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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/34618?offset=270</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38743/molinspiration-broad-range-of-cheminformatics-software-tools-supporting-molecule-manipulation</guid>
	<pubDate>Sun, 20 Jan 2019 05:32:40 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38743/molinspiration-broad-range-of-cheminformatics-software-tools-supporting-molecule-manipulation</link>
	<title><![CDATA[molinspiration: broad range of cheminformatics software tools supporting molecule manipulation]]></title>
	<description><![CDATA[<p><span>Molinspiration offers&nbsp;</span><a href="https://www.molinspiration.com/products.html">broad range of cheminformatics software tools</a><span>&nbsp;supporting molecule manipulation and processing, including SMILES and SDfile conversion, normalization of molecules, generation of tautomers, molecule fragmentation, calculation of various molecular properties needed in QSAR, molecular modelling and drug design, high quality molecule depiction, molecular database tools supporting substructure and similarity searches. Our products support also fragment-based virtual screening, bioactivity prediction and data visualization. Molinspiration tools are written in Java, therefore can be used practically on any computer platform.</span></p><p>Address of the bookmark: <a href="https://www.molinspiration.com/" rel="nofollow">https://www.molinspiration.com/</a></p>]]></description>
	<dc:creator>BioJoker</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42359/dnasp-dna-sequence-polymorphism-is-a-software-package-for-the-analysis-of-dna-polymorphisms</guid>
	<pubDate>Wed, 25 Nov 2020 19:51:38 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42359/dnasp-dna-sequence-polymorphism-is-a-software-package-for-the-analysis-of-dna-polymorphisms</link>
	<title><![CDATA[DnaSP: DNA Sequence Polymorphism, is a software package for the analysis of DNA polymorphisms]]></title>
	<description><![CDATA[<p><span>DnaSP, DNA Sequence Polymorphism, is a software package for the analysis of DNA polymorphisms using data from a single locus (a multiple sequence aligned -MSA data), or from several loci (a Multiple-MSA data, such as formats generated by some assembler RAD-seq software). DnaSP can estimate several measures of DNA sequence variation within and between populations in noncoding, synonymous or nonsynonymous sites, or in various sorts of codon positions), as well as linkage disequilibrium, recombination, gene flow and gene conversion parameters.</span></p><p>Address of the bookmark: <a href="http://www.ub.edu/dnasp/" rel="nofollow">http://www.ub.edu/dnasp/</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43766/genometools-the-versatile-open-source-genome-analysis-software</guid>
	<pubDate>Wed, 02 Feb 2022 04:00:21 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43766/genometools-the-versatile-open-source-genome-analysis-software</link>
	<title><![CDATA[GenomeTools: The versatile open source genome analysis software]]></title>
	<description><![CDATA[<p>The&nbsp;<em>GenomeTools</em>&nbsp;genome analysis system is a&nbsp;<a href="http://genometools.org/license.html">free</a>&nbsp;collection of bioinformatics&nbsp;<a href="http://genometools.org/tools.html">tools</a>&nbsp;(in the realm of genome informatics) combined into a single binary named&nbsp;<em>gt</em>. It is based on a C library named &ldquo;libgenometools&rdquo; which consists of several modules.</p>
<p><img src="http://genometools.org/images/annotation.png" alt="image" style="border: 0px;"></p>
<p>If you are interested in gene prediction, have a look at&nbsp;<a href="http://genomethreader.org/" title="GenomeThreader gene prediction        software"><em>GenomeThreader</em></a>.</p>
<p>http://genometools.org/pub/</p><p>Address of the bookmark: <a href="http://genometools.org/" rel="nofollow">http://genometools.org/</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44491/cgviewjs-is-a-circular-genome-viewing-tool</guid>
	<pubDate>Wed, 27 Mar 2024 11:16:24 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44491/cgviewjs-is-a-circular-genome-viewing-tool</link>
	<title><![CDATA[CGView.js is a Circular Genome Viewing tool]]></title>
	<description><![CDATA[<p>CGView.js is a&nbsp;<span>C</span>ircular&nbsp;<span>G</span>enome&nbsp;<span>View</span>ing tool for visualizing and interacting with small genomes. This software is an adaptation of the Java program&nbsp;<a href="https://paulstothard.github.io/cgview/">CGView</a>.</p>
<div>
<p>CGView.js is the genome viewer of Proksee, an expert system for genome assembly, annotation and visualization.</p>
<a href="https://proksee.ca/"></a></div>
<h1 id="features">Features</h1>
<ul>
<li>
<p>Circular and linear views of genomes</p>
</li>
<li>
<p>Capable of drawing genomes up to 10 Mbp with 1000's of features and 100's contigs</p>
</li>
<li>
<p>Smooth zooming down to the sequence level</p>
</li>
<li>
<p>Easily generate features and plots directly form the sequence (e.g. ORFs, GC-content and GC-Skew)</p>
</li>
<li>
<p>Save high resolution PNG maps up to 8000x8000px</p>
</li>
<li>
<p>Fully documented API for interacting with CGView.js maps</p>
</li>
</ul><p>Address of the bookmark: <a href="https://js.cgview.ca/" rel="nofollow">https://js.cgview.ca/</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/33847/omega2-metagenome-assembly-pipeline</guid>
	<pubDate>Mon, 10 Jul 2017 05:56:07 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/33847/omega2-metagenome-assembly-pipeline</link>
	<title><![CDATA[Omega2: metagenome assembly pipeline]]></title>
