<?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/13415?offset=40</link>
	<atom:link href="https://bioinformaticsonline.com/related/13415?offset=40" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/33976/goldgenomes-online-database</guid>
	<pubDate>Wed, 26 Jul 2017 07:49:29 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/33976/goldgenomes-online-database</link>
	<title><![CDATA[GOLD:Genomes Online Database]]></title>
	<description><![CDATA[<p><span>GOLD</span><span>:Genomes Online Database, is a World Wide Web resource for comprehensive access to information regarding genome and metagenome sequencing projects, and their associated metadata, around the world.</span></p>
<p>https://gold.jgi.doe.gov/</p><p>Address of the bookmark: <a href="https://gold.jgi.doe.gov/" rel="nofollow">https://gold.jgi.doe.gov/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/34711/1mb-long-dna-with-nanopore-technology</guid>
	<pubDate>Tue, 19 Dec 2017 18:49:28 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/34711/1mb-long-dna-with-nanopore-technology</link>
	<title><![CDATA[1mb long DNA with Nanopore technology]]></title>
	<description><![CDATA[<p>The first continuous DNA read of more than a million bases (&gt;1Mb) has been achieved, using Oxford Nanopore sequencing technology. Congratulations to Martin Smith and collaborators! Read more: http://bit.ly/2j5TNCO</p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35420/telomerehunter</guid>
	<pubDate>Fri, 02 Feb 2018 04:23:59 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35420/telomerehunter</link>
	<title><![CDATA[TelomereHunter]]></title>
	<description><![CDATA[<p><span>TelomereHunter is a tool for estimating telomere content from human whole-genome sequencing data. It is designed to take BAM files from a tumor and a matching control sample as input. However, it is also possible to run TelomereHunter with one input file. TelomereHunter extracts and sorts telomeric reads from the input sample(s). For the estimation of telomere content, GC biases are taken into account. Finally, the results of TelomereHunter are visualized in several diagrams.</span><br><br><span>TelomereHunter is available for download at the following address:&nbsp;</span><a href="https://pypi.python.org/pypi/telomerehunter/" target="_blank">https://pypi.python.org/pypi/telomerehunter/</a></p><p>Address of the bookmark: <a href="http://www.dkfz.de/en/applied-bioinformatics/telomerehunter/telomerehunter.html" rel="nofollow">http://www.dkfz.de/en/applied-bioinformatics/telomerehunter/telomerehunter.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36512/hisat2-a-fast-and-sensitive-alignment-program-for-mapping-next-generation-sequencing-reads</guid>
	<pubDate>Tue, 08 May 2018 04:27:22 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36512/hisat2-a-fast-and-sensitive-alignment-program-for-mapping-next-generation-sequencing-reads</link>
	<title><![CDATA[HISAT2: a fast and sensitive alignment program for mapping next-generation sequencing reads]]></title>
	<description><![CDATA[<p><strong>HISAT2</strong><span>&nbsp;is a fast and sensitive alignment program for mapping next-generation sequencing reads (both DNA and RNA) to a population of human genomes (as well as to a single reference genome). Based on an extension of BWT for graphs&nbsp;</span><a href="http://dl.acm.org/citation.cfm?id=2674828">[Sir&eacute;n et al. 2014]</a><span>, we designed and implemented a graph FM index (GFM), an original approach and its first implementation to the best of our knowledge. In addition to using one global GFM index that represents a population of human genomes, HISAT2 uses a large set of small GFM indexes that collectively cover the whole genome (each index representing a genomic region of 56 Kbp, with 55,000 indexes needed to cover the human population). These small indexes (called local indexes), combined with several alignment strategies, enable rapid and accurate alignment of sequencing reads. This new indexing scheme is called a Hierarchical Graph FM index (HGFM).&nbsp;</span></p>
<p><span>more at&nbsp;https://ccb.jhu.edu/software/hisat2/index.shtml</span></p><p>Address of the bookmark: <a href="https://github.com/infphilo/hisat2" rel="nofollow">https://github.com/infphilo/hisat2</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36739/blasr-mapping-single-molecule-sequencing-reads-using-basic-local-alignment-with-successive-refinement-blasr-theory-and-application</guid>
	<pubDate>Wed, 23 May 2018 06:54:32 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36739/blasr-mapping-single-molecule-sequencing-reads-using-basic-local-alignment-with-successive-refinement-blasr-theory-and-application</link>
	<title><![CDATA[BlasR Mapping single molecule sequencing reads using Basic Local Alignment with Successive Refinement (BLASR): Theory and Application,]]></title>
	<description><![CDATA[<p><span>BLASR (Basic Local Alignment with Successive Refinement) for mapping Single Molecule Sequencing (SMS) reads that are thousands to tens of thousands of bases long with divergence between the read and genome dominated by insertion and deletion error.</span></p>
<p>Here is how I use the blasr to align PacBio reads to the contigs (target.fasta). The &ldquo;target.fasta.sa&rdquo; is the suffix array from &ldquo;target.fasta&rdquo; generated by sawriter.</p>
<blockquote>
<p>blasr query.fa ./target.fasta -sa ./target.fasta.sa -bestn 40 -maxScore -500 -m 4 -nproc 24 -out target.m4 -maxLCPLength 15</p>
</blockquote>
<p>the output format option &ldquo;-m 4&Prime; generate the alignment coordinate. Not fully documented, but I can explain that to you.&nbsp;</p>
