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<channel>
	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/27430?offset=940</link>
	<atom:link href="https://bioinformaticsonline.com/related/27430?offset=940" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/19786/shrec3d</guid>
	<pubDate>Thu, 25 Dec 2014 23:14:52 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/19786/shrec3d</link>
	<title><![CDATA[ShRec3D]]></title>
	<description><![CDATA[<p><strong>ShRec3D</strong> is a program that aims at reconstructing a genome 3D structure (b) from the sole knowledge of the contacts between different genomic regions (a) as determined by Hi-C (http://www.ncbi.nlm.nih.gov/pubmed/19815776).</p>
<p>There are two options to run ShRec3D (on linuX only so far): the first one uses the Matlab complier runtime environment (MCR), the second one doesn't need any other library to be installed but only works with the latest versions of Linux (equivalent to Fedora 19 and above).</p><p>Address of the bookmark: <a href="https://sites.google.com/site/julienmozziconacci/#TOC-Downloads" rel="nofollow">https://sites.google.com/site/julienmozziconacci/#TOC-Downloads</a></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
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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/poll/view/19921/which-of-the-followings-are-the-best-place-to-study-bioinformatics</guid>
	<pubDate>Sun, 28 Dec 2014 00:20:30 -0600</pubDate>
	<link>https://bioinformaticsonline.com/poll/view/19921/which-of-the-followings-are-the-best-place-to-study-bioinformatics</link>
	<title><![CDATA[Which of the followings are the best place to study Bioinformatics ?]]></title>
	<description><![CDATA[<p>Bioinformatics is a major growth area and qualified Bioinformaticians are in high demand. An explosion in biological data has resulted from genome projects, next generation sequencing and other 'omics' techniques. Bioinformatics provides the tools to analyse and exploit such data sets.<br /><br />Can you please suggest me the best place to study bioinformatics ( Grad/PostGrad).</p>]]></description>
	<dc:creator>Reshma Khatun</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/44672/libraries-or-management-tools-for-high-throughput-sequencing-data</guid>
	<pubDate>Fri, 04 Oct 2024 02:45:06 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/44672/libraries-or-management-tools-for-high-throughput-sequencing-data</link>
	<title><![CDATA[Libraries or management tools for high throughput sequencing data]]></title>
	<description><![CDATA[<ul>
<li><a href="http://gatb.inria.fr/"><span>GATB</span></a>&nbsp;Library.&nbsp;The&nbsp;<span>Genome Analysis Toolbox with de-Bruijn graph.&nbsp;</span>A large part of tools developed by the GenScale team are based on this library.<br />These methods enable the analysis of data sets of any size on multi-core desktop computers, including very huge amount of reads data coming from any kind of organisms such as bacteria, plants, animals and even complex samples (<em>e.g.</em>&nbsp;metagenomes). Among them are (the full is available here:&nbsp;<a href="https://gatb.inria.fr/software/">https://gatb.inria.fr/software/</a>):</li>
<li><a href="https://github.com/morispi/LRez"><span>LRez</span></a>: C++ Library and toolkit for the barcode-based management and indexation of linked-read datasets.</li>
</ul><h2>Variant calling and/or genotyping</h2><ul>
<li><a href="https://gatb.inria.fr/software/discosnp/" title="DiscoSNP">DiscoSNP++ and&nbsp;discoSnpRAD</a>: Reference-free small variant discovery (SNPs and indels)</li>
<li><a href="https://gatb.inria.fr/software/mind-the-gap/" title="MindTheGap">MindTheGap</a>: Detection and assembly of large insertion variants</li>
<li><a href="https://gatb.inria.fr/software/takeabreak/" title="TakeABreak">TakeABreak</a>:&nbsp;reference-free inversion discovery tool</li>
<li><a href="https://github.com/llecompte/SVJedi">SVJedi</a>: Structural Variant genotyper with long read data</li>
<li><a href="https://github.com/SandraLouise/SVJedi-graph">SVJedi-graph</a>: Structural Variant genotyper with long read data using a variation graph</li>
</ul><h2>Sequence assembly</h2><ul>
<li><a href="https://github.com/cguyomar/MinYS">MinYS</a>: reference-guided genome assembly in metagenomics data</li>
<li><a href="https://github.com/anne-gcd/MTG-Link">MTG-link</a>: local assembly tool for linked-read data</li>
<li><a href="https://gatb.inria.fr/software/minia/" title="Minia">Minia</a>: De novo short read assembler</li>
<li><a href="https://gatb.inria.fr/de-novo-genome-assembly/">de-novo pipeline</a>:&nbsp;<em>de-novo</em>&nbsp;assembly pipeline (error correction / contigs / scaffolding) for genomes and meta-genomes</li>
<li><a href="https://gatb.inria.fr/software/mapsembler/" title="Mapsembler2">Mapsembler2</a>: Targeted assembly (not maintained)</li>
</ul><h2>Managing k-mers &amp; indexation</h2><ul>
<li><a href="https://github.com/lrobidou/findere">findere</a>:&nbsp;simple strategy for speeding up queries and for reducing false positive calls from any Approximate Membership Query data structure.
