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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/43057?offset=340</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35885/multi-car-a-tool-of-contig-scaffolding-using-multiple-references</guid>
	<pubDate>Tue, 06 Mar 2018 16:39:41 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35885/multi-car-a-tool-of-contig-scaffolding-using-multiple-references</link>
	<title><![CDATA[Multi-CAR: a tool of contig scaffolding using multiple references]]></title>
	<description><![CDATA[<p><span>we design a simple heuristic method to further revise our single reference-based scaffolding tool CAR into a new one called Multi-CAR such that it can utilize multiple complete genomes of related organisms as references to more accurately order and orient the contigs of a draft genome. In practical usage, our Multi-CAR does not require prior knowledge concerning phylogenetic relationships among the draft and reference genomes and libraries of paired-end reads. To validate Multi-CAR, we have tested it on a real dataset composed of several prokaryotic genomes and also compared its accuracy performance with other multiple reference-based scaffolding tools Ragout and MeDuSa.&nbsp;</span></p><p>Address of the bookmark: <a href="http://genome.cs.nthu.edu.tw/Multi-CAR/" rel="nofollow">http://genome.cs.nthu.edu.tw/Multi-CAR/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34940/jpred4-a-protein-secondary-structure-prediction-server</guid>
	<pubDate>Fri, 29 Dec 2017 16:14:28 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34940/jpred4-a-protein-secondary-structure-prediction-server</link>
	<title><![CDATA[JPred4: A Protein Secondary Structure Prediction Server]]></title>
	<description><![CDATA[<p><span>JPred4 (</span><a href="http://www.compbio.dundee.ac.uk/jpred4" target="">http://www.compbio.dundee.ac.uk/jpred4</a><span>) is the latest version of the popular JPred protein secondary structure prediction server which provides predictions by the JNet algorithm, one of the most accurate methods for secondary structure prediction.</span></p><p>Address of the bookmark: <a href="http://www.compbio.dundee.ac.uk/jpred4/" rel="nofollow">http://www.compbio.dundee.ac.uk/jpred4/</a></p>]]></description>
	<dc:creator>Poonam Mahapatra</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41969/shadowcaster-a-hybrid-approach-for-the-detection-of-horizontal-gene-transfer-events-in-prokaryotes</guid>
	<pubDate>Tue, 14 Jul 2020 06:42:10 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41969/shadowcaster-a-hybrid-approach-for-the-detection-of-horizontal-gene-transfer-events-in-prokaryotes</link>
	<title><![CDATA[ShadowCaster: a hybrid approach for the detection of horizontal gene transfer events in prokaryotes]]></title>
	<description><![CDATA[<p><span>ShadowCaster implements an evolutionary model to calculate Bayesian likelihoods for each &lsquo;alien genes&rsquo; with an unusual sequence composition according to the host genome background to detect HGT events in prokaryotes.</span></p>
<p><a href="https://www.mdpi.com/2073-4425/11/7/756/htm">https://www.mdpi.com/2073-4425/11/7/756/htm</a></p>
<p><a href="https://shadowcaster.readthedocs.io/en/latest/">https://shadowcaster.readthedocs.io/en/latest/</a></p>
<p><a href="https://github.com/dani2s/ShadowCaster_testData">https://github.com/dani2s/ShadowCaster_testData</a></p><p>Address of the bookmark: <a href="https://github.com/dani2s/ShadowCaster" rel="nofollow">https://github.com/dani2s/ShadowCaster</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34246/unicycler-hybrid-assembly-pipeline-for-bacterial-genomes</guid>
	<pubDate>Fri, 10 Nov 2017 03:58:27 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34246/unicycler-hybrid-assembly-pipeline-for-bacterial-genomes</link>
	<title><![CDATA[Unicycler: Hybrid assembly pipeline for bacterial genomes]]></title>
	<description><![CDATA[<p><span>Unicycler is an assembly pipeline for bacterial genomes. It can assemble&nbsp;</span><a href="http://www.illumina.com/">Illumina</a><span>-only read sets where it functions as a&nbsp;</span><a href="http://cab.spbu.ru/software/spades/">SPAdes</a><span>-optimiser. It can also assembly long-read-only sets (</span><a href="http://www.pacb.com/">PacBio</a><span>&nbsp;or&nbsp;</span><a href="https://nanoporetech.com/">Nanopore</a><span>) where it runs a&nbsp;</span><a href="https://github.com/lh3/miniasm">miniasm</a><span>+</span><a href="https://github.com/isovic/racon">Racon</a><span>&nbsp;pipeline. For the best possible assemblies, give it both Illumina reads&nbsp;</span><em>and</em><span>&nbsp;long reads, and it will conduct a hybrid assembly.</span></p><p>Address of the bookmark: <a href="https://github.com/rrwick/Unicycler" rel="nofollow">https://github.com/rrwick/Unicycler</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36621/hapcut2-robust-and-accurate-haplotype-assembly-for-diverse-sequencing-technologies</guid>
	<pubDate>Tue, 15 May 2018 07:35:26 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36621/hapcut2-robust-and-accurate-haplotype-assembly-for-diverse-sequencing-technologies</link>
	<title><![CDATA[HapCUT2: robust and accurate haplotype assembly for diverse sequencing technologies]]></title>
	<description><![CDATA[HapCUT2 is a maximum-likelihood-based tool for assembling haplotypes from DNA sequence reads, designed to "just work" with excellent speed and accuracy. We found that previously described haplotype assembly methods are specialized for specific read technologies or protocols, with slow or inaccurate performance on others. With this in mind, HapCUT2 is designed for speed and accuracy across diverse sequencing technologies, including but not limited to:

NGS short reads (Illumina HiSeq)
clone-based sequencing (Fosmid or BAC clones)
SMRT reads (PacBio)
Oxford Nanopore reads
10X Genomics Linked-Reads
proximity-ligation (Hi-C) reads
high-coverage sequencing (&gt;40x coverage-per-SNP) using above technologies
combinations of the above technologies (e.g. scaffold long reads with Hi-C reads)
See below for specific examples of command line options and best practices for some of these technologies.

NOTE: At this time HapCUT2 is for diploid organisms only. VCF input should contain diploid variants.

If you use HapCUT2 in your research, please cite:

Edge, P., Bafna, V. &amp; Bansal, V. HapCUT2: robust and accurate haplotype assembly for diverse sequencing technologies. Genome Res. gr.213462.116 (2016). doi:10.1101/gr.213462.116<p>Address of the bookmark: <a href="https://github.com/vibansal/HapCUT2" rel="nofollow">https://github.com/vibansal/HapCUT2</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39098/sda-long-read-sequence-and-assembly-of-segmental-duplications</guid>
	<pubDate>Tue, 05 Mar 2019 10:00:57 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39098/sda-long-read-sequence-and-assembly-of-segmental-duplications</link>
	<title><![CDATA[SDA: Long-read sequence and assembly of segmental duplications]]></title>
	<description><![CDATA[<p><span><span>Segmental Duplication Assembler (SDA; https://github.com/mvollger/SDA) constructs graphs in which paralogous sequence variants define the nodes and long-read sequences provide attraction and repulsion edges, enabling the partition and assembly of long reads corresponding to distinct paralogs.<br></span></span></p>
<p><span><span>https://github.com/mvollger/SDA</span></span></p><p>Address of the bookmark: <a href="https://www.nature.com/articles/s41592-018-0236-3" rel="nofollow">https://www.nature.com/articles/s41592-018-0236-3</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40099/contiguator</guid>
	<pubDate>Fri, 04 Oct 2019 01:27:58 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40099/contiguator</link>
	<title><![CDATA[CONTIGuator !]]></title>
	<description><![CDATA[<p><span>CONTIGuator is a Python script for Linux environments whose purpose is to speed-up the bacterial genome assembly process and to obtain a first insight of the genome structure using the well-known artemis comparison tool (ACT).</span></p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="https://sourceforge.net/projects/contiguator/" rel="nofollow">https://sourceforge.net/projects/contiguator/</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41734/supernova-generates-phased-whole-genome-de-novo-assemblies-from-a-chromium-prepared-library</guid>
	<pubDate>Sun, 31 May 2020 01:59:30 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41734/supernova-generates-phased-whole-genome-de-novo-assemblies-from-a-chromium-prepared-library</link>
	<title><![CDATA[Supernova: generates phased, whole-genome de novo assemblies from a Chromium-prepared library.]]></title>
	<description><![CDATA[<p>Supernova generates phased, whole-genome&nbsp;<em>de novo</em>&nbsp;assemblies from a Chromium-prepared library.</p>
<p>Please see&nbsp;<a href="https://support.10xgenomics.com/de-novo-assembly/guidance/doc/achieving-success-with-de-novo-assembly">Achieving Success with De Novo Assembly</a>&nbsp;and&nbsp;<a href="https://support.10xgenomics.com/de-novo-assembly/software/overview/system-requirements">System Requirements</a>&nbsp;<em>before</em>&nbsp;creating your Chromium libraries for assembly.</p>
