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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/36723?offset=480</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26925/reapr-a-universal-tool-for-genome-assembly-evaluation</guid>
	<pubDate>Wed, 06 Apr 2016 18:26:31 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26925/reapr-a-universal-tool-for-genome-assembly-evaluation</link>
	<title><![CDATA[REAPR: a universal tool for genome assembly evaluation]]></title>
	<description><![CDATA[<p>REAPR is a tool that evaluates the accuracy of a genome assembly using mapped paired end reads, without the use of a reference genome for comparison. It can be used in any stage of an assembly pipeline to automatically break incorrect scaffolds and flag other errors in an assembly for manual inspection. It reports mis-assemblies and other warnings, and produces a new broken assembly based on the error calls.</p>
<p>The software requires as input an assembly in FASTA format and paired reads mapped to the assembly in a BAM file. Mapping information such as the fragment coverage and insert size distribution is analysed to locate mis-assemblies. REAPR works best using mapped read pairs from a large insert library (at least 1000bp). Additionally, if a short insert Illumina library is also available, REAPR can combine this with the large insert library in order to score each base of the assembly.</p>
<p>http://www.sanger.ac.uk/science/tools/reapr</p><p>Address of the bookmark: <a href="https://genomebiology.biomedcentral.com/articles/10.1186/gb-2013-14-5-r47" rel="nofollow">https://genomebiology.biomedcentral.com/articles/10.1186/gb-2013-14-5-r47</a></p>]]></description>
	<dc:creator>Jitendra Prajapati</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27076/ale-a-generic-assembly-likelihood-evaluation-framework-for-assessing-the-accuracy-of-genome-and-metagenome-assemblies</guid>
	<pubDate>Tue, 26 Apr 2016 03:38:43 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27076/ale-a-generic-assembly-likelihood-evaluation-framework-for-assessing-the-accuracy-of-genome-and-metagenome-assemblies</link>
	<title><![CDATA[ALE: a Generic Assembly Likelihood Evaluation Framework for Assessing the Accuracy of Genome and Metagenome Assemblies]]></title>
	<description><![CDATA[<p>Assembly Likelihood Evaluation (ALE) framework that overcomes these limitations, systematically evaluating the accuracy of an assembly in a reference-independent manner using rigorous statistical methods. This framework is comprehensive, and integrates read quality, mate pair orientation and insert length (for paired-end reads), sequencing coverage, read alignment and k-mer frequency. ALE pinpoints synthetic errors in both single and metagenomic assemblies, including single-base errors, insertions/deletions, genome rearrangements and chimeric assemblies presented in metagenomes. At the genome level with real-world data, ALE identifies three large misassemblies from the Spirochaeta smaragdinae finished genome, which were all independently validated by Pacific Biosciences sequencing. At the single-base level with Illumina data, ALE recovers 215 of 222 (97%) single nucleotide variants in a training set from a GC-rich Rhodobacter sphaeroides genome. Using real Pacific Biosciences data, ALE identifies 12 of 12 synthetic errors in a Lambda Phage genome, surpassing even Pacific Biosciences' own variant caller, EviCons. In summary, the ALE framework provides a comprehensive, reference-independent and statistically rigorous measure of single genome and metagenome assembly accuracy, which can be used to identify misassemblies or to optimize the assembly process.</p>
<p>More at&nbsp;http://www.ncbi.nlm.nih.gov/pubmed/23303509</p><p>Address of the bookmark: <a href="http://sc932.github.io/ALE/about.html" rel="nofollow">http://sc932.github.io/ALE/about.html</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27818/gaemr</guid>
	<pubDate>Tue, 14 Jun 2016 06:18:37 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27818/gaemr</link>
	<title><![CDATA[GAEMR]]></title>
	<description><![CDATA[<p>The&nbsp;<span>G</span>enome&nbsp;<span>A</span>ssembly&nbsp;<span>E</span>valuation&nbsp;<span>M</span>etrics and&nbsp;<span>R</span>eporting (GAEMR) package is an assembly analysis framework composed a number of integrated modules. These modules can be executed as a single program to generate a complete analysis report, or executed individually to generate specific charts and tables. GAEMR standardizes input by converting a variety of read types to Binary Alignment Map (BAM) format, allowing a single input format to be entered into GAEMR&rsquo;s analysis pipeline, hence enabling the generation of standard reports.</p>