<ul>
<li><a href="https://github.com/lrobidou/fimpera">fimpera</a>&nbsp;extends findere adding the abundance information.</li>
</ul>
</li>
<li><a href="https://github.com/tlemane/kmtricks">kmtricks</a>:&nbsp;modular tool suite for counting kmers, and constructing Bloom filters or kmer matrices, for large collections of sequencing data.</li>
<li><a href="https://github.com/tlemane/kmindex">kmindex&nbsp;</a>is a tool for indexing and querying sequencing samples. It is built on top of kmtricks.</li>
<li><a href="https://github.com/pierrepeterlongo/back_to_sequences">back to sequences</a>: Find sequences (reads, unitigs, genes) related to a set of kmers in large datasets, in a matter of seconds.</li>
<li><a href="https://github.com/vicLeva/bqf">Backpack Quotient Filter</a>:&nbsp;k-mer indexing data structure with abundance</li>
<li><a href="http://github.com/GATB/rconnector">short read connector</a>:&nbsp;Detect similar reads from potentially large read set</li>
<li><a href="https://gatb.inria.fr/software/dsk/" title="DSK">DSK</a>:&nbsp;Count K-mer in sequences</li>
</ul><h2>Pangenome graph manipulation</h2><ul>
<li><a href="https://github.com/Tharos-ux/pancat">Pancat</a>: Pangenome Comparison and Analysis Toolkit</li>
<li><a href="https://pypi.org/project/gfagraphs/">GFAGraphs</a>: a Python library to handle pangenome graph files in GFA format.</li>
</ul><h2>Comparative metagenomics with k-mers</h2><ul>
<li><a href="https://github.com/GATB/simka">Simka and SimkaMin</a>:&nbsp;Comparative metagenomics for large-scale datasets</li>
<li><a href="https://team.inria.fr/genscale/high-throughput-sequence-analysis/compreads-metagenomic-data-analysis/">Comparead &amp; Commet</a>:&nbsp;comparison of metagenomic datasets</li>
</ul><h2>Species and bacterial strains identification</h2><ul>
<li><a href="https://github.com/gsiekaniec/ORI">ORI</a>: software using long nanopore reads to identify bacteria present in a sample at the strain level</li>
<li><a href="https://github.com/kevsilva/StrainFLAIR">StrainFLAIR</a>:&nbsp;STRAIN-level proFiLing using vArIation gRaph</li>
</ul><h2>General-purpose sequencing data manipulation</h2><ul>
<li><a href="https://team.inria.fr/genscale/ngs-software/gassst/">GASSST</a>:&nbsp;long read mapper</li>
<li><a href="https://gatb.inria.fr/software/leon/" title="Leon">Leon</a>: short read compressor (now included in GATB-core)</li>
<li><a href="https://gatb.inria.fr/software/bloocoo/" title="Bloocoo">Bloocoo</a>:&nbsp;short read corrector</li>
<li><a href="https://github.com/GATB/bcalm">BCALM</a>:&nbsp;Construct compacted de Bruijn graphs (unitigs)</li>
</ul><h2>&nbsp;Protein Structure</h2><ul>
<li><a href="https://team.inria.fr/genscale/protein-structure/a-purva-contact-map-overlap-solver/">A_Purva</a>:&nbsp;Contact Map Overlap solver</li>
<li><a href="https://team.inria.fr/genscale/protein-structure/md-jeep-distance-geomtry-solver/">MD-Jeep</a>:&nbsp;Distance Geometry solver</li>
<li><a href="https://team.inria.fr/genscale/csa-comparative-structural-alignment/">CSA</a>:&nbsp;Comparative Structural Alignment</li>
</ul><h2>Workflow</h2><ul>
<li><a href="https://team.inria.fr/genscale/workflows/slicee/">SLICEE</a>:&nbsp;parallel execution of bioinformatics workflows</li>
</ul><h3>Comparative Genomics</h3><ul>
<li><a href="https://team.inria.fr/genscale/comparative-genomics/cassis/">CASSIS</a>:&nbsp;detection of rearrangement breakpoints</li>
<li><a href="https://team.inria.fr/genscale/high-throughput-sequence-analysis/plast-intensive-sequence-comparison/">PLAST</a>:&nbsp;intensive bank-to-bank sequence comparison</li>
<li><a href="https://github.com/stephanierobin/DrjBreakpointFinder">DRJBreakpointFinder</a>: detection and precise localization of excision sites in proviral segments</li>
</ul>]]></description>
	<dc:creator>LEGE</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/20007/roche-has-acquired-bina-technologies</guid>
	<pubDate>Tue, 30 Dec 2014 09:42:16 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/20007/roche-has-acquired-bina-technologies</link>
	<title><![CDATA[Roche has acquired Bina Technologies !!!]]></title>
