<?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/43447?offset=170</link>
	<atom:link href="https://bioinformaticsonline.com/related/43447?offset=170" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36510/scallop-reference-based-transcriptome-assembler-for-rna-seq</guid>
	<pubDate>Tue, 08 May 2018 04:23:27 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36510/scallop-reference-based-transcriptome-assembler-for-rna-seq</link>
	<title><![CDATA[Scallop: reference-based transcriptome assembler for RNA-seq]]></title>
	<description><![CDATA[<p>Scallop is an accurate reference-based transcript assembler. Scallop features its high accuracy in assembling multi-exon transcripts as well as lowly expressed transcripts. Scallop achieves this improvement through a novel algorithm that can be proved preserving all phasing paths from reads and paired-end reads, while also achieves both transcripts parsimony and coverage deviation minimization.</p>
<p>Scallop paper has been published at&nbsp;<a href="https://www.nature.com/articles/nbt.4020"><span>Nature Biotechnology</span></a>. The datasets and scripts used in this paper to compare the performance of Scallop and other assemblers are available at&nbsp;<a href="https://github.com/Kingsford-Group/scalloptest"><span>scalloptest</span></a>.</p>
<p>Please also checkout the&nbsp;<span>podcast</span>&nbsp;about Scallop (thanks&nbsp;<a href="https://ro-che.info/">Roman Cheplyaka</a>&nbsp;for the interview). It is available at both&nbsp;<a href="https://bioinformatics.chat/scallop">the bioinformatics chat</a>&nbsp;and&nbsp;<a href="https://itunes.apple.com/us/podcast/the-bioinformatics-chat/id1227281398">iTunes</a>.</p>
<p>&nbsp;</p>
<p>https://github.com/Kingsford-Group/scallop</p><p>Address of the bookmark: <a href="https://github.com/Kingsford-Group/scallop" rel="nofollow">https://github.com/Kingsford-Group/scallop</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43025/modular-efficient-and-constant-memory-single-cell-rna-seq-preprocessing</guid>
	<pubDate>Mon, 05 Apr 2021 11:19:43 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43025/modular-efficient-and-constant-memory-single-cell-rna-seq-preprocessing</link>
	<title><![CDATA[Modular, efficient and constant-memory single-cell RNA-seq preprocessing]]></title>
	<description><![CDATA[<p>With&nbsp;<strong>kallisto | bustools</strong>&nbsp;you can</p>
<ul>
<li>Generate a&nbsp;<em>cell x gene</em>&nbsp;or&nbsp;<em>cell x transcript equivalence class</em>&nbsp;count matrix</li>
<li>Perform RNA velocity and single-nuclei RNA-seq analsis</li>
<li>Quantify data from numerous technologies such as 10x, inDrops, and Dropseq.</li>
<li>Customize workflows for new technologies and protocols.</li>
<li>Process feature barcoding data such as CITE-seq, REAP-seq, MULTI-seq, Clicktags, and Perturb-seq.</li>
<li>Obtain QC reports from single-cell RNA-seq data</li>
</ul>
<p>The&nbsp;<strong>kallisto | bustools</strong>&nbsp;workflow is described in:</p>
<p>P&aacute;ll Melsted*, A. Sina Booeshaghi*, Lauren Liu, Fan Gao, Lambda Lu, Kyung Hoi (Joseph) Min, Eduardo da Veiga Beltrame, Kristj&aacute;n Eldj&aacute;rn Hj&ouml;rleifsson, Jase Gehring &amp; Lior Pachter&dagger;&nbsp;<a href="https://doi.org/10.1038/s41587-021-00870-2" target="_blank">Modular and efficient pre-processing of single-cell RNA-seq</a>, Nature Biotechnology (2021).</p>
<p>&nbsp;</p>
<p><span>Documentation and tutorials for the kallisto bustools workflow are available at&nbsp;</span><a href="http://pachterlab.github.io/kallistobustools">http://pachterlab.github.io/kallistobustools</a><span>.&nbsp;</span></p>
<p>https://www.nature.com/articles/s41587-021-00870-2</p><p>Address of the bookmark: <a href="https://pachterlab.github.io/kallistobustools/" rel="nofollow">https://pachterlab.github.io/kallistobustools/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/10966/genxpro-gmbh</guid>
