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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/36890?offset=440</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32485/bacterial-genome-assembly</guid>
	<pubDate>Fri, 05 May 2017 06:11:22 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32485/bacterial-genome-assembly</link>
	<title><![CDATA[Bacterial genome assembly !!]]></title>
	<description><![CDATA[<p>This tutorial will serve as an example of how to use free and open-source genome assembly and secondary scaffolding tools to generate high quality assemblies of&nbsp;bacterial sequence data. The bacterial sample used in this tutorial will be referred&nbsp;to simply&nbsp;as &ldquo;Species&rdquo; since it is&nbsp;live data. This data is paired-end data, meaning that there are forward and reverse reads, which we will designate as Sample_R1.fastq and Sample_R2.fastq, respectively.</p>
<p>https://github.com/jennomics/WorkflowPaper/blob/master/Genome%20Assembly%20and%20Annotation.md</p><p>Address of the bookmark: <a href="http://bioinformatics.uconn.edu/bacterial-genome-assembly-tutorial/" rel="nofollow">http://bioinformatics.uconn.edu/bacterial-genome-assembly-tutorial/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32849/car-reconstructing-contiguous-regions-of-an-ancestral-genome</guid>
	<pubDate>Thu, 18 May 2017 05:24:01 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32849/car-reconstructing-contiguous-regions-of-an-ancestral-genome</link>
	<title><![CDATA[CAR: Reconstructing Contiguous Regions of an Ancestral Genome]]></title>
	<description><![CDATA[<div id="abstract-1">
<p id="p-5">We describe a new method for predicting the ancestral order and orientation of those intervals from their observed adjacencies in modern species. We combine the results from this method with data from chromosome painting experiments to produce a map of an early mammalian genome that accounts for 96.8% of the available human genome sequence data. The precision is further increased by mapping inversions as small as 31 bp. Analysis of the predicted evolutionary breakpoints in the human lineage confirms certain published observations but disagrees with others. Although only a few mammalian genomes are currently sequenced to high precision, our theoretical analyses and computer simulations indicate that our results are reasonably accurate and that they will become highly accurate in the foreseeable future. Our methods were developed as part of a project to reconstruct the genome sequence of the last ancestor of human, dogs, and most other placental mammals;</p>
</div><p>Address of the bookmark: <a href="http://www.bx.psu.edu/miller_lab/car/" rel="nofollow">http://www.bx.psu.edu/miller_lab/car/</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/33973/list-of-genome-announcement-notes-and-reporting-journals</guid>
	<pubDate>Wed, 26 Jul 2017 08:01:38 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/33973/list-of-genome-announcement-notes-and-reporting-journals</link>
	<title><![CDATA[List of genome announcement, notes and reporting journals]]></title>
	<description><![CDATA[<p><span>Faced with an increasing number of articles describing DNA data and a need for more appropriate venues to present these data, some publishers and journals have responded by changing the structure and format of genome papers. Specifically, certain journals have started accepting very short manuscripts (500&ndash;1500 words) that present a new chromosome sequence, its GenBank accession number and little else. These pint-sized articles go by various names, such as genome reports, genome announcements, genome notes or genome letters</span><span>, but will be referred to here broadly as genome reports. Their short length and minimal number (or complete absence) of figures, tables and article subheadings are a significant departure from long-form genome papers, which typically span 8&ndash;10 journal pages, contain many supporting items and have formal introduction, methods, results and discussion sections.