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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/36954?offset=270</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34482/ribbon-visualizing-complex-genome-alignments-and-structural-variation</guid>
	<pubDate>Wed, 29 Nov 2017 07:40:22 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34482/ribbon-visualizing-complex-genome-alignments-and-structural-variation</link>
	<title><![CDATA[Ribbon: Visualizing complex genome alignments and structural variation:]]></title>
	<description><![CDATA[<p>Ribbon can be used for long reads, short reads, paired-end reads, and assembly/genome alignments. Instructions for each data format are available by clicking on "instructions" in each tab on the right.</p>
<p>Local installation:</p>
<p>You can install Ribbon locally from Github by following the instructions here:&nbsp;<a href="https://github.com/MariaNattestad/ribbon" target="_blank">https://github.com/MariaNattestad/Ribbon</a></p><p>Address of the bookmark: <a href="http://genomeribbon.com/" rel="nofollow">http://genomeribbon.com/</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/35131/giggle-a-search-engine-for-large-scale-integrated-genome-analysis</guid>
	<pubDate>Wed, 10 Jan 2018 03:10:45 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35131/giggle-a-search-engine-for-large-scale-integrated-genome-analysis</link>
	<title><![CDATA[GIGGLE: a search engine for large-scale integrated genome analysis]]></title>
	<description><![CDATA[<p><span>GIGGLE is a genomics search engine that identifies and ranks the significance of genomic loci shared between query features and thousands of genome interval files. GIGGLE (</span><a href="https://github.com/ryanlayer/giggle">https://github.com/ryanlayer/giggle</a><span>) scales to billions of intervals and is over three orders of magnitude faster than existing methods. Its speed extends the accessibility and utility of resources such as ENCODE, Roadmap Epigenomics, and GTEx by facilitating data integration and hypothesis generation.</span></p>
<p>https://www.nature.com/articles/nmeth.4556</p><p>Address of the bookmark: <a href="https://github.com/ryanlayer/giggle" rel="nofollow">https://github.com/ryanlayer/giggle</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35543/genometools-the-versatile-open-source-genome-analysis-software</guid>
	<pubDate>Wed, 07 Feb 2018 10:44:18 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35543/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>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>Address of the bookmark: <a href="http://genometools.org/" rel="nofollow">http://genometools.org/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36516/metassembler-merging-and-optimizing-de-novo-genome-assemblies</guid>
	<pubDate>Tue, 08 May 2018 04:52:33 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36516/metassembler-merging-and-optimizing-de-novo-genome-assemblies</link>
	<title><![CDATA[Metassembler: merging and optimizing de novo genome assemblies]]></title>
	<description><![CDATA[<p><span>Metassembler combines multiple whole genome de novo assemblies into a combined consensus assembly using the best segments of the individual assemblies.</span></p>
<p><span><span>Genome assembly projects typically run multiple algorithms in an attempt to find the single best assembly, although those assemblies often have complementary, if untapped, strengths and weaknesses. We present our metassembler algorithm that merges multiple assemblies of a genome into a single superior sequence.&nbsp;</span></span></p><p>Address of the bookmark: <a href="https://sourceforge.net/projects/metassembler/?source=directory" rel="nofollow">https://sourceforge.net/projects/metassembler/?source=directory</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37239/kat-a-k-mer-analysis-toolkit-to-quality-control-ngs-datasets-and-genome-assemblies</guid>
	<pubDate>Fri, 06 Jul 2018 03:36:45 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37239/kat-a-k-mer-analysis-toolkit-to-quality-control-ngs-datasets-and-genome-assemblies</link>
	<title><![CDATA[KAT: a K-mer analysis toolkit to quality control NGS datasets and genome assemblies]]></title>
	<description><![CDATA[<p>KAT is a suite of tools that analyse jellyfish hashes or sequence files (fasta or fastq) using kmer counts. The following tools are currently available in KAT:</p>
<ul>
<li><span>hist</span>: Create an histogram of k-mer occurrences from a sequence file. Adds metadata in output for easy plotting.</li>
<li><span>gcp:</span>&nbsp;K-mer GC Processor. Creates a matrix of the number of K-mers found given a GC count and a K-mer count.</li>
<li><span>comp</span>: K-mer comparison tool. Creates a matrix of shared K-mers between two (or three) sequence files or hashes.</li>
<li><span>sect</span>: SEquence Coverage estimator Tool. Estimates the coverage of each sequence in a file using K-mers from another sequence file.</li>
<li><span>blob</span>: Given, reads and an assembly, calculates both the read and assembly K-mer coverage along with GC% for each sequence in the assembly.SEquence Coverage estimator Tool.</li>
<li><span>filter</span>: Filtering tools. Contains tools for filtering k-mer hashes and FastQ/A files:
<ul>
<li><span>kmer</span>: Produces a k-mer hash containing only k-mers within specified coverage and GC tolerances.</li>
<li><span>seq</span>: Filters a sequence file based on whether or not the sequences contain k-mers within a provided hash.</li>
</ul>
</li>
<li><span>plot</span>: Plotting tools. Contains several plotting tools to visualise K-mer and compare distributions. The following plot tools are available:
<ul>
<li><span>density</span>: Creates a density plot from a matrix created with the "comp" tool. Typically this is used to compare two K-mer hashes produced by different NGS reads.</li>
<li><span>profile</span>: Creates a K-mer coverage plot for a single sequence. Takes in fasta coverage output coverage from the "sect" tool</li>
<li><span>spectra-cn</span>: Creates a stacked histogram using a matrix created with the "comp" tool. Typically this is used to compare a jellyfish hash produced from a read set to a jellyfish hash produced from an assembly. The plot shows the amount of distinct K-mers absent, as well as the copy number variation present within the assembly.</li>
<li><span>spectra-hist</span>: Creates a K-mer spectra plot for a set of K-mer histograms produced either by jellyfish-histo or kat-histo.</li>
<li><span>spectra-mx</span>: Creates a K-mer spectra plot for a set of K-mer histograms that are derived from selected rows or columns in a matrix produced by the "comp".</li>
</ul>
</li>
</ul>
<p>In addition, KAT contains a python script for analysing the mathematical distributions present in the K-mer spectra in order to determine how much content is present in each peak.</p>
<p>This README only contains some brief details of how to install and use KAT. For more extensive documentation please visit:&nbsp;<a href="https://kat.readthedocs.org/en/latest/">https://kat.readthedocs.org/en/latest/</a></p>
<p><a href="https://academic.oup.com/bioinformatics/article/33/4/574/2664339">https://academic.oup.com/bioinformatics/article/33/4/574/2664339&nbsp;</a></p><p>Address of the bookmark: <a href="https://github.com/TGAC/KAT" rel="nofollow">https://github.com/TGAC/KAT</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/37411/my-commonly-used-commands-in-bioinformatics</guid>
	<pubDate>Thu, 26 Jul 2018 04:58:45 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/37411/my-commonly-used-commands-in-bioinformatics</link>
	<title><![CDATA[My commonly used commands in Bioinformatics]]></title>
	<description><![CDATA[<p>FYI, I've found it useful to use MUMmer to extract the specific changes that Racon makes, so I can evaluate them individually:</p><pre><code>minimap -t 24 assembly.fasta long_reads.fastq.gz | racon -t 24 long_reads.fastq.gz - assembly.fasta racon_assembly.fasta
nucmer -p nucmer assembly.fasta racon_assembly.fasta
show-snps -C -T -r nucmer.delta
</code></pre><p>This reports Racon's changes in a table. You can exclude indels with the&nbsp;<code>-I</code>&nbsp;option in&nbsp;<code>show-snps</code>.&nbsp;</p><p>This process (Racon -&gt; MUMmer -&gt; SNP table) solves the problem I originally raised in this issue. So as far as I'm concerned, you can close this issue (or keep it open if you still want to implement some kind of variant table).</p>]]></description>
	<dc:creator>Rahul Nayak</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/38008/quast-lg-versatile-genome-assembly-evaluation</guid>
	<pubDate>Thu, 25 Oct 2018 10:46:55 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38008/quast-lg-versatile-genome-assembly-evaluation</link>
	<title><![CDATA[QUAST-LG: Versatile genome assembly evaluation]]></title>
	<description><![CDATA[<p>QUAST-LG-a tool that compares large genomic de novo assemblies against reference sequences and computes relevant quality metrics. Since genomes generally cannot be reconstructed completely due to complex repeat patterns and low coverage regions, we introduce a concept of upper bound assembly for a given genome and set of reads, and compute theoretical limits on assembly correctness and completeness. Using QUAST-LG, we show how close the assemblies are to the theoretical optimum, and how far this optimum is from the finished reference.</p>
<h4>AVAILABILITY AND IMPLEMENTATION:</h4>
<p>http://cab.spbu.ru/software/quast-lg</p><p>Address of the bookmark: <a href="http://cab.spbu.ru/software/quast-lg/" rel="nofollow">http://cab.spbu.ru/software/quast-lg/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38166/pygenometracks-standalone-program-and-library-to-plot-beautiful-genome-browser-tracks</guid>
	<pubDate>Fri, 09 Nov 2018 12:34:23 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38166/pygenometracks-standalone-program-and-library-to-plot-beautiful-genome-browser-tracks</link>
	<title><![CDATA[pyGenomeTracks: Standalone program and library to plot beautiful genome browser tracks]]></title>
	<description><![CDATA[<p>pyGenomeTracks aims to produce high-quality genome browser tracks that are highly customizable. Currently, it is possible to plot:</p>
<ul>
<li>bigwig</li>
<li>bed (many options)</li>
<li>bedgraph</li>
<li>links (represented as arcs)</li>
<li>Hi-C matrices (if&nbsp;<a href="http://hicexplorer.readthedocs.io/">HiCExplorer</a>&nbsp;is installed)</li>
</ul><p>Address of the bookmark: <a href="https://github.com/deeptools/pyGenomeTracks" rel="nofollow">https://github.com/deeptools/pyGenomeTracks</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>

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