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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/42941?offset=90</link>
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	<description><![CDATA[]]></description>
	
	<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/bookmarks/view/41686/catbat-tool-for-taxonomic-classification-of-contigs-and-metagenome-assembled-genomes-mags</guid>
	<pubDate>Mon, 18 May 2020 10:53:32 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41686/catbat-tool-for-taxonomic-classification-of-contigs-and-metagenome-assembled-genomes-mags</link>
	<title><![CDATA[CAT/BAT: tool for taxonomic classification of contigs and metagenome-assembled genomes (MAGs)]]></title>
	<description><![CDATA[<p>Contig Annotation Tool (CAT) and Bin Annotation Tool (BAT) are pipelines for the taxonomic classification of long DNA sequences and metagenome assembled genomes (MAGs/bins) of both known and (highly) unknown microorganisms, as generated by contemporary metagenomics studies. The core algorithm of both programs involves gene calling, mapping of predicted ORFs against the nr protein database, and voting-based classification of the entire contig / MAG based on classification of the individual ORFs. CAT and BAT can be run from intermediate steps if files are formated appropriately (see <a href="https://github.com/dutilh/CAT#usage">Usage</a>).</p><p>Address of the bookmark: <a href="https://github.com/dutilh/CAT" rel="nofollow">https://github.com/dutilh/CAT</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42357/irscope-an-online-program-to-visualize-the-junction-sites-of-chloroplast-genomes</guid>
	<pubDate>Wed, 25 Nov 2020 19:44:46 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42357/irscope-an-online-program-to-visualize-the-junction-sites-of-chloroplast-genomes</link>
	<title><![CDATA[IRscope: an online program to visualize the junction sites of chloroplast genomes]]></title>
	<description><![CDATA[<p><span>eMPRess, a software program for phylogenetic tree reconciliation under the duplication-transfer-loss model that systematically addresses the problems of choosing event costs and selecting representative solutions, enabling users to make more robust inferences.</span></p><p>Address of the bookmark: <a href="https://sites.google.com/g.hmc.edu/empress/home" rel="nofollow">https://sites.google.com/g.hmc.edu/empress/home</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36271/heap-a-highly-sensitive-and-accurate-snp-detection-tool-for-low-coverage-high-throughput-sequencing-data</guid>
	<pubDate>Thu, 19 Apr 2018 08:06:03 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36271/heap-a-highly-sensitive-and-accurate-snp-detection-tool-for-low-coverage-high-throughput-sequencing-data</link>
	<title><![CDATA[Heap: a highly sensitive and accurate SNP detection tool for low-coverage high-throughput sequencing data]]></title>
	<description><![CDATA[<p><span>Heap, that enables robustly sensitive and accurate calling of SNPs, particularly with a low coverage NGS data, which must be aligned to the reference genome sequences in advance. To reduce false positive SNPs, Heap determines genotypes and calls SNPs at each site except for sites at the both end of reads or containing a minor allele supported by only one read. Performance comparison with existing tools showed that Heap achieved the highest F-scores with low coverage (7X) restriction-site associated DNA sequencing reads of sorghum and rice individuals. This will facilitate cost-effective GWAS and GP studies in this NGS era. Code and documentation of Heap are freely available from&nbsp;</span><a href="https://github.com/meiji-bioinf/heap">https://github.com/meiji-bioinf/heap</a><span>&nbsp;and our web site (</span><a href="http://bioinf.mind.meiji.ac.jp/lab/en/tools.html">http://bioinf.mind.meiji.ac.jp/lab/en/tools.html</a><span>).</span></p><p>Address of the bookmark: <a href="https://github.com/meiji-bioinf/heap" rel="nofollow">https://github.com/meiji-bioinf/heap</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/3868/next-generation-sequencing-ngs-tutorials</guid>
	<pubDate>Sat, 24 Aug 2013 06:01:37 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/3868/next-generation-sequencing-ngs-tutorials</link>
	<title><![CDATA[Next Generation Sequencing (NGS) Tutorials]]></title>
	<description><![CDATA[<p>Institute of computational biomedicine, Cornell University provide an NGS workshop tutorial at&nbsp;<a href="http://chagall.med.cornell.edu/NGScourse/">http://chagall.med.cornell.edu/NGScourse/</a>&nbsp;</p>
<p>You can also add your favourite NGS educational material, or workshop tutorial by commenting on this bookmarks for user benefit.&nbsp;</p>
<p>Understanding the basics of genome sequencing:</p>
<p>Tutorial by Luke Jostins.</p>
