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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/27076?offset=360</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29274/strudel</guid>
	<pubDate>Fri, 30 Sep 2016 09:47:02 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29274/strudel</link>
	<title><![CDATA[Strudel]]></title>
	<description><![CDATA[<p>Strudel is our graphical tool for visualizing genetic and physical maps of genomes for comparative purposes. The application aims to let the user examine their data at a variety of different levels of resolution, from entire maps to individual markers, and explore syntenic relationships between genomes. All browsing and interaction with Strudel happens in real-time &ndash; there is no need to wait while the maps are generated. It is built using Java 1.6 and ships with its own JRE, so there is no need for users to install or update Java.</p><p>Address of the bookmark: <a href="https://ics.hutton.ac.uk/strudel/" rel="nofollow">https://ics.hutton.ac.uk/strudel/</a></p>]]></description>
	<dc:creator>Anjana</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/38765/list-of-tools-frequently-used-while-genome-assembly</guid>
	<pubDate>Tue, 22 Jan 2019 09:39:02 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/38765/list-of-tools-frequently-used-while-genome-assembly</link>
	<title><![CDATA[List of tools frequently used while genome assembly]]></title>
	<description><![CDATA[<h4>List of tools frequently used while genome assembly:</h4><p>I have used the following assemblers</p><ul>
<li><a href="http://bioinf.spbau.ru/spades">Spades</a>&nbsp;(v. 3.10.1)</li>
<li><a href="http://canu.readthedocs.io/en/stable/index.html">CANU</a>&nbsp;(v. 1.6)</li>
<li><a href="https://github.com/rrwick/Unicycler">Unicycler&nbsp;</a>(v. v0.4.1)</li>
<li><a href="https://github.com/lh3/miniasm">Miniasm</a>&nbsp;(v. 0.2-r137-dirty)</li>
</ul><p>I have used the following mappers</p><ul>
<li><a href="https://github.com/lh3/minimap2">minimap2</a>&nbsp;(v.&nbsp;2.0rc1-r232)</li>
<li><a href="https://github.com/lh3/minimap">minimap&nbsp;</a>(v. 0.2-r124-dirty)</li>
<li><a href="https://github.com/lh3/bwa">bwa</a>&nbsp;(v.&nbsp;0.7.12-r1039)</li>
</ul><p>I have used the following polishing tools</p><ul>
<li><a href="https://github.com/isovic/racon">Racon</a>&nbsp;(v. not available)</li>
<li><a href="https://github.com/broadinstitute/pilon">Pilon</a>&nbsp;(v. 1.18)</li>
<li><a href="https://github.com/jts/nanopolish">Nanopolish</a>&nbsp;(v. 0.8.3)</li>
</ul><p>I have used the following tools to assess genome assembly characteristics</p><ul>
<li><a href="https://github.com/chjp/ANI">ANI.pl</a>&nbsp;(https://github.com/chjp/ANI)</li>
<li><a href="http://ecogenomics.github.io/CheckM/">CheckM</a>&nbsp;(v. 1.0.7)</li>
<li><a href="https://github.com/tseemann/prokka">Prokka</a>&nbsp;(v. 1.12)</li>
<li><a href="http://bioinf.spbau.ru/en/quast">QUAST</a>&nbsp;(v. 2.3)</li>
<li><a href="http://mummer.sourceforge.net/">mummer&nbsp;</a>(v. not available)</li>
</ul><p>If you have any ideas or superior tools we have missed please let us know in the comments.</p>]]></description>
	<dc:creator>BioStar</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39856/tritex-sequence-assembly-pipeline-for-triticeae-genomes</guid>
	<pubDate>Tue, 20 Aug 2019 09:47:14 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39856/tritex-sequence-assembly-pipeline-for-triticeae-genomes</link>
	<title><![CDATA[TRITEX sequence assembly pipeline for Triticeae genomes]]></title>
	<description><![CDATA[<div>
<p>The pipeline is open-source and hosted in a public Bitbucket&nbsp;<a href="https://bitbucket.org/tritexassembly/tritexassembly.bitbucket.io/src/master/">repository</a>.</p>
</div>
<div>
<p>TRITEX has been run on highly inbred genotypes of barley (<em>Hordeum vulgare</em>), tetraploid wheat (<em>Triticum turgidum</em>) and hexaploid wheat (<em>T. aestivum</em>) with reasonable results: super-scaffold N50 values in the range of dozens of Mb and pseudomolecules with better gene space representation than a BAC-by-BAC assembly. It has never been tested and is not expected to work on heterozygous or autopolyploid genomes.</p>
</div>
<div>
<p>A protocol for generating chromosome-conformation capture sequencing (Hi-C) data suitable for use with the pipeline is described in&nbsp;<a href="https://bio-protocol.org/e2955">Himmelbach et al. 2018</a>. Refer to the&nbsp;<a href="https://www.10xgenomics.com/resources/technical-notes/">technical notes</a>&nbsp;of 10X Genomics on how to generate Chromium data.</p>
</div><p>Address of the bookmark: <a href="https://tritexassembly.bitbucket.io/" rel="nofollow">https://tritexassembly.bitbucket.io/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29576/impute2</guid>
	<pubDate>Thu, 27 Oct 2016 11:21:44 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29576/impute2</link>
	<title><![CDATA[IMPUTE2]]></title>
	<description><![CDATA[<p><strong>IMPUTE2</strong>&nbsp;is a computer program for phasing observed genotypes and imputing missing genotypes. Most people use just a couple of the program's basic functions, but we have also built up a collection of specialized and powerful options. If you are new to&nbsp;<strong>IMPUTE2</strong>, or indeed to phasing and imputation in general, we suggest that you start by learning the basics.</p>