	<description><![CDATA[<p>Bina Technologies is a privately held company that provides a big data platform for centralized management and processing of next generation sequencing (NGS) data for the academic and translational research markets.&nbsp; Bina will be integrated into the Roche Sequencing Unit, and will continue to focus on development of their innovative genomic analysis solution.<br /><br />Roche has acquired Bina Technologies, a privately-owned biotech company based in California. The biotech&rsquo;s first product was the Bina Box, a platform for secondary genomic analysis, sequence alignment, and variant calling, but since 2012, it has developed other products and platforms. <br /><br />It is our shared vision with Roche that informatics and data sciences are critical elements of an end-to-end genomics solution. Fast, easy-to-use, scalable, and robust informatics solutions make a big difference in the quality and impact of the work of scientists and researchers. We believe in the future of data-driven, personalized medicine. We are passionate about accelerating that future together with Roche.<br /><br />Financial details of the deal were not disclosed. For Roche, the move is yet another in a string of acquisitions. Last week (December 18), Roche paid $489 million for antibody maker Dutalys. And earlier this month, Roche bought prenatal testing company Ariosa Diagnostics.</p><p>Reference</p><p>http://blog.bina.com/news/bina-technologies-acquired-by-roche?&amp;__hssc=109677338.1.1419953400266&amp;__hstc=109677338.b8350f2729889b08f1325906d5236cd3.1419953400266.1419953400266.1419953400266.1&amp;hsCtaTracking=96cac941-9372-4bbf-bacb-3ca6f1ff8cfd|3fce0f18-835b-4086-9345-388880861732</p><p>http://www.the-scientist.com/?articles.view/articleNo/41750/title/Roche-Buys-Bioinformatics-Firm/</p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/37411/my-commonly-used-commands-in-bioinformatics</guid>
	<pubDate>Thu, 26 Jul 2018 04:58:45 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/37411/my-commonly-used-commands-in-bioinformatics</link>
	<title><![CDATA[My commonly used commands in Bioinformatics]]></title>
	<description><![CDATA[<p>FYI, I've found it useful to use MUMmer to extract the specific changes that Racon makes, so I can evaluate them individually:</p><pre><code>minimap -t 24 assembly.fasta long_reads.fastq.gz | racon -t 24 long_reads.fastq.gz - assembly.fasta racon_assembly.fasta
nucmer -p nucmer assembly.fasta racon_assembly.fasta
show-snps -C -T -r nucmer.delta
</code></pre><p>This reports Racon's changes in a table. You can exclude indels with the&nbsp;<code>-I</code>&nbsp;option in&nbsp;<code>show-snps</code>.&nbsp;</p><p>This process (Racon -&gt; MUMmer -&gt; SNP table) solves the problem I originally raised in this issue. So as far as I'm concerned, you can close this issue (or keep it open if you still want to implement some kind of variant table).</p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/20331/type-hinting</guid>
	<pubDate>Fri, 09 Jan 2015 22:26:13 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/20331/type-hinting</link>
	<title><![CDATA[Type Hinting]]></title>
	<description><![CDATA[<p>Python creator Guido van Rossum&rsquo;s proposal for static type-checking annotations is inching closer to reality, and the feature has taken on a new name: type hinting.</p><p><img src="http://sdtimes.com/wp-content/uploads/2015/01/0107.sdt-python-typehinting.png" alt="image" width="619" height="219" style="border: 0px; border: 0px;"></p><p>Back in August, van Rossum published a proposal on the Python mailing list recommending type-checking annotations as a valuable feature for the next version of Python to improve the performance of editors and IDEs, linter capabilities, standard notation, and refactoring. Van Rossum&rsquo;s <a href="http://lwn.net/Articles/627558/">latest proposal</a>, posted late last month, outlined plans to publish a Python Enhancement Proposal (PEP) in early January to put the feature now known as type hinting on track for inclusion in Python 3.5, slated for release this September.</p><p>Reference</p><p>https://quip.com/r69HA9GhGa7J</p>]]></description>