<p>GAEMR&rsquo;s analysis philosophy is centered on contiguity, correctness, and completeness -- how many pieces in an assembly composed of, how well those pieces accurately represent the genome sequenced, and how much of that genome is represented by those pieces. By performing over twenty different analyses based on these principles, GAEMR gives a clear picture of the condition of a genome assembly.&nbsp;</p><p>Address of the bookmark: <a href="https://www.broadinstitute.org/software/gaemr/" rel="nofollow">https://www.broadinstitute.org/software/gaemr/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30012/swalo</guid>
	<pubDate>Wed, 30 Nov 2016 05:06:05 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30012/swalo</link>
	<title><![CDATA[SWALO]]></title>
	<description><![CDATA[<p>SWALO (scaffolding with assembly likelihood optimization) is a method for scaffolding based on likelihood of genome assemblies computed using generative models for sequencing.</p>
<p><a href="https://atifrahman.github.io/SWALO/swalo-0.9.7-beta.tar.gz"><strong>Download</strong></a></p>
<p><strong>Git repository of SWALO is at <a href="https://github.com/atifrahman/SWALO">https://github.com/atifrahman/SWALO</a>.</strong></p><p>Address of the bookmark: <a href="https://atifrahman.github.io/SWALO/" rel="nofollow">https://atifrahman.github.io/SWALO/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35540/hinge-long-read-assembly-achieves-optimal-repeat-resolution</guid>
	<pubDate>Wed, 07 Feb 2018 09:40:22 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35540/hinge-long-read-assembly-achieves-optimal-repeat-resolution</link>
	<title><![CDATA[HINGE: Long-Read Assembly Achieves Optimal Repeat Resolution]]></title>
	<description><![CDATA[<p>Software accompanying "HINGE: Long-Read Assembly Achieves Optimal Repeat Resolution"</p>
<ul>
<li>
<p>Preprint:&nbsp;<a href="http://biorxiv.org/content/early/2016/08/01/062117">http://biorxiv.org/content/early/2016/08/01/062117</a></p>
</li>
<li>
<p>Paper:&nbsp;<a href="http://genome.cshlp.org/content/27/5/747.full">http://genome.cshlp.org/content/27/5/747.full</a></p>
</li>
<li>
<p>An ipython notebook to reproduce results in the paper can be found in this&nbsp;<a href="https://github.com/govinda-kamath/HINGE-analyses">repository</a>.</p>
</li>
</ul>
<p>HINGE is an OLC(Overlap-Layout-Consensus) assembler. The idea of the pipeline is shown below.</p>
<p><a href="https://github.com/HingeAssembler/HINGE/blob/master/misc/High_level_overview.png" target="_blank"><img src="https://github.com/HingeAssembler/HINGE/raw/master/misc/High_level_overview.png" alt="image" style="border: 0px;"></a></p><p>Address of the bookmark: <a href="https://github.com/HingeAssembler/HINGE" rel="nofollow">https://github.com/HingeAssembler/HINGE</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/42626/spades-team-announce-new-version-spades-v315</guid>
	<pubDate>Fri, 15 Jan 2021 10:24:27 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/42626/spades-team-announce-new-version-spades-v315</link>
	<title><![CDATA[SPADes team announce new version SPADes v3.15]]></title>
	<description><![CDATA[<p>New SPAdes 3.15.0.0. announced by the SPADes team This release includes such new features as:&nbsp;<br />- CoronaSPAdes pipeline for the assembly of transcriptomic and metatranscriptomic data of full-length coronaviridae genomes;&nbsp;<br />- Meta-Viral and RNA-Viral pipelines for metagenomic and metatranscriptomic data defining viral genomes;&nbsp;<br />-New trusted contiguous use algorithm;&nbsp;<br />-Switched to the memory allocator mimalloc;&nbsp;<br />- PlasmidSPAdes and bgcSPAdes are now provided as an input assembly graph;&nbsp;<br />- Important improvements and corrections to the metaplasmid pipeline;&nbsp;<br />- Multiple performance improvements in procedures for simplification and repeat resolving.&nbsp;<br />Please, consider updating.</p><p>Check out more at&nbsp;https://cab.spbu.ru/software/spades/</p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/33960/mgra-breakpoint-graphs-and-ancestral-genome-reconstructions</guid>
	<pubDate>Tue, 25 Jul 2017 08:48:25 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/33960/mgra-breakpoint-graphs-and-ancestral-genome-reconstructions</link>
	<title><![CDATA[MGRA: Breakpoint graphs and ancestral genome reconstructions]]></title>
	<description><![CDATA[<p>MGRA (Multiple Genome Rearrangements and Ancestors) is a tool for reconstruction of ancestor genomes and evolutionary history of extant genomes.</p>