	<pubDate>Thu, 22 May 2014 07:18:35 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/10966/genxpro-gmbh</link>
	<title><![CDATA[GenXPro GmbH]]></title>
	<description><![CDATA[<p><strong>GenXPro</strong>&nbsp;GMbH is service provider for entire spectrum of nucleotide-based information&nbsp;of any biological sample. By combining intelligent data reduction techniques and&nbsp;latest next generation sequencing technologies, our service portfolio provides most accurate and cost efficient solutions for&nbsp;transcriptomic-, genomic- or epigenomic research.</p><p><span><span><strong><span>GENXPRO GMBH</span>,&nbsp;</strong></span></span><span>ALTENH&Ouml;FERALLEE 3,&nbsp;</span><span>60438 FRANKFURT MAIN,&nbsp;</span><span>GERMANY</span></p><p><span><span><strong>Website</strong></span>:&nbsp;<a href="http://www.genxpro.info/products_and_services/"></a><a href="http://www.genxpro.info/products_and_services/">http://www.genxpro.info/products_and_services/</a></span></p><p><span><strong>PHONE</strong>: +49 (0)69- 95 73 97 10,&nbsp;FAX: +49 (0)69- 95 73 97 06</span></p><p><span>EMAIL: info@genxpro.de</span></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/19631/rosalind-bioinformatics-problems</guid>
	<pubDate>Thu, 18 Dec 2014 10:32:48 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/19631/rosalind-bioinformatics-problems</link>
	<title><![CDATA[Rosalind Bioinformatics problems !!!]]></title>
	<description><![CDATA[<p>Rosalind is a platform for learning bioinformatics and programming through problem solving. <a href="http://rosalind.info/problems/list-view/">Take a tour</a> to get the hang of how Rosalind works.</p>
<p>http://rosalind.info/problems/list-view/</p><p>Address of the bookmark: <a href="http://rosalind.info/problems/list-view/" rel="nofollow">http://rosalind.info/problems/list-view/</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/34197/strand-life-sciences-announces-the-release-of-strand-ngs-v31-at-ashg-2017</guid>
	<pubDate>Mon, 23 Oct 2017 02:39:24 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/34197/strand-life-sciences-announces-the-release-of-strand-ngs-v31-at-ashg-2017</link>
	<title><![CDATA[Strand Life Sciences announces the release of Strand NGS v3.1 at ASHG 2017]]></title>
	<description><![CDATA[<h1><a href="http://www.strand-ngs.com/strand-announce-strandngss-v31">Strand Life Sciences announces the release of Strand NGS v3.1 at ASHG 2017</a></h1><p><strong><em>ORLANDO, USA, Oct 17, 2017/ PRNewswire/</em></strong></p><p><em>Strand NGS now supports large scale RNA- and small-RNA-Seq and Unique Molecular Identifiers (UMIs) for DNA-, RNA-, and small-RNA-Seq.</em></p><p>Strand Life Sciences announced the latest version release of its bioinformatics flagship product, Strand NGS, at the Annual Meeting of the American Society of Human Genetics today. Two major themes in Strand NGS v3.1 address recent challenges in next generation sequencing (NGS).</p><p>The first theme is large-scale RNA-Seq data analysis. Current cross-cohort RNA- and small-RNA-Seq studies span tens of replicates and batches across hundreds of samples, sometimes conducted across several different institutions. For such studies, Strand NGS v3.1 includes confounding variable analysis to eliminate technical effects, including batch effects; the t-SNE plot; profile and heat-map plots of gene-body coverage; and several other notable visual enhancements.</p><p>The second new feature is support for Unique Molecular Identifiers, or UMIs, for DNA-, RNA- and small-RNA-Seq. UMI support in Strand NGS is end-to-end, spanning alignment to variant calling in DNA-Seq, and alignment to quantification in RNA- and small-RNA-Seq. The Bioo Scientific, Qiagen, and Rubicon UMI protocols are natively supported, and an intuitive interface allows the specification of custom UMI protocols.