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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/28051?offset=140</link>
	<atom:link href="https://bioinformaticsonline.com/related/28051?offset=140" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39441/snakepipes-a-toolkit-based-on-snakemake-and-python-for-analysis-of-ngs-data</guid>
	<pubDate>Thu, 30 May 2019 04:06:13 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39441/snakepipes-a-toolkit-based-on-snakemake-and-python-for-analysis-of-ngs-data</link>
	<title><![CDATA[snakepipes: A toolkit based on snakemake and python for analysis of NGS data]]></title>
	<description><![CDATA[<p><span><span>snakePipes are flexible and powerful workflows built using&nbsp;</span><a href="https://github.com/maxplanck-ie/snakepipes/blob/master/snakemake.readthedocs.io">snakemake</a><span>&nbsp;that simplify the analysis of NGS data.</span></span></p>
<ul>
<li>DNA-mapping*</li>
<li>ChIP-seq*</li>
<li>RNA-seq*</li>
<li>ATAC-seq*</li>
<li>scRNA-seq</li>
<li>Hi-C</li>
<li>Whole Genome Bisulfite Seq/WGBS</li>
</ul>
<p><span>(*Also available in "allele-specific" mode)</span></p>
<p><span>snakePipes can be installed via conda : </span></p>
<p><span>'conda install -c mpi-ie -c bioconda -c conda-forge snakePipes'. </span></p>
<p><span>Source code (</span><a href="https://github.com/maxplanck-ie/snakepipes" target="">https://github.com/maxplanck-ie/snakepipes</a><span>) and documentation (</span><a href="https://snakepipes.readthedocs.io/en/latest/" target="">https://snakepipes.readthedocs.io/en/latest/</a><span>) are available online.</span></p><p>Address of the bookmark: <a href="https://github.com/maxplanck-ie/snakepipes" rel="nofollow">https://github.com/maxplanck-ie/snakepipes</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40208/ragoo-fast-reference-guided-scaffolding-of-genome-assembly-contigs</guid>
	<pubDate>Sun, 27 Oct 2019 00:57:23 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40208/ragoo-fast-reference-guided-scaffolding-of-genome-assembly-contigs</link>
	<title><![CDATA[RaGOO: Fast Reference-Guided Scaffolding of Genome Assembly Contigs]]></title>
	<description><![CDATA[<p>Alonge M, Soyk S, Ramakrishnan S, Wang X, Goodwin S, Sedlazeck FJ, Lippman ZB, Schatz MC:&nbsp;<a href="https://www.biorxiv.org/content/early/2019/01/13/519637">Fast and accurate reference-guided scaffolding of draft genomes</a>.&nbsp;<em>bioRxiv</em>&nbsp;2019.</p>
<p>RaGOO is a tool for coalescing genome assembly contigs into pseudochromosomes via minimap2 alignments to a closely related reference genome. The focus of this tool is on practicality and therefore has the following features:</p>
<ol>
<li>Good performance. On a MacBook Pro using Arabidopsis data, pseudochromosome construction takes less than a minute and the whole pipeline with SV calling takes ~2 minutes.</li>
<li>Intact ordering and orienting of contigs.</li>
<li><a href="https://github.com/malonge/RaGOO/wiki/Misassembly-Correction">Misassembly correction</a></li>
<li><a href="https://github.com/malonge/RaGOO/wiki/GFF-File-Lift-Over">GFF lift-over</a></li>
<li><a href="https://github.com/malonge/RaGOO/wiki/Calling-Structural-Variants">Structural variant calling with and integrated version of Assemblytics</a></li>
<li>Confidence scores associated with the grouping, localization, and orientation for each contig.</li>
</ol><p>Address of the bookmark: <a href="https://github.com/malonge/RaGOO" rel="nofollow">https://github.com/malonge/RaGOO</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/42418/scientist-b-bioinformatics-at-aiims-delhi</guid>
  <pubDate>Sun, 20 Dec 2020 04:34:55 -0600</pubDate>
  <link></link>
  <title><![CDATA[Scientist-B (Bioinformatics) at AIIMS, Delhi]]></title>
  <description><![CDATA[
<p>Name of the Project: “Artificial intelligence in Oncology, Harnessing big data and advanced computing to provide personalized diagnosis and treatment for Cancer patients”</p>

<p>Age Limit: 35</p>

<p>How to Apply for the AIIMS Life Science Job:</p>

<p>Interested applicants are asked to send out a detailed CV to Dr Ashok Sharma (aioncoaiims@gmail.com). Laboratory of Chromatin and also Cancer Epigenetics, Department of Biochemistry with the subject line “Application for Scientist-B position for MeitY project” latest by January 01st, 2021.<br />Complete Information of the year of passing, experience, marks, etc. ought to be mentioned in the CV Incomplete. applications will certainly be rejected Just shortlisted applicants will be called for interview. Chosen candidates will certainly be intimated by email/phone.<br />No TA/DA will certainly be paid for appearing in the interview.<br />Note, The institute reserved the right to fill up or not to fill up the post advertised.</p>