<p>http://www.genetic-inference.co.uk/blog/2009/04/basics-sequencing-dna-part-1/</p>
<p>http://www.genetic-inference.co.uk/blog/2009/08/basics-sequencing-dna-part-2/</p>
<p>A window into third-generation sequencing</p>
<p>http://hmg.oxfordjournals.org/content/19/R2/R227.full.pdf</p>
<p>==============================================</p>
<p>NGS data analysis pipelines</p>
<ul>
<li><strong>Detecting and annotating genetic variations using the HugeSeq pipeline</strong>&nbsp; DOI: <a href="http://dx.doi.org/10.1038/nbt.2134">10.1038/nbt.2134</a></li>
<li><strong> NARWHAL, a primary analysis pipeline for NGS data</strong> <a href="http://bioinformatics.oxfordjournals.org/cgi/content/abstract/28/2/284?etoc">http://bioinformatics.oxfordjournals.org/cgi/content/abstract/28/2/284?etoc</a></li>
<li><strong>RseqFlow: Workflows for RNA-Seq data analysis</strong>&nbsp; DOI: <a href="http://dx.doi.org/10.1093/bioinformatics/btr441">10.1093/bioinformatics/btr441</a></li>
<li><strong>ngs_backbone: a pipeline for read cleaning, mapping and SNP calling using Next Generation Sequence</strong>&nbsp;&nbsp;<a href="http://dx.doi.org/10.1186/1471-2164-12-285">10.1186/1471-2164-12-285</a></li>
<li><strong>A framework for variation discovery and genotyping using next-generation DNA sequencing data</strong>&nbsp; PubMed: <a href="http://www.ncbi.nlm.nih.gov/pubmed/21478889">21478889</a></li>
<li><strong>SNiPlay: a web-based tool for detection, management and analysis of SNPs. Application to grapevine diversity projects</strong>&nbsp; DOI: <a href="http://dx.doi.org/10.1186/1471-2105-12-134">10.1186/1471-2105-12-134</a> Abstract: <a href="http://www.biomedcentral.com/1471-2105/12/134/abstract">http://www.biomedcentral.com/1471-2105/12/134/abstract</a></li>
<li><strong>WEP: a high-performance analysis pipeline for whole-exome data&nbsp;</strong>http://www.biomedcentral.com/1471-2105/14/S7/S11</li>
<li><strong>DDBJ read annotation pipeline: a cloud computing-based pipeline for high-throughput analysis of next-generation sequencing data.&nbsp;</strong>http://www.ncbi.nlm.nih.gov/pubmed/23657089</li>
<li><strong>GATK: a Toolkit for Genome Analysis&nbsp;</strong>http://www.broadinstitute.org/gatk/</li>
<li><strong>Metagenomics</strong>:http://www.nbic.nl/education/nbic-phd-school/course-schedule/ngsmetagenomics/</li>
<li><strong>RNASeq</strong>:http://www.nbic.nl/education/nbic-phd-school/course-schedule/ngsrnaseq/</li>
<li><strong>Bioinformatics and Seq courses</strong>:&nbsp;http://www.isb-sib.ch/training/training-activities-schedule/archive-2013.html</li>
<li><strong>Variant Detection (Model organism) Advanced tutorial</strong> https://docs.google.com/document/pub?id=1CuKkKylVDb03tnN7RSWl5EUzleetn0ctjmvaidPKLxM</li>
<li><strong>Variant Detection Introductory tutorial</strong> https://docs.google.com/document/pub?id=1ZRzrjjOCvtAu3m-IKL-rbJ1f4On60dDL_IEwG7oejdI</li>
<li><strong>Microbial de novo Assembly for Illumina Data Introductory tutorial</strong> https://docs.google.com/document/pub?id=1N3AB9ptISUu4zULqe1kXpVF0BDyGb5f5yzxWSJd_WNM</li>
<li><strong>RNAseq Differential Gene Expression Introductory tutorial</strong> https://docs.google.com/document/pub?id=1KbTiBHtvHLfPRZ39AY3uriazrINA8TJzgjjwn1zPP7Y</li>
</ul>
<blockquote>
<p>" Please add your favourite NGS link below in comment section for the benefit of bioinformatics community ".&nbsp;</p>
</blockquote><p>Address of the bookmark: <a href="http://chagall.med.cornell.edu/NGScourse/" rel="nofollow">http://chagall.med.cornell.edu/NGScourse/</a></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/28844/teannot</guid>
	<pubDate>Thu, 18 Aug 2016 10:02:03 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/28844/teannot</link>
	<title><![CDATA[TEannot]]></title>
	<description><![CDATA[<p>We advise to run first the TEdenovo pipeline but it is not compulsory. We suppose you begin by running the TEannot pipeline on the example provided in the directory "db/" rather than directly on your own genomic sequences. Thus, from now on, the project name is "DmelChr4".</p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="https://urgi.versailles.inra.fr/Tools/REPET/TEannot-tuto" rel="nofollow">https://urgi.versailles.inra.fr/Tools/REPET/TEannot-tuto</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36632/tulip-the-uncorrected-long-read-integration-pipeline</guid>
	<pubDate>Tue, 15 May 2018 09:06:37 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36632/tulip-the-uncorrected-long-read-integration-pipeline</link>
	<title><![CDATA[TULIP - The Uncorrected Long read Integration Pipeline]]></title>
	<description><![CDATA[TULIP currently consists of two Perl scripts, tulipseed.perl and tulipbulb.perl. These are very much intended as prototypes, and additional components and/or implementations are likely to follow.

