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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/40460?offset=70</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42354/vsfilt-a-tool-to-improve-virtual-screening-by-structural-filtration-of-docking-poses</guid>
	<pubDate>Wed, 25 Nov 2020 02:39:16 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42354/vsfilt-a-tool-to-improve-virtual-screening-by-structural-filtration-of-docking-poses</link>
	<title><![CDATA[vsFilt: A tool to improve virtual screening by structural filtration of docking poses]]></title>
	<description><![CDATA[<p><span>The vsFilt is the first open application for post-docking structural filtration, available as a web-server. The new tool is easy to use and configure to detect a wide range of interaction types that are known to be involved in molecular recognition, including hydrogen and halogen bonds, ionic interactions, hydrophobic contacts, &pi;-stacking, and cation-&pi; interactions. The web-server can process large libraries of up to 150&rsquo;000 docked ligand poses. The results are web-based and can be operated on-line using the built-in HTML5 interactive analysis tools, or can be downloaded for a local use. The vsFilt is freely available on-line, no login required.</span></p><p>Address of the bookmark: <a href="https://biokinet.belozersky.msu.ru/vsfilt" rel="nofollow">https://biokinet.belozersky.msu.ru/vsfilt</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44499/severus-a-somatic-structural-variation-sv-caller-for-long-reads</guid>
	<pubDate>Sun, 31 Mar 2024 02:41:27 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44499/severus-a-somatic-structural-variation-sv-caller-for-long-reads</link>
	<title><![CDATA[Severus: a somatic structural variation (SV) caller for long reads]]></title>
	<description><![CDATA[<p dir="auto">Severus is a somatic structural variation (SV) caller for long reads (both PacBio and ONT). It is designed for matching tumor/normal analysis, supports multiple tumor samples, and produces accurate and complete somatic and germline calls. Severus takes advantage of long-read phasing and uses the breakpoint graph framework to model complex chromosomal rearrangements.</p>
<p dir="auto">If you use Severus, please cite&nbsp;<a href="https://www.medrxiv.org/content/10.1101/2024.03.22.24304756v1">https://www.medrxiv.org/content/10.1101/2024.03.22.24304756v1</a></p><p>Address of the bookmark: <a href="https://github.com/KolmogorovLab/Severus" rel="nofollow">https://github.com/KolmogorovLab/Severus</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41916/truvari-structural-variant-comparison-tool-for-vcfs</guid>
	<pubDate>Tue, 30 Jun 2020 21:30:44 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41916/truvari-structural-variant-comparison-tool-for-vcfs</link>
	<title><![CDATA[truvari: Structural variant comparison tool for VCFs]]></title>
	<description><![CDATA[<p>Structural variant comparison tool for VCFs</p>
<p>Given benchmark and comparsion sets of SVs, calculate the recall, precision, and f-measure.</p>
<p><a href="https://github.com/spiralgenetics/www.spiralgenetics.com">Spiral Genetics</a></p>
<p><a href="https://docs.google.com/presentation/d/17mvC1XOpOm7khAbZwF3SgtG2Rl4M9Mro37yF2nN7GhE/edit">Motivation</a></p><p>Address of the bookmark: <a href="https://github.com/spiralgenetics/truvari" rel="nofollow">https://github.com/spiralgenetics/truvari</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/23253/resolving-the-complexity-of-the-human-genome-using-single-molecule-sequencing</guid>
	<pubDate>Sat, 11 Jul 2015 12:47:34 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/23253/resolving-the-complexity-of-the-human-genome-using-single-molecule-sequencing</link>
	<title><![CDATA[Resolving the complexity of the human genome using single-molecule sequencing]]></title>
	<description><![CDATA[<p>The human genome is arguably the most complete mammalian reference assembly yet more than 160 euchromatic gaps remain and aspects of its structural variation remain poorly understood ten years after its completion. The results in this paper https://www.genomeweb.com/sequencing/team-uses-single-molecule-sequencing-close-gaps-chart-complexity-human-reference suggest a greater complexity of the human genome in the form of variation of longer and more complex repetitive DNA that can now be largely resolved with the application of this longer-read sequencing technology.</p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="http://www.nature.com/nature/journal/v517/n7536/full/nature13907.html" rel="nofollow">http://www.nature.com/nature/journal/v517/n7536/full/nature13907.html</a></p>]]></description>
	<dc:creator>Rahul Agarwal</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/3030/illuminating-next-generation-sequencing-data-with-go</guid>
	<pubDate>Fri, 23 Aug 2013 07:13:33 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/3030/illuminating-next-generation-sequencing-data-with-go</link>
	<title><![CDATA[Illuminating next generation sequencing data with Go]]></title>
	<description><![CDATA[<p>Another good lecture for Illumina sequencing data analysis from&nbsp;</p>
<p>Dan Kortschak,&nbsp;Bioinformatics Group,&nbsp;School of Molecular and Biomedical Science ,The University of Adelaide</p><p>Address of the bookmark: <a href="http://talks.biogo.googlecode.com/git/illumination/illumination.pdf" rel="nofollow">http://talks.biogo.googlecode.com/git/illumination/illumination.pdf</a></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26906/paired-end-assembler-for-dna-sequences</guid>
	<pubDate>Wed, 06 Apr 2016 05:25:34 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26906/paired-end-assembler-for-dna-sequences</link>
	<title><![CDATA[PAired-eND Assembler for DNA sequences]]></title>