<p>Emoluments: Rs. 56,000/- plus 24 percent HRA</p>

<p>Eligibility:<br />2nd class Master’s Degree with a PhD in a pertinent subject (Bioinformatics) from.a recognized University<br />1st class Master’s degree in Life Sciences (Bioinformatics) from a recognized university OR.<br />Bachelor’s Degree in Engineering or-Technology with minimal 60% marks from a recognized University or equivalent.</p>

<p>Desirable Qualifications:<br />Experience in Bioinformatics/NGS data. Analysis/System Biology/Computer Science/ statistics with experience in Machine learning/Al project.<br />Experience of Deep learning applications in biological data ( image/text).<br />Proficient in Rf Python machine learning libraries.<br />Prior experience in the cancer-related project (ML-based) will be advantageous.<br />Experience with PyTorch/TensorFlow will certainly be very desirable.<br />Applicant should have strong scientific writing as well as. verbal abilities.<br />Papers in sci-indexed journals demonstrating ML skill sets.<br />Database handling will certainly be plus yet not required.</p>

<p>More detail at https://www.aiims.edu/images/pdf/recruitment/advertisement/biochem-16-12-20.pdf</p>
]]></description>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/41041/post-doc-computational-biology-bioinformatics-network-biology-data-science-ngs-mfd</guid>
  <pubDate>Sat, 15 Feb 2020 06:13:35 -0600</pubDate>
  <link></link>
  <title><![CDATA[Post Doc Computational Biology, Bioinformatics - Network Biology &amp; Data Science, NGS (m/f/d)]]></title>
  <description><![CDATA[
<p>https://www.jobvector.de/jobs-stellenangebote/biologie-life-sciences/forschung-entwicklung/post-doc-computational-biology-bioinformatics-network-biology-data-science-ngs-129867.html?suid=e522e9793b41817e52ac58d6963b94e2519920df</p>

<p>Requirements<br />Doctoral degree in Bioinformatics, Computational Biology, (Bio)physics/-mathematics, Biochemistry/Biology or similar with strong quantitative and numeric focus<br />Ability to numerically process complex and large data sets<br />Good programming skills (R/Bioconductor and/or Python preferred, Linux is a plus)<br />Experience in analyzing next-generation sequencing data sets using network biology<br />Scientific publication record in applied bioinformatics<br />Familiarity with single cell NGS analyses and other –omics techniques is a plus, but not essential</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/42329/10-ngs-services-companies-around-the-globe</guid>
	<pubDate>Sun, 22 Nov 2020 23:56:17 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/42329/10-ngs-services-companies-around-the-globe</link>
	<title><![CDATA[10 NGS services companies around the globe !]]></title>
	<description><![CDATA[<p><strong>The global&nbsp;NGS services market&nbsp;is expected to reach USD 13.1 billion by 2025.&nbsp;</strong>Here are the&nbsp;<strong style="font-size: 12.8px;">top 10 NGS services companies to look for &ndash;</strong></p><p><strong>1.&nbsp;<a href="https://www.illumina.com/">Illumina, Inc. (U.S.)</a></strong></p><p>Illumina, Inc. was founded in 1998 and is headquartered at San Diego, U.S. Illumina, Inc. is one of the leading players in DNA sequencing and array-based technologies, serving customers in the research, clinical, and applied markets. The company offers products for applications in the life sciences, oncology, reproductive health, agriculture, and other emerging segments. The company serves government laboratories, genomic research centers, academics institutions as well as pharmaceutical, biotechnology, agrigenomics, commercial molecular diagnostics laboratories and consumer genomics companies. Illumina, Inc. has its geographic presence in North America, Europe, Latin America, Asia-pacific, and others.</p><p><strong>2.&nbsp;<a href="https://www.qiagen.com/us/">QIAGEN N.V. (Netherlands)</a></strong></p><p>QIAGEN N.V. was incorporated in 1986 and is headquartered at Venlo, The Netherlands. The Company is engaged in providing Sample to Insight solutions that transform biological samples into molecular insights. QIAGEN provides its workflow to customers in molecular diagnostics, assay technologies, bioservices and automation systems.