</p><p><em>&ldquo;For liquid biopsies and low-grade FFPE samples, UMI support in DNA-Seq enables the detection of somatic variants at low concentrations. In RNA-Seq, large-scale and UMI support can be used in single-cell-based studies that reveal tumor-cell heterogeneity, even at low concentrations&rdquo;, says<strong>&nbsp;Dr. Vamsi Veeramachaneni, Chief Scientific Officer, Strand Life Sciences.</strong></em></p><p><em>&ldquo;At Strand, we are continuously working towards improving the accuracy and efficiency of NGS data analysis. Customers can look forward to Strand NGS becoming available on the cloud in the near future&rdquo;, says&nbsp;<strong>Dr. Ramesh Hariharan, Chief Executive Officer, Strand Life Sciences.</strong></em></p><p>Visit Strand Life Sciences at ASHG booth #1017 to know more about Strand NGS v3.1 and other products and service offerings from Strand Life Sciences. Click here to access detailed agenda and v3.1&nbsp;<a href="http://www.strand-ngs.com/download/releasenotes">release notes</a>.</p><p><strong>About Strand Life Sciences</strong></p><p>Strand Life Sciences is a premier life science informatics innovation company. Founded in 2000, Strand is a leader in technology innovations for healthcare using genomics. By enhancing sequence-based diagnostics and clinical genomic data interpretation using a strong foundation of computational, scientific, and medical expertise, Strand is bringing individualized medicine to the world. To know more, visit&nbsp;<a href="http://www.strandls.com/" title="www.strandls.com">www.strandls.com</a></p>]]></description>
	<dc:creator>Yeshodari</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42040/proactiv-estimation-of-promoter-activity-from-rna-seq-data</guid>
	<pubDate>Thu, 13 Aug 2020 10:21:44 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42040/proactiv-estimation-of-promoter-activity-from-rna-seq-data</link>
	<title><![CDATA[proActiv: Estimation of Promoter Activity from RNA-Seq data]]></title>
	<description><![CDATA[<p>proActiv is an R package that estimates promoter activity from RNA-Seq data. proActiv uses aligned reads and genome annotations as input, and provides absolute and relative promoter activity as output. The package can be used to identify active promoters and alternative promoters, the details of the method are described in&nbsp;<a href="https://github.com/GoekeLab/proActiv#reference">Demircioglu et al</a>.</p>
<p>Additional data on differential promoters in tissues and cancers from TCGA, ICGC, GTEx, and PCAWG can be downloaded here:&nbsp;<a href="https://jglab.org/data-and-software/">https://jglab.org/data-and-software/</a></p><p>Address of the bookmark: <a href="https://github.com/GoekeLab/proActiv" rel="nofollow">https://github.com/GoekeLab/proActiv</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/32950/genespring-webinar-uncovering-mechanisms-of-hepatotoxicity-on-14-june-at-8am-pst</guid>
	<pubDate>Tue, 23 May 2017 06:48:40 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/32950/genespring-webinar-uncovering-mechanisms-of-hepatotoxicity-on-14-june-at-8am-pst</link>
	<title><![CDATA[GeneSpring webinar- Uncovering mechanisms of hepatotoxicity on 14 June at 8AM PST]]></title>
	<description><![CDATA[<p><a href="http://genespring-support.com/content/webinar-uncovering-mechanisms-hepatotoxicity-high-affinity-antisense-oligonucleotides-using-"><strong>Uncovering Mechanisms of Hepatotoxicity for High Affinity Antisense Oligonucleotides &ndash; 3&rsquo; end RNA-seq Profiling Using GeneSpring GX</strong></a></p><p>High affinity antisense oligonucleotides (ASOs) containing bicylic modifications (BNA) such as locked nucleic acid (LNA) or constrained ethyl (cEt) designed to induce target RNA cleavage have been shown to have enhanced potency along with a higher propensity to cause hepatotoxicity. In order to unravel the mechanism of this hepatotoxicity, we leveraged GeneSpring GX analysis software to analyze transcriptional profiles from the livers of mice treated with a panel of highly efficacious hepatotoxic or non-hepatotoxic LNA ASOs.