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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/42633?offset=110</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43088/iva-accurate-de-novo-assembly-of-rna-virus-genomes</guid>
	<pubDate>Wed, 23 Jun 2021 07:51:59 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43088/iva-accurate-de-novo-assembly-of-rna-virus-genomes</link>
	<title><![CDATA[IVA: accurate de novo assembly of RNA virus genomes]]></title>
	<description><![CDATA[<p>IVA (Iterative Virus Assembler) designed specifically for read pairs sequenced at highly variable depth from RNA virus samples. We tested IVA on datasets from 140 sequenced samples from human immunodeficiency virus-1 or influenza-virus-infected people and demonstrated that IVA outperforms all other virus de novo assemblers.</p>
<p><strong> Availability and implementation: </strong> The software runs under Linux, has the GPLv3 licence and is freely available from http://sanger-pathogens.github.io/iva</p>
<p>https://pubmed.ncbi.nlm.nih.gov/25725497/</p><p>Address of the bookmark: <a href="https://github.com/sanger-pathogens/iva" rel="nofollow">https://github.com/sanger-pathogens/iva</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/44377/mitochondrial-genome-assembly-tools</guid>
	<pubDate>Wed, 06 Sep 2023 00:37:18 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/44377/mitochondrial-genome-assembly-tools</link>
	<title><![CDATA[Mitochondrial genome assembly tools !]]></title>
	<description><![CDATA[<p>Mitochondrial genome assembly tools are specialized software and algorithms designed to accurately reconstruct the mitochondrial genome (mitogenome) from sequencing data, typically obtained through techniques like next-generation sequencing (NGS). The mitochondrial genome is relatively small compared to the nuclear genome, making it an ideal target for assembly. Here are some commonly used mitochondrial genome assembly tools:</p><p><strong>MitoFinder:</strong> Mitofinder is a pipeline to assemble mitochondrial genomes and annotate mitochondrial genes from trimmed read sequencing data.</p><p><strong>MitoHiFi:</strong> a python pipeline for mitochondrial genome assembly from PacBio high fidelity reads</p><p>MITObim: MITObim is a tool specifically developed for the iterative assembly of mitochondrial genomes. It starts with a reference mitogenome and iteratively refines the assembly using the read data.</p><p><strong>MITOS:</strong> MITOS is a web-based platform that provides a pipeline for annotating mitochondrial genomes. It integrates multiple software tools for assembly, annotation, and visualization of mitogenomes.</p><p><strong>MIRA:</strong> MIRA (Mimicking Intelligent Read Assembly) is a versatile genome assembly tool that can be used for mitochondrial genome assembly. It supports various sequencing technologies and allows for reference-based or de novo assembly.</p><p><strong>NOVOPlasty:</strong> NOVOPlasty is a user-friendly tool designed for de novo assembly of organelle genomes, including mitochondria. It utilizes a seed-and-extend algorithm and is suitable for both short-read and long-read data.</p><p><strong>MITOS2:</strong> MITOS2 is an updated version of the MITOS pipeline, which automates the annotation of mitochondrial genomes. It provides improved accuracy and additional features for mitochondrial genome analysis.</p><p><strong>GetOrganelle:</strong> While primarily designed for chloroplast genome assembly, GetOrganelle can also be used for mitochondrial genome assembly. It is particularly useful for dealing with high-throughput sequencing data.</p><p><strong>SPAdes:</strong> SPAdes (St. Petersburg genome assembler) is a versatile genome assembly tool that can be employed for mitochondrial genome assembly, especially when dealing with complex datasets that may contain nuclear mitochondrial DNA sequences (numts).</p><p><strong>IDBA-UD:</strong> IDBA-UD (Iterative De Bruijn Graph De Novo Assembler) is another de novo assembly tool that can be used for mitochondrial genome assembly, especially in cases with relatively low coverage.</p><p><strong>Velvet:</strong> Velvet is a de novo assembly tool that can be applied to mitochondrial genome assembly, especially when working with short-read data.</p><p>When selecting a mitochondrial genome assembly tool, it's important to consider the specific characteristics of your sequencing data, such as read length and coverage, as well as the complexity of the mitochondrial genome. Additionally, some tools are better suited for specific organisms or research objectives, so choosing the right tool will depend on your particular project requirements.</p>]]></description>
