<?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/12944?offset=840</link>
	<atom:link href="https://bioinformaticsonline.com/related/12944?offset=840" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/29407/live-webinar-on-rna-seq-data-analysis-on-9-nov-2016</guid>
	<pubDate>Wed, 19 Oct 2016 05:25:27 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/29407/live-webinar-on-rna-seq-data-analysis-on-9-nov-2016</link>
	<title><![CDATA[Live Webinar on RNA-Seq Data Analysis on 9 Nov 2016]]></title>
	<description><![CDATA[<p><strong><a href="http://www.strand-ngs.com/webinar_registration">Live Webinar on RNA-Seq Data Analysis</a></strong></p><p><a href="http://www.strand-ngs.com/webinar_registration">Abstract: </a>Strand NGS supports an extensive workflow for the analysis and visualization of RNA-Seq data. The workflow includes Transcriptome / Genome alignment, Differential expression analysis with Statistical approach and Splicing events detection. Strand NGS also supports novel discovery like identification of novel genes, exons and Novel splice junctions, alongside it can also detect gene fusion events. Further downstream analysis such as GO and pathway analysis can be performed on the set of interesting genes. The product has an option to create pipelines for time consuming jobs which automates analysis and leaves more time for end data interpretation. This webinar will give an overview of the features in the RNA-Seq data analysis workflow in Strand NGS and also highlights on parameters within each feature that can be optimized depending on datasets and analysis needs.</p><p><a href="http://www.strand-ngs.com/webinar_registration">Speaker:</a> Mr. Sugandan Sivamani, Senior Application Scientist, Strand Life Sciences</p><p>Date: 9th Nov, <a href="http://www.strand-ngs.com/webinar_registration">Session 1</a> for SAPK/ APFO: 2:30 PM IST Date: 9th Nov, <a href="http://www.strand-ngs.com/webinar_registration">Session 2</a> for AFO/ EMEA: 9:00 AM PST</p><p>Register here <a href="http://www.strand-ngs.com/webinar_registration">http://www.strand-ngs.com/webinar_registration</a></p>]]></description>
	<dc:creator>Strand</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/33486/quick-next-generation-sequencing-ngs-terms-definition</guid>
	<pubDate>Fri, 09 Jun 2017 04:52:26 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/33486/quick-next-generation-sequencing-ngs-terms-definition</link>
	<title><![CDATA[Quick next generation sequencing (NGS) terms definition]]></title>
	<description><![CDATA[<p><strong>fragment size:</strong><span>&nbsp;the Illumina WGS protocol generates paired-end reads from both ends of longer fragments. The lengths of these fragments are assumed to be sampled from a normal distribution. Therefore, in the absence of structural variants, mapping locations of the paired ends span within an interval [&delta;min,&delta;max]. Most (&gt;90%) of paired-end reads are sampled from no-SV regions, therefore the fragment size distribution can be learned empirically for each WGS data set separately.</span><br /><br /><strong>concordant reads:</strong><span>&nbsp;a read pair is called concordant if they can be mapped to the reference genome as &ldquo;expected&rdquo;: (a) mapped to opposing strands where the upstream read is mapped to the forward strand and the downstream read is mapped to the reverse strand2, (b) the distance between ends is between the minimum and maximum expected fragment size.</span><br /><br /><strong>discordant reads:</strong><span>&nbsp;briefly, any non-concordant read pair is considered discordant. Note that, by definition, the discordant read pairs signal potential SVs. The sequence signature produced by these type of reads is known as read-pair signature.</span><br /><br /><strong>split reads:</strong><span>&nbsp;a read that can only be mapped to the reference genome by breaking into two sub-reads is called a split-read. These types of reads also indicate a potential SV or a short insertion or deletion (indel).</span><br /><br /><strong>read depth:</strong><span>&nbsp;number of reads that map within a region of the genome. Overall genome-wide read depth is also referred to as depth of coverage. It is expected that the number of reads that &ldquo;cover&rdquo; each base-pair to follow a Poisson distribution. Therefore, if the read depth over a certain region deviates significantly from this distribution, it signals for a potential copy number variation (CNV).</span></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35571/medusa-a-multi-draft-based-scaffolder</guid>
