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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/44499?offset=20</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41442/gsp4pdb-a-web-tool-to-visualize-search-and-explore-protein-ligand-structural-patterns</guid>
	<pubDate>Sun, 15 Mar 2020 03:41:12 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41442/gsp4pdb-a-web-tool-to-visualize-search-and-explore-protein-ligand-structural-patterns</link>
	<title><![CDATA[GSP4PDB: a web tool to visualize, search and explore protein-ligand structural patterns]]></title>
	<description><![CDATA[<p><span><span>GSP4PDB is a user-friendly and efficient application to search and discover new patterns of protein-ligand interaction.</span></span></p>
<p><span>GSP4PDB</span><span>&nbsp;is part of the services provided by the&nbsp;</span><a href="https://structuralbio.utalca.cl/" target="_blank">Bioinformatic Group</a><span>&nbsp;of the&nbsp;</span><a href="http://www.utalca.cl/" target="_blank">University of Talca</a></p>
<p><a href="http://gdblab.com/gsp4pdb/gsp4pdb2/">http://gdblab.com/gsp4pdb/gsp4pdb2/</a></p>
<p>https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-020-3352-x</p><p>Address of the bookmark: <a href="http://gdblab.com/gsp4pdb/gsp4pdb2/" rel="nofollow">http://gdblab.com/gsp4pdb/gsp4pdb2/</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43888/syri-compares-alignments-between-two-chromosome-level-assemblies-and-identifies-synteny-and-structural-rearrangements</guid>
	<pubDate>Wed, 01 Jun 2022 02:01:13 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43888/syri-compares-alignments-between-two-chromosome-level-assemblies-and-identifies-synteny-and-structural-rearrangements</link>
	<title><![CDATA[Syri compares alignments between two chromosome-level assemblies and identifies synteny and structural rearrangements.]]></title>
	<description><![CDATA[<p><span>Syri compares alignments between two chromosome-level assemblies and identifies synteny and structural rearrangements.</span></p>
<p><span><img src="https://github.com/schneebergerlab/syri/raw/master/example/ampril_col0_chr3_6600000_10000000.png" alt="image" style="border: 0px;"></span></p><p>Address of the bookmark: <a href="https://github.com/schneebergerlab/syri" rel="nofollow">https://github.com/schneebergerlab/syri</a></p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40460/sviper-swipe-your-structural-variants-called-on-long-ontpacbio-reads-with-short-exact-illumina-reads</guid>
	<pubDate>Sun, 22 Dec 2019 03:48:28 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40460/sviper-swipe-your-structural-variants-called-on-long-ontpacbio-reads-with-short-exact-illumina-reads</link>
	<title><![CDATA[SViper: Swipe your Structural Variants called on long (ONT/PacBio) reads with short exact (Illumina) reads.]]></title>
	<description><![CDATA[<p>Call sviper</p>
<pre><code>~$ ./sviper -s short-reads.bam -l long-reads.bam -r ref.fa -c variants.vcf -o polished_variants
</code></pre>
<p>This will output a&nbsp;<code>polished_variants.vcf</code>&nbsp;file, that contains all the refined variants.</p>
<p>Sometimes it is helpful to look at the polished sequence, e.g. with the IGV browser. In that case you want SViper to output the polished and aligned sequences in a bam file via the option&nbsp;<code>--output-polished-bam</code>:</p>
<pre><code>~$ ./sviper -s short-reads.bam -l long-reads.bam -r ref.fa -c variants.vcf -o polished_variants --output-</code>polished-bam</pre><p>Address of the bookmark: <a href="https://github.com/smehringer/SViper" rel="nofollow">https://github.com/smehringer/SViper</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26543/breakseq2</guid>
	<pubDate>Mon, 29 Feb 2016 17:45:38 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26543/breakseq2</link>
	<title><![CDATA[BreakSeq2]]></title>
	<description><![CDATA[<p>Ultrafast and accurate nucleotide-resolution analysis of structural variants</p>
<p>More at http://bioinform.github.io/breakseq2/</p>
<p>Download BreakSeq2</p>
<p>Latest version: https://github.com/bioinform/breakseq2/archive/2.2.tar.gz<br><br>For other versions, see "releases". https://github.com/bioinform/breakseq2/releases</p><p>Address of the bookmark: <a href="http://bioinform.github.io/breakseq2/" rel="nofollow">http://bioinform.github.io/breakseq2/</a></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/45289/the-atlas-of-nine-billion-possibilities</guid>
	<pubDate>Wed, 09 Sep 2026 02:07:58 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/45289/the-atlas-of-nine-billion-possibilities</link>
	<title><![CDATA[The Atlas of Nine Billion Possibilities]]></title>
	<description><![CDATA[<p>Imagine a book that holds all the instructions for building a human, made up of billions of letters. What if you changed just one letter? Maybe nothing would happen. Or that tiny change could affect how a gene works, quietly shaping a cell&rsquo;s biology or even helping cause disease.</p><p>Scientists face a big challenge with the human genome. They can read its letters, but understanding their roles is much harder. Only about 2 percent of the genome codes for proteins. The rest acts like a huge control panel, deciding when and where genes turn on. With about 9 billion possible single-letter changes, testing them all in a lab just isn&rsquo;t possible.</p><p>So, Google DeepMind asked a new question: what if we could predict what those changes might do?