	<dc:creator>Abhi</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/45314/nf-coremag-v5-advancing-genome-resolved-metagenomics</guid>
	<pubDate>Sat, 12 Sep 2026 20:27:51 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/45314/nf-coremag-v5-advancing-genome-resolved-metagenomics</link>
	<title><![CDATA[nf-core/mag v5: Advancing Genome-Resolved Metagenomics]]></title>
	<description><![CDATA[<p>Metagenomics is rapidly moving beyond short-read sequencing. With the increasing adoption of long-read technologies, researchers can generate more contiguous assemblies&mdash;but converting these reads into reliable metagenome-assembled genomes (MAGs) remains computationally challenging.</p><p>nf-core/mag v5 (https://github.com/nf-core/mag) addresses this challenge by extending its reproducible Nextflow-based workflow for modern genome-resolved metagenomics.</p><p>A key addition is support for long-read-only metagenomic assembly and bin refinement, enabling long-read data to be processed through an integrated workflow. The release also introduces five additional binning tools, providing complementary strategies for recovering genomes from complex microbial communities.</p><p>The workflow has also expanded beyond conventional bacterial and archaeal MAGs, with improved classification of viruses and eukaryotes, together with enhanced genome-quality assessment.</p><p>Conceptually, the workflow brings together:</p><p>Reads &rarr; QC &rarr; Assembly &rarr; Binning &rarr; Bin refinement &rarr; Taxonomic classification &rarr; MAG quality assessment</p><p>The real strength of nf-core/mag is not any single algorithm, but the integration and reproducibility of multiple tools within a standardized workflow. This is particularly important for large-scale metagenomic studies where software versions, parameters, databases and computational environments can strongly influence results.</p><p>After seven years of development involving multiple curator teams and the wider nf-core community, v5 demonstrates how community-driven workflow development can keep metagenomic analysis aligned with rapidly evolving sequencing technologies.</p><p>The future of genome-resolved metagenomics is not simply longer reads&mdash;it is better integration of assembly, binning, refinement and quality control within reproducible computational workflows.</p><p>Read the full paper in Bioinformatics https://academic.oup.com/bioinformatics/article/42/9/btag628/8770536?</p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26306/busco</guid>
	<pubDate>Sun, 07 Feb 2016 16:02:39 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26306/busco</link>
	<title><![CDATA[BUSCO]]></title>
	<description><![CDATA[<p>Assessing genome assembly and annotation completeness with Benchmarking Universal Single-Copy Orthologs</p>
<p>More at http://busco.ezlab.org/</p><p>Address of the bookmark: <a href="http://busco.ezlab.org/" rel="nofollow">http://busco.ezlab.org/</a></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26906/paired-end-assembler-for-dna-sequences</guid>
	<pubDate>Wed, 06 Apr 2016 05:25:34 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26906/paired-end-assembler-for-dna-sequences</link>
	<title><![CDATA[PAired-eND Assembler for DNA sequences]]></title>
	<description><![CDATA[<p>PANDASEQ is a program to align Illumina reads, optionally with PCR primers embedded in the sequence, and reconstruct an overlapping sequence.</p>
<p>&nbsp;</p>
<p>More at https://github.com/neufeld/pandaseq</p><p>Address of the bookmark: <a href="https://github.com/neufeld/pandaseq" rel="nofollow">https://github.com/neufeld/pandaseq</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27328/platanus</guid>
	<pubDate>Fri, 13 May 2016 05:12:40 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27328/platanus</link>
	<title><![CDATA[Platanus]]></title>
	<description><![CDATA[<p>Platanus is a novel <em>de novo</em> sequence assembler that can reconstruct genomic sequences of<br> highly heterozygous diploids from massively parallel shotgun sequencing data.</p>
<p>The latest version is <a href="http://platanus.bio.titech.ac.jp/platanus/?page_id=14">1.2.4</a>.</p>
<p>To cite Platanus, please use the following:</p>
<p>Kajitani R, Toshimoto K, Noguchi H, Toyoda A, Ogura Y, Okuno M, Yabana M, Harada M, Nagayasu E, Maruyama H, Kohara Y, Fujiyama A, Hayashi T, Itoh T, &ldquo;Efficient de novo assembly of highly heterozygous genomes from whole-genome shotgun short reads&rdquo;.&nbsp;Genome Res. 2014 Aug;24(8):1384-95. doi: 10.1101/gr.170720.113. [<a href="http://www.ncbi.nlm.nih.gov/pubmed/24755901">abstract</a> |<a href="http://genome.cshlp.org/content/24/8/1384.long"> full text</a>]</p><p>Address of the bookmark: <a href="http://platanus.bio.titech.ac.jp/" rel="nofollow">http://platanus.bio.titech.ac.jp/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31100/vaguevelvet-assembler-graphical-front-end</guid>