<p>You should begin by downloading the program from&nbsp;<a href="https://mathgen.stats.ox.ac.uk/impute/impute_v2.html#download">here</a>. You will need to choose the link that matches your computing platform and then follow the instructions for opening the download package.</p>
<p>Once you have done this, you will be ready to try some example analyses on the test data that are provided with the download. The section on&nbsp;<a href="https://mathgen.stats.ox.ac.uk/impute/impute_v2.html#examples">Examples</a>&nbsp;shows how to use the most common&nbsp;<strong>IMPUTE2</strong>&nbsp;functions. We suggest that you work through these examples and try to understand what the elements of each command are doing. If you don't understand something or would like to know if the program can perform a function that isn't listed, you can read our&nbsp;<a href="https://mathgen.stats.ox.ac.uk/impute/impute_v2.html#faq">FAQ</a>&nbsp;or submit a question to our&nbsp;<a href="https://mathgen.stats.ox.ac.uk/impute/impute_v2.html#mail_list">mail list</a>.</p>
<p>When you have learned the basic functionality of the program, you can use several features of this website to prepare your own analysis:</p>
<ul>
<li>Learn about&nbsp;<a href="https://mathgen.stats.ox.ac.uk/impute/impute_v2.html#best_practices">best practices</a>&nbsp;for imputation.</li>
<li>Download&nbsp;<a href="https://mathgen.stats.ox.ac.uk/impute/impute_v2.html#reference">reference data</a>&nbsp;that you can use to impute genotypes in your study.</li>
<li>Look through a complete list of&nbsp;<a href="https://mathgen.stats.ox.ac.uk/impute/impute_v2.html#options">program options</a>.</li>
</ul><p>Address of the bookmark: <a href="https://mathgen.stats.ox.ac.uk/impute/impute_v2.html" rel="nofollow">https://mathgen.stats.ox.ac.uk/impute/impute_v2.html</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/41459/jcvipython-utility-libraries-on-genome-assembly-annotation-and-comparative-genomics</guid>
	<pubDate>Tue, 17 Mar 2020 06:19:06 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41459/jcvipython-utility-libraries-on-genome-assembly-annotation-and-comparative-genomics</link>
	<title><![CDATA[JCVI:Python utility libraries on genome assembly, annotation and comparative genomics]]></title>
	<description><![CDATA[<p>Collection of Python libraries to parse bioinformatics files, or perform computation related to assembly, annotation, and comparative genomics.</p>
<p>https://github.com/tanghaibao/jcvi</p>
<p>More at https://github.com/tanghaibao/jcvi/wiki</p><p>Address of the bookmark: <a href="https://github.com/tanghaibao/jcvi" rel="nofollow">https://github.com/tanghaibao/jcvi</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/42941/csa-a-high-throughput-chromosome-scale-assembly-pipeline-for-vertebrate-genomes</guid>
	<pubDate>Wed, 10 Mar 2021 06:13:49 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42941/csa-a-high-throughput-chromosome-scale-assembly-pipeline-for-vertebrate-genomes</link>
	<title><![CDATA[CSA: A high-throughput chromosome-scale assembly pipeline for vertebrate genomes]]></title>
	<description><![CDATA[<p>The pipeline can use information from scaffolded assemblies (for example from HiC or 10X Genomics), or even from diverged (~65-100 Mya) reference genomes for ordering the contigs and thus support the assembly process. This typically results in improved contig N50 when compared to current state of the art methods.</p>
<p><img src="https://github.com/HMPNK/CSA2.6/raw/master/Fig1.png" alt="image" style="border: 0px;"></p>
<p>For smaller vertebrate genomes (~1 Gbp) chromosome scale assemblies can be achieved within 12h on high-end Desktop computers (Intel i7, 12 CPU threads, 128 GB RAM). Larger mammalian genomes (~3Gbp) can be processed within 15-18 h on server equipment (Xeon, 96 CPU threads, 1TB RAM).</p><p>Address of the bookmark: <a href="https://github.com/HMPNK/CSA2.6" rel="nofollow">https://github.com/HMPNK/CSA2.6</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<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>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43614/mitoz-a-toolkit-for-animal-mitochondrial-genome-assembly-annotation-and-visualization</guid>
	<pubDate>Tue, 30 Nov 2021 23:23:57 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43614/mitoz-a-toolkit-for-animal-mitochondrial-genome-assembly-annotation-and-visualization</link>
	<title><![CDATA[MitoZ: a toolkit for animal mitochondrial genome assembly, annotation and visualization]]></title>
	<description><![CDATA[<p>MitoZ, consisting of independent modules of <em>de novo</em> assembly, findMitoScaf (find Mitochondrial Scaffolds), annotation and visualization, that can generate mitogenome assembly together with annotation and visualization results from HTS raw reads.</p>
<p>https://academic.oup.com/nar/article/47/11/e63/5377471</p><p>Address of the bookmark: <a href="https://github.com/linzhi2013/MitoZ" rel="nofollow">https://github.com/linzhi2013/MitoZ</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>

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