	<pubDate>Wed, 14 Feb 2018 02:49:00 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35571/medusa-a-multi-draft-based-scaffolder</link>
	<title><![CDATA[MeDuSa: a multi-draft based scaffolder]]></title>
	<description><![CDATA[<p><span>MeDuSa (Multi-Draft based Scaffolder), an algorithm for genome scaffolding. MeDuSa exploits information obtained from a set of (draft or closed) genomes from related organisms to determine the correct order and orientation of the contigs. MeDuSa formalises the scaffolding problem by means of a combinatorial optimisation formulation on graphs and implements an efficient constant factor approximation algorithm to solve it. In contrast to currently used scaffolders, it does not require either prior knowledge on the microrganisms dataset under analysis (e.g. their phylogenetic relationships) or the availability of paired end read libraries.&nbsp;</span></p><p>Address of the bookmark: <a href="https://github.com/combogenomics/medusa" rel="nofollow">https://github.com/combogenomics/medusa</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36812/porechop-tool-for-finding-and-removing-adapters-from-oxford-nanopore-reads</guid>
	<pubDate>Tue, 29 May 2018 07:33:44 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36812/porechop-tool-for-finding-and-removing-adapters-from-oxford-nanopore-reads</link>
	<title><![CDATA[Porechop:  tool for finding and removing adapters from Oxford Nanopore reads]]></title>
	<description><![CDATA[<p>Porechop is a tool for finding and removing adapters from <a href="https://nanoporetech.com/">Oxford Nanopore</a> reads. Adapters on the ends of reads are trimmed off, and when a read has an adapter in its middle, it is treated as chimeric and chopped into separate reads. Porechop performs thorough alignments to effectively find adapters, even at low sequence identity.</p>
<p>Porechop also supports demultiplexing of Nanopore reads that were barcoded with the <a href="https://store.nanoporetech.com/native-barcoding-kit-1d.html">Native Barcoding Kit</a>, <a href="https://store.nanoporetech.com/pcr-barcoding-kit-96.html">PCR Barcoding Kit</a> or <a href="https://store.nanoporetech.com/rapid-barcoding-sequencing-kit.html">Rapid Barcoding Kit</a>.</p><p>Address of the bookmark: <a href="https://github.com/rrwick/Porechop" rel="nofollow">https://github.com/rrwick/Porechop</a></p>]]></description>
	<dc:creator>Rahul Nayak</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/blog/view/11592/xampp-starting-apache-fail-ubuntu</guid>
	<pubDate>Sat, 07 Jun 2014 05:52:35 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/11592/xampp-starting-apache-fail-ubuntu</link>
	<title><![CDATA[XAMPP: Starting Apache fail Ubuntu]]></title>
	<description><![CDATA[<p>Once you install XAMMP on linux, the most common problem you face is Apache failure. To fix the issues please use following command to first stop and then again start it.</p><p>sudo /etc/init.d/apache2 stop</p><p>sudo /etc/init.d/mysql stop</p><p>sudo /etc/init.d/proftpd stop</p><p>sudo /opt/lampp/lampp start</p><p>&nbsp;</p><p><strong>PhpMyAdmin &ldquo;Wrong permissions on configuration file, should not be world writable!&rdquo;</strong></p><p>Once the Xammp is installed, it might be possible to set up the configuration file in writable mode. Try the following steps:</p><p>Just chmod 0755 the file</p><pre>sudo chmod 0755 config.inc.php</pre>]]></description>
	<dc:creator>Ram Yash Pal</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/28051/convert-ensembl-gtf-to-annotation-table-geneid-genesymbol-genewisechrlocation-geneclass-strand-raw</guid>
	<pubDate>Fri, 24 Jun 2016 18:08:49 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/28051/convert-ensembl-gtf-to-annotation-table-geneid-genesymbol-genewisechrlocation-geneclass-strand-raw</link>
	<title><![CDATA[Convert EnsEMBL GTF to Annotation table (Geneid, GeneSymbol, GeneWiseChrLocation, GeneClass, Strand) Raw]]></title>