	<pubDate>Fri, 24 Feb 2017 08:56:49 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31100/vaguevelvet-assembler-graphical-front-end</link>
	<title><![CDATA[VAGUE:Velvet Assembler Graphical Front End]]></title>
	<description><![CDATA[<p>VAGUE is a vague acronym for "Velvet Assembler Graphical Front End", which means it is a GUI for the Velvet <em>de novo</em> assembler. The command line version of Velvet can be complicated for beginners to use, but VAGUE makes it clear and simple</p>
<p>More at&nbsp;http://www.vicbioinformatics.com/software.vague.shtml</p><p>Address of the bookmark: <a href="http://www.vicbioinformatics.com/software.vague.shtml" rel="nofollow">http://www.vicbioinformatics.com/software.vague.shtml</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30076/sga-string-graph-assembler</guid>
	<pubDate>Thu, 08 Dec 2016 05:08:59 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30076/sga-string-graph-assembler</link>
	<title><![CDATA[SGA: String Graph Assembler]]></title>
	<description><![CDATA[<p><span>SGA is a de novo genome assembler based on the concept of string graphs. The major goal of SGA is to be very memory efficient, which is achieved by using a compressed representation of DNA sequence reads.</span></p>
<p><span>More at</span></p>
<p><span>https://github.com/jts/sga</span></p>
<p>SGA dependencies:<br> -google sparse hash library (http://code.google.com/p/google-sparsehash/)<br> -the bamtools library (https://github.com/pezmaster31/bamtools)<br> -zlib (http://www.zlib.net/)<br> -(optional but suggested) the jemalloc memory allocator (http://www.canonware.com/jemalloc/download.html)</p><p>Address of the bookmark: <a href="https://github.com/jts/sga" rel="nofollow">https://github.com/jts/sga</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30124/understanding-greedy-algorithms</guid>
	<pubDate>Mon, 12 Dec 2016 04:37:40 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30124/understanding-greedy-algorithms</link>
	<title><![CDATA[Understanding Greedy Algorithms]]></title>
	<description><![CDATA[<p>Learning greedy algo for biologist.&nbsp;</p>
<p>https://www.topcoder.com/community/data-science/data-science-tutorials/greedy-is-good/</p>
<p>This webpage is also useful for the same:</p>
<p>http://learninglover.com/examples.php?id=59</p>
<p>http://www.cs.rpi.edu/~magdon/ps/conference/super_biokdd.pdf</p>
<p>https://ocw.mit.edu/courses/biology/7-91j-foundations-of-computational-and-systems-biology-spring-2014/lecture-slides/MIT7_91JS14_Lecture6.pdf</p>
<p>http://schatzlab.cshl.edu/teaching/AssemblyClass/01.%20Assembly%20Intro.pdf</p>
<p>http://lsl.sinica.edu.tw/Services/Class/files/20150612449.pdf</p>
<p>http://www.cs.jhu.edu/~langmea/resources/lecture_notes/assembly_scs.pdf</p>
<p>https://www2.eecs.berkeley.edu/Pubs/TechRpts/2016/EECS-2016-43.pdf</p><p>Address of the bookmark: <a href="https://www.topcoder.com/community/data-science/data-science-tutorials/greedy-is-good/" rel="nofollow">https://www.topcoder.com/community/data-science/data-science-tutorials/greedy-is-good/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30207/gam-ngs-genomic-assemblies-merger-for-next-generation-sequencing</guid>
	<pubDate>Mon, 19 Dec 2016 06:07:05 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30207/gam-ngs-genomic-assemblies-merger-for-next-generation-sequencing</link>
	<title><![CDATA[GAM-NGS: genomic assemblies merger for next generation sequencing]]></title>
	<description><![CDATA[<p><span>GAM-NGS (Genomic Assemblies Merger for Next Generation Sequencing), whose primary goal is to merge two or more assemblies in order to enhance contiguity and correctness of both. GAM-NGS does not rely on global alignment: regions of the two assemblies representing the same genomic&nbsp;</span><em>locus</em><span>&nbsp;(called&nbsp;</span><em>blocks</em><span>) are identified through reads' alignments and stored in a&nbsp;</span><em>weighted</em><span>graph. The merging phase is carried out with the help of this weighted graph that allows an&nbsp;</span><em>optimal</em><span>&nbsp;resolution of&nbsp;</span><em>local</em><span>&nbsp;problematic regions.</span></p><p>Address of the bookmark: <a href="https://github.com/vice87/gam-ngs" rel="nofollow">https://github.com/vice87/gam-ngs</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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