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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/34216?offset=30</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37650/p-rna-scaffolder-a-fast-and-accurate-genome-scaffolder-using-paired-end-rna-sequencing-reads</guid>
	<pubDate>Fri, 07 Sep 2018 05:19:06 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37650/p-rna-scaffolder-a-fast-and-accurate-genome-scaffolder-using-paired-end-rna-sequencing-reads</link>
	<title><![CDATA[P_RNA_scaffolder: a fast and accurate genome scaffolder using paired-end RNA-sequencing reads]]></title>
	<description><![CDATA[<p><span>P_RNA_scaffolder is a novel scaffolding tool using Pair-end RNA-seq to scaffold genome fragments. The method is suitable for most genomes. The program could utilize Illumina Paired-end RNA-sequencing reads from target speciesies. Our method provides another practical alternative to existing mate-pair_based approaches or other Protein-based approaches (for instance,&nbsp;</span><a href="http://www.fishbrowser.org/software/PEP_scaffolder/">PEP_scaffolder&nbsp;</a><span>) for scaffolding genome sequences. The most important feature of this method is to improve the completeness of gene regions and long-coding gene regions (for instance,&nbsp;</span><a href="http://circrna.org/">circRNA</a><span>).</span></p><p>Address of the bookmark: <a href="http://www.fishbrowser.org/software/P_RNA_scaffolder/#" rel="nofollow">http://www.fishbrowser.org/software/P_RNA_scaffolder/#</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43254/quasr-quantification-and-annotation-of-short-reads-in-r</guid>
	<pubDate>Fri, 13 Aug 2021 07:44:05 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43254/quasr-quantification-and-annotation-of-short-reads-in-r</link>
	<title><![CDATA[QuasR: Quantification and annotation of short reads in R]]></title>
	<description><![CDATA[<p>The <em><a href="https://bioconductor.org/packages/3.14/QuasR">QuasR</a></em> package (short for <em>Qu</em>antify and <em>a</em>nnotate <em>s</em>hort reads in <em>R</em>) integrates the functionality of several <strong>R</strong> packages (such as <em><a href="https://bioconductor.org/packages/3.14/IRanges">IRanges</a></em> <span>(Lawrence et al. 2013)</span> and <em><a href="https://bioconductor.org/packages/3.14/Rsamtools">Rsamtools</a></em>) and external software (e.g.&nbsp;<code>bowtie</code>, through the <em><a href="https://bioconductor.org/packages/3.14/Rbowtie">Rbowtie</a></em> package, and <code>HISAT2</code>, through the <em><a href="https://bioconductor.org/packages/3.14/Rhisat2">Rhisat2</a></em> package). The package aims to cover the whole analysis workflow of typical high throughput sequencing experiments, starting from the raw sequence reads, over pre-processing and alignment, up to quantification. A single <strong>R</strong> script can contain all steps of a complete analysis, making it simple to document, reproduce or share the workflow containing all relevant details.</p><p>Address of the bookmark: <a href="https://www.bioconductor.org/packages/devel/bioc/vignettes/QuasR/inst/doc/QuasR.html" rel="nofollow">https://www.bioconductor.org/packages/devel/bioc/vignettes/QuasR/inst/doc/QuasR.html</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36257/aligngraph-algorithm-for-secondary-de-novo-genome-assembly-guided-by-closely-related-references</guid>
	<pubDate>Tue, 17 Apr 2018 16:21:20 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36257/aligngraph-algorithm-for-secondary-de-novo-genome-assembly-guided-by-closely-related-references</link>
	<title><![CDATA[AlignGraph: algorithm for secondary de novo genome assembly guided by closely related references]]></title>
	<description><![CDATA[<p>AlignGraph is a software that extends and joins contigs or scaffolds by reassembling them with help provided by a reference genome of a closely related organism.</p>
<p>Using AlignGraph</p>
<pre><code>AlignGraph --read1 reads_1.fa --read2 reads_2.fa --contig contigs.fa --genome genome.fa --distanceLow distanceLow --distanceHigh distancehigh --extendedContig extendedContigs.fa --remainingContig remainingContigs.fa [--kMer k --insertVariation insertVariation --coverage coverage --part p --fastMap --ratioCheck --iterativeMap --misassemblyRemoval --resume]</code></pre>
