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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/32076?offset=510</link>
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	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41207/blobtoolkit-a-toolkit-for-genome-assembly-qc</guid>
	<pubDate>Fri, 21 Feb 2020 00:17:50 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41207/blobtoolkit-a-toolkit-for-genome-assembly-qc</link>
	<title><![CDATA[BlobToolKit: A toolkit for genome assembly QC]]></title>
	<description><![CDATA[<p>Filtering raw genomic datasets is essential to avoid chimeric assemblies and to increase the validity of sequence-based biological inference. BlobToolKit extends the BlobTools<span>1</span>/Blobology<span>2</span>&nbsp;approach to simplify interactive and reproducible filtering.</p>
<p>BlobToolKit is comprised of four components:</p>
<ol>
<li><a href="https://blobtoolkit.genomehubs.org/btk-viewer/">BlobToolKit Viewer</a>&nbsp;allows browser-based interactive visualisation and filtering of preliminary or published genomic datasets even for highly fragmented assemblies.</li>
<li><a href="https://blobtoolkit.genomehubs.org/blobtools2/">BlobTools2</a>&nbsp;is a command-line program to convert assemblies and analysis results into datasets that can be further processed using&nbsp;<a href="https://blobtoolkit.genomehubs.org/blobtools2/">BlobTools2</a>&nbsp;and/or visualised in the Viewer.</li>
<li>The&nbsp;<a href="https://blobtoolkit.genomehubs.org/specification/">BlobToolKit Specification</a>&nbsp;features a formal schema and validator for the JSON-based BlobDir format used by&nbsp;<a href="https://blobtoolkit.genomehubs.org/blobtools2/">BlobTools2</a>&nbsp;and the&nbsp;<a href="https://blobtoolkit.genomehubs.org/btk-viewer/">Viewer</a>.</li>
<li>The&nbsp;<a href="https://blobtoolkit.genomehubs.org/pipeline/">BlobToolKit Pipeline</a>&nbsp;is a configurable Snakemake pipeline that automates all steps from retrieving public datasets through running analyses and generating a BlobDir dataset with&nbsp;<a href="https://blobtoolkit.genomehubs.org/blobtools2/">BlobTools2</a>, ready for visualisation in the&nbsp;<a href="https://blobtoolkit.genomehubs.org/btk-viewer/">Viewer</a>.</li>
</ol>
<p>Paper&nbsp;<a href="https://www.biorxiv.org/content/10.1101/844852v1.full.pdf">https://www.biorxiv.org/content/10.1101/844852v1.full.pdf</a></p><p>Address of the bookmark: <a href="https://blobtoolkit.genomehubs.org/" rel="nofollow">https://blobtoolkit.genomehubs.org/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/29588/research-associate-and-junior-research-fellow-at-north-eastern-hill-university-tura-meghalaya</guid>
  <pubDate>Fri, 28 Oct 2016 09:54:43 -0500</pubDate>
  <link></link>
  <title><![CDATA[Research Associate and Junior Research Fellow at North-Eastern Hill University - Tura, Meghalaya]]></title>
  <description><![CDATA[
<p>Research Associate and Junior Research Fellow <br />North-Eastern Hill University - Tura, Meghalaya <br />₹18,000 a month<br />Applications are invited for the post of Research Associate and JRF in the DBT sponsored Bioinformatics Infrastructure Facility (BIF), posts are purely temporary and terminable at anytime without prior notice or assigning any reason thereof. </p>

<p>Research Associate : <br />Essential Qualification: Ph.D in Bioinformatics/Biotechnology/Life Science from a reocngised univeristy/institute <br />Pay: Rs.36000-/- + Admissible 10% HRA per month <br />Age: Below 35 years </p>

<p>Junior Research Fellow <br />Essential Qualification: M.Sc in Bioinformatics/Biotechnology/Life Science from a reocngised univeristy/institute <br />Pay: Rs.18000-/- + per month <br />Age: Below 35 years </p>

<p>Last date for receving application by mail or post is 08.11.2016 </p>

<p>Company Info. <br />North-Eastern Hill University </p>

<p>Bioinformatics Infrastructure Facility (BIF) Department of RDAP North-Eastern Hill University, Tura Campus Tura-794002, Meghalaya</p>