<p>It takes as an input a set of genomes represented as sequences of genes (or synteny blocks) and produces such sequences for ancestral genomes at the internal nodes of the phylogenetic tree.</p>
<p>The phylogenetic tree may be also specified completely or partially, in the latter case MGRA can reconstruct conserved ancestral regions (CARs) of the ancestral genome of interest.</p>
<p>Since version 2 MGRA supports gene insertion and deletions in addition to genome rearrangements and allows the input genomes to have different gene content.</p>
<p>It also can reconstruct most plausible phylogenetic tree based on the rearrangement characters.</p><p>Address of the bookmark: <a href="http://mgra.cblab.org/" rel="nofollow">http://mgra.cblab.org/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34567/jobtree-based-python-wrapper-to-run-the-genome-simulation-tool-suite-evolver</guid>
	<pubDate>Fri, 08 Dec 2017 16:26:32 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34567/jobtree-based-python-wrapper-to-run-the-genome-simulation-tool-suite-evolver</link>
	<title><![CDATA[jobTree based python wrapper to run the genome simulation tool suite Evolver]]></title>
	<description><![CDATA[<p><span>evolverSimControl</span><span>&nbsp;(</span><span>eSC</span><span>) can be used to simulate multi-chromosome genome evolution on an arbitrary phylogeny (</span><a href="http://evolution.genetics.washington.edu/phylip/newicktree.html">Newick format</a><span>). In addition to simply running evolver,&nbsp;</span><span>eSC</span><span>&nbsp;also automatically creates statistical summaries of the simulation as it runs including text and image files. Also included are convenience scripts to: check on a running simulation and see detailed status and logging information; extract fasta sequence files from the leaf nodes of a completed simulation; extract pairwise multiple alignment files (</span><a href="http://genome.ucsc.edu/FAQ/FAQformat.html#format5">.maf</a><span>) from leaf and branch nodes from a completed simulation and with the help of&nbsp;</span><a href="https://github.com/dentearl/mafTools/">mafJoin</a><span>, join them together into a single maf covering the entire simulation.</span></p><p>Address of the bookmark: <a href="https://github.com/dentearl/evolverSimControl" rel="nofollow">https://github.com/dentearl/evolverSimControl</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34620/mash-fast-genome-and-metagenome-distance-estimation-using-minhash</guid>
	<pubDate>Tue, 12 Dec 2017 17:30:12 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34620/mash-fast-genome-and-metagenome-distance-estimation-using-minhash</link>
	<title><![CDATA[Mash: fast genome and metagenome distance estimation using MinHash]]></title>
	<description><![CDATA[<p>Mash is normally distributed as a dependency-free binary for Linux or OSX (see&nbsp;<a href="https://github.com/marbl/Mash/releases">https://github.com/marbl/Mash/releases</a>). This source distribution is intended for other operating systems or for development. Mash requires c++11 to build, which is available in and GCC &gt;= 4.8 and OSX &gt;= 10.7.</p>
<p>See&nbsp;<a href="http://mash.readthedocs.org/">http://mash.readthedocs.org</a>&nbsp;for more information.</p><p>Address of the bookmark: <a href="https://github.com/marbl/Mash/releases" rel="nofollow">https://github.com/marbl/Mash/releases</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35135/alitv%E2%80%94interactive-visualization-of-whole-genome-comparisons</guid>
	<pubDate>Wed, 10 Jan 2018 07:08:17 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35135/alitv%E2%80%94interactive-visualization-of-whole-genome-comparisons</link>
	<title><![CDATA[AliTV—interactive visualization of whole genome comparisons]]></title>
	<description><![CDATA[<p>AliTV, which provides interactive visualization of whole genome alignments. AliTV reads multiple whole genome alignments or automatically generates alignments from the provided data. Optional feature annotations and phylo- genetic information are supported. The user-friendly, web-browser based and highly customizable interface allows rapid exploration and manipulation of the visualized data as well as the export of publication-ready high-quality figures. AliTV is freely available at&nbsp;<a href="https://github.com/AliTVTeam/AliTV">https://github.com/AliTVTeam/AliTV</a></p>
<p>https://alitvteam.github.io/AliTV/</p><p>Address of the bookmark: <a href="https://github.com/AliTVTeam/AliTV" rel="nofollow">https://github.com/AliTVTeam/AliTV</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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