</p><p><a href="http://genespring-support.com/content/webinar-uncovering-mechanisms-hepatotoxicity-high-affinity-antisense-oligonucleotides-using-"><strong>Speaker:</strong></a><br />Sebastien A. Burel, PhD<br />Director, Nonclinical Development, Ionis Pharmaceuticals, California</p><p><a href="http://genespring-support.com/content/webinar-uncovering-mechanisms-hepatotoxicity-high-affinity-antisense-oligonucleotides-using-"><strong>Details:</strong></a><br />14 June 2017, 8 AM PST</p><h3><a href="http://genespring-support.com/content/webinar-uncovering-mechanisms-hepatotoxicity-high-affinity-antisense-oligonucleotides-using-">Register for this Webinar</a></h3>]]></description>
	<dc:creator>Yeshodari</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/2461/taverna-workflow-management-system</guid>
	<pubDate>Thu, 15 Aug 2013 19:34:32 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/2461/taverna-workflow-management-system</link>
	<title><![CDATA[Taverna Workflow Management System]]></title>
	<description><![CDATA[<p>Taverna is an open source domain independent Workflow Management System &ndash; a suite of tools used to design and execute scientific workflows. Taverna has been created by the myGrid project and is funded through a range of organisations and projects.</p>
<p>The Taverna suite is written in Java and includes the Taverna Engine(used for enacting workflows) that powers both the Taverna Workbench(the desktop client application) and the Taverna Server (which allows remote execution of workflows). Taverna is also available as a Command Line Tool for a quick execution of workflows from a terminal.</p><p>Address of the bookmark: <a href="http://www.taverna.org.uk/" rel="nofollow">http://www.taverna.org.uk/</a></p>]]></description>
	<dc:creator>Madhvan Reddy</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43398/waafle-a-workflow-to-annotate-assemblies-and-find-lgt-events</guid>
	<pubDate>Thu, 23 Sep 2021 14:31:06 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43398/waafle-a-workflow-to-annotate-assemblies-and-find-lgt-events</link>
	<title><![CDATA[WAAFLE: a Workflow to Annotate Assemblies and Find LGT Events.]]></title>
	<description><![CDATA[<p><span>Lateral gene transfer (LGT) is an important mechanism for genome diversification in microbial communities, including the human microbiome. While methods exist to identify LGTs from sequenced isolate genomes, identifying LGTs from community metagenomes remains an open problem. To address this, we developed&nbsp;</span><span>WAAFLE</span><span>: a&nbsp;</span><span>W</span><span>orkflow to&nbsp;</span><span>A</span><span>nnotate&nbsp;</span><span>A</span><span>ssemblies and&nbsp;</span><span>F</span><span>ind&nbsp;</span><span>L</span><span>GT&nbsp;</span><span>E</span><span>vents.</span></p><p>Address of the bookmark: <a href="http://huttenhower.sph.harvard.edu/waafle" rel="nofollow">http://huttenhower.sph.harvard.edu/waafle</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39720/snakemake-workflow-dna-seq-gatk-variant-calling</guid>
	<pubDate>Thu, 25 Jul 2019 12:55:07 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39720/snakemake-workflow-dna-seq-gatk-variant-calling</link>
	<title><![CDATA[Snakemake workflow: dna-seq-gatk-variant-calling]]></title>
	<description><![CDATA[<p><span>This Snakemake pipeline implements the&nbsp;</span><a href="https://software.broadinstitute.org/gatk/best-practices/workflow?id=11145">GATK best-practices workflow</a><span>&nbsp;for calling small genomic variants.</span></p><p>Address of the bookmark: <a href="https://github.com/snakemake-workflows/dna-seq-gatk-variant-calling" rel="nofollow">https://github.com/snakemake-workflows/dna-seq-gatk-variant-calling</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

</channel>
</rss>