	<description><![CDATA[<p><strong>Bash Script source:</strong></p><p>https://gist.github.com/santhilalsubhash/367befcf5216be4b1fd9</p><p>&nbsp;</p><p><strong>Information</strong>:</p><p>This script converts EnsEMBL GTF (Ex:&nbsp;<a href="https://gist.githubusercontent.com/santhilalsubhash/1e7cca357e52a181dc25/raw/cfb803e07900a2baefbb6534f1299fd30cb57a29/sample.GTF">https://gist.githubusercontent.com/santhilalsubhash/1e7cca357e52a181dc25/raw/cfb803e07900a2baefbb6534f1299fd30cb57a29/sample.GTF</a>) file to annotation table format. It generated two files<br />1) Transcript wise chromosome location with information about transcripts (Ex:&nbsp;<a href="https://gist.githubusercontent.com/santhilalsubhash/c7dec516e0338503a4b6/raw/de0af1a39f0005c4ce7321c5ae57fc8b4a14c7f4/sample.GTF_enst_annotation.txt">https://gist.githubusercontent.com/santhilalsubhash/c7dec516e0338503a4b6/raw/de0af1a39f0005c4ce7321c5ae57fc8b4a14c7f4/sample.GTF_enst_annotation.txt</a>)<br />2) Gene wise chromosome location with information about genes (Ex:&nbsp;<a href="https://gist.githubusercontent.com/santhilalsubhash/c92006c5080f0333bec2/raw/d16e0b2440d73b09b486d3c9751cdb248a73fa0b/sample.GTF_ensg_annotation.txt">https://gist.githubusercontent.com/santhilalsubhash/c92006c5080f0333bec2/raw/d16e0b2440d73b09b486d3c9751cdb248a73fa0b/sample.GTF_ensg_annotation.txt</a>)</p><p>Note: You can download GTF files from&nbsp;<a href="http://www.ensembl.org/info/data/ftp/index.html">http://www.ensembl.org/info/data/ftp/index.html</a></p>]]></description>
	<dc:creator>EagleEye</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/file/view/37581/comparativegenomics-exercise2</guid>
	<pubDate>Wed, 22 Aug 2018 22:10:56 -0500</pubDate>
	<link>https://bioinformaticsonline.com/file/view/37581/comparativegenomics-exercise2</link>
	<title><![CDATA[ComparativeGenomics Exercise2]]></title>
	<description><![CDATA[<p>COMPARATIVE MICROBIAL GENOMICS ANALYSIS WORKSHOP&nbsp; @&nbsp;cbs.dtu.dk</p><p>Free Bioinformatics workbench https://www.mn.uio.no/ifi/english/research/networks/clsi/earlier_seminars/2012/tammivesth_osloseminarfinal.pdf</p>]]></description>
	<dc:creator>Neel</dc:creator>
	<enclosure url="https://bioinformaticsonline.com/file/download/37581" length="139956" type="application/pdf" />
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37957/base-a-practical-de-novo-assembler-for-large-genomes-using-long-ngs-reads</guid>
	<pubDate>Fri, 19 Oct 2018 07:25:21 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37957/base-a-practical-de-novo-assembler-for-large-genomes-using-long-ngs-reads</link>
	<title><![CDATA[BASE: a practical de novo assembler for large genomes using long NGS reads]]></title>
	<description><![CDATA[<p><span>new&nbsp;</span><em>de novo</em><span>&nbsp;assembler called BASE. It enhances the classic seed-extension approach by indexing the reads efficiently to generate adaptive seeds that have high probability to appear uniquely in the genome. Such seeds form the basis for BASE to build extension trees and then to use reverse validation to remove the branches based on read coverage and paired-end information, resulting in high-quality consensus sequences of reads sharing the seeds. Such consensus sequences are then extended to contigs.</span></p><p>Address of the bookmark: <a href="https://github.com/dhlbh/BASE" rel="nofollow">https://github.com/dhlbh/BASE</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/14215/the-8000-years-old-tibetian-gene-mutation</guid>
	<pubDate>Wed, 20 Aug 2014 21:57:44 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/14215/the-8000-years-old-tibetian-gene-mutation</link>
	<title><![CDATA[The 8000 years old Tibetian gene mutation !!!]]></title>
	<description><![CDATA[<p>A new study has provided insight into how gene mutation around 8,000 years ago helped Tibetans' to survive in the thin air on the Tibetan Plateau, where an average elevation is of 14,800 feet.<br /><br />A study led by University of Utah scientists is the first to find a genetic cause for the adaptation, a single DNA base pair change that dates back 8,000 years and demonstrate how it contributes to the Tibetans' ability to live in low oxygen conditions.</p><p>About 8,000 years ago, the gene EGLN1 changed by a single DNA base pair. Today, a relatively short time later on the scale of human history, 88 percent of Tibetans have the genetic variation, and it was virtually absent from closely related lowland Asians. The findings indicate the genetic variation endows its carriers with an advantage.<br /><br />In those without the adaptation, low oxygen caused their blood to become thick with oxygen-carrying red blood cells, an attempt to feed starved tissues, which could cause long-term complications such as heart failure. The researchers found that the newly identified genetic variation protected Tibetans by decreasing the over-response to low oxygen.</p><p>Reference: http://www.nature.com/nature/journal/v512/n7513/abs/nature13408.html</p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>

</channel>
</rss>