<p>More at http://www.nehu.ac.in/Advertisements/BIFTuraManpowerAdvt_25102016.pdf</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41501/hicanu-accurate-assembly-of-segmental-duplications-satellites-and-allelic-variants-from-high-fidelity-long-reads</guid>
	<pubDate>Fri, 27 Mar 2020 22:49:31 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41501/hicanu-accurate-assembly-of-segmental-duplications-satellites-and-allelic-variants-from-high-fidelity-long-reads</link>
	<title><![CDATA[HiCanu: accurate assembly of segmental duplications, satellites, and allelic variants from high-fidelity long reads]]></title>
	<description><![CDATA[<p><span>HiCanu, a significant modification of the Canu assembler designed to leverage the full potential of HiFi reads via homopolymer compression, overlap-based error correction, and aggressive false overlap filtering.&nbsp;</span></p>
<p>More at&nbsp;<a href="https://www.biorxiv.org/content/10.1101/2020.03.14.992248v3?fbclid=IwAR2PaN4GLjvAZpWmCE2q0EWk2dtwY7wiKxVlXn9PPG7OBSP06PP2gcCrv3A">https://www.biorxiv.org/content/10.1101/2020.03.14.992248v3</a></p><p>Address of the bookmark: <a href="https://github.com/marbl/canu" rel="nofollow">https://github.com/marbl/canu</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29620/hybpiper</guid>
	<pubDate>Fri, 04 Nov 2016 05:02:10 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29620/hybpiper</link>
	<title><![CDATA[HybPiper]]></title>
	<description><![CDATA[<p>HybPiper was designed for targeted sequence capture, in which DNA sequencing libraries are enriched for gene regions of interest, especially for phylogenetics. HybPiper is a suite of Python scripts that wrap and connect bioinformatics tools in order to extract target sequences from high-throughput DNA sequencing reads.</p>
<p>Targeted bait capture is a technique for sequencing many loci simultaneously based on bait sequences. HybPiper pipeline starts with high-throughput sequencing reads (for example from Illumina MiSeq), and assigns them to target genes using BLASTx or BWA. The reads are distributed to separate directories, where they are assembled separately using SPAdes. The main output is a FASTA file of the (in frame) CDS portion of the sample for each target region, and a separate file with the translated protein sequence.</p>
<p>HybPiper also includes post-processing scripts, run after the main pipeline, to also extract the intronic regions flanking each exon, investigate putative paralogs, and calculate sequencing depth. For more information,&nbsp;<a href="https://github.com/mossmatters/HybPiper/wiki/">please see our wiki</a>.</p>
<p>HybPiper is run separately for each sample (single or paired-end sequence reads). When HybPiper generates sequence files from the reads, it does so in a standardized directory hierarchy. Many of the post-processing scripts rely on this directory hierarchy, so do not modify it after running the initial pipeline. It is a good idea to run the pipeline for each sample from the same directory. You will end up with one directory per run of HybPiper, and some of the later scripts take advantage of this predictable directory structure.</p><p>Address of the bookmark: <a href="https://github.com/mossmatters/HybPiper" rel="nofollow">https://github.com/mossmatters/HybPiper</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41734/supernova-generates-phased-whole-genome-de-novo-assemblies-from-a-chromium-prepared-library</guid>
	<pubDate>Sun, 31 May 2020 01:59:30 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41734/supernova-generates-phased-whole-genome-de-novo-assemblies-from-a-chromium-prepared-library</link>
	<title><![CDATA[Supernova: generates phased, whole-genome de novo assemblies from a Chromium-prepared library.]]></title>
	<description><![CDATA[<p>Supernova generates phased, whole-genome&nbsp;<em>de novo</em>&nbsp;assemblies from a Chromium-prepared library.</p>