	<description><![CDATA[<p>PANDASEQ is a program to align Illumina reads, optionally with PCR primers embedded in the sequence, and reconstruct an overlapping sequence.</p>
<p>&nbsp;</p>
<p>More at https://github.com/neufeld/pandaseq</p><p>Address of the bookmark: <a href="https://github.com/neufeld/pandaseq" rel="nofollow">https://github.com/neufeld/pandaseq</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30625/pandaseq</guid>
	<pubDate>Mon, 23 Jan 2017 04:54:32 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30625/pandaseq</link>
	<title><![CDATA[PANDASEQ]]></title>
	<description><![CDATA[<p>PANDASEQ assembles paired-end Illumina reads into sequences, trying to correct for errors and uncalled bases. The assembler reads two files in FASTQ format with quality information. If amplification primers were used (e.g., to isolate a variable region of the 16S gene, or the constant regions around zinc finger binding residues), they can be removed from the sequence during assembly. The final sequence will correct any uncalled bases in the overlapping region using the complementary strand. When mismatches occur in the overlapping region, the base with the better quality score is chosen.<br>The algorithm is as follows:<br><br>1.Find the positions where the forward and reverse primers match best above the threshold and discard the ends of the sequence, including the primer.<br>2.Pick and overlap to maximise the probability of the forward and reverse reads having come from a single piece of DNA.<br>3.Identify the masking of the end of the read with the quality score B or # as done by CASAVA and adjust the probabilities in this region.<br>4.Construct an assembled sequence between the primers and calculate the quality.<br>5.Check for various constraints, including quality, length, uncalled bases, and user-supplied modules.</p>
<p>http://neufeldserver.uwaterloo.ca/~apmasell/pandaseq_man1.html</p><p>Address of the bookmark: <a href="http://neufeldserver.uwaterloo.ca/~apmasell/pandaseq_man1.html" rel="nofollow">http://neufeldserver.uwaterloo.ca/~apmasell/pandaseq_man1.html</a></p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36833/bfc-a-standalone-high-performance-tool-for-correcting-sequencing-errors-from-illumina-sequencing-data</guid>
	<pubDate>Thu, 31 May 2018 09:35:23 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36833/bfc-a-standalone-high-performance-tool-for-correcting-sequencing-errors-from-illumina-sequencing-data</link>
	<title><![CDATA[BFC: a standalone high-performance tool for correcting sequencing errors from Illumina sequencing data]]></title>
	<description><![CDATA[BFC is a standalone high-performance tool for correcting sequencing errors from Illumina sequencing data. It is specifically designed for high-coverage whole-genome human data, though also performs well for small genomes.

The BFC algorithm is a variant of the classical spectrum alignment algorithm introduced by Pevzner et al (2001). It uses an exhaustive search to find a k-mer path through a read that minimizes a heuristic objective function jointly considering penalties on correction, quality and k-mer support. This algorithm was first implemented in my fermi assembler and then refined a few times in fermi, fermi2 and now in BFC. In the k-mer counting phase, BFC uses a blocked bloom filter to filter out most singleton k-mers and keeps the rest in a hash table (Melsted and Pritchard, 2011). The use of bloom filter is how BFC is named, though other correctors such as Lighter and Bless actually rely more on bloom filter than BFC.

https://github.com/lh3/bfc<p>Address of the bookmark: <a href="https://github.com/lh3/bfc" rel="nofollow">https://github.com/lh3/bfc</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/4191/high-density-sheep-snp-genotyping-chip-released</guid>
	<pubDate>Tue, 03 Sep 2013 13:58:04 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/4191/high-density-sheep-snp-genotyping-chip-released</link>
	<title><![CDATA[High Density Sheep SNP Genotyping Chip released!!!]]></title>
	<description><![CDATA[<p>If you are working on Sheep genomics then there is a good news for you. FarmIQ in conjunction with Illumina and the International Sheep Genomics Consortium (ISGC) are today announcing completion of the &ldquo;Ovine Infinium&reg; HD SNP BeadChip&rdquo;,&nbsp;a high definition SNP chip for ship genome. The OvineSNP50 BeadChip features over 54,241 evenly spaced probes that target SNPs, offering more than sufficient SNP density for genome-wide association studies and other applications such as genome-wide selection, determination of genetic merit, identification of quantitative trait loci, and comparative genetic studies.</p><p>The BeadChip was developed in collaboration with leading ovine researchers from AgResearch, Baylor UCSC, CSIRO, and the USDA as part of the International Sheep Genomics Consortium. It features over 54,241 evenly spaced probes that target single nucleotide polymorphisms (SNPs). More than 18,000 of these markers were discovered through sequencing reduced representation libraries with the Illumina Genome Analyzer IIx. A set of 600 SNPs were identified by BAC end sequencing and validated with Illumina GoldenGate Genotyping Assays over 403 animals from 23 breeds. The remaining SNPs were derived from the draft ovine genome.</p><p>Read more @</p><p><a href="http://res.illumina.com/documents/products/datasheets/datasheet_ovinesnp50.pdf">http://res.illumina.com/documents/products/datasheets/datasheet_ovinesnp50.pdf</a><a href="http://www.scoop.co.nz/stories/SC1309/S00004/high-density-snp-genotyping-chip-for-the-sheep-genome.htm"><br /></a></p><p><a href="http://www.illumina.com/products/ovinesnp50_dna_analysis_kit.ilmn">http://www.illumina.com/products/ovinesnp50_dna_analysis_kit.ilmn</a></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
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