</span></p><p>Following are the list of journals publishing&nbsp;<span>pint-sized articles go by various names, such as genome reports, genome announcements, genome notes or genome letters</span><span>, but will be referred to here broadly as genome reports.</span></p><p>1. <strong>Genome Announcements</strong>, American Society for Microbiology, Genome announcement, Impact factor 1.3, &nbsp;A 500-word report stating that the genome of a particular organism (prokaryote, eukaryote or virus) has been sequenced and providing a citable record of the corresponding GenBank submission. Must include abstract but no text headings can be used except for &lsquo;Acknowledgments&rsquo; and &lsquo;References&rsquo;. Cannot include figures, tables or supplemental material to present data or analysis.</p><p>Link: https://mra.asm.org/</p><p>2. <strong>Genome Biology and Evolution</strong>, Oxford University Press, Genome report, Impact factor 4.2, Focused 1500-word papers (up to six tables or figures) that publish the main evolutionary message of new genome sequences as they become submitted to GenBank. May also contain specifically focused comparative analyses of previously published genomes that contain a substantial and novel insight of broadest evolutionary significance.</p><p>Link: https://academic.oup.com/gbe</p><p>3. <strong>Journal of Biotechnology</strong>, Elsevier, Genome announcement, Impact factor 2.9, A 500-word report announcing the availability of the completely annotated genome sequence of a biotechnologically relevant organism in the corresponding database (for eukaryotes, advanced draft genomes will also be considered). Articles can contain an Abstract, a brief report on the organism and its biotechnological relevance, a table summarizing the genome features, References and an Acknowledgement. Figures are generally not allowed.</p><p>Link: https://www.journals.elsevier.com/journal-of-biotechnology</p><p>4. <strong>Journal of Genomics</strong>, Ivyspring, Genome note, Impact factor N/A, A 1000-word report (10 reference limit; conclusions not permitted) describing novel data sets from high-throughput analysis of genotypes, phenotypes, gene expression, metabolomes, proteomes or genome assemblies.Standard metrics for data quality and the experimental design must be clearly reported.</p><p>Link: http://www.jgenomics.com/</p><p>5. <strong>Mem&oacute;rias do Instituto</strong>, Oswaldo Cruz Oswaldo Cruz Foundation, Genome announcement and highlight, Impact factor 1.6, Dedicated to publishing new genome information from eukaryote parasites, virus, bacteria and their respective vectors, as well as re-sequencing or comparative genome analyses. Should occupy no more than three printed pages including figures and/or tables.</p><p>Link: http://memorias.ioc.fiocruz.br/</p><p>6. <strong>Molecular Ecology Resources,</strong> Wiley, Genomic resources note, &nbsp;Impact factor 3.7, Short notes on newly assembled and annotated transcriptomes, genome fractions or whole genomes, and/or a library of SNP/SSR markers.Authors submit a short manuscript describing how the resource was developed and where the data can be accessed. Do not appear in journal as individual papers but are instead published as part of a summary article.</p><p>Link: https://onlinelibrary.wiley.com/journal/17550998</p><p>7. <strong>Standards in Genomic Science</strong>, BioMed Central (Springer), Short genome report, Impact factor 3.2,&nbsp;<span>Short (&sim;500-word) article on newly sequenced genome. Article format must follow guidelines and template (available from journal Web site) put forward by the SGS. Any manuscripts not using template or that are missing key figures, tables and/or references (as per the guidelines) will be returned to authors. Rationale of the content model is to provide information that is consistently and uniformly presented for rapid and easy consumption by both human and machine readers.&nbsp;</span></p><p><span>Link: https://standardsingenomics.biomedcentral.com/</span></p><p><span>8. <strong>3biotech</strong>, Springer,&nbsp;<span>Short genome report, Impact factor 1.3,&nbsp;</span><span>Short (&sim;500-word) article on newly sequenced genome. Article format must follow guidelines (available from journal Web site).&nbsp;<span>&nbsp;Genome of a particular organism (prokaryote, eukaryote or virus) has been sequenced and providing a citable record of the corresponding GenBank submission.</span></span></span></p><p><span><span><span>Link: https://link.springer.com/journal/13205</span></span></span></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37746/funannotate-eukaryotic-genome-annotation-pipeline</guid>