<p>Please see&nbsp;<a href="https://support.10xgenomics.com/de-novo-assembly/guidance/doc/achieving-success-with-de-novo-assembly">Achieving Success with De Novo Assembly</a>&nbsp;and&nbsp;<a href="https://support.10xgenomics.com/de-novo-assembly/software/overview/system-requirements">System Requirements</a>&nbsp;<em>before</em>&nbsp;creating your Chromium libraries for assembly.</p>
<p>Supernova should be run using 38-56x coverage of the genome.<br>&bull; Somewhat higher coverage is&nbsp;<em>sometimes</em>&nbsp;advantageous.<br>&bull; Supernova will exit if it finds that coverage is far from the recommended range.<br>&bull; Note that at most 2.14 billion reads are allowed.<br>&bull; Please note that we have not extensively tested genomes larger than human, and any genome above approximately 4 GB should be considered experimental and is not supported.</p><p>Address of the bookmark: <a href="https://support.10xgenomics.com/de-novo-assembly/software/pipelines/latest/using/running" rel="nofollow">https://support.10xgenomics.com/de-novo-assembly/software/pipelines/latest/using/running</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/file/view/29638/r-graphical-cookbook-by-winston-chang</guid>
	<pubDate>Fri, 04 Nov 2016 12:50:30 -0500</pubDate>
	<link>https://bioinformaticsonline.com/file/view/29638/r-graphical-cookbook-by-winston-chang</link>
	<title><![CDATA[R Graphical Cookbook by Winston Chang]]></title>
	<description><![CDATA[<p>R Graphical Cookbook by Winston Chang</p><p>A very nice book by Winston Chang for R ethusiast. The R code presented in these pages is the R code actually used to produce the Figures in the book. There will be differences compared to the code chunks shown in the text of the book, but in most cases the differences will be that these pages contain additional code to lay out multiple plots on a single "page".</p><p>The code presented for each figure is self-contained, i.e., all code required to produce the figure is included. This means that there is sometimes considerable overlap of code between several figures  In some cases, it may be necessary to install an add-on package from CRAN to get the code to run.</p><p>More books at http://www.e-reading.club/bookreader.php/137370/C486x_APPb.pdf</p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
	<enclosure url="https://bioinformaticsonline.com/file/download/29638" length="37521" type="image/png" />
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42497/genome-assembly-training-tutorial-at-galaxy</guid>
	<pubDate>Sun, 27 Dec 2020 05:25:45 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42497/genome-assembly-training-tutorial-at-galaxy</link>
	<title><![CDATA[Genome assembly training tutorial at Galaxy !]]></title>
	<description><![CDATA[<p>In this tutorial we assemble and annotate the genome of <em>E. coli</em> strain <a href="http://cgsc2.biology.yale.edu/Strain.php?ID=8232">C-1</a>. This strain is routinely used in experimental evolution studies involving bacteriophages. For instance, now classic works by Holly Wichman and Jim Bull (<a href="https://training.galaxyproject.org/training-material/topics/assembly/tutorials/unicycler-assembly/tutorial.html#Bull1997">Bull 1997</a>, <a href="https://training.galaxyproject.org/training-material/topics/assembly/tutorials/unicycler-assembly/tutorial.html#Bull1998">Bull 1998</a>, <a href="https://training.galaxyproject.org/training-material/topics/assembly/tutorials/unicycler-assembly/tutorial.html#Wichman1999">Wichman 1999</a>) have been performed using this strain and bacteriophage phiX174.</p><p>Address of the bookmark: <a href="https://training.galaxyproject.org/training-material/topics/assembly/tutorials/unicycler-assembly/tutorial.html" rel="nofollow">https://training.galaxyproject.org/training-material/topics/assembly/tutorials/unicycler-assembly/tutorial.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29656/statistics-and-probability</guid>
	<pubDate>Tue, 08 Nov 2016 07:34:25 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29656/statistics-and-probability</link>
	<title><![CDATA[Statistics and probability]]></title>
	<description><![CDATA[<h3><span>Topics</span></h3>