Tulipseed takes as input alignments files of long reads to sparse short seeds, and outputs a graph and scaffold structures.<p>Address of the bookmark: <a href="https://github.com/Generade-nl/TULIP" rel="nofollow">https://github.com/Generade-nl/TULIP</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39903/integrative-meta-assembly-pipeline-imap-chromosome-level-genome-assembler-combining-multiple-de-novo-assemblies</guid>
	<pubDate>Sat, 31 Aug 2019 11:30:41 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39903/integrative-meta-assembly-pipeline-imap-chromosome-level-genome-assembler-combining-multiple-de-novo-assemblies</link>
	<title><![CDATA[Integrative Meta-Assembly Pipeline (IMAP): Chromosome-level genome assembler combining multiple de novo assemblies]]></title>
	<description><![CDATA[<p><span>Chromosome-level genome assembler combining multiple de novo assemblies</span></p>
<p><span><a href="https://github.com/jkimlab/IMAP">https://github.com/jkimlab/IMAP</a></span></p><p>Address of the bookmark: <a href="https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0221858" rel="nofollow">https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0221858</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44591/yamp-yet-another-metagenomic-pipeline</guid>
	<pubDate>Sat, 06 Jul 2024 04:26:00 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44591/yamp-yet-another-metagenomic-pipeline</link>
	<title><![CDATA[YAMP: Yet Another Metagenomic Pipeline]]></title>
	<description><![CDATA[<p><span>YAMP is constructed on&nbsp;</span><a href="https://www.nextflow.io/docs/latest/index.html">Nextflow</a><span>, a framework based on the dataflow programming model, which allows writing workflows that are highly parallel, easily portable (including on distributed systems), and very flexible and customisable, characteristics which have been inherited by YAMP. New modules can be added easily and the existing ones can be customised -- even though we have already provided default parameters deriving from our own experience.</span></p><p>Address of the bookmark: <a href="https://github.com/alesssia/YAMP" rel="nofollow">https://github.com/alesssia/YAMP</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/26290/webinar-on-streamlining-large-scale-analysis-using-the-strand-ngs-pipeline-manager-on-24-feb-2016</guid>
	<pubDate>Fri, 05 Feb 2016 06:43:28 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/26290/webinar-on-streamlining-large-scale-analysis-using-the-strand-ngs-pipeline-manager-on-24-feb-2016</link>
	<title><![CDATA[Webinar on Streamlining large scale analysis using the Strand NGS Pipeline Manager on 24 Feb 2016]]></title>
	<description><![CDATA[<p><a href="http://www.strand-ngs.com/webinar_registration" title="webinar"><strong>Live Webinar on Streamlining large scale NGS data analysis using the Strand NGS Pipeline Manager on 24 Feb 2016</strong></a></p><p><strong>Abstract:</strong> Strand NGS includes comprehensive workflows for DNA-Seq, RNA-Seq, Small RNA-Seq, ChIP-Seq, MeDIP-Seq, and Methyl-Seq analysis. Each workflow includes a quality assessment and filter section, followed by a workflow-specific analysis section. The pipeline functionality in Strand NGS allows users to execute a sequence of analysis steps with specific parameters - all without any manual intervention. This simplifies the analysis in large scale sequencing projects where every sample needs to be processed identically.</p><p>In this webinar we will discuss the pre-packaged pipelines present in Strand NGS. The packaged pipelines have well-chosen default parameters and are suitable for users analyzing data for the first time in the tool. We will also show how advanced users can customize pipelines and share them with other Strand NGS users. Finally, we will show a brief glimpse of an elaborate pipeline that aligns reads, filters poor-quality matches, computes coverage metrics, identifies variants, checks for sample cross-contamination, and emails quality reports - all from within Strand NGS.</p><p><strong>Speaker:</strong> Dr. Vamsi Veeramachaneni, Vice President - Bioinformatics, Strand Life Sciences</p><p><strong>Details:</strong> Session 1: 2:30 PM IST, Session 2 : 10:30 PM IST<br /><strong>Register here:</strong> http://www.strand-ngs.com/webinar_registration</p><h3>&nbsp;</h3>]]></description>
	<dc:creator>Yeshodari</dc:creator>
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