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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/38169?offset=390</link>
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	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37643/lorma-a-tool-for-correcting-sequencing-errors-in-long-reads</guid>
	<pubDate>Thu, 06 Sep 2018 16:21:01 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37643/lorma-a-tool-for-correcting-sequencing-errors-in-long-reads</link>
	<title><![CDATA[LoRMA: A tool for correcting sequencing errors in long reads]]></title>
	<description><![CDATA[<p><span>An error correction method that uses long reads only. The method consists of two phases: first, we use an iterative alignment-free correction method based on de Bruijn graphs with increasing length of&nbsp;</span><em>k</em><span>-mers, and second, the corrected reads are further polished using long-distance dependencies that are found using multiple alignments. According to our experiments, the proposed method is the most accurate one relying on long reads only for read sets with high coverage. Furthermore