<?xml version='1.0'?><rss version="2.0" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:georss="http://www.georss.org/georss" xmlns:atom="http://www.w3.org/2005/Atom" >
<channel>
	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/26309?offset=910</link>
	<atom:link href="https://bioinformaticsonline.com/related/26309?offset=910" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38515/genome-annotation-using-maker-tutorial</guid>
	<pubDate>Thu, 20 Dec 2018 17:39:23 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38515/genome-annotation-using-maker-tutorial</link>
	<title><![CDATA[Genome Annotation using MAKER tutorial !]]></title>
	<description><![CDATA[<p><a href="http://www.yandell-lab.org/software/maker.html">MAKER</a><span>&nbsp;is a great tool for annotating a reference genome using empirical and&nbsp;</span><em>ab initio</em><span>gene predictions.&nbsp;</span><a href="http://gmod.org/wiki/Main_Page">GMOD</a><span>, the umbrella organization that includes MAKER, has some nice tutorials online for running MAKER. However, these were quite simplified examples and it took a bit of effort to wrap my head completely around everything. Here I will describe a&nbsp;</span><em>de novo</em><span>&nbsp;genome annotation for&nbsp;</span><em>Boa constrictor</em><span>&nbsp;in detail, so that there is a record and that it is easy to use this as a guide to annotate any genome.</span></p><p>Address of the bookmark: <a href="https://www.biostars.org/p/261203/" rel="nofollow">https://www.biostars.org/p/261203/</a></p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/28303/fancy-oneliner-for-bioinformatics</guid>
	<pubDate>Thu, 07 Jul 2016 12:05:50 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/28303/fancy-oneliner-for-bioinformatics</link>
	<title><![CDATA[Fancy Oneliner for Bioinformatics !!]]></title>
	<description><![CDATA[<p><span>This webpage lists some of the one-liners that we frequently use in metagenomic analyses. You can click on the following links to browse through different topics. You can copy/paste the commands as they are in your terminal screen, provided you follow the same naming conventions and folder structures as we have. We are sharing these codes with the intention that if they are useful and help you in your analyses, then we will be appropriately credited as considerable effort has been put into devising them.</span></p><p>Address of the bookmark: <a href="http://userweb.eng.gla.ac.uk/umer.ijaz/bioinformatics/oneliners.html" rel="nofollow">http://userweb.eng.gla.ac.uk/umer.ijaz/bioinformatics/oneliners.html</a></p>]]></description>
	<dc:creator>Poonam Mahapatra</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41571/wego-simple-but-useful-tool-for-visualizing-comparing-and-plotting-go-gene-ontology-annotation-results</guid>
	<pubDate>Sun, 12 Apr 2020 10:02:22 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41571/wego-simple-but-useful-tool-for-visualizing-comparing-and-plotting-go-gene-ontology-annotation-results</link>
	<title><![CDATA[WEGO : simple but useful tool for visualizing, comparing and plotting GO (Gene Ontology) annotation results]]></title>
	<description><![CDATA[<p><span>WEGO (Web Gene Ontology Annotation Plot) is a simple but useful tool for visualizing, comparing and plotting GO (Gene Ontology) annotation results. As the GO vocabulary became more and more popular, WEGO was widely adopted and used in many researches. Therefore we have updated WEGO 2.0 in 2018. Here are some changes we&rsquo;ve made:</span><br><span>1. The limit of input file numbers was cancelled. Now the users could upload as many files as they want with one operation.</span><br><span>2. We have added the reference data of 9 species for users selection.</span><br><span>3. Besides the traditional WEGO histogram, WEGO 2.0 outputs an additional type of bar graph showing GO terms with significant gene number differences.</span></p><p>Address of the bookmark: <a href="http://wego.genomics.org.cn/" rel="nofollow">http://wego.genomics.org.cn/</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/28554/megan6</guid>
	<pubDate>Mon, 25 Jul 2016 05:45:22 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/28554/megan6</link>
	<title><![CDATA[MEGAN6]]></title>