<p>Supernova should be run using 38-56x coverage of the genome.<br>&bull; Somewhat higher coverage is&nbsp;<em>sometimes</em>&nbsp;advantageous.<br>&bull; Supernova will exit if it finds that coverage is far from the recommended range.<br>&bull; Note that at most 2.14 billion reads are allowed.<br>&bull; Please note that we have not extensively tested genomes larger than human, and any genome above approximately 4 GB should be considered experimental and is not supported.</p><p>Address of the bookmark: <a href="https://support.10xgenomics.com/de-novo-assembly/software/pipelines/latest/using/running" rel="nofollow">https://support.10xgenomics.com/de-novo-assembly/software/pipelines/latest/using/running</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42806/graphunzip-phases-an-assembly-graph-using-hi-c-data-andor-long-reads</guid>
	<pubDate>Fri, 05 Feb 2021 21:22:24 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42806/graphunzip-phases-an-assembly-graph-using-hi-c-data-andor-long-reads</link>
	<title><![CDATA[GraphUnzip: Phases an assembly graph using Hi-C data and/or long reads.]]></title>
	<description><![CDATA[<p>GraphUnzip, a fast, memory-efficient and accurate tool to unzip assembly graphs into their constituent haplotypes using long reads and/or Hi-C data. As GraphUnzip only connects sequences in the assembly graph that already had a potential link based on overlaps, it yields high-quality gap-less supercontigs. To demonstrate the efficiency of GraphUnzip, we tested it on a simulated diploid Escherichia coli genome, and on two real datasets for the genomes of the rotifer Adineta vaga and the potato Solanum tuberosum. In all cases, GraphUnzip yielded highly continuous phased assemblies.</p>
<p>https://www.biorxiv.org/content/biorxiv/early/2021/02/01/2021.01.29.428779.full.pdf</p><p>Address of the bookmark: <a href="https://github.com/nadegeguiglielmoni/GraphUnzip" rel="nofollow">https://github.com/nadegeguiglielmoni/GraphUnzip</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26332/pilon</guid>
	<pubDate>Mon, 08 Feb 2016 15:56:18 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26332/pilon</link>
	<title><![CDATA[Pilon]]></title>
	<description><![CDATA[<p>Pilon is a software tool which can be used to:</p>
<ul>
<li>Automatically improve draft assemblies</li>
<li>Find variation among strains, including large event detection</li>
</ul>
<p>Pilon requires as input a FASTA file of the genome along with one or more BAM files of reads aligned to the input FASTA file. Pilon uses read alignment analysis to identify inconsistencies between the input genome and the evidence in the reads. It then attempts to make improvements to the input genome, including:</p>
<ul>
<li>Single base differences</li>
<li>Small indels</li>
<li>Larger indel or block substitution events</li>
<li>Gap filling</li>
<li>Identification of local misassemblies, including optional opening of new gaps</li>
</ul>
<p>More at https://github.com/broadinstitute/pilon/wiki</p><p>Address of the bookmark: <a href="https://github.com/broadinstitute/pilon/wiki" rel="nofollow">https://github.com/broadinstitute/pilon/wiki</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>

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