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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/37602?offset=200</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34445/inc-seq-accurate-single-molecule-reads-using-nanopore-sequencing</guid>
	<pubDate>Mon, 27 Nov 2017 10:38:56 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34445/inc-seq-accurate-single-molecule-reads-using-nanopore-sequencing</link>
	<title><![CDATA[INC-Seq: accurate single molecule reads using nanopore sequencing]]></title>
	<description><![CDATA[<p><span>INC-Seq reads enabled accurate species-level classification, identification of species at 0.1&nbsp;% abundance and robust quantification of relative abundances, providing a cheap and effective approach for pathogen detection and microbiome profiling on the MinION system.</span></p><p>Address of the bookmark: <a href="https://github.com/CSB5/INC-Seq" rel="nofollow">https://github.com/CSB5/INC-Seq</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34914/ra-assembler-a-de-novo-dna-assembler-for-third-generation-sequencing-data</guid>
	<pubDate>Wed, 27 Dec 2017 20:36:54 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34914/ra-assembler-a-de-novo-dna-assembler-for-third-generation-sequencing-data</link>
	<title><![CDATA[Ra assembler - a de novo DNA assembler for third generation sequencing data]]></title>
	<description><![CDATA[<p>Integration of the Ra assembler - a de novo DNA assembler for third generation sequencing data developed on Faculty of Electrical Engineering and Computing (FER), Ruder Boskovic Institute (RBI) and Genome Institute of Singapore (GIS).</p>
<p>Ra is in development since 2014 in the form of several separate components that used to be run individually.<br>This project aims to ease the usage of Ra by integrating it into a complete de novo assembly tool.</p>
<p>Unlike other state-of-the-art assemblers,&nbsp;<span>Ra does not have an error correction step.</span>&nbsp;Instead, it relies on detecting overlaps using a very sensitive and specific overlapper ("graphmap -w owler",&nbsp;<a href="https://github.com/isovic/graphmap">https://github.com/isovic/graphmap</a>) and constructing and reducing an overlap graph (Ra layout,&nbsp;<a href="https://github.com/mariokostelac/ra">https://github.com/mariokostelac/ra</a>).</p><p>Address of the bookmark: <a href="https://github.com/mariokostelac/ra-integrate/" rel="nofollow">https://github.com/mariokostelac/ra-integrate/</a></p>]]></description>
	<dc:creator>biogeek</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36476/flye-fast-and-accurate-de-novo-assembler-for-single-molecule-sequencing-reads</guid>
	<pubDate>Fri, 04 May 2018 19:16:22 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36476/flye-fast-and-accurate-de-novo-assembler-for-single-molecule-sequencing-reads</link>
	<title><![CDATA[Flye: Fast and accurate de novo assembler for single molecule sequencing reads]]></title>
	<description><![CDATA[<p><span>Flye is a de novo assembler for long and noisy reads, such as those produced by PacBio and Oxford Nanopore Technologies. The algorithm uses an A-Bruijn graph to find the overlaps between reads and does not require them to be error-corrected. After the initial assembly, Flye performs an extra repeat classification and analysis step to improve the structural accuracy of the resulting sequence. The package also includes a polisher module, which produces the final assembly of high nucleotide-level quality.</span></p><p>Address of the bookmark: <a href="https://github.com/fenderglass/Flye" rel="nofollow">https://github.com/fenderglass/Flye</a></p>]]></description>
	<dc:creator>Jit</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/37223/chopstitch-exon-annotation-and-splice-graph-construction-using-transcriptome-assembly-and-whole-genome-sequencing-data</guid>
	<pubDate>Tue, 03 Jul 2018 04:14:52 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37223/chopstitch-exon-annotation-and-splice-graph-construction-using-transcriptome-assembly-and-whole-genome-sequencing-data</link>
	<title><![CDATA[ChopStitch: exon annotation and splice graph construction using transcriptome assembly and whole genome sequencing data]]></title>
	<description><![CDATA[ChopStitch is a new method for finding putative exons and constructing splice graphs using an assembled transcriptome and whole genome shotgun sequencing (WGSS) data. ChopStitch identifies exon-exon boundaries in de novo assembled RNA-seq data with the help of a Bloom filter that represents the k-mer spectrum of WGSS reads. The algorithm also detects base substitutions in transcript sequences corresponding to sequencing or assembly errors, haplotype variations, or putative RNA editing events. The primary output of our tool is a FASTA file containing putative exons. Further, exon edges are interrogated for alternative exon-exon boundaries to detect transcript isoforms, which are reported as splice graphs in dot output format.<p>Address of the bookmark: <a href="https://github.com/bcgsc/ChopStitch" rel="nofollow">https://github.com/bcgsc/ChopStitch</a></p>]]></description>