</p><p>This question led to the AlphaGenome Atlas (https://deepmind.google.com/science/alphagenome/atlas?), a detailed map of nearly every possible single-letter change in the human genome. Instead of checking each change one by one, researchers can use the Atlas to spot the ones most likely to matter. The AlphaGenome Variant Impact (AVI) score works like a trail marker, pointing scientists toward the changes worth a closer look.</p><p>This is where the Atlas gets especially useful. Much of the genome lies outside the protein-coding regions, where DNA acts as a switch or controller for genes. AlphaGenome lets researchers explore these areas and see how small changes could affect gene activity.</p><p>An atlas isn't the destination; it's a guide.</p><p>The AlphaGenome Atlas doesn&rsquo;t replace experiments or solve every mystery. Instead, it helps scientists decide where to begin. From billions of possibilities, it turns the vast genetic landscape into something researchers can start to explore.</p><p>There are nine billion possibilities, a vast map, and maybe among them therWith nine billion possibilities and a huge map to explore, there may be clues hidden here to some of medicine&rsquo;s toughest mysteries.</p><p>More at&nbsp;https://storage.googleapis.com/deepmind-media/DeepMind.com/Blog/alphagenome-atlas-a-predictive-map-of-every-possible-dna-letter-change-in-the-human-genome/alphagenome-atlas.pdf</p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41146/lofreq-a-sequence-quality-aware-ultra-sensitive-variant-caller-for-ngs-data</guid>
	<pubDate>Tue, 18 Feb 2020 03:24:22 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41146/lofreq-a-sequence-quality-aware-ultra-sensitive-variant-caller-for-ngs-data</link>
	<title><![CDATA[LoFreq*: A sequence-quality aware, ultra-sensitive variant caller for NGS data]]></title>
	<description><![CDATA[<p>LoFreq* (i.e. LoFreq version 2) is a fast and sensitive variant-caller for inferring SNVs and indels from next-generation sequencing data. It makes full use of base-call qualities and other sources of errors inherent in sequencing (e.g. mapping or base/indel alignment uncertainty), which are usually ignored by other methods or only used for filtering.</p>
<p>https://github.com/CSB5/lofreq</p>
<p>http://csb5.github.io/lofreq/installation/</p>
<p>https://github.com/CSB5/lofreq/tree/master/dist</p><p>Address of the bookmark: <a href="http://csb5.github.io/lofreq/" rel="nofollow">http://csb5.github.io/lofreq/</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/33482/tardis-toolkit-for-automated-and-rapid-discovery-of-structural-variants</guid>
	<pubDate>Fri, 09 Jun 2017 04:43:31 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/33482/tardis-toolkit-for-automated-and-rapid-discovery-of-structural-variants</link>
	<title><![CDATA[TARDIS: Toolkit for automated and rapid discovery of structural variants]]></title>
	<description><![CDATA[<p>tardis</p>
<p>Toolkit for Automated and Rapid DIscovery of Structural variants</p>
<p>Requirements</p>
<p>zlib (http://www.zlib.net)<br>mrfast (https://github.com/BilkentCompGen/mrfast)<br>htslib (included as submodule; http://htslib.org/)<br>Fetching tardis</p>
<p>git clone https://github.com/BilkentCompGen/tardis.git --recursive</p>
<p>&nbsp;</p>
<p>https://github.com/BilkentCompGen/tardis</p><p>Address of the bookmark: <a href="https://github.com/BilkentCompGen/tardis" rel="nofollow">https://github.com/BilkentCompGen/tardis</a></p>]]></description>
	<dc:creator>Neel</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>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41730/parliament2-runs-a-combination-of-tools-to-generate-structural-variant-calls-on-whole-genome-sequencing-data</guid>
	<pubDate>Thu, 28 May 2020 21:57:03 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41730/parliament2-runs-a-combination-of-tools-to-generate-structural-variant-calls-on-whole-genome-sequencing-data</link>
	<title><![CDATA[Parliament2: Runs a combination of tools to generate structural variant calls on whole-genome sequencing data]]></title>
	<description><![CDATA[<p>Parliament2 identifies structural variants in a given sample relative to a reference genome. These structural variants cover large deletion events that are called as Deletions of a region, Insertions of a sequence into a region, Duplications of a region, Inversions of a region, or Translocations between two regions in the genome.</p>
<p>Parliament2 runs a combination of tools to generate structural variant calls on whole-genome sequencing data. It can run the following callers: Breakdancer, Breakseq2, CNVnator, Delly2, Manta, and Lumpy. Because of synergies in how the programs use computational resources, these are all run in parallel. Parliament2 will produce the outputs of each of the tools for subsequent investigation.</p><p>Address of the bookmark: <a href="https://github.com/dnanexus/parliament2" rel="nofollow">https://github.com/dnanexus/parliament2</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/9695/learn-genetics-online</guid>
	<pubDate>Wed, 09 Apr 2014 19:12:42 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/9695/learn-genetics-online</link>
	<title><![CDATA[Learn Genetics Online]]></title>
	<description><![CDATA[<p>Great source to learn genetics and other relevant stuffs online.</p><p>Address of the bookmark: <a href="http://learn.genetics.utah.edu/" rel="nofollow">http://learn.genetics.utah.edu/</a></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
</item>

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