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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/43384?offset=160</link>
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	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42038/pyparanoid-a-pipeline-for-rapid-identification-of-homologous-gene-families-in-a-set-of-genomes</guid>
	<pubDate>Thu, 13 Aug 2020 10:06:19 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42038/pyparanoid-a-pipeline-for-rapid-identification-of-homologous-gene-families-in-a-set-of-genomes</link>
	<title><![CDATA[PyParanoid: a pipeline for rapid identification of homologous gene families in a set of genomes]]></title>
	<description><![CDATA[<p>PyParanoid is a pipeline for rapid identification of homologous gene families in a set of genomes - a central task of any comparative genomics analysis. The "gold standard" for identifying homologs is to use reciprocal best hits (RBHs) which depends on performing a all-vs-all sequence comparison, usually using BLAST, to determine homology. However, these methods are computationally expensive, requiring&nbsp;O(n2)&nbsp;resources to identify RBHs. This is problematic, as the modern deluge of sequencing data means that comparative genomics analyses could be performed on datasets of thousands of strains.</p><p>Address of the bookmark: <a href="https://github.com/ryanmelnyk/PyParanoid" rel="nofollow">https://github.com/ryanmelnyk/PyParanoid</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43062/jcvi-utility-libraries</guid>
	<pubDate>Sat, 08 May 2021 22:04:02 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43062/jcvi-utility-libraries</link>
	<title><![CDATA[JCVI utility libraries]]></title>
	<description><![CDATA[<p><span>Collection of Python libraries to parse bioinformatics files, or perform computation related to assembly, annotation, and comparative genomics.</span></p><p>Address of the bookmark: <a href="https://github.com/tanghaibao/jcvi" rel="nofollow">https://github.com/tanghaibao/jcvi</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44375/phyloherb-a-high%E2%80%90throughput-phylogenomic-pipeline-for-processing-genome-skimming-data</guid>
	<pubDate>Wed, 06 Sep 2023 00:14:28 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44375/phyloherb-a-high%E2%80%90throughput-phylogenomic-pipeline-for-processing-genome-skimming-data</link>
	<title><![CDATA[PhyloHerb: A high‐throughput phylogenomic pipeline for processing genome skimming data]]></title>
	<description><![CDATA[<p dir="auto"><span>Phylo</span>genomic Analysis Pipeline for&nbsp;<span>Herb</span>arium Specimens</p>
<p dir="auto"><span>What is PhyloHerb</span>: PhyloHerb is a wrapper program to process&nbsp;<span>genome skimming</span>&nbsp;data collected from plant materials. The outcomes include the plastid genome (plastome) assemblies, mitochondrial genome assemblies, nuclear ribosomal DNAs (NTS+ETS+18S+ITS1+5.8S+ITS2+28S), alignments of gene and intergenic regions, and a species tree. It is designed to be a high throughput program dealing with lower quality data. Examples include&nbsp;<span>low-coverage (5x cpDNA) plastome phylogeny, recycling plastid genes from target enrichment data, retrieving low-copy nuclear genes from medium coverage (5x nucDNA) genome skimming</span>.</p>
<p dir="auto"><span>License</span>: GNU General Public License</p>
<p dir="auto"><span>Citation</span>:</p>
<ul dir="auto">
<li>Cai, Liming, Hongrui Zhang, and Charles C. Davis. 2022. PhyloHerb: A high‐throughput phylogenomic pipeline for processing genome‐skimming data. Applications in Plant Sciences 10(3): 1&ndash;9.&nbsp;<a href="https://doi.org/10.1002/aps3.11475">https://doi.org/10.1002/aps3.11475</a></li>
</ul><p>Address of the bookmark: <a href="https://github.com/lmcai/PhyloHerb/" rel="nofollow">https://github.com/lmcai/PhyloHerb/</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44597/imagine-in-silico-metagenomics-pipeline</guid>
	<pubDate>Sat, 06 Jul 2024 04:32:18 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44597/imagine-in-silico-metagenomics-pipeline</link>
	<title><![CDATA[iMAGine - in silico MetAGenomics pipeline]]></title>
	<description><![CDATA[<p dir="auto"><span>iMAGine</span>&nbsp;is a metagenomic workflow which includes filtering, assembling, and binning.</p>
<p dir="auto">This workflow includes the following tools which are needed to be installed in the system.</p>
<ol dir="auto">
<li><a href="https://github.com/OpenGene/fastp">fastp</a></li>
<li><a href="https://github.com/ablab/spades">spades assembler</a></li>
<li><a href="https://github.com/ablab/quast">QUAST</a></li>
<li><a href="https://github.com/lh3/bwa">bwa</a></li>
<li><a href="https://github.com/samtools/samtools">samtools</a></li>
<li><a href="https://bitbucket.org/berkeleylab/metabat/src/master/">metabat2</a></li>
<li><a href="https://github.com/Ecogenomics/CheckM">CheckM</a></li>
</ol><p>Address of the bookmark: <a href="https://github.com/avishekdutta14/iMAGine" rel="nofollow">https://github.com/avishekdutta14/iMAGine</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/21150/webinar-on-an-integrated-rna-and-dna-approach-to-unravel-genetic-regulation-in-cancer</guid>
	<pubDate>Wed, 11 Feb 2015 04:59:57 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/21150/webinar-on-an-integrated-rna-and-dna-approach-to-unravel-genetic-regulation-in-cancer</link>
	<title><![CDATA[Webinar on 'An integrated RNA and DNA approach to unravel genetic regulation in cancer']]></title>