<div>
<div><a href="https://www.khanacademy.org/math/statistics-probability/displaying-describing-data">Displaying and describing data</a></div>
<div><a href="https://www.khanacademy.org/math/statistics-probability/modeling-distributions-of-data">Modeling distributions of data</a></div>
<div><a href="https://www.khanacademy.org/math/statistics-probability/describing-relationships-quantitative-data">Describing relationships in quantitative data</a></div>
<div><a href="https://www.khanacademy.org/math/statistics-probability/designing-studies">Designing studies</a></div>
<div><a href="https://www.khanacademy.org/math/statistics-probability/probability-library">Probability</a></div>
<div><a href="https://www.khanacademy.org/math/statistics-probability/random-variables-stats-library">Random variables</a></div>
<div><a href="https://www.khanacademy.org/math/statistics-probability/sampling-distributions-library">Sampling distributions</a></div>
<div><a href="https://www.khanacademy.org/math/statistics-probability/confidence-intervals-one-sample">Confidence intervals (one sample)</a></div>
<div><a href="https://www.khanacademy.org/math/statistics-probability/significance-tests-one-sample">Significance tests (one sample)</a></div>
<div><a href="https://www.khanacademy.org/math/statistics-probability/significance-tests-confidence-intervals-two-samples">Significance tests and confidence intervals (two samples)</a></div>
<div><a href="https://www.khanacademy.org/math/statistics-probability/inference-categorical-data-chi-square-tests">Inference for categorical data (chi-square tests)</a></div>
<div><a href="https://www.khanacademy.org/math/statistics-probability/advanced-regression-inference-transforming">Advanced regression (inference and tran</a></div>
</div><p>Address of the bookmark: <a href="https://www.khanacademy.org/math/statistics-probability" rel="nofollow">https://www.khanacademy.org/math/statistics-probability</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43088/iva-accurate-de-novo-assembly-of-rna-virus-genomes</guid>
	<pubDate>Wed, 23 Jun 2021 07:51:59 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43088/iva-accurate-de-novo-assembly-of-rna-virus-genomes</link>
	<title><![CDATA[IVA: accurate de novo assembly of RNA virus genomes]]></title>
	<description><![CDATA[<p>IVA (Iterative Virus Assembler) designed specifically for read pairs sequenced at highly variable depth from RNA virus samples. We tested IVA on datasets from 140 sequenced samples from human immunodeficiency virus-1 or influenza-virus-infected people and demonstrated that IVA outperforms all other virus de novo assemblers.</p>
<p><strong> Availability and implementation: </strong> The software runs under Linux, has the GPLv3 licence and is freely available from http://sanger-pathogens.github.io/iva</p>
<p>https://pubmed.ncbi.nlm.nih.gov/25725497/</p><p>Address of the bookmark: <a href="https://github.com/sanger-pathogens/iva" rel="nofollow">https://github.com/sanger-pathogens/iva</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29693/bioistats-online-course</guid>
	<pubDate>Thu, 10 Nov 2016 04:22:51 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29693/bioistats-online-course</link>
	<title><![CDATA[Bioistats Online course]]></title>
	<description><![CDATA[<p><span>One of our primary focuses will be to develop an understanding of the various ways in which we can assign a probability to some chance event. We'll also learn the&nbsp;</span><strong>fundamental&nbsp;</strong><span><strong>properties of probability</strong>, investigate how probability behaves, and learn how to calculate the probability of a new chance event.</span></p>
<p><span>This book is handy understanding basic concepts.</span></p><p>Address of the bookmark: <a href="https://onlinecourses.science.psu.edu/stat414/node/287" rel="nofollow">https://onlinecourses.science.psu.edu/stat414/node/287</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
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