	<description><![CDATA[<p>Microbiome analysis using a single application</p>
<p>MEGAN6 is a comprehensive toolbox for interactively analyzing microbiome data. All the interactive tools you need in one application.</p>
<ul>
<li>Taxonomic analysis using the NCBI taxonomy or a customized taxonomy such as SILVA</li>
<li>Functional analysis using InterPro2GO, SEED, eggNOG or KEGG</li>
<li>Bar charts, word clouds, Voronoi tree maps and many other charts</li>
<li>PCoA, clustering and networks</li>
<li>Supports metadata</li>
<li>MEGAN parses many different types of input</li>
</ul>
<p>Why use MEGAN6?</p>
<div>&nbsp;The software is:</div>
<div><ol>
<li>Easy to use. MEGAN6 is a single application and all features are available through menus, toolbars and graphics. No scripting skills required.</li>
<li>Powerful. MEGAN6 allows you to work with hundreds of samples containing&nbsp;hundreds of millions of sequencing reads. Blast-like analysis can be performed using DIAMOND.</li>
<li>Comprehensive. MEGAN6 offers a large range of analysis tools, and is under active development.</li>
</ol></div><p>Address of the bookmark: <a href="https://ab.inf.uni-tuebingen.de/software/megan6" rel="nofollow">https://ab.inf.uni-tuebingen.de/software/megan6</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38579/genomeview-genome-browser-and-annotation-editor</guid>
	<pubDate>Wed, 02 Jan 2019 04:09:06 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38579/genomeview-genome-browser-and-annotation-editor</link>
	<title><![CDATA[GenomeView: genome browser and annotation editor]]></title>
	<description><![CDATA[<p><span>GenomeView is a genome browser and annotation editor that displays reference sequence, annotation, multiple alignments, short read alignments and graphs. Most major data formats are supported. Local and internet files can be loaded.</span><br><span>This project has moved to GitHub:&nbsp;</span><a href="https://github.com/GenomeView/genomeview" target="_blank">https://github.com/GenomeView/genomeview</a></p><p>Address of the bookmark: <a href="https://sourceforge.net/projects/genomeview/" rel="nofollow">https://sourceforge.net/projects/genomeview/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43062/jcvi-utility-libraries</guid>
	<pubDate>Sat, 08 May 2021 22:04:02 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43062/jcvi-utility-libraries</link>
	<title><![CDATA[JCVI utility libraries]]></title>
	<description><![CDATA[<p><span>Collection of Python libraries to parse bioinformatics files, or perform computation related to assembly, annotation, and comparative genomics.</span></p><p>Address of the bookmark: <a href="https://github.com/tanghaibao/jcvi" rel="nofollow">https://github.com/tanghaibao/jcvi</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44902/hite-a-fast-and-accurate-dynamic-boundary-adjustment-approach-for-full-length-transposable-elements-detection-and-annotation-in-genome-assemblies</guid>
	<pubDate>Sat, 20 Sep 2025 09:34:04 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44902/hite-a-fast-and-accurate-dynamic-boundary-adjustment-approach-for-full-length-transposable-elements-detection-and-annotation-in-genome-assemblies</link>
	<title><![CDATA[HiTE: a fast and accurate dynamic boundary adjustment approach for full-length Transposable Elements detection and annotation in Genome Assemblies]]></title>
	<description><![CDATA[<p dir="auto"><code>HiTE</code>&nbsp;is a Python software that uses a dynamic boundary adjustment approach to detect and annotate full-length Transposable Elements in Genome Assemblies. In comparison to other tools, HiTE demonstrates superior performance in detecting a greater number of full-length TEs.</p>
<div dir="auto">
<h2 dir="auto">panHiTE</h2>
<a href="https://github.com/CSU-KangHu/HiTE#panhite"></a></div>
<p dir="auto">We have developed panHiTE, a comprehensive and accurate pipeline for TE detection in large-scale population genomes. It has been successfully applied to hundreds of plant population genomes, demonstrating its effectiveness and scalability.</p>
<p dir="auto">For detailed instructions, please refer to the&nbsp;<a href="https://github.com/CSU-KangHu/HiTE/wiki/panHiTE-tutorial">panHiTE tutorial</a>.</p><p>Address of the bookmark: <a href="https://github.com/CSU-KangHu/HiTE" rel="nofollow">https://github.com/CSU-KangHu/HiTE</a></p>]]></description>