	<description><![CDATA[<p><span>Omega found overlaps between reads using a prefix/suffix hash table. The overlap graph of reads was simplified by removing transitive edges and trimming short branches. Unitigs were generated based on minimum cost flow analysis of the overlap graph and then merged to contigs and scaffolds using mate-pair information. In comparison with three de Bruijn graph assemblers (SOAPdenovo, IDBA-UD and MetaVelvet), Omega provided comparable overall performance on a HiSeq 100-bp dataset and superior performance on a MiSeq 300-bp dataset. In comparison with Celera on the MiSeq dataset, Omega provided more continuous assemblies overall using a fraction of the computing time of existing overlap-layout-consensus assemblers. This indicates Omega can more efficiently assemble longer Illumina reads, and at deeper coverage, for metagenomic datasets.</span></p><p>Address of the bookmark: <a href="http://omega.omicsbio.org/" rel="nofollow">http://omega.omicsbio.org/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35762/genome-assembly-stats-plotting</guid>
	<pubDate>Wed, 28 Feb 2018 03:45:39 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35762/genome-assembly-stats-plotting</link>
	<title><![CDATA[Genome assembly stats plotting]]></title>
	<description><![CDATA[<p>A&nbsp;<em>de novo</em>&nbsp;genome assembly can be summarised b</p>
<p>y a number of metrics, including:</p>
<ul>
<li>Overall assembly length</li>
<li>Number of scaffolds/contigs</li>
<li>Length of longest scaffold/contig</li>
<li>Scaffold/contig N50 and N90Assembly base composition, in particular percentage GC and percentage Ns</li>
<li>CEGMA completeness</li>
<li>Scaffold/contig length/count distribution</li>
</ul>
<p>assembly-stats supports two widely used presentations of these values, tabular and cumulative length plots, and introduces an additional circular plot that summarises most commonly used assembly metrics in a single visualisation. Each of these presentations is generated using javascript from a common (JSON) data structure, allowing toggling between alternative views, and each can be applied to a single or multiple assemblies to allow direct comparison of alternate assemblies.</p>
<p>Tabular presentation allows direct comparison of exact values between assemblies, the limitations of this approach lie in the necessary omission of distributions and the challenge of interpreting ratios of values that may vary by several orders of magnitude.</p><p>Address of the bookmark: <a href="https://github.com/rjchallis/assembly-stats" rel="nofollow">https://github.com/rjchallis/assembly-stats</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/37291/transrate-understanding-your-transcriptome-assembly</guid>
	<pubDate>Fri, 13 Jul 2018 07:49:26 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37291/transrate-understanding-your-transcriptome-assembly</link>
	<title><![CDATA[transrate: Understanding your transcriptome assembly]]></title>
	<description><![CDATA[<p><span>Transrate is software for&nbsp;</span><em>de-novo</em><span>&nbsp;transcriptome assembly quality analysis. It examines your assembly in detail and compares it to experimental evidence such as the sequencing reads, reporting quality scores for contigs and assemblies. This allows you to choose between assemblers and parameters, filter out the bad contigs from an assembly, and help decide when to stop trying to improve the assembly.</span></p><p>Address of the bookmark: <a href="http://hibberdlab.com/transrate/index.html" rel="nofollow">http://hibberdlab.com/transrate/index.html</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37785/haplomerger2-rebuilding-both-haploid-sub-assemblies-from-high-heterozygosity-diploid-genome-assembly</guid>
	<pubDate>Thu, 27 Sep 2018 07:08:47 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37785/haplomerger2-rebuilding-both-haploid-sub-assemblies-from-high-heterozygosity-diploid-genome-assembly</link>
	<title><![CDATA[HaploMerger2: rebuilding both haploid sub-assemblies from high-heterozygosity diploid genome assembly]]></title>
	<description><![CDATA[<p><span><span>HM2 can process any diploid assemblies, but it is especially suitable for diploid assemblies with high heterozygosity (&ge;3%), which can be difficult for other tools. This pipeline also implements flexible and sensitive assembly error detection, a hierarchical scaffolding procedure and a reliable gap-closing method for haploid sub-assemblies.</span></span></p>
<p><span>Source code, executables and the testing dataset are freely available at&nbsp;</span><a href="https://github.com/mapleforest/HaploMerger2/releases/" target="">https://github.com/mapleforest/HaploMerger2/releases/</a><span>.</span></p><p>Address of the bookmark: <a href="https://github.com/mapleforest/HaploMerger2/releases/" rel="nofollow">https://github.com/mapleforest/HaploMerger2/releases/</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38063/referee-genome-assembly-quality-scores</guid>
	<pubDate>Sun, 04 Nov 2018 16:44:30 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38063/referee-genome-assembly-quality-scores</link>
	<title><![CDATA[Referee: Genome assembly quality scores]]></title>
	<description><![CDATA[<p>Modern genome sequencing technologies provide a succint measure of quality at each position in every read, however all of this information is lost in the assembly process. Referee summarizes the quality information from the reads that map to a site in an assembled genome to calculate a quality score for each position in the genome assembly.</p>
<p>We accomplish this by first calculating genotype likelihoods for every site. For a given site in a diploid genome, there are 10 possible genotypes (AA, AC, AG, AT, CC, CG, CT, GG, GT, TT). Referee takes as input the genotype likelihoods calculated for all 10 genotypes given the called reference base at each position.</p>
<h3>Referee is a program to calculate a quality score for every position in a genome assembly. This allows for easy filtering of low quality sites for any downstream analysis.</h3>
<p>https://github.com/gwct/referee</p><p>Address of the bookmark: <a href="https://gwct.github.io/referee/#" rel="nofollow">https://gwct.github.io/referee/#</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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