&nbsp; The company&rsquo;s genome services are suitable for custom/tailored projects that allow access to genomic sequence information.&nbsp; The Company market its products in more than 100 countries across the Americas, Europe, Asia, Australia, and the Middle-East &amp;Africa through its subsidiaries and channel partners.</p><p><strong>3.&nbsp;<a href="https://www.perkinelmer.com/">PerkinElmer, Inc. (U.S.)</a></strong></p><p>PerkinElmer, Inc. was founded in 1947 and is headquartered in Waltham, Massachusetts, the U.S. PerkinElmer, Inc. offers its products &amp; services and solutions for the diagnostics, food, environmental, industrial, life sciences research and laboratory services markets. The company offer comprehensive genetic testing solutions that help to provide insight into the complex nature of rare and inherited diseases. Some of the subsidiaries of the company are Caliper Life Sciences, Improvision, Viacell Inc., ViaCord LLC, among many others. The company has its facilities located in Europe (France, Germany, and Belgium), U.S. and Asia (China, India, and Japan).</p><p><strong>4.&nbsp;<a href="https://www.eurofins.com/">Eurofins Scientific SE (Luxembourg)</a></strong></p><p>Eurofins Scientific SE was founded in 1987 and is headquartered in Luxembourg, Europe. The company offers a portfolio of over 130,000 analytical methods and more than 150 million assays performed each year to establish the safety, identity, composition, authenticity, origin, traceability, and purity of biological substances and products, as well as carry out human diagnostic services. The company has its geographic presence across 39 countries in Europe, North and South America, and Asia-Pacific.</p><p><strong>5.&nbsp;<a href="https://www.gatc-biotech.com/en/index.html">GATC Biotech AG (Germany)</a></strong></p><p>GATC Biotech AG was founded in 1990 and is headquartered in Constance, Germany. The company provides DNA and RNA sequencing and bioservices solutions to academics and industrial areas. It also provides next generation sequencing services including genomes, targeted (re)-sequencing, human sample sequencing, transcriptomes, metagenomes, regulomes, pre-sequencing, NGS barcode labels, and next generation sequencing technologies; and bioservices services, including bioservices tools, pipelines and workflows, compute resources, data analysis reports, and case studies. GATC Biotech AG operates as a subsidiary of Eurofins Scientific SE. It offers its products through distributors in Italy, Japan, Portugal, Spain, and the Czech Republic.</p><p><strong>6.<a href="https://www.macrogen.com/">&nbsp;Macrogen, Inc. (South Korea)</a></strong></p><p>Macrogen, Inc. was founded in 1997 and is headquartered in Seoul, South Korea. Macrogen, Inc. provides next generation sequencing services such as whole genome, de novo, exome, targeted, transcriptomics, metagenome, and epigenome sequencing.&nbsp; The company also provides a variety of services such as oligo synthesis, database construction, genome research, and bioservices analysis system consulting services. Macrogen, Inc. provides genome research services in Korea and internationally.</p><p><strong>7.&nbsp;<a href="https://www.genotypic.co.in/">Genotypic Technology Pvt. Ltd. (India)</a></strong></p><p>Genotypic Technology Pvt. Ltd. was incorporated in 1998 and is headquartered in Bangalore, India. Genotypic Technology is the first Genomics service provider in India providing Microarray, Next Generation Sequencing (NGS), Bioservices and solutions to domestic/ international pharma, biotech companies and academia. The company provides its services for protocol optimization, probe designing, array layouts, project designing, and nucleic acid analysis to in-depth analysis. Genotypic Technology has its geographic presence in North America, Europe, Asia Pacific, Middle East &amp; Africa, and Latin America.</p><p><strong>8.&nbsp;<a href="https://www.genewiz.com/">GENEWIZ, Inc. (U.S.)</a></strong></p><p>GENEWIZ, Inc. was founded in 1999 and is headquartered in South Plainfield, New Jersey, the U.S.; The company is a leading provider of research service in the field of Next Generation Sequencing, Sanger DNA sequencing, sequencing of bacteria and phage, gene synthesis, DNA cloning, genomics including mutation analysis, single nucleotide polymorphism, and bioservices. GENEWIZ, Inc. has its geographic presence in U.S., China, Germany, France, Japan, and the U.K.