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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/43806?offset=530</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36880/jvarkit-java-utilities-for-bioinformatics</guid>
	<pubDate>Fri, 08 Jun 2018 09:31:55 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36880/jvarkit-java-utilities-for-bioinformatics</link>
	<title><![CDATA[Jvarkit : Java utilities for Bioinformatics]]></title>
	<description><![CDATA[Collection of Java tool kits for bioinformatics works:

Jvarkit : Java utilities for Bioinformatics<p>Address of the bookmark: <a href="http://lindenb.github.io/jvarkit/" rel="nofollow">http://lindenb.github.io/jvarkit/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37257/asar-advanced-metagenomic-sequence-analysis-in-r</guid>
	<pubDate>Mon, 09 Jul 2018 05:20:50 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37257/asar-advanced-metagenomic-sequence-analysis-in-r</link>
	<title><![CDATA[ASAR: Advanced metagenomic Sequence Analysis in R]]></title>
	<description><![CDATA[<p><span>An interactive data analysis tool for selection, aggregation and visualization of metagenomic data is presented. Functional analysis with a SEED hierarchy and pathway diagram based on KEGG orthology based upon MG-RAST annotation results is available.</span></p>
<p><span><span>To read the manual, please click the link&nbsp;</span><a href="https://askarbek-orakov.github.io/ASAR/">https://askarbek-orakov.github.io/ASAR/</a></span></p><p>Address of the bookmark: <a href="https://github.com/Askarbek-orakov/ASAR" rel="nofollow">https://github.com/Askarbek-orakov/ASAR</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37984/baum-%E2%80%93-improving-genome-assembly-by-adaptive-unique-mapping-and-local-overlap-layout-consensus</guid>
	<pubDate>Wed, 24 Oct 2018 23:35:09 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37984/baum-%E2%80%93-improving-genome-assembly-by-adaptive-unique-mapping-and-local-overlap-layout-consensus</link>
	<title><![CDATA[BAUM – Improving Genome Assembly by Adaptive Unique Mapping and Local Overlap-Layout-Consensus]]></title>
	<description><![CDATA[<p><span>BAUM, breaks the whole genome into regions by adaptive unique mapping; then the local OLC is used to assemble each region in parallel. BAUM can: (1) perform reference-assisted assembly based on the genome of a close species; (2) or improve the results of existing assemblies that are obtained based on short or long sequencing reads.&nbsp;</span></p><p>Address of the bookmark: <a href="http://www.zhanyuwang.xin/wordpress/index.php/2017/07/21/baum-improving-genome-assembly-by-adaptive-unique-mapping-and-local-overlap-layout-consensus/" rel="nofollow">http://www.zhanyuwang.xin/wordpress/index.php/2017/07/21/baum-improving-genome-assembly-by-adaptive-unique-mapping-and-local-overlap-layout-consensus/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38316/simba-a-genome-assembly-project-management-system</guid>
	<pubDate>Thu, 29 Nov 2018 08:52:25 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38316/simba-a-genome-assembly-project-management-system</link>
	<title><![CDATA[SIMBA: a Genome Assembly Project Management System]]></title>
	<description><![CDATA[<p><span>SIMBA</span><span>, SImple Manager for Bacterial Assemblies, is a Web interface for managing assembly projects of bacterial genomes. SIMBA was created to assist bioinformaticians to assemble bacterial genomes sequenced with NextGeneration Sequencing (NGS) platforms quickly, easily and effectively. SIMBA also is open source tool, i.e., can be freely downloaded, shared and modified.</span></p><p>Address of the bookmark: <a href="http://ufmg-simba.sourceforge.net/" rel="nofollow">http://ufmg-simba.sourceforge.net/</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38735/genome-assembly-tutorial-genome-assembly-for-short-and-long-reads</guid>
	<pubDate>Sat, 19 Jan 2019 17:29:53 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38735/genome-assembly-tutorial-genome-assembly-for-short-and-long-reads</link>
	<title><![CDATA[Genome assembly tutorial &quot;Genome Assembly for short and long reads&quot;]]></title>
	<description><![CDATA[<p>In this lab we will perform de novo genome assembly of a bacterial genome. You will be guided through the genome assembly starting with data quality control, through to building contigs and analysis of the results. At the end of the lab you will know:</p>
<ol>
<li>How to perform basic quality checks on the input data</li>
<li>How to run a short read assembler on Illumina data</li>
<li>How to run a long read assembler on Pacific Biosciences or Oxford Nanopore data</li>
<li>How to improve the accuracy of a long read assembly using short reads</li>
<li>How to assess the quality of an assembly</li>
</ol>
<p>https://bioinformaticsdotca.github.io/high-throughput_biology_2017</p><p>Address of the bookmark: <a href="https://bioinformaticsdotca.github.io/high-throughput_biology_2017_module6_lab" rel="nofollow">https://bioinformaticsdotca.github.io/high-throughput_biology_2017_module6_lab</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39250/darwin-wga-a-co-processor-provides-increased-sensitivity-in-whole-genome-alignments-with-high-speedup</guid>
	<pubDate>Sat, 13 Apr 2019 08:55:31 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39250/darwin-wga-a-co-processor-provides-increased-sensitivity-in-whole-genome-alignments-with-high-speedup</link>
