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<channel>
	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/40531?offset=580</link>
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	<description><![CDATA[]]></description>
	
	<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/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/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/35432/mummer4-a-fast-and-versatile-genome-alignment-system</guid>
	<pubDate>Sat, 03 Feb 2018 04:59:17 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35432/mummer4-a-fast-and-versatile-genome-alignment-system</link>
	<title><![CDATA[MUMmer4: A fast and versatile genome alignment system]]></title>
	<description><![CDATA[<p><span>MUMmer4, a substantially improved version of MUMmer that addresses genome size constraints by changing the 32-bit suffix tree data structure at the core of MUMmer to a 48-bit suffix array, and that offers improved speed through parallel processing of input query sequences. With a theoretical limit on the input size of 141Tbp, MUMmer4 can now work with input sequences of any biologically realistic length. We show that as a result of these enhancements, the&nbsp;</span><span>nucmer</span><span>&nbsp;program in MUMmer4 is easily able to handle alignments of large genomes;&nbsp;</span></p><p>Address of the bookmark: <a href="https://mummer4.github.io/" rel="nofollow">https://mummer4.github.io/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36218/g-compass-a-comparative-genome-browser</guid>
	<pubDate>Thu, 12 Apr 2018 10:00:27 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36218/g-compass-a-comparative-genome-browser</link>
	<title><![CDATA[G-compass: a comparative genome browser]]></title>
	<description><![CDATA[<p><span>G-compass (</span><a href="http://www.h-invitational.jp/g-compass/" target="_top">http://www.h-invitational.jp/g-compass/</a><span>) is a comparative genome browser. It visualizes evolutionarily conserved genomic regions between human and other 12 vertebrates based on original genome alignments pursuing higher coverage (1,2). Annotations of human genes/transcripts and their ortholog information were derived from&nbsp;</span><a href="http://www.h-invitational.jp/hinv/ahg-db/index.jsp" target="_top">H-InvDB</a><span>&nbsp;and its subdatabase&nbsp;</span><a href="http://www.h-invitational.jp/evola/" target="_top">Evola</a><span>, respectively. G-compass is available for free of charge. [&nbsp;</span><a href="http://www.h-invitational.jp/g-compass/cgi-bin/gc_main.cgi?species_1=Hg18&amp;species_2=pt2&amp;strand_1=%2B&amp;strand_2=%2B&amp;from_win=main&amp;gen_str=2&amp;chr_1=01&amp;chr_2=01&amp;st_1=103804298&amp;ed_1=104204297&amp;st_2=105235351&amp;ed_2=105635350" target="_top">Sample</a><span>&nbsp;]</span></p><p>Address of the bookmark: <a href="http://www.h-invitational.jp/g-compass/" rel="nofollow">http://www.h-invitational.jp/g-compass/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36635/circlator-automated-circularization-of-genome-assemblies-using-long-sequencing-reads</guid>
	<pubDate>Tue, 15 May 2018 09:42:32 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36635/circlator-automated-circularization-of-genome-assemblies-using-long-sequencing-reads</link>
	<title><![CDATA[Circlator: automated circularization of genome assemblies using long sequencing reads]]></title>
	<description><![CDATA[A tool to circularize genome assemblies. The algorithm and benchmarks are described in the Genome Biology manuscript. 

Citation: "Circlator: automated circularization of genome assemblies using long sequencing reads", Hunt et al, Genome Biology 2015 Dec 29;16(1):294. doi: 10.1186/s13059-015-0849-0. PMID: 26714481.<p>Address of the bookmark: <a href="http://sanger-pathogens.github.io/circlator/" rel="nofollow">http://sanger-pathogens.github.io/circlator/</a></p>]]></description>
	<dc:creator>Poonam Mahapatra</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36935/assemblytics-delta-file-to-analyze-alignments-of-an-assembly-to-another-assembly-or-a-reference-genome</guid>
	<pubDate>Thu, 14 Jun 2018 07:31:00 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36935/assemblytics-delta-file-to-analyze-alignments-of-an-assembly-to-another-assembly-or-a-reference-genome</link>
	<title><![CDATA[assemblytics: delta file to analyze alignments of an assembly to another assembly or a reference genome]]></title>
	<description><![CDATA[Download and install MUMmer
Align your assembly to a reference genome using nucmer (from MUMmer package)
$ nucmer -maxmatch -l 100 -c 500 REFERENCE.fa ASSEMBLY.fa -prefix OUT
Consult the MUMmer manual if you encounter problems

Optional: Gzip the delta file to speed up upload (usually 2-4X faster)
$ gzip OUT.delta
Then use the OUT.delta.gz file for upload.
Upload the .delta or delta.gz file (view example) to Assemblytics
Important: Use only contigs rather than scaffolds from the assembly. This will prevent false positives when the number of Ns in the scaffolded sequence does not match perfectly to the distance in the reference.