</p><p><strong>9.&nbsp;<a href="https://www.genomics.cn/">Beijing Genomics Institute (China)</a></strong></p><p>Beijing Genomics Institute (BGI) is the world&rsquo;s largest genomics organization and non-profit research institution that was founded in 1999 and is headquartered in Shenzhen, China. The Company provides a wide range of commercial next generation sequencing services and genetic tests for medical institutions, agricultural and environmental applications. The Company operates all across the globe through its subsidiaries, namely, BGI China (Mainland), BGI Asia Pacific, BGI Americas (North and South America) and BGI Europe (Europe and Africa).</p><p><strong>10.&nbsp;<a href="https://www.scigenom.com/">SciGenom Labs Pvt. Ltd (India)</a></strong></p><p>SciGenom Labs Pvt. Ltd was founded in 2010 and is headquartered in Cochin, India with offices in Chennai &amp; Hyderabad in India, and San Francisco in the U.S. It is a Genomics R&amp;D services company that provides genomic sequencing and NGS services to life sciences and healthcare businesses globally as well as academic and government institutions in India.</p><p>Popular mentions &ndash; MedGenome (India), DNA Link, Inc. (South Korea), Otogenetics Corporation (U.S.), Novogene Corporation (China), LGC Limited (U.K.), CD Genomics (U.S.), SeqLL, LLC (U.S.)</p>]]></description>
	<dc:creator>BioStar</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43828/understanding-hifi-reads</guid>
	<pubDate>Thu, 24 Mar 2022 19:48:11 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43828/understanding-hifi-reads</link>
	<title><![CDATA[Understanding HiFi Reads !]]></title>
	<description><![CDATA[<p><span>While little public data is available for either of the new synthetic long read approaches, Illumina showed an example comparison earlier this year at the&nbsp;</span><a href="https://www.festivalofgenomics.com/rami-mehio" target="_blank">Festival of Genomics &amp; Biodata conference</a><span>&nbsp;(FoG 2022). In the IGV screenshot presented (below), synthetic Infinity reads &ndash; labeled &ldquo;Longas&rdquo; &ndash; are at the top, followed by standard Illumina short reads, and PacBio HiFi reads labeled &ldquo;CCS&rdquo; depicted at the bottom:</span></p><p>Address of the bookmark: <a href="http://pacb.com/blog/the-hifi-difference-true-long-reads-vs-synthetic-long-reads/" rel="nofollow">http://pacb.com/blog/the-hifi-difference-true-long-reads-vs-synthetic-long-reads/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/42972/list-of-bioinformatics-workflow-management-tools</guid>
	<pubDate>Sat, 20 Mar 2021 00:15:25 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/42972/list-of-bioinformatics-workflow-management-tools</link>
	<title><![CDATA[List of bioinformatics workflow management tools !]]></title>
	<description><![CDATA[<h3>Here are list of&nbsp;Workflow Managers</h3><ul>
<li><span><a href="https://github.com/pcingola/BigDataScript">BigDataScript</a></span>&nbsp;&ndash; A cross-system scripting language for working with big data pipelines in computer systems of different sizes and capabilities. [&nbsp;<a href="https://pubmed.ncbi.nlm.nih.gov/25189778">paper-2014</a>&nbsp;|&nbsp;<a href="https://pcingola.github.io/BigDataScript">web</a>&nbsp;]</li>
<li><span><a href="https://github.com/ssadedin/bpipe">Bpipe</a></span>&nbsp;&ndash; A small language for defining pipeline stages and linking them together to make pipelines. [&nbsp;<a href="http://docs.bpipe.org/">web</a>&nbsp;]</li>
<li><span><a href="https://github.com/common-workflow-language/common-workflow-language">Common Workflow Language</a></span>&nbsp;&ndash; a specification for describing analysis workflows and tools that are portable and scalable across a variety of software and hardware environments, from workstations to cluster, cloud, and high performance computing (HPC) environments. [&nbsp;<a href="http://www.commonwl.org/">web</a>&nbsp;]</li>
<li><span><a href="https://github.com/broadinstitute/cromwell">Cromwell</a></span>&nbsp;&ndash; A Workflow Management System geared towards scientific workflows. [&nbsp;<a href="https://cromwell.readthedocs.io/">web</a>&nbsp;]</li>