	<description><![CDATA[<div><p><strong>Webinar on 'An integrated RNA and DNA approach to unravel genetic regulation in cancer'</strong></p><p><strong>Abstract</strong></p><p>Whole exome DNA sequencing (WES) or whole genome DNA sequencing (WGS) allows detection of mutations and polymorphisms in all exonic and genomic regions, respectively, while messenger RNA sequencing (RNA-Seq) enables quantitative analysis of gene expression. Mutations in the genome result in diverse transcriptional aberrations that can be missed in a stand-alone WES/WGS analysis. An integration of DNA variant analysis and RNA-Seq analysis enables one to investigate the consequences of genomic changes in the RNA transcripts including germline and somatic changes, imprinting, RNA editing and allele specific expression (ASE). In this webinar, we will demonstrate this integrated approach using Strand NGS to identify high confidence mutations, RNA editing events and ASE in cancer.</p><p><strong>Webinar Details</strong></p><table width="100%" border="1" cellspacing="0" cellpadding="0">
<tbody>
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<td valign="top">
<p style="text-align: center;"><br /> <strong>Sessions</strong></p>
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<p style="text-align: center;"><a href="http://www.strand-ngs.com/webinar_registration"><strong>San Francisco Time<br /> (PST)</strong></a></p>
</td>
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<p style="text-align: center;"><a href="http://www.strand-ngs.com/webinar_registration"><strong>Tokyo Time<br /> (GMT+09:00)</strong></a></p>
</td>
<td valign="top">
<p style="text-align: center;"><a href="http://www.strand-ngs.com/webinar_registration"><strong>Berlin Time<br /> (GMT+01:00)</strong></a></p>
</td>
<td valign="top">
<p style="text-align: center;"><a href="http://www.strand-ngs.com/webinar_registration"><strong>Mumbai Time<br /> (GMT+05:30)</strong></a></p>
</td>
</tr>
<tr>
<td>
<p style="text-align: center;"><a href="http://www.strand-ngs.com/webinar_registration"><strong>Session 1</strong></a></p>
</td>
<td valign="top">
<p style="text-align: center;">25 Feb&nbsp;<br /> 12:30 AM</p>
</td>
<td>
<p style="text-align: center;">25 Feb&nbsp;<br /> 5:30 PM</p>
</td>
<td>
<p style="text-align: center;">25 Feb&nbsp;<br /> 9:30 AM</p>
</td>
<td>
<p style="text-align: center;">25 Feb&nbsp;<br /> 2:00 PM</p>
</td>
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<tr>
<td valign="top">
<p style="text-align: center;"><a href="http://www.strand-ngs.com/webinar_registration"><strong>Session 2</strong></a></p>
</td>
<td valign="top">
<p style="text-align: center;">25 Feb&nbsp;<br /> 9:00 AM</p>
</td>
<td>
<p style="text-align: center;">26 Feb<br /> 2:00 AM</p>
</td>
<td>
<p style="text-align: center;">25 Feb&nbsp;<br /> 6:00 PM</p>
</td>
<td>
<p style="text-align: center;">25 Feb&nbsp;<br /> 10:30 PM</p>
</td>
</tr>
</tbody>
</table><p><strong style="font-size: 12.8000001907349px;">Register here: </strong><a href="http://www.strand-ngs.com/webinar_registration">http://www.strand-ngs.com/webinar_registration</a></p><p><strong>About Speaker:</strong></p><p>Dr. Veena Hedatale, has a PhD in Plant Genetics from The Radboud University, Netherlands focused on meiosis and recombination. Her prior academic experience at Cornell University was on genetic mapping and gene transformation in Rice. She has worked with Monsanto, and contributed to data mining, database development as well as gene/promoter/pathway discovery for traits related to yield and stress in crop species. At Strand, Veena has worked on Pharmacogenomic analysis of targets and Gene family analysis projects. Currently, she is part of the Strand NGS Application Science team and is involved in the analysis of next generation sequencing data.</p><p>Please feel free to contact us 24/5, for availing free online training or if you have any questions.</p></div><div><p><strong style="font-size: 12.8000001907349px;">Email:</strong> sales@strandngs.com</p><p><strong>Phone (USA):</strong> 1-800-752-9122</p><p><strong>Phone (ROW):</strong> +1-650-353-5060</p><p>&nbsp;</p></div>]]></description>
	<dc:creator>Yeshodari</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37233/rna-seq-analysis-workshop-course-materials</guid>
	<pubDate>Tue, 03 Jul 2018 08:14:14 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37233/rna-seq-analysis-workshop-course-materials</link>
	<title><![CDATA[RNA-seq Analysis Workshop Course Materials]]></title>
	<description><![CDATA[RNAseq can be roughly divided into two "types":

Reference genome-based - an assembled genome exists for a species for which an RNAseq experiment is performed. It allows reads to be aligned against the reference genome and significantly improves our ability to reconstruct transcripts. This category would obviously include humans and most model organisms but excludes the majority of truly biologically intereting species (e.g., Hyacinth macaw);

Reference genome-free - no genome assembly for the species of interest is available. In this case one would need to assemble the reads into transcripts using de novo approaches. This type of RNAseq is as much of an art as well as science because assembly is heavily parameter-dependent and difficult to do well.
In this lesson we will focus on the Reference genome-based type of RNA seq.

http://chagall.med.cornell.edu/RNASEQcourse/<p>Address of the bookmark: <a href="http://chagall.med.cornell.edu/RNASEQcourse/" rel="nofollow">http://chagall.med.cornell.edu/RNASEQcourse/</a></p>]]></description>
	<dc:creator>Jit</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>

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