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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/37962?offset=70</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37576/lrcstats-a-tool-for-evaluating-long-reads-correction-methods</guid>
	<pubDate>Wed, 22 Aug 2018 11:05:04 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37576/lrcstats-a-tool-for-evaluating-long-reads-correction-methods</link>
	<title><![CDATA[LRCstats: a tool for evaluating long reads correction methods]]></title>
	<description><![CDATA[<p><span>LRCstats is an open-source pipeline for benchmarking DNA long read correction algorithms for long reads outputted by third generation sequencing technology such as machines produced by Pacific Biosciences. The reads produced by third generation sequencing technology, as the name suggests, are longer in length than reads produced by next generation sequencing technologies, such as those produced by Illumina. However, long reads are plagued by high error rates, which can cause issues in downstream analysis. Long read correction algorithms reduce the error rate of long reads either through self-correcting methods or using accurate, short reads outputted by next generation sequencing technologies to correct long reads.</span></p><p>Address of the bookmark: <a href="https://github.com/cchauve/lrcstats" rel="nofollow">https://github.com/cchauve/lrcstats</a></p>]]></description>
	<dc:creator>Aaryan Lokwani</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38012/cosine-non-seeding-method-for-mapping-long-noisy-sequences</guid>
	<pubDate>Fri, 26 Oct 2018 00:41:59 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38012/cosine-non-seeding-method-for-mapping-long-noisy-sequences</link>
	<title><![CDATA[COSINE: non-seeding method for mapping long noisy sequences]]></title>
	<description><![CDATA[<p><span>Third generation sequencing (TGS) are highly promising technologies but the long and noisy reads from TGS are difficult to align using existing algorithms. Here, we present COSINE, a conceptually new method designed specifically for aligning long reads contaminated by a high level of errors.</span></p><p>Address of the bookmark: <a href="https://github.com/SUwonglab/COSINE" rel="nofollow">https://github.com/SUwonglab/COSINE</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31139/pbsuite-software-for-long-read-sequencing-data-from-pacbio</guid>
	<pubDate>Mon, 27 Feb 2017 09:54:47 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31139/pbsuite-software-for-long-read-sequencing-data-from-pacbio</link>
	<title><![CDATA[PBSuite: Software for Long-Read Sequencing Data from PacBio]]></title>
	<description><![CDATA[<p><span>PBJelly - the genome upgrading tool.&nbsp;</span><br><span>PBHoney - the structural variation discovery tool&nbsp;</span><br><br><span>Both are contained within the PBSuite code found in downloads.</span><br><br><span>----- PBJelly -----</span><br><span>Read The Paper&nbsp;</span><br><a href="http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0047768" target="_blank">http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0047768</a><br><br><span>PBJelly is a highly automated pipeline that aligns long sequencing reads (such as PacBio RS reads or long 454 reads in fasta format) to high-confidence draft assembles. PBJelly fills or reduces as many captured gaps as possible to produce upgraded draft genomes.&nbsp;</span><br><br><span>----- PBHoney -----</span><br><span>Read The Paper</span><br><a href="http://www.biomedcentral.com/1471-2105/15/180/abstract" target="_blank">http://www.biomedcentral.com/1471-2105/15/180/abstract</a><br><br><span>PBHoney is an implementation of two variant-identification approaches designed to exploit the high mappability of long reads (i.e., greater than 10,000 bp). PBHoney considers both intra-read discordance and soft-clipped tails of long reads to identify structural variants.</span></p><p>Address of the bookmark: <a href="https://sourceforge.net/projects/pb-jelly/" rel="nofollow">https://sourceforge.net/projects/pb-jelly/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37645/lsc-improving-pacbio-long-read-accuracy-by-short-read-alignment</guid>
	<pubDate>Thu, 06 Sep 2018 16:27:35 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37645/lsc-improving-pacbio-long-read-accuracy-by-short-read-alignment</link>
	<title><![CDATA[LSC: Improving PacBio Long Read Accuracy by Short Read Alignment]]></title>
	<description><![CDATA[<ul>
<li>Added Command line argument support.</li>