	<pubDate>Wed, 19 Sep 2018 07:47:22 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37746/funannotate-eukaryotic-genome-annotation-pipeline</link>
	<title><![CDATA[funannotate: Eukaryotic Genome Annotation Pipeline]]></title>
	<description><![CDATA[<p><span>Funannotate is a genome prediction, annotation, and comparison software package. It was originally written to annotate fungal genomes (small eukaryotes ~ 30 Mb genomes), but has evolved over time to accomodate larger genomes. The impetus for this software package was to be able to accurately and easily annotate a genome for submission to NCBI GenBank. Existing tools (such as Maker) require significant manually editing to comply with GenBank submission rules, thus funannotate is aimed at simplifying the genome submission process.</span></p><p>Address of the bookmark: <a href="https://github.com/nextgenusfs/funannotate" rel="nofollow">https://github.com/nextgenusfs/funannotate</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36239/scilifelab-tutorial-for-bioinformatics-analysis</guid>
	<pubDate>Tue, 17 Apr 2018 04:33:00 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36239/scilifelab-tutorial-for-bioinformatics-analysis</link>
	<title><![CDATA[SciLifeLab tutorial for bioinformatics analysis !]]></title>
	<description><![CDATA[<p>SciLifeLab is a national center for molecular biosciences with focus on health and environmental research.</p>
<h2 id="courses">Courses</h2>
<p><a href="http://uppnex.se/twiki/bin/view/Courses/">Old courses (2012-2014)</a></p>
<h3 id="metagenomics-workshop">Metagenomics Workshop</h3>
<p><a href="https://scilifelab.github.io/courses/Metagenomics/1511/">2015 November - Uppsala</a><br><a href="https://scilifelab.github.io/courses/Metagenomics/1611/">2016 November - Uppsala</a><br><a href="https://scilifelab.github.io/courses/Metagenomics/1711/">2017 November - Uppsala</a></p>
<h3 id="introduction-to-bioinformatics-using-ngs-data">Introduction to Bioinformatics Using NGS Data</h3>
<p><a href="https://scilifelab.github.io/courses/ngsintro/1502/">2015 February - Uppsala</a>&nbsp;<br><a href="https://scilifelab.github.io/courses/ngsintro/1505/">2015 May - Gothenburg</a><br><a href="https://scilifelab.github.io/courses/ngsintro/1509/">2015 September - Uppsala</a><br><a href="https://scilifelab.github.io/courses/ngsintro/1511/">2015 November - Lund</a><br><a href="https://scilifelab.github.io/courses/ngsintro/1601/">2016 January - Uppsala</a><br><a href="https://scilifelab.github.io/courses/ngsintro/1604/">2016 April - Link&ouml;ping</a><br><a href="https://scilifelab.github.io/courses/ngsintro/1609/">2016 September - Uppsala</a><br><a href="https://scilifelab.github.io/courses/ngsintro/1611/">2016 November - Ume&aring;</a><br><a href="https://scilifelab.github.io/courses/ngsintro/1701/">2017 January - Uppsala</a><br><a href="https://scilifelab.github.io/courses/ngsintro/1705/">2017 May - Gothenburg</a><br><a href="https://scilifelab.github.io/courses/ngsintro/1709/">2017 September - Lund</a><br><a href="https://scilifelab.github.io/courses/ngsintro/1711/">2017 November - Uppsala</a><br><a href="https://scilifelab.github.io/courses/ngsintro/1802/">2018 February - Uppsala</a></p>
<h3 id="introduction-to-genome-annotation">Introduction to Genome Annotation</h3>
<p><a href="https://scilifelab.github.io/courses/annotation/2015/">2015 April - Uppsala</a><br><a href="https://scilifelab.github.io/courses/annotation/2016/">2016 April - Uppsala</a><br><a href="https://scilifelab.github.io/courses/annotation/2017/">2017 April - Uppsala</a><br><a href="https://scilifelab.github.io/courses/annotation/2018/">2018 May - Uppsala</a></p>
