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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/41736?offset=160</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37502/alignqc-a-tool-for-assessing-an-alignment-and-generating-reports-that-are-easy-to-share</guid>
	<pubDate>Tue, 07 Aug 2018 04:41:07 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37502/alignqc-a-tool-for-assessing-an-alignment-and-generating-reports-that-are-easy-to-share</link>
	<title><![CDATA[AlignQC: A tool for assessing an alignment, and generating reports that are easy to share]]></title>
	<description><![CDATA[<p><span>Long read alignment analysis. Generate a reports on sequence alignments for mappability vs read sizes, error patterns, annotations and rarefraction curve analysis. The most basic analysis only requires a BAM file, and outputs a web browser compatible xhtml to visualize/share/store/extract analysis results.</span></p>
<p>https://f1000research.com/articles/6-100/</p>
<p>https://github.com/jason-weirather/AlignQC</p><p>Address of the bookmark: <a href="https://www.healthcare.uiowa.edu/labs/au/AlignQC/" rel="nofollow">https://www.healthcare.uiowa.edu/labs/au/AlignQC/</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/37800/heatmapper-web-enabled-heat-mapping-for-all</guid>
	<pubDate>Mon, 01 Oct 2018 08:34:41 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37800/heatmapper-web-enabled-heat-mapping-for-all</link>
	<title><![CDATA[Heatmapper: web-enabled heat mapping for all]]></title>
	<description><![CDATA[<p><span>Heatmapper is a freely available web server that allows users to interactively visualize their data in the form of heat maps through an easy-to-use graphical interface. Heatmapper is a versatile tool that allows users to easily create a wide variety of heat maps for many different data types and applications. Heatmapper allows users to generate, cluster and visualize: </span></p>
<p><span>1)&nbsp;</span><span>expression-based heat maps</span><span>&nbsp;from transcriptomic, proteomic and metabolomic experiments; 2)&nbsp;</span><span>pairwise distance maps</span><span>; </span></p>
<p><span>3)&nbsp;</span><span>correlation maps</span><span>; </span></p>
<p><span>4)&nbsp;</span><span>image overlay heat maps</span><span>; </span></p>
<p><span>5)&nbsp;</span><span>latitude and longitude heat maps</span><span>&nbsp;and </span></p>
<p><span>6)&nbsp;</span><span>geopolitical (choropleth) heat maps</span><span>. </span></p>
<p><span>Heatmapper offers a number of simple and intuitive customization options for easy adjustments to each heat map&rsquo;s appearance and plotting parameters. Heatmapper also allows users to interactively explore their numeric data values by hovering their cursor over each heat map, or by using a searchable/sortable data table view.</span></p>
<p><span>Ref&nbsp;https://www.ncbi.nlm.nih.gov/pubmed/27190236</span></p><p>Address of the bookmark: <a href="http://www2.heatmapper.ca/" rel="nofollow">http://www2.heatmapper.ca/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38749/clipcrop-a-tool-for-detecting-structural-variations-with-single-base-resolution-using-soft-clipping-information</guid>
	<pubDate>Sun, 20 Jan 2019 06:34:36 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38749/clipcrop-a-tool-for-detecting-structural-variations-with-single-base-resolution-using-soft-clipping-information</link>
	<title><![CDATA[ClipCrop: a tool for detecting structural variations with single-base resolution using soft-clipping information]]></title>
	<description><![CDATA[<p><span>ClipCrop for detecting SVs with single-base resolution using soft-clipping information. A soft-clipped sequence is an unmatched fragment in a partially mapped read. To assess the performance of ClipCrop with other SV-detecting tools, we generated various patterns of simulation data &ndash; SV lengths, read lengths, and the depth of coverage of short reads &ndash; with insertions, deletions, tandem duplications, inversions and single nucleotide alterations in a human chromosome.&nbsp;</span></p><p>Address of the bookmark: <a href="https://github.com/shinout/clipcrop" rel="nofollow">https://github.com/shinout/clipcrop</a></p>]]></description>
	<dc:creator>BioJoker</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40359/minipolish-a-tool-for-racon-polishing-of-miniasm-assemblies</guid>
	<pubDate>Tue, 03 Dec 2019 02:40:54 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40359/minipolish-a-tool-for-racon-polishing-of-miniasm-assemblies</link>
	<title><![CDATA[Minipolish: A tool for Racon polishing of miniasm assemblies]]></title>
	<description><![CDATA[<p><a href="https://github.com/lh3/miniasm">Miniasm</a>&nbsp;is a great long-read assembly tool: straight-forward, effective and very fast. However, it does not include a polishing step, so its assemblies have a high error rate &ndash; they are essentially made of stitched-together pieces of long reads.</p>