<li>Multi-stage execution modes.</li>
<li>Support for parallelization. Now execution proceeds in batches of long reads the size of which can be set by --long_read_batch_size N.</li>
<li>Better compressed intermediate files.</li>
<li>Added utilities folder.</li>
<li>Added support for multiple short read files.</li>
<li>Removed use of configuration file.</li>
</ul><p>Address of the bookmark: <a href="https://www.healthcare.uiowa.edu/labs/au/LSC/" rel="nofollow">https://www.healthcare.uiowa.edu/labs/au/LSC/</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38762/katuali-is-a-flexible-consensus-pipeline-implemented-in-snakemake-to-basecall-assemble-and-polish-oxford-nanopore-technologies-sequencing-data</guid>
	<pubDate>Tue, 22 Jan 2019 06:26:55 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38762/katuali-is-a-flexible-consensus-pipeline-implemented-in-snakemake-to-basecall-assemble-and-polish-oxford-nanopore-technologies-sequencing-data</link>
	<title><![CDATA[Katuali is a flexible consensus pipeline implemented in Snakemake to basecall, assemble, and polish Oxford Nanopore Technologies&#039; sequencing data]]></title>
	<description><![CDATA[<ul>
<li>Run a pipeline processing fast5s to a consensus in a single command.</li>
<li>Recommended fixed "standard" and "fast" pipelines.</li>
<li>Interchange basecaller, assembler, and consensus components of the pipelines simply by changing the target filepath.</li>
<li>Seemless distribution of tasks over local or distributed compute.</li>
<li>Highly configurable.</li>
<li>Open source (Mozilla Public License 2.0).</li>
</ul>
<p>Documentation can be found at&nbsp;<a href="https://nanoporetech.github.io/katuali/">https://nanoporetech.github.io/katuali/</a>.</p><p>Address of the bookmark: <a href="https://github.com/nanoporetech/katuali" rel="nofollow">https://github.com/nanoporetech/katuali</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31105/understanding-pacbio</guid>
	<pubDate>Fri, 24 Feb 2017 10:17:36 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31105/understanding-pacbio</link>
	<title><![CDATA[Understanding PacBio]]></title>
	<description><![CDATA[<p>This tutorial includes resources for learning more about PacBio data and bioinformatics analysis, and includes content suitable for both beginners and experts. Below are links to training modules (webinars and PowerPoint presentations) to help you get started with your data processing, as well as information for specialized applications.</p>
<p>Training Resources:</p>
<ul>
<li><a href="https://github.com/PacificBiosciences/Bioinformatics-Training/wiki/Bioinformatics-Workshop">Bioinformatics Workshop (Webinars)</a></li>
<li><a href="https://github.com/PacificBiosciences/Bioinformatics-Training/wiki/Bioinformatics-Training-Slides">Bioinformatics Training Slides</a></li>
</ul>
<p>Specialized Applications:</p>
<ul>
<li><a href="https://github.com/PacificBiosciences/Bioinformatics-Training/wiki/De-Novo-Assembly">De Novo Assembly</a></li>
<li><a href="https://github.com/PacificBiosciences/cDNA_primer/wiki">Transcriptome analysis</a></li>
<li><a href="https://github.com/PacificBiosciences/Bioinformatics-Training/wiki/Base-modification-analysis">Base Modification Analysis</a></li>
<li><a href="https://github.com/PacificBiosciences/Bioinformatics-Training/wiki/Barcoding">Barcoding</a></li>
<li><a href="https://github.com/PacificBiosciences/Bioinformatics-Training/wiki/Data-Analysis-Tools">Data Analysis Tools</a></li>
<li><a href="https://github.com/PacificBiosciences/Bioinformatics-Training/wiki/Minor-Variants-and-Phasing-Analysis">Minor Variants and Phasing Analysis</a></li>
</ul><p>Address of the bookmark: <a href="https://github.com/PacificBiosciences/Bioinformatics-Training/wiki" rel="nofollow">https://github.com/PacificBiosciences/Bioinformatics-Training/wiki</a></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44373/mitohifi-a-python-pipeline-for-mitochondrial-genome-assembly-from-pacbio-high-fidelity-reads</guid>
	<pubDate>Tue, 05 Sep 2023 07:31:35 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44373/mitohifi-a-python-pipeline-for-mitochondrial-genome-assembly-from-pacbio-high-fidelity-reads</link>
	<title><![CDATA[MitoHiFi: a python pipeline for mitochondrial genome assembly from PacBio high fidelity reads]]></title>
	<description><![CDATA[<p dir="auto">MitoHiFi v3.2 is a python pipeline distributed under&nbsp;<a href="https://github.com/marcelauliano/MitoHiFi/blob/master/LICENSE">MIT License</a>&nbsp;!</p>
