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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/38208?offset=550</link>
	<atom:link href="https://bioinformaticsonline.com/related/38208?offset=550" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<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/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>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36830/crossmap-a-program-for-convenient-conversion-of-genome-coordinates</guid>
	<pubDate>Thu, 31 May 2018 06:00:47 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36830/crossmap-a-program-for-convenient-conversion-of-genome-coordinates</link>
	<title><![CDATA[CrossMap: a program for convenient conversion of genome coordinates]]></title>
	<description><![CDATA[CrossMap is a program for convenient conversion of genome coordinates (or annotation files) between different assemblies (such as Human hg18 (NCBI36) &lt;&gt; hg19 (GRCh37), Mouse mm9 (MGSCv37) &lt;&gt; mm10 (GRCm38)).

It supports most commonly used file formats including SAM/BAM, Wiggle/BigWig, BED, GFF/GTF, VCF.

CrossMap is designed to liftover genome coordinates between assemblies. 

It’s not a program for aligning sequences to reference genome.

We do not recommend using CrossMap to convert genome coordinates between species.<p>Address of the bookmark: <a href="http://crossmap.sourceforge.net" rel="nofollow">http://crossmap.sourceforge.net</a></p>]]></description>
	<dc:creator>Jit</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/41673/lr-gapcloser-a-tiling-path-based-gap-closer-that-uses-long-reads-to-complete-genome-assembly</guid>
	<pubDate>Thu, 14 May 2020 15:09:52 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41673/lr-gapcloser-a-tiling-path-based-gap-closer-that-uses-long-reads-to-complete-genome-assembly</link>
	<title><![CDATA[LR_Gapcloser: a tiling path-based gap closer that uses long reads to complete genome assembly]]></title>
	<description><![CDATA[<p>LR_Gapcloser is a gap closing tool using long reads from studied species. The long reads could be downloaed from public read archive database (for instance, NCBI SRA database ) or be your own data. Then they are fragmented and aligned to scaffolds using BWA mem algorithm in BWA package. In the package, we provided a compiled bwa, so the user needn't to install bwa. LR_Gapcloser uses the alignments to find the bridging that cross the gap, and then fills the long read original sequence into the genomic gaps.</p><p>Address of the bookmark: <a href="https://github.com/CAFS-bioinformatics/LR_Gapcloser" rel="nofollow">https://github.com/CAFS-bioinformatics/LR_Gapcloser</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38006/scribl-html5-canvas-genomics-graphic-library</guid>
	<pubDate>Thu, 25 Oct 2018 09:38:53 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38006/scribl-html5-canvas-genomics-graphic-library</link>
	<title><![CDATA[Scribl : HTML5 canvas genomics graphic library]]></title>
	<description><![CDATA[<p>Scribl is a javascript, Canvas-based graphics library that easily generates biological visuals of genomic regions, alignments, and assembly data. Scribl can also be used in conventional offline pipelines, since everything needed to generate charts can be contained in a single html file.</p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="http://chmille4.github.io/Scribl/" rel="nofollow">http://chmille4.github.io/Scribl/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38053/swgis-v20-a-seqword-genomic-island-sniffer</guid>
	<pubDate>Thu, 01 Nov 2018 12:35:52 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38053/swgis-v20-a-seqword-genomic-island-sniffer</link>
	<title><![CDATA[swgis v2.0 : a seqword genomic island sniffer]]></title>
	<description><![CDATA[<p><strong>swgis v2.0</strong>&nbsp;is the modified version of the seqword genomic island sniffer. this version is specifically optimized for predicting genomic islands in eukaryotic genomes. swgis v2.0 was tested on several eukaryotic species of different lineages. all identified genomic islands were deposited in the&nbsp;<a href="http://eugi.bi.up.ac.za/" title="Go to EuGI database">eugi database</a>.</p>
<p><a href="http://eugi.bi.up.ac.za/download_swgis/swgisv2.0.zip" title="Download SWGIS v2.0">download swgis v2.0</a></p><p>Address of the bookmark: <a href="http://eugi.bi.up.ac.za/eugi_download_swgis.php" rel="nofollow">http://eugi.bi.up.ac.za/eugi_download_swgis.php</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38224/novograph-building-whole-genome-graphs-from-long-read-based-de-novo-assemblies</guid>
	<pubDate>Thu, 15 Nov 2018 12:48:30 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38224/novograph-building-whole-genome-graphs-from-long-read-based-de-novo-assemblies</link>
	<title><![CDATA[NovoGraph: building whole genome graphs from long-read-based de novo assemblies]]></title>
	<description><![CDATA[<p><span>NovoGraph: building whole genome graphs from long-read-based de novo assemblies</span></p>
<p><span><span>An algorithmically novel approach to construct a genome graph representation of long-read-based&nbsp;</span><em>de novo</em><span>&nbsp;sequence assemblies. We then provide a proof of principle by creating a genome graph of seven ethnically-diverse human genomes.</span></span></p>
<p>&nbsp;</p>
<p>https://f1000research.com/articles/7-1391/v1</p><p>Address of the bookmark: <a href="https://github.com/NCBI-Hackathons/NovoGraph" rel="nofollow">https://github.com/NCBI-Hackathons/NovoGraph</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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