<h3>&nbsp;</h3><p>Address of the bookmark: <a href="https://github.com/baoe/AlignGraph" rel="nofollow">https://github.com/baoe/AlignGraph</a></p>]]></description>
	<dc:creator>Manisha Mishra</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36861/eagler-a-scaffolding-tool-for-long-reads</guid>
	<pubDate>Mon, 04 Jun 2018 05:26:03 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36861/eagler-a-scaffolding-tool-for-long-reads</link>
	<title><![CDATA[EAGLER: a scaffolding tool for long reads.]]></title>
	<description><![CDATA[<p>EAGLER is a scaffolding tool for long reads. The scaffolder takes as input a draft genome created by any NGS assembler and a set of long reads. The long reads are used to extend the contigs present in the NGS draft and possibly join overlapping contigs. EAGLER supports both PacBio and Oxford Nanopore reads.</p>
<p>The tool should be compatible with most UNIX flavors and has been successfully tested on the following operating systems:</p>
<ul>
<li>Mac OS X 10.11.1</li>
<li>Mac OS X 10.10.3</li>
<li>Ubuntu 14.04 LTS</li>
</ul>

https://bib.irb.hr/datoteka/844447.Diplomski_2015_Luka_terbi.pdf<p>Address of the bookmark: <a href="https://github.com/mculinovic/EAGLER" rel="nofollow">https://github.com/mculinovic/EAGLER</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37840/long-read-assembly-workshop</guid>
	<pubDate>Thu, 04 Oct 2018 17:23:18 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37840/long-read-assembly-workshop</link>
	<title><![CDATA[Long read assembly workshop !]]></title>
	<description><![CDATA[<p>This is a tutorial for a workshop on long-read (PacBio) genome assembly.</p>
<p>It demonstrates how to use long PacBio sequencing reads to assemble a bacterial genome, and includes additional steps for circularising, trimming, finding plasmids, and correcting the assembly with short-read Illumina data.</p>
<p>&nbsp;Please comment if you know any other long read addembly tutorial.</p><p>Address of the bookmark: <a href="http://sepsis-omics.github.io/tutorials/modules/cmdline_assembly_v2/" rel="nofollow">http://sepsis-omics.github.io/tutorials/modules/cmdline_assembly_v2/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41599/haslr-a-hybrid-assembler-which-uses-both-second-and-third-generation-sequencing-reads</guid>
	<pubDate>Mon, 04 May 2020 02:04:03 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41599/haslr-a-hybrid-assembler-which-uses-both-second-and-third-generation-sequencing-reads</link>
	<title><![CDATA[HASLR: a hybrid assembler which uses both second and third generation sequencing reads]]></title>
	<description><![CDATA[<p><span>HASLR, a hybrid assembler which uses both second and third generation sequencing reads to efficiently generate accurate genome assemblies. Our experiments show that HASLR is not only the fastest assembler but also the one with the lowest number of misassemblies on all the samples compared to other tested assemblers. Furthermore, the generated assemblies in terms of contiguity and accuracy are on par with the other tools on most of the samples. Availability. HASLR is an open source tool available at https://github.com/vpc-ccg/haslr.</span></p><p>Address of the bookmark: <a href="https://github.com/vpc-ccg/haslr" rel="nofollow">https://github.com/vpc-ccg/haslr</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43736/odgi-optimized-dynamic-genomegraph-implementation</guid>
	<pubDate>Tue, 01 Feb 2022 23:42:21 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43736/odgi-optimized-dynamic-genomegraph-implementation</link>
	<title><![CDATA[odgi: optimized dynamic genome/graph implementation]]></title>
	<description><![CDATA[<p dir="auto"><code>odgi</code>&nbsp;provides an efficient and succinct dynamic DNA sequence graph model, as well as a host of algorithms that allow the use of such graphs in bioinformatic analyses.</p>
<p dir="auto">Careful encoding of graph entities allows&nbsp;<code>odgi</code>&nbsp;to efficiently compute and transform&nbsp;<a href="https://pangenome.github.io/">pangenomes</a>&nbsp;with minimal overheads.&nbsp;<code>odgi</code>&nbsp;implements a dynamic data structure that leveraged multi-core CPUs and can be updated on the fly.</p>
