp;for more details on how to use Juicebox for assembly.</p>
<p>GUI at&nbsp;<a href="https://aidenlab.org/juicebox/">https://aidenlab.org/juicebox/</a></p><p>Address of the bookmark: <a href="https://github.com/aidenlab/Juicebox" rel="nofollow">https://github.com/aidenlab/Juicebox</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42362/magic-a-tool-for-predicting-transcription-factors-and-cofactors-driving-gene-sets-using-encode-data</guid>
	<pubDate>Thu, 26 Nov 2020 11:05:04 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42362/magic-a-tool-for-predicting-transcription-factors-and-cofactors-driving-gene-sets-using-encode-data</link>
	<title><![CDATA[MAGIC: A tool for predicting transcription factors and cofactors driving gene sets using ENCODE data]]></title>
	<description><![CDATA[<p><span>The algorithm presented herein,&nbsp;</span><strong>M</strong><span>ining&nbsp;</span><strong>A</strong><span>lgorithm for&nbsp;</span><strong>G</strong><span>enet</span><strong>I</strong><span>c&nbsp;</span><strong>C</strong><span>ontrollers (MAGIC), uses ENCODE ChIP-seq data to look for statistical enrichment of TFs and cofactors in gene bodies and flanking regions in gene lists without an&nbsp;</span><em>a priori</em><span>&nbsp;binary classification of genes as targets or non-targets. When compared to other TF mining resources, MAGIC displayed favourable performance in predicting TFs and cofactors that drive gene changes in 4 settings: </span></p>
<p><span>1) A cell line expressing or lacking single TF, </span></p>
<p><span>2) Breast tumors divided along PAM50 designations </span></p>
<p><span>3) Whole brain samples from WT mice or mice lacking a single TF in a particular neuronal subtype </span></p>
<p><span>4) Single cell RNAseq analysis of neurons divided by Immediate Early Gene expression levels. </span></p>
<p><span>In summary, MAGIC is a standalone application that produces meaningful predictions of TFs and cofactors in transcriptomic experiments.</span></p>
<p><span>More at&nbsp;https://uwmadison.app.box.com/s/8j90e5h2rjrsz3bacaxnq8kor2o64vyg</span></p><p>Address of the bookmark: <a href="https://github.com/asroopra/MAGIC" rel="nofollow">https://github.com/asroopra/MAGIC</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43090/loretta-a-user-friendly-tool-for-assembling-viral-genomes-from-pacbio-sequence-data</guid>
	<pubDate>Wed, 23 Jun 2021 07:54:53 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43090/loretta-a-user-friendly-tool-for-assembling-viral-genomes-from-pacbio-sequence-data</link>
	<title><![CDATA[LoReTTA, a user-friendly tool for assembling viral genomes from PacBio sequence data]]></title>
	<description><![CDATA[<p>LoReTTA (Long Read Template-Targeted Assembler), a tool designed for performing <em>de novo</em> assembly of long reads generated from viral genomes on the PacBio platform. LoReTTA exploits a reference genome to guide the assembly process, an approach that has been successful with short reads.</p>
<p>https://academic.oup.com/ve/article/7/1/veab042/6248116</p><p>Address of the bookmark: <a href="https://academic.oup.com/ve/article/7/1/veab042/6248116" rel="nofollow">https://academic.oup.com/ve/article/7/1/veab042/6248116</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/42324/comparative-genomics-data-set-including-240-mammals-released</guid>
	<pubDate>Thu, 19 Nov 2020 06:45:39 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/42324/comparative-genomics-data-set-including-240-mammals-released</link>
	<title><![CDATA[Comparative Genomics Data Set Including 240 Mammals Released !]]></title>
	<description><![CDATA[<p>The genome of 130 mammals was sequenced by a large international consortium and the data was analyzed together with 110 existing genomes to allow scientists to identify the important positions in the DNA. This report, published in Nature today will help advance research on human disease mutations and inform how best to protect endangered species.</p><p>In addition to the knowledge of the human genome, all these genomes, widely sampled across mammals, can be used to research how particular organisms respond to different conditions. Some otters, for example, have a thick, water-resistant shell, and some rodents, but not all, have adapted to hibernation. These animal traits will help us to understand human traits, such as metabolic diseases.</p><p><img src="https://media.springernature.com/lw685/springer-static/image/art%3A10.1038%2Fs41586-020-2876-6/MediaObjects/41586_2020_2876_Fig1_HTML.png?as=webp" alt="image" style="border: 0px; border: 0px;"></p><p>With climate change and more animal ecosystems being threatened by human activity, the protection of endangered species is becoming increasingly important. Scientists have historically researched several people in various populations of a species to understand the genetic variation that occurs in that species. This is important for understanding how particular species can be protected. In this study, animals on the Red List of Endangered Species of the International Union for Conservation of Nature had fewer differences in their genomes, which is consistent with their endangered status.</p><p>Ref @&nbsp;A comparative genomics multitool for scientific discovery and conservation&nbsp;https://www.nature.com/articles/s41586-020-2876-6</p><p>&nbsp;Data at&nbsp;http://zoonomiaproject.org/</p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

</channel>
</rss>