<h3 id="de-novo-genome-assembly">De Novo Genome Assembly</h3>
<p><a href="https://scilifelab.github.io/courses/assembly/1611/">2016 November - Uppsala</a><br><a href="https://scilifelab.github.io/courses/assembly/2017-11-15/">2017 November - Uppsala</a></p>
<h3 id="rna-seq-course">RNA-seq course</h3>
<p><a href="https://scilifelab.github.io/courses/rnaseq/1510/">2015 October - Uppsala</a><br><a href="https://scilifelab.github.io/courses/rnaseq/1604/">2016 April - Uppsala</a><br><a href="https://scilifelab.github.io/courses/rnaseq/1610/">2016 October - Uppsala</a><br><a href="https://scilifelab.github.io/courses/rnaseq/1703/">2017 March - Uppsala</a><br><a href="https://scilifelab.github.io/courses/rnaseq/1711/">2017 November - Uppsala</a><br><a href="https://scilifelab.github.io/courses/rnaseq/labs">RNAseq tutorials</a></p>
<h3 id="r-programming-foundations-for-life-scientists">R Programming Foundations for Life Scientists</h3>
<p><a href="https://scilifelab.github.io/courses/r_programming/1611/">2016 November - Uppsala</a><br><a href="https://scilifelab.github.io/courses/r_programming/1703/">2017 Mars - Uppsala</a></p>
<h3 id="single-cell-rna-sequencing-analysis">Single cell RNA sequencing analysis</h3>
<p><a href="https://scilifelab.github.io/courses/scrnaseq/1710/">2017 October - Uppsala</a></p><p>Address of the bookmark: <a href="https://scilifelab.github.io/courses/" rel="nofollow">https://scilifelab.github.io/courses/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36997/cgview-circular-genome-viewer</guid>
	<pubDate>Wed, 20 Jun 2018 10:15:57 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36997/cgview-circular-genome-viewer</link>
	<title><![CDATA[CGView - Circular Genome Viewer]]></title>
	<description><![CDATA[CGView is a Java package for generating high quality, zoomable maps of circular genomes. Its primary purpose is to serve as a component of sequence annotation pipelines, as a means of generating visual output suitable for the web. Feature information and rendering options are supplied to the program using an XML file, a tab delimited file, or an NCBI ptt file. CGView converts the input into a graphical map (PNG, JPG, or Scalable Vector Graphics format), complete with labels, a title, legends, and footnotes. In addition to the default full view map, the program can generate a series of hyperlinked maps showing expanded views. The linked maps can be explored using any web browser, allowing rapid genome browsing, and facilitating data sharing. The feature labels in maps can be hyperlinked to external resources, allowing CGView maps to be integrated with existing web site content or databases. For examples of the various output types, see the CGView gallery.

http://wishart.biology.ualberta.ca/cgview/gallery.html

http://stothard.afns.ualberta.ca/downloads/CCT/index.html

https://www.gview.ca/wiki/GView/WebHome

https://server.gview.ca/

http://stothard.afns.ualberta.ca/cgview_server/

Paper https://academic.oup.com/bib/advance-article/doi/10.1093/bib/bbx081/4037458<p>Address of the bookmark: <a href="http://wishart.biology.ualberta.ca/cgview/" rel="nofollow">http://wishart.biology.ualberta.ca/cgview/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/37927/you-cant-hide-from-genome-hackers</guid>
	<pubDate>Sat, 13 Oct 2018 14:17:28 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/37927/you-cant-hide-from-genome-hackers</link>
	<title><![CDATA[You can't hide from Genome Hackers]]></title>
	<description><![CDATA[<p><span>Young computational biologist named Yaniv Erlich shocked the research world by showing it was possible to&nbsp;</span><a href="https://www.wired.com/2013/01/your-genome-could-reveal-your-identity/">unmask the identities</a><span>&nbsp;of people listed in anonymous genetic databases using&nbsp;</span><a href="http://science.sciencemag.org/content/339/6117/321" target="_blank">only an Internet connection</a></p><p>Paper: http://science.sciencemag.org/content/early/2018/10/10/science.aau4832</p><p>More at&nbsp;https://www.wired.com/story/genome-hackers-show-no-ones-dna-is-anonymous-anymore/</p>]]></description>