	<title><![CDATA[Darwin-WGA: A Co-processor Provides Increased Sensitivity in Whole Genome Alignments with High Speedup]]></title>
	<description><![CDATA[<p>Darwin-WGA, is the first hardware accelerator for whole genome alignment and accelerates the gapped filtering stage. Darwin-WGA also employs GACT-X, a novel algorithm used in the extension stage to align arbitrarily long genome sequences using a small on-chip memory, that provides better quality alignments at 2&times; improvement in memory and speed over the previously published GACT algorithm. Implemented on an FPGA, Darwin-WGA provides up to 24&times; improvement (performance/$) in WGA over iso-sensitive software.</p>
<p><a href="https://stanford.edu/~yatisht/pubs/darwin-wga.pdf">https://stanford.edu/~yatisht/pubs/darwin-wga.pdf</a></p><p>Address of the bookmark: <a href="https://github.com/gsneha26/Darwin-WGA" rel="nofollow">https://github.com/gsneha26/Darwin-WGA</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40549/mgse-mapping-based-genome-size-estimation</guid>
	<pubDate>Fri, 17 Jan 2020 02:11:43 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40549/mgse-mapping-based-genome-size-estimation</link>
	<title><![CDATA[MGSE: Mapping-based Genome Size Estimation]]></title>
	<description><![CDATA[<p>MGSE can harness the power of files generated in genome sequencing projects to predict the genome size. Required are the FASTA file containing a high continuity assembly and a BAM file with all available reads mapped to this assembly. The script construct_cov_file.py (https://doi.org/10.1186/s12864-018-5360-z) allows the generation of a COV file based on the (sorted) BAM file (also possible via MGSE directly). Next, this COV file can be used by MGSE to calculate the coverage in provided reference regions and to calculate the total number of mapped bases. Both values are subjected to the genome size estimation. Providing accurate reference regions is crucial for this genome size estimation.</p><p>Address of the bookmark: <a href="https://github.com/bpucker/MGSE" rel="nofollow">https://github.com/bpucker/MGSE</a></p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41330/u-plot-genome-u-plot-sample-implementation</guid>
	<pubDate>Tue, 03 Mar 2020 01:39:12 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41330/u-plot-genome-u-plot-sample-implementation</link>
	<title><![CDATA[U-Plot: Genome U-Plot sample implementation]]></title>
	<description><![CDATA[<p>The Genome U-Plot is a JavaScript tool to visualize Chromosomal abnormalities in the Human Genome using a U-shape layout.</p>
<p><img src="https://raw.githubusercontent.com/gaitat/GenomeUPlot/master/public/data/LNCAP.png" alt="image" style="border: 0px;"></p><p>Address of the bookmark: <a href="https://github.com/gaitat/GenomeUPlot" rel="nofollow">https://github.com/gaitat/GenomeUPlot</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42497/genome-assembly-training-tutorial-at-galaxy</guid>
	<pubDate>Sun, 27 Dec 2020 05:25:45 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42497/genome-assembly-training-tutorial-at-galaxy</link>
	<title><![CDATA[Genome assembly training tutorial at Galaxy !]]></title>
	<description><![CDATA[<p>In this tutorial we assemble and annotate the genome of <em>E. coli</em> strain <a href="http://cgsc2.biology.yale.edu/Strain.php?ID=8232">C-1</a>. This strain is routinely used in experimental evolution studies involving bacteriophages. For instance, now classic works by Holly Wichman and Jim Bull (<a href="https://training.galaxyproject.org/training-material/topics/assembly/tutorials/unicycler-assembly/tutorial.html#Bull1997">Bull 1997</a>, <a href="https://training.galaxyproject.org/training-material/topics/assembly/tutorials/unicycler-assembly/tutorial.html#Bull1998">Bull 1998</a>, <a href="https://training.galaxyproject.org/training-material/topics/assembly/tutorials/unicycler-assembly/tutorial.html#Wichman1999">Wichman 1999</a>) have been performed using this strain and bacteriophage phiX174.</p><p>Address of the bookmark: <a href="https://training.galaxyproject.org/training-material/topics/assembly/tutorials/unicycler-assembly/tutorial.html" rel="nofollow">https://training.galaxyproject.org/training-material/topics/assembly/tutorials/unicycler-assembly/tutorial.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43110/quasimodo-quasispecies-metric-determination-on-omics</guid>
	<pubDate>Sat, 26 Jun 2021 15:22:56 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43110/quasimodo-quasispecies-metric-determination-on-omics</link>
	<title><![CDATA[QuasiModo - Quasispecies Metric Determination on Omics]]></title>
	<description><![CDATA[<p><span>This repository contains the scripts and pipeline that reproduces the results of the HCMV benchmarking study. In this study we evaluated genome assemblers and variant callers on 10 in vitro generated, mixed strain HCMV sequence samples, each consisting of two lab strains in different abundance ratios. This tool can also be used to evaluate assemblies and variant calling results on other similar datasets.</span></p>
<p><span>https://academic.oup.com/bib/article/22/3/bbaa123/5868070</span></p><p>Address of the bookmark: <a href="https://github.com/hzi-bifo/Quasimodo" rel="nofollow">https://github.com/hzi-bifo/Quasimodo</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>

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