	<dc:creator>Pranjali Yadav</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38063/referee-genome-assembly-quality-scores</guid>
	<pubDate>Sun, 04 Nov 2018 16:44:30 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38063/referee-genome-assembly-quality-scores</link>
	<title><![CDATA[Referee: Genome assembly quality scores]]></title>
	<description><![CDATA[<p>Modern genome sequencing technologies provide a succint measure of quality at each position in every read, however all of this information is lost in the assembly process. Referee summarizes the quality information from the reads that map to a site in an assembled genome to calculate a quality score for each position in the genome assembly.</p>
<p>We accomplish this by first calculating genotype likelihoods for every site. For a given site in a diploid genome, there are 10 possible genotypes (AA, AC, AG, AT, CC, CG, CT, GG, GT, TT). Referee takes as input the genotype likelihoods calculated for all 10 genotypes given the called reference base at each position.</p>
<h3>Referee is a program to calculate a quality score for every position in a genome assembly. This allows for easy filtering of low quality sites for any downstream analysis.</h3>
<p>https://github.com/gwct/referee</p><p>Address of the bookmark: <a href="https://gwct.github.io/referee/#" rel="nofollow">https://gwct.github.io/referee/#</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/20363/postdoctoral-researcher-in-cancer-systems-biology</guid>
  <pubDate>Mon, 12 Jan 2015 01:44:11 -0600</pubDate>
  <link></link>
  <title><![CDATA[Postdoctoral Researcher in Cancer Systems Biology]]></title>
  <description><![CDATA[
<p>Postdoctoral Researcher in Cancer Systems Biology<br />Department of Oncology, Old Road Campus Research Building, Roosevelt Drive, Oxford<br />Grade 7: £30,434 - £37,394 with a discretionary range to £40,847 p.a.<br />Applications are invited for a Postdoctoral Researcher in Cancer Systems Biology to join a rapidly developing Bioinformatics Research Core group headed by Dr Anastasia Samsonova. The purpose of the role is to develop and deliver integrative approaches to dissect the complexity of cancer as a genomic disease. The research will focus on development and application of effective strategies for mining and integration of complex human *omics datasets and clinical/phenotypic data in cancer studies.</p>

<p>The role sits at the critical interface between genetics and cancer systems biology, and would suit a candidate who is interested in developing a career at the confluence of Statistics/Data Mining/Machine Learning and Biology. Ideally, you will have experience in development of analytical approaches to high-throughput and multivariate data mining and integration gained through a PhD (or equivalent) in a quantitative subject (eg mathematics, statistics, physics, engineering or computer science).</p>

<p>Experience of statistics and/or machine learning techniques is highly desirable as is evidence of prior experience of developing bioinformatics software and/or analysing complex *omics data sets. You will be able to work as part of a team and independently and deliver results to the required standard and schedule. You should be able to organise and prioritise your own work, as well as have excellent communication skills, both written and oral. The post will involve interactions with collaborators from such diverse fields as applied mathematics, statistics, computer science and medicine.</p>

<p>This is a full-time post, fixed-term until 31 March 2017. For informal enquiries, contact Dr Anastasia Samsonova (bioinformatics@oncology.ox.ac.uk).</p>

<p>All applicants must complete a short application form and upload a CV and supporting statement.</p>

<p>The closing date for applications is 12.00 noon on 26 January 2015.</p>

<p>More at https://www.recruit.ox.ac.uk/pls/hrisliverecruit/erq_jobspec_version_4.display_form</p>
]]></description>
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	<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>
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