<p>I use a 24 cores / 48G ram server for the alignment. It took about 2 to 3 hours aligning 3G PacBio Reads to 10^6 sequences of short read contigs with a mean 3.5kbp length.</p><p>Address of the bookmark: <a href="http://bix.ucsd.edu/projects/blasr/" rel="nofollow">http://bix.ucsd.edu/projects/blasr/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37457/nanofilt-filtering-and-trimming-of-long-read-sequencing-data</guid>
	<pubDate>Mon, 30 Jul 2018 12:01:52 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37457/nanofilt-filtering-and-trimming-of-long-read-sequencing-data</link>
	<title><![CDATA[nanofilt: Filtering and trimming of long read sequencing data]]></title>
	<description><![CDATA[<p>Filtering on quality and/or read length, and optional trimming after passing filters.<br>Reads from stdin, writes to stdout.</p>
<p>Intended to be used:</p>
<ul>
<li>directly after fastq extraction</li>
<li>prior to mapping</li>
<li>in a stream between extraction and mapping</li>
</ul>
<p>https://github.com/wdecoster/nanofilt</p><p>Address of the bookmark: <a href="https://github.com/wdecoster/nanofilt" rel="nofollow">https://github.com/wdecoster/nanofilt</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37527/nanopack-visualizing-and-processing-long-read-sequencing-data</guid>
	<pubDate>Fri, 10 Aug 2018 18:41:34 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37527/nanopack-visualizing-and-processing-long-read-sequencing-data</link>
	<title><![CDATA[NanoPack: visualizing and processing long-read sequencing data]]></title>
	<description><![CDATA[<p>The NanoPack tools are written in Python3 and released under the GNU GPL3.0 License. The source code can be found at&nbsp;<a href="https://github.com/wdecoster/nanopack" target="">https://github.com/wdecoster/nanopack</a>, together with links to separate scripts and their documentation. The scripts are compatible with Linux, Mac OS and the MS Windows 10 subsystem for Linux and are available as a graphical user interface, a web service at&nbsp;<a href="http://nanoplot.bioinf.be/" target="">http://nanoplot.bioinf.be</a>&nbsp;and command line tools.</p>
<p>&nbsp;https://academic.oup.com/bioinformatics/article/34/15/2666/4934939</p><p>Address of the bookmark: <a href="https://github.com/wdecoster/nanoQC" rel="nofollow">https://github.com/wdecoster/nanoQC</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37650/p-rna-scaffolder-a-fast-and-accurate-genome-scaffolder-using-paired-end-rna-sequencing-reads</guid>
	<pubDate>Fri, 07 Sep 2018 05:19:06 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37650/p-rna-scaffolder-a-fast-and-accurate-genome-scaffolder-using-paired-end-rna-sequencing-reads</link>
	<title><![CDATA[P_RNA_scaffolder: a fast and accurate genome scaffolder using paired-end RNA-sequencing reads]]></title>
	<description><![CDATA[<p><span>P_RNA_scaffolder is a novel scaffolding tool using Pair-end RNA-seq to scaffold genome fragments. The method is suitable for most genomes. The program could utilize Illumina Paired-end RNA-sequencing reads from target speciesies. Our method provides another practical alternative to existing mate-pair_based approaches or other Protein-based approaches (for instance,&nbsp;</span><a href="http://www.fishbrowser.org/software/PEP_scaffolder/">PEP_scaffolder&nbsp;</a><span>) for scaffolding genome sequences. The most important feature of this method is to improve the completeness of gene regions and long-coding gene regions (for instance,&nbsp;</span><a href="http://circrna.org/">circRNA</a><span>).</span></p><p>Address of the bookmark: <a href="http://www.fishbrowser.org/software/P_RNA_scaffolder/#" rel="nofollow">http://www.fishbrowser.org/software/P_RNA_scaffolder/#</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37835/variantbam-filtering-and-profiling-of-next-generational-sequencing-data-using-region-specific-rules</guid>
	<pubDate>Thu, 04 Oct 2018 16:30:44 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37835/variantbam-filtering-and-profiling-of-next-generational-sequencing-data-using-region-specific-rules</link>
	<title><![CDATA[VariantBam: Filtering and profiling of next-generational sequencing data using region-specific rules]]></title>
	<description><![CDATA[<p>VariantBam is a tool to extract/count specific sets of sequencing reads from next-generational sequencing files. To save money, disk space and I/O, one may not want to store an entire BAM on disk. In many cases, it would be more efficient to store only those read-pairs or reads who intersect some region around the variant locations. Alternatively, if your scientific question is focused on only one aspect of the data (e.g. breakpoints), many reads can be removed without losing the information relevant to the problem.</p>
<h5>&nbsp;</h5><p>Address of the bookmark: <a href="https://github.com/broadinstitute/VariantBam" rel="nofollow">https://github.com/broadinstitute/VariantBam</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38535/nanopack-visualizing-and-processing-long-read-sequencing-data</guid>
	<pubDate>Tue, 25 Dec 2018 21:20:50 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38535/nanopack-visualizing-and-processing-long-read-sequencing-data</link>
	<title><![CDATA[NanoPack: visualizing and processing long-read sequencing data]]></title>
	<description><![CDATA[The NanoPack tools are written in Python3 and released under the GNU GPL3.0 License. The source code can be found at https://github.com/wdecoster/nanopack, together with links to separate scripts and their documentation. The scripts are compatible with Linux, Mac OS and the MS Windows 10 subsystem for Linux and are available as a graphical user interface, a web service at http://nanoplot.bioinf.be and command line tools.<p>Address of the bookmark: <a href="https://github.com/wdecoster/nanopack" rel="nofollow">https://github.com/wdecoster/nanopack</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

</channel>
</rss>