<p dir="auto">MitoHiFi was first developed to assemble the mitogenomes for a wide range of species in the Darwin Tree of Life Project (DToL)</p>
<p dir="auto">https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-023-05385-y&nbsp;</p>
<p dir="auto"><a href="https://github.com/marcelauliano/MitoHiFi/blob/master/docs/dtol-logo-round-300x132.png" target="_blank"><img src="https://github.com/marcelauliano/MitoHiFi/raw/master/docs/dtol-logo-round-300x132.png" alt="" style="border: 0px; border: 0px;"></a></p><p>Address of the bookmark: <a href="https://github.com/marcelauliano/MitoHiFi" rel="nofollow">https://github.com/marcelauliano/MitoHiFi</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40940/consed-a-finishing-package-bam-file-viewer-assembly-editor-autofinish-autoreport-autoedit-and-align-reads-to-reference-sequence</guid>
	<pubDate>Fri, 07 Feb 2020 07:16:22 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40940/consed-a-finishing-package-bam-file-viewer-assembly-editor-autofinish-autoreport-autoedit-and-align-reads-to-reference-sequence</link>
	<title><![CDATA[Consed--A Finishing Package (BAM File Viewer, Assembly Editor, Autofinish, Autoreport, Autoedit, and Align Reads To Reference Sequence)]]></title>
	<description><![CDATA[<ul>
<li>Supports Illumina, 454, other Next-Gen and Sanger Reads and allows mixtures of these read types</li>
<li>Consed includes BamScape which can view bam files with unlimited numbers of reads. BamScape can bring up consed to edit reads and the reference sequence in targeted regions.</li>
<li>Consed is compatible with Newbler, Cross_match, Phrap, MIRA, Velvet and PCAP output.</li>
<li>Quickly takes the user to each variant site for viewing (also available as an automated report)</li>
<li>Overview of assembly can help detect and fix misassemblies</li>
<li>Editing time reduced by the program's ability to pin-point problem areas</li>
<li>Editing is guided by error probabilities</li>
</ul><p>Address of the bookmark: <a href="http://www.phrap.org/consed/consed.html" rel="nofollow">http://www.phrap.org/consed/consed.html</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40531/shasta-long-read-assembler</guid>
	<pubDate>Tue, 14 Jan 2020 06:47:07 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40531/shasta-long-read-assembler</link>
	<title><![CDATA[Shasta long read assembler]]></title>
	<description><![CDATA[<p>The goal of the Shasta long read assembler is to rapidly produce accurate assembled sequence using as input DNA reads generated by&nbsp;<a href="https://nanoporetech.com/">Oxford Nanopore</a>&nbsp;flow cells.</p>
<p>Computational methods used by the Shasta assembler include:</p>
<ul>
<li>Using a&nbsp;<a href="https://en.wikipedia.org/wiki/Run-length_encoding">run-length</a>&nbsp;representation of the read sequence. This makes the assembly process more resilient to errors in homopolymer repeat counts, which are the most common type of errors in Oxford Nanopore reads.</li>
<li>Using in some phases of the computation a representation of the read sequence based on&nbsp;<em>markers</em>, a fixed subset of short k-mers (k &asymp; 10).</li>
</ul>
<p>More at&nbsp;<a href="https://chanzuckerberg.github.io/shasta/index.html">https://chanzuckerberg.github.io/shasta/index.html</a></p><p>Address of the bookmark: <a href="https://github.com/chanzuckerberg/shasta" rel="nofollow">https://github.com/chanzuckerberg/shasta</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42477/hifiasm-a-haplotype-resolved-assembler-for-accurate-hifi-reads</guid>
	<pubDate>Thu, 24 Dec 2020 10:03:36 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42477/hifiasm-a-haplotype-resolved-assembler-for-accurate-hifi-reads</link>
	<title><![CDATA[Hifiasm: a haplotype-resolved assembler for accurate Hifi reads]]></title>
	<description><![CDATA[<p><span>Hifiasm is a fast haplotype-resolved de novo assembler for PacBio Hifi reads. It can assemble a human genome in several hours and works with the California redwood genome, one of the most complex genomes sequenced so far. Hifiasm can produce primary/alternate assemblies of quality competitive with the best assemblers. It also introduces a new graph binning algorithm and achieves the best haplotype-resolved assembly given trio data.</span></p><p>Address of the bookmark: <a href="https://github.com/chhylp123/hifiasm" rel="nofollow">https://github.com/chhylp123/hifiasm</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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