<p dir="auto">The edges and path steps are recorded as deltas between the current node id and the target node id, where the node id corresponds to the rank in the global array of nodes. Graphs built from biological data sets tend to have local partial order and, when sorted, the deltas be small. This allows them to be compressed with a variable length integer representation, resulting in a small in-memory footprint at the cost of packing and unpacking.</p>
<p dir="auto">The RAM and computational savings are substantial. In partially ordered regions of the graph, most deltas will require only a single byte.</p><p>Address of the bookmark: <a href="https://github.com/pangenome/odgi" rel="nofollow">https://github.com/pangenome/odgi</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40573/de-novo-genome-assembly-for-illumina-data</guid>
	<pubDate>Mon, 20 Jan 2020 05:13:29 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40573/de-novo-genome-assembly-for-illumina-data</link>
	<title><![CDATA[De novo Genome Assembly for Illumina Data]]></title>
	<description><![CDATA[<p>Written and maintained by <a href="mailto:simon.gladman@unimelb.edu.au">Simon Gladman</a> - Melbourne Bioinformatics (formerly VLSCI)</p>
<p>Protocol Overview / Introduction</p>
<p>In this protocol we discuss and outline the process of de novo assembly for small to medium sized genomes.</p>
<p>https://www.melbournebioinformatics.org.au/tutorials/tutorials/assembly/assembly-protocol/</p><p>Address of the bookmark: <a href="https://www.melbournebioinformatics.org.au/tutorials/tutorials/assembly/assembly-protocol/" rel="nofollow">https://www.melbournebioinformatics.org.au/tutorials/tutorials/assembly/assembly-protocol/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34413/coursera-genome-assembly-tutorial</guid>
	<pubDate>Sat, 25 Nov 2017 08:57:25 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34413/coursera-genome-assembly-tutorial</link>
	<title><![CDATA[coursera genome assembly tutorial]]></title>
	<description><![CDATA[<p><span>Solutions to Coursera Genome Sequencing (Bioinformatics II)</span></p><p>Address of the bookmark: <a href="https://github.com/iansealy/coursera-assembly" rel="nofollow">https://github.com/iansealy/coursera-assembly</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34931/3d-dna-3d-de-novo-assembly-3d-dna-pipeline</guid>
	<pubDate>Thu, 28 Dec 2017 10:09:37 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34931/3d-dna-3d-de-novo-assembly-3d-dna-pipeline</link>
	<title><![CDATA[3d-dna: 3D de novo assembly (3D DNA) pipeline]]></title>
	<description><![CDATA[<p>This code is designed to enable anyone to reproduce the Hs2-HiC and the AaegL4 genomes reported in:&nbsp;<a href="http://science.sciencemag.org/content/early/2017/03/22/science.aal3327.full">Dudchenko et al., De novo assembly of the Aedes aegypti genome using Hi-C yields chromosome-length scaffolds. Science, 2017.</a></p>
<p>Unless otherwise noted, all terminology below is consistent with this paper, and all references to figures and tables in this readme refer to this paper. Specifically, some of the terminology used below is outlined in&nbsp;<code>Figure S2</code>. The assembly procedure is described in detail in the&nbsp;<a href="http://science.sciencemag.org/content/suppl/2017/03/22/science.aal3327.DC1?_ga=1.9816115.760837492.1490574064">Supporting Online Materials</a>, specifically in the section labelled &ldquo;Pipeline description&rdquo;.</p>
<p>In addition, the pipeline uses tools and methods from&nbsp;<a href="http://www.cell.com/cell-systems/abstract/S2405-4712(16)30219-8">Juicer (Durand &amp; Shamim et al., Cell Systems, 2016)</a>&nbsp;and&nbsp;<a href="http://www.cell.com/cell-systems/abstract/S2405-4712(15)00054-X">Juicebox (Durand &amp; Robinson et al., Cell Systems, 2016)</a>, as well as additional dependencies noted below.</p>
<p>Feel free to post your questions and comments at:&nbsp;<a href="http://www.aidenlab.org/forum.html">http://www.aidenlab.org/forum.html</a></p>
<p>http://aidenlab.org/documentation.html</p><p>Address of the bookmark: <a href="https://github.com/theaidenlab/3d-dna" rel="nofollow">https://github.com/theaidenlab/3d-dna</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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