The unique sequence length required represents an anchor for determining if a sequence is unique enough to safely call variants from, which is an alternative to the mapping quality filter for read alignment.

http://assemblytics.com/<p>Address of the bookmark: <a href="http://assemblytics.com/" rel="nofollow">http://assemblytics.com/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/36960/links-scaffolder-bloomfilter-setting</guid>
	<pubDate>Fri, 15 Jun 2018 10:39:54 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/36960/links-scaffolder-bloomfilter-setting</link>
	<title><![CDATA[LINKS scaffolder bloomfilter setting !]]></title>
	<description><![CDATA[
<p>➜  bin git:(master) ✗ ls -l<br />total 68<br />drwxrwxr-x 3 urbe urbe  4096 Jun 15 12:15 lib<br />-rwxrwxrwx 1 urbe urbe 65141 Jun 15 17:13 LINKS<br />➜  bin git:(master) ✗ pwd<br />/home/urbe/Tools/LINKS_1.8.6/bin</p>

<p>➜  bloomfilter git:(master) ✗ swig -Wall -c++ -perl5 BloomFilter.i<br />➜  bloomfilter git:(master) ✗ g++ -c BloomFilter_wrap.cxx -I/home/urbe/anaconda3/lib/perl5/5.22.0/x86_64-linux-thread-multi/CORE/ -fPIC -Dbool=char -O3<br />BloomFilter_wrap.cxx:1892:30: fatal error: ../BloomFilter.hpp: No such file or directory<br />compilation terminated.<br />➜  bloomfilter git:(master) ✗ cd swig <br />➜  swig git:(master) ✗ g++ -c BloomFilter_wrap.cxx -I/home/urbe/anaconda3/lib/perl5/5.22.0/x86_64-linux-thread-multi/CORE/ -fPIC -Dbool=char -O3<br />In file included from BloomFilter_wrap.cxx:1877:0:<br />../BloomFilter.hpp: In member function ‘void BloomFilter::loadHeader(FILE*)’:<br />../BloomFilter.hpp:141:59: warning: ignoring return value of ‘size_t fread(void*, size_t, size_t, FILE*)’, declared with attribute warn_unused_result [-Wunused-result]<br />         fread(&amp;header, sizeof(struct FileHeader), 1, file);<br />                                                           ^<br />➜  swig git:(master) ✗ g++ -Wall -shared BloomFilter_wrap.o -o BloomFilter.so -O3<br />➜  swig git:(master) ✗ cd ..<br />➜  bloomfilter git:(master) ✗ cd ..<br />➜  lib git:(master) ✗ cd ..<br />➜  bin git:(master) ✗ ./LINKS  <br />Usage: ./LINKS [v1.8.6]<br />-f  sequences to scaffold (Multi-FASTA format, required)<br />-s  file-of-filenames, full path to long sequence reads or MPET pairs [see below] (Multi-FASTA/fastq format, required)<br />-m  MPET reads (default -m 1 = yes, default = no, optional)<br />	! DO NOT SET IF NOT USING MPET. WHEN SET, LINKS WILL EXPECT A SPECIAL FORMAT UNDER -s<br />	! Paired MPET reads in their original outward orientation &lt;- -&gt; must be separated by ":"<br />	  &gt;template_name<br />	  ACGACACTATGCATAAGCAGACGAGCAGCGACGCAGCACG:ATATATAGCGCACGACGCAGCACAGCAGCAGACGAC<br />-d  distance between k-mer pairs (ie. target distances to re-scaffold on. default -d 4000, optional)<br />	Multiple distances are separated by comma. eg. -d 500,1000,2000,3000<br />-k  k-mer value (default -k 15, optional)<br />-t  step of sliding window when extracting k-mer pairs from long reads (default -t 2, optional)<br />	Multiple steps are separated by comma. eg. -t 10,5<br />-o  offset position for extracting k-mer pairs (default -o 0, optional)<br />-e  error (%) allowed on -d distance   e.g. -e 0.1  == distance +/- 10% (default -e 0.1, optional)<br />-l  minimum number of links (k-mer pairs) to compute scaffold (default -l 5, optional)<br />-a  maximum link ratio between two best contig pairs (default -a 0.3, optional)<br />	 *higher values lead to least accurate scaffolding*<br />-z  minimum contig length to consider for scaffolding (default -z 500, optional)<br />-b  base name for your output files (optional)<br />-r  Bloom filter input file for sequences supplied in -s (optional, if none provided will output to .bloom)<br />	 NOTE: BLOOM FILTER MUST BE DERIVED FROM THE SAME FILE SUPPLIED IN -f WITH SAME -k VALUE<br />	 IF YOU DO NOT SUPPLY A BLOOM FILTER, ONE WILL BE CREATED (.bloom)<br />-p  Bloom filter false positive rate (default -p 0.001, optional; increase to prevent memory allocation errors)<br />-x  Turn off Bloom filter functionality (-x 1 = yes, default = no, optional)<br />-v  Runs in verbose mode (-v 1 = yes, default = no, optional)</p>

<p>Error: Missing mandatory options -f and -s.</p>

<p>ERROR fixed</p>

<p>perl: symbol lookup error: /home/urbe/Tools/LINKS_new/bin/./lib/bloomfilter/swig/BloomFilter.so: undefined symbol: Perl_Gthr_key_ptr</p>
]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37416/gfinisher-a-new-strategy-to-refine-and-finish-bacterial-genome-assemblies</guid>
	<pubDate>Thu, 26 Jul 2018 09:31:55 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37416/gfinisher-a-new-strategy-to-refine-and-finish-bacterial-genome-assemblies</link>
	<title><![CDATA[GFinisher: a new strategy to refine and finish bacterial genome assemblies]]></title>
	<description><![CDATA[<p>GFinisher is an application tools for refinement and finalization of prokaryotic genomes assemblies using the bias of GC Skew to identify assembly errors and organizes the contigs/scaffolds with genomes references.</p>
<pre>java -Xms2G -Xmx4G -jar GenomeFinisher.jar  \
    -i target_contigs.fasta  \
    -ds alternative_assemblies.fasta -ref reference.fasta  \
    -o outputDirectory</pre><p>Address of the bookmark: <a href="http://gfinisher.sourceforge.net" rel="nofollow">http://gfinisher.sourceforge.net</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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