<p><a href="https://github.com/isovic/racon">Racon</a>&nbsp;is a great polishing tool that can be used to clean up assembly errors. It's also very fast and well suited for long-read data. However, it operates on FASTA files, not the&nbsp;<a href="https://github.com/GFA-spec/GFA-spec/blob/master/GFA1.md">GFA graphs</a>&nbsp;that miniasm makes.</p>
<p>That's where Minipolish comes in. With a single command, it will use Racon to polish up a miniasm assembly, while keeping the assembly in graph form.</p>
<p>It also takes care of some of the other nuances of polishing a miniasm assembly:</p>
<ul>
<li>Adding read depth information to contigs</li>
<li>Fixing sequence truncation that can occur in Racon</li>
<li>Adding circularising links to circular contigs if not already present (so they display better in&nbsp;<a href="https://github.com/rrwick/Bandage">Bandage</a>)</li>
<li>'Rotating' circular contigs between polishing rounds to ensure clean circularisation</li>
</ul><p>Address of the bookmark: <a href="https://github.com/rrwick/Minipolish" rel="nofollow">https://github.com/rrwick/Minipolish</a></p>]]></description>
	<dc:creator>BioStar</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>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41571/wego-simple-but-useful-tool-for-visualizing-comparing-and-plotting-go-gene-ontology-annotation-results</guid>
	<pubDate>Sun, 12 Apr 2020 10:02:22 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41571/wego-simple-but-useful-tool-for-visualizing-comparing-and-plotting-go-gene-ontology-annotation-results</link>
	<title><![CDATA[WEGO : simple but useful tool for visualizing, comparing and plotting GO (Gene Ontology) annotation results]]></title>
	<description><![CDATA[<p><span>WEGO (Web Gene Ontology Annotation Plot) is a simple but useful tool for visualizing, comparing and plotting GO (Gene Ontology) annotation results. As the GO vocabulary became more and more popular, WEGO was widely adopted and used in many researches. Therefore we have updated WEGO 2.0 in 2018. Here are some changes we&rsquo;ve made:</span><br><span>1. The limit of input file numbers was cancelled. Now the users could upload as many files as they want with one operation.</span><br><span>2. We have added the reference data of 9 species for users selection.</span><br><span>3. Besides the traditional WEGO histogram, WEGO 2.0 outputs an additional type of bar graph showing GO terms with significant gene number differences.</span></p><p>Address of the bookmark: <a href="http://wego.genomics.org.cn/" rel="nofollow">http://wego.genomics.org.cn/</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41991/sequence-ontology-bioinformatics-analysis-soba-tool-to-provide-a-simple-statistical-and-graphical-summary-of-an-annotated-genome</guid>
	<pubDate>Wed, 22 Jul 2020 10:11:13 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41991/sequence-ontology-bioinformatics-analysis-soba-tool-to-provide-a-simple-statistical-and-graphical-summary-of-an-annotated-genome</link>
	<title><![CDATA[Sequence Ontology Bioinformatics Analysis (SOBA) tool to provide a simple statistical and graphical summary of an annotated genome]]></title>
	<description><![CDATA[<p><span>We have developed the Sequence Ontology Bioinformatics Analysis (SOBA) tool to provide a simple statistical and graphical summary of an annotated genome. We envisage its use during annotation jamborees, genome comparison and for use by developers for rapid feedback during annotation software development and testing. SOBA also provides annotation consistency feedback to ensure correct use of terminology within annotations, and guides users to add new terms to the Sequence Ontology when required. SOBA is available at http://www.sequenceontology.org/cgi-bin/soba.cgi.</span></p>
<p><span>More at <a href="https://pubmed.ncbi.nlm.nih.gov/20494974/">https://pubmed.ncbi.nlm.nih.gov/20494974/</a></span></p><p>Address of the bookmark: <a href="http://www.sequenceontology.org/cgi-bin/soba.cgi" rel="nofollow">http://www.sequenceontology.org/cgi-bin/soba.cgi</a></p>]]></description>
	<dc:creator>BioStar</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/43791/comparative-genomics-visualisation-tools</guid>
	<pubDate>Thu, 17 Feb 2022 05:37:55 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43791/comparative-genomics-visualisation-tools</link>
	<title><![CDATA[Comparative genomics visualisation tools !]]></title>
	<description><![CDATA[<p>Comparative genomics visualisation tools !</p><p>Address of the bookmark: <a href="https://cmdcolin.github.io/awesome-genome-visualization/?latest=true&amp;selected=%23BRIG&amp;tag=Comparative" rel="nofollow">https://cmdcolin.github.io/awesome-genome-visualization/?latest=true&amp;selected=%23BRIG&amp;tag=Comparative</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>

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