	<dc:creator>Rahul Nayak</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/37830/nquire-a-statistical-framework-for-ploidy-estimation-using-next-generation-sequencing</guid>
	<pubDate>Thu, 04 Oct 2018 05:23:59 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37830/nquire-a-statistical-framework-for-ploidy-estimation-using-next-generation-sequencing</link>
	<title><![CDATA[nQuire: a statistical framework for ploidy estimation using next generation sequencing]]></title>
	<description><![CDATA[<p>nQuire provides a statistical framework to study organisms with intraspecific variation in ploidy. nQuire is likely to be useful in epidemiological studies of pathogens, artificial selection experiments, and for historical or ancient samples where intact nuclei are not preserved. It is implemented as a stand-alone Linux command line tool in the C programming language and is available at https://github.com/clwgg/nQuireunder the MIT license.</p><p>Address of the bookmark: <a href="https://github.com/clwgg/nQuireunder" rel="nofollow">https://github.com/clwgg/nQuireunder</a></p>]]></description>
	<dc:creator>Jit</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>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39726/jackalope-a-swift-versatile-phylogenomic-and-high-throughput-sequencing-simulator</guid>
	<pubDate>Fri, 26 Jul 2019 00:58:12 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39726/jackalope-a-swift-versatile-phylogenomic-and-high-throughput-sequencing-simulator</link>
	<title><![CDATA[jackalope: A swift, versatile phylogenomic and high-throughput sequencing simulator]]></title>
	<description><![CDATA[<p><code>jackalope</code> simply and efficiently simulates (i) variants from reference genomes and (ii) reads from both Illumina and Pacific Biosciences (PacBio) platforms. It can either read reference genomes from FASTA files or simulate new ones. Genomic variants can be simulated using summary statistics, phylogenies, Variant Call Format (VCF) files, and coalescent simulations&mdash;the latter of which can include selection, recombination, and demographic fluctuations. <code>jackalope</code> can simulate single, paired-end, or mate-pair Illumina reads, as well as reads from Pacific Biosciences These simulations include sequencing errors, mapping qualities, multiplexing, and optical/PCR duplicates. All outputs can be written to standard file formats.</p>
<p><span>A swift, versatile phylogenomic and high-throughput sequencing simulator </span> <span><a href="https://jackalope.lucasnell.com">https://jackalope.lucasnell.com</a></span></p><p>Address of the bookmark: <a href="https://github.com/lucasnell/jackalope" rel="nofollow">https://github.com/lucasnell/jackalope</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40611/deepvariant-an-analysis-pipeline-that-uses-a-deep-neural-network-to-call-genetic-variants-from-next-generation-dna-sequencing-data</guid>
	<pubDate>Sat, 25 Jan 2020 13:28:09 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40611/deepvariant-an-analysis-pipeline-that-uses-a-deep-neural-network-to-call-genetic-variants-from-next-generation-dna-sequencing-data</link>
	<title><![CDATA[DeepVariant : an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data.]]></title>
	<description><![CDATA[<p><span>DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data.</span></p>
<p><span><span>DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data. DeepVariant relies on&nbsp;</span><a href="https://github.com/google/nucleus">Nucleus</a><span>, a library of Python and C++ code for reading and writing data in common genomics file formats (like SAM and VCF) designed for painless integration with the&nbsp;</span><a href="https://www.tensorflow.org/">TensorFlow</a><span>&nbsp;machine learning framework.</span></span></p>
<p><span><a href="https://ai.googleblog.com/2017/12/deepvariant-highly-accurate-genomes.html">https://ai.googleblog.com/2017/12/deepvariant-highly-accurate-genomes.html</a></span></p>
<p><span><a href="https://www.biorxiv.org/content/10.1101/092890v6">https://www.biorxiv.org/content/10.1101/092890v6</a></span></p>
<p><span><img src="https://4.bp.blogspot.com/-2KlXZO60sWE/WiGc8qlZfxI/AAAAAAAACOs/s1pNiKI8jsAvJLr1E_po5udDO8eObm_awCLcBGAs/s640/image3.png" width="640" height="427" alt="image" style="border: 0px;"></span></p><p>Address of the bookmark: <a href="https://github.com/google/deepvariant" rel="nofollow">https://github.com/google/deepvariant</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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