	<dc:creator>Neel</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38215/pwhatshap-a-parallel-high-performance-version-of-whatshap</guid>
	<pubDate>Wed, 14 Nov 2018 08:20:27 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38215/pwhatshap-a-parallel-high-performance-version-of-whatshap</link>
	<title><![CDATA[pWhatsHap: a parallel, high-performance version of WhatsHap]]></title>
	<description><![CDATA[<div id="ASec4">
<p>Given the potential relevance of efficient haplotyping in several analysis pipelines, we have designed and engineered&nbsp;pWhatsHap, a parallel, high-performance version of&nbsp;WhatsHap.&nbsp;pWhatsHap&nbsp;is embedded in a toolkit developed in Python and supports genomics datasets in standard file formats. Building on&nbsp;WhatsHap,&nbsp;pWhatsHap&nbsp;exhibits the same complexity exploring a number of possible solutions which is exponential in the coverage of the dataset. The parallel implementation on multi-core architectures allows for a relevant reduction of the execution time for haplotyping, while the provided results enjoy the same high accuracy as that provided by&nbsp;WhatsHap, which increases with coverage.</p>
</div>
<p>https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-016-1170-y</p><p>Address of the bookmark: <a href="https://bitbucket.org/whatshap/whatshap" rel="nofollow">https://bitbucket.org/whatshap/whatshap</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38515/genome-annotation-using-maker-tutorial</guid>
	<pubDate>Thu, 20 Dec 2018 17:39:23 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38515/genome-annotation-using-maker-tutorial</link>
	<title><![CDATA[Genome Annotation using MAKER tutorial !]]></title>
	<description><![CDATA[<p><a href="http://www.yandell-lab.org/software/maker.html">MAKER</a><span>&nbsp;is a great tool for annotating a reference genome using empirical and&nbsp;</span><em>ab initio</em><span>gene predictions.&nbsp;</span><a href="http://gmod.org/wiki/Main_Page">GMOD</a><span>, the umbrella organization that includes MAKER, has some nice tutorials online for running MAKER. However, these were quite simplified examples and it took a bit of effort to wrap my head completely around everything. Here I will describe a&nbsp;</span><em>de novo</em><span>&nbsp;genome annotation for&nbsp;</span><em>Boa constrictor</em><span>&nbsp;in detail, so that there is a record and that it is easy to use this as a guide to annotate any genome.</span></p><p>Address of the bookmark: <a href="https://www.biostars.org/p/261203/" rel="nofollow">https://www.biostars.org/p/261203/</a></p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38801/genome-assembly-forensics-finding-the-elusive-mis-assembly</guid>
	<pubDate>Sat, 26 Jan 2019 18:02:01 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38801/genome-assembly-forensics-finding-the-elusive-mis-assembly</link>
	<title><![CDATA[Genome assembly forensics: finding the elusive mis-assembly]]></title>
	<description><![CDATA[<p><span>We present the first collection of tools aimed at automated genome assembly validation. This work formalizes several mechanisms for detecting mis-assemblies, and describes their implementation in our automated validation pipeline, called&nbsp;</span><em>amosvalidate</em><span>. We demonstrate the application of our pipeline in both bacterial and eukaryotic genome assemblies, and highlight several assembly errors in both draft and finished genomes. The software described is compatible with common assembly formats and is released, open-source, at&nbsp;</span><a href="http://amos.sourceforge.net/" target="_blank">http://amos.sourceforge.net</a><span>.</span></p>
<p>https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2397507/&nbsp;</p>
<p>http://amos.sourceforge.net/wiki/index.php/AMOS</p><p>Address of the bookmark: <a href="http://amos.sourceforge.net/wiki/index.php/AMOS" rel="nofollow">http://amos.sourceforge.net/wiki/index.php/AMOS</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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