<li><span><a href="https://github.com/galaxyproject">Galaxy</a></span>&nbsp;&ndash; a popular open-source, web-based platform for data intensive biomedical research. Has several features, from data analysis to workflow management to visualization tools. [&nbsp;<a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6030816">paper-2018</a>&nbsp;|&nbsp;<a href="https://galaxyproject.org/">web</a>&nbsp;]</li>
<li><span><a href="https://github.com/nextflow-io/nextflow">Nextflow</a>&nbsp;(recommended)</span>&nbsp;&ndash; A fluent DSL modelled around the UNIX pipe concept, that simplifies writing parallel and scalable pipelines in a portable manner. [&nbsp;<a href="https://pubmed.ncbi.nlm.nih.gov/29412134">paper-2018</a>&nbsp;|&nbsp;<a href="http://nextflow.io/">web</a>&nbsp;]</li>
<li><span><a href="https://github.com/cgat-developers/ruffus">Ruffus</a></span>&nbsp;&ndash; Computation Pipeline library for python widely used in science and bioinformatics. [&nbsp;<a href="https://pubmed.ncbi.nlm.nih.gov/20847218">paper-2010</a>&nbsp;|&nbsp;<a href="http://www.ruffus.org.uk/">web</a>&nbsp;]</li>
<li><span><a href="https://github.com/SeqWare/seqware">SeqWare</a></span>&nbsp;&ndash; Hadoop Oozie-based workflow system focused on genomics data analysis in cloud environments. [&nbsp;<a href="https://pubmed.ncbi.nlm.nih.gov/21210981">paper-2010</a>&nbsp;|&nbsp;<a href="https://seqware.github.io/">web</a>&nbsp;]</li>
<li><span><a href="https://bitbucket.org/snakemake">Snakemake</a></span>&nbsp;&ndash; A workflow management system in Python that aims to reduce the complexity of creating workflows by providing a fast and comfortable execution environment. [&nbsp;<a href="https://pubmed.ncbi.nlm.nih.gov/29788404">paper-2018</a>&nbsp;|&nbsp;<a href="https://snakemake.readthedocs.io/">web</a>&nbsp;]</li>
<li><span><a href="https://github.com/broadinstitute/wdl">Workflow Descriptor Language</a></span>&nbsp;&ndash; Workflow standard developed by the Broad. [&nbsp;<a href="https://software.broadinstitute.org/wdl">web</a>&nbsp;]</li>
</ul>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37674/qualimap2-evaluating-next-generation-sequencing-alignment-data</guid>
	<pubDate>Tue, 11 Sep 2018 04:44:29 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37674/qualimap2-evaluating-next-generation-sequencing-alignment-data</link>
	<title><![CDATA[Qualimap2: Evaluating next generation sequencing alignment data]]></title>
	<description><![CDATA[<p><strong>Qualimap 2</strong><span>&nbsp;is a platform-independent application written in Java and R that provides both a Graphical User Inteface (GUI) and a command-line interface to facilitate the quality control of alignment sequencing data and its derivatives like feature counts.&nbsp;</span><br><br><span>Supported types of experiments include:</span></p>
<ul>
<li>Whole-genome sequencing</li>
<li>Whole-exome sequencing</li>
<li>RNA-seq (speical mode available)</li>
<li>ChIP-seq</li>
</ul><p>Address of the bookmark: <a href="http://qualimap.bioinfo.cipf.es/" rel="nofollow">http://qualimap.bioinfo.cipf.es/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38199/pacasus-correction-of-palindromes-in-long-reads-from-pacbio-and-nanopore</guid>
	<pubDate>Mon, 12 Nov 2018 05:26:48 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38199/pacasus-correction-of-palindromes-in-long-reads-from-pacbio-and-nanopore</link>
	<title><![CDATA[Pacasus: Correction of palindromes in long reads from PacBio and Nanopore]]></title>
	<description><![CDATA[<p><br>Tool for detecting and cleaning PacBio / Nanopore long reads after whole genome amplification. Check the poster from the Revolutionizing Next-Generation Sequencing (2nd edition) conference in the source folder:&nbsp;<a href="https://github.com/swarris/Pacasus/blob/master/vib2017.pdf">https://github.com/swarris/Pacasus/blob/master/vib2017.pdf</a>.</p>
<p>The prepint version is found on&nbsp;<a href="http://www.biorxiv.org/content/early/2017/08/09/173872">http://www.biorxiv.org/content/early/2017/08/09/173872</a></p>
<p>It uses the pyPaSWAS framework for sequence alignment (<a href="https://github.com/swarris/pyPaSWAS">https://github.com/swarris/pyPaSWAS</a>)</p><p>Address of the bookmark: <a href="https://github.com/swarris/Pacasus" rel="nofollow">https://github.com/swarris/Pacasus</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
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	<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>
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