	<dc:creator>LEGE</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/pages/view/34418/spades-hybrid-genome-assembly</guid>
	<pubDate>Mon, 27 Nov 2017 08:05:40 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/34418/spades-hybrid-genome-assembly</link>
	<title><![CDATA[SPAdes hybrid genome assembly]]></title>
	<description><![CDATA[<p>When you have both Illumina and Nanopore data, then SPAdes remains a good option for hybrid assembly - SPAdes was used to produce the&nbsp;<a href="https://gigascience.biomedcentral.com/articles/10.1186/s13742-015-0101-6">B fragilis assembly</a>&nbsp;by Mick Watson&rsquo;s group.</p><p>Again, running spades.py will show you the options:</p><div><pre><code>spades.py
</code></pre></div><p>This produces:</p><div><pre><code>SPAdes genome assembler v3.10.1

Usage: /usr/local/SPAdes-3.10.1-Linux/bin/spades.py [options] -o &lt;output_dir&gt;

Basic options:
-o      &lt;output_dir&gt;    directory to store all the resulting files (required)
--sc                    this flag is required for MDA (single-cell) data
--meta                  this flag is required for metagenomic sample data
--rna                   this flag is required for RNA-Seq data
--plasmid               runs plasmidSPAdes pipeline for plasmid detection
--iontorrent            this flag is required for IonTorrent data
--test                  runs SPAdes on toy dataset
-h/--help               prints this usage message
-v/--version            prints version

Input data:
--12    &lt;filename&gt;      file with interlaced forward and reverse paired-end reads
-1      &lt;filename&gt;      file with forward paired-end reads
-2      &lt;filename&gt;      file with reverse paired-end reads
-s      &lt;filename&gt;      file with unpaired reads
--pe&lt;#&gt;-12      &lt;filename&gt;      file with interlaced reads for paired-end library number &lt;#&gt; (&lt;#&gt; = 1,2,..,9)
--pe&lt;#&gt;-1       &lt;filename&gt;      file with forward reads for paired-end library number &lt;#&gt; (&lt;#&gt; = 1,2,..,9)
--pe&lt;#&gt;-2       &lt;filename&gt;      file with reverse reads for paired-end library number &lt;#&gt; (&lt;#&gt; = 1,2,..,9)
--pe&lt;#&gt;-s       &lt;filename&gt;      file with unpaired reads for paired-end library number &lt;#&gt; (&lt;#&gt; = 1,2,..,9)
--pe&lt;#&gt;-&lt;or&gt;    orientation of reads for paired-end library number &lt;#&gt; (&lt;#&gt; = 1,2,..,9; &lt;or&gt; = fr, rf, ff)
--s&lt;#&gt;          &lt;filename&gt;      file with unpaired reads for single reads library number &lt;#&gt; (&lt;#&gt; = 1,2,..,9)
--mp&lt;#&gt;-12      &lt;filename&gt;      file with interlaced reads for mate-pair library number &lt;#&gt; (&lt;#&gt; = 1,2,..,9)
--mp&lt;#&gt;-1       &lt;filename&gt;      file with forward reads for mate-pair library number &lt;#&gt; (&lt;#&gt; = 1,2,..,9)
--mp&lt;#&gt;-2       &lt;filename&gt;      file with reverse reads for mate-pair library number &lt;#&gt; (&lt;#&gt; = 1,2,..,9)
--mp&lt;#&gt;-s       &lt;filename&gt;      file with unpaired reads for mate-pair library number &lt;#&gt; (&lt;#&gt; = 1,2,..,9)
--mp&lt;#&gt;-&lt;or&gt;    orientation of reads for mate-pair library number &lt;#&gt; (&lt;#&gt; = 1,2,..,9; &lt;or&gt; = fr, rf, ff)
--hqmp&lt;#&gt;-12    &lt;filename&gt;      file with interlaced reads for high-quality mate-pair library number &lt;#&gt; (&lt;#&gt; = 1,2,..,9)
--hqmp&lt;#&gt;-1     &lt;filename&gt;      file with forward reads for high-quality mate-pair library number &lt;#&gt; (&lt;#&gt; = 1,2,..,9)
--hqmp&lt;#&gt;-2     &lt;filename&gt;      file with reverse reads for high-quality mate-pair library number &lt;#&gt; (&lt;#&gt; = 1,2,..,9)
--hqmp&lt;#&gt;-s     &lt;filename&gt;      file with unpaired reads for high-quality mate-pair library number &lt;#&gt; (&lt;#&gt; = 1,2,..,9)
--hqmp&lt;#&gt;-&lt;or&gt;  orientation of reads for high-quality mate-pair library number &lt;#&gt; (&lt;#&gt; = 1,2,..,9; &lt;or&gt; = fr, rf, ff)
--nxmate&lt;#&gt;-1   &lt;filename&gt;      file with forward reads for Lucigen NxMate library number &lt;#&gt; (&lt;#&gt; = 1,2,..,9)
--nxmate&lt;#&gt;-2   &lt;filename&gt;      file with reverse reads for Lucigen NxMate library number &lt;#&gt; (&lt;#&gt; = 1,2,..,9)
--sanger        &lt;filename&gt;      file with Sanger reads
--pacbio        &lt;filename&gt;      file with PacBio reads
--nanopore      &lt;filename&gt;      file with Nanopore reads
--tslr  &lt;filename&gt;      file with TSLR-contigs
--trusted-contigs       &lt;filename&gt;      file with trusted contigs
--untrusted-contigs     &lt;filename&gt;      file with untrusted contigs

Pipeline options:
--only-error-correction runs only read error correction (without assembling)
--only-assembler        runs only assembling (without read error correction)
--careful               tries to reduce number of mismatches and short indels
--continue              continue run from the last available check-point
--restart-from  &lt;cp&gt;    restart run with updated options and from the specified check-point ('ec', 'as', 'k&lt;int&gt;', 'mc')
--disable-gzip-output   forces error correction not to compress the corrected reads
--disable-rr            disables repeat resolution stage of assembling

Advanced options:
--dataset       &lt;filename&gt;      file with dataset description in YAML format
-t/--threads    &lt;int&gt;           number of threads
                                [default: 16]
-m/--memory     &lt;int&gt;           RAM limit for SPAdes in Gb (terminates if exceeded)
                                [default: 250]
--tmp-dir       &lt;dirname&gt;       directory for temporary files
                                [default: &lt;output_dir&gt;/tmp]
-k              &lt;int,int,...&gt;   comma-separated list of k-mer sizes (must be odd and
                                less than 128) [default: 'auto']
--cov-cutoff    &lt;float&gt;         coverage cutoff value (a positive float number, or 'auto', or 'off') [default: 'off']
--phred-offset  &lt;33 or 64&gt;      PHRED quality offset in the input reads (33 or 64)
                                [default: auto-detect]
</code></pre></div><p>As you can see this is also a &ldquo;pipeline&rdquo; of tools that can be switched on or off. SPAdes takes quite a long time, so for the purposes of this practical, something like this may suffice:</p><div><pre><code>spades.py -t 4 <span>\</span>
          -m 32 <span>\</span>
          -k 31,51,71 <span>\</span>
          --only-assembler <span>\</span>
          -1 miseq.1.fastq -2 miseq.2.fastq <span>\</span>
          --nanopore minion.fastq <span>\</span>
          -o hybrid_assembly
</code></pre></div><p>In turn, these parameters mean</p><ul>
<li>use 4 threads</li>
<li>max memory is 32Gb</li>
<li>use 3 kmer values to build the de bruijn graph(s) - 31, 51 and 71</li>
<li>only run the assembler, not the correction algorithm (for speed)</li>
<li>read 1 and read 2 of the MiSeq data</li>
<li>the nanopore data</li>
<li>put the output in folder &ldquo;hybrid_assembly&rdquo;</li>
</ul>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36257/aligngraph-algorithm-for-secondary-de-novo-genome-assembly-guided-by-closely-related-references</guid>
	<pubDate>Tue, 17 Apr 2018 16:21:20 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36257/aligngraph-algorithm-for-secondary-de-novo-genome-assembly-guided-by-closely-related-references</link>
	<title><![CDATA[AlignGraph: algorithm for secondary de novo genome assembly guided by closely related references]]></title>
	<description><![CDATA[<p>AlignGraph is a software that extends and joins contigs or scaffolds by reassembling them with help provided by a reference genome of a closely related organism.</p>
<p>Using AlignGraph</p>
<pre><code>AlignGraph --read1 reads_1.fa --read2 reads_2.fa --contig contigs.fa --genome genome.fa --distanceLow distanceLow --distanceHigh distancehigh --extendedContig extendedContigs.fa --remainingContig remainingContigs.fa [--kMer k --insertVariation insertVariation --coverage coverage --part p --fastMap --ratioCheck --iterativeMap --misassemblyRemoval --resume]</code></pre>
<h3>&nbsp;</h3><p>Address of the bookmark: <a href="https://github.com/baoe/AlignGraph" rel="nofollow">https://github.com/baoe/AlignGraph</a></p>]]></description>
	<dc:creator>Manisha Mishra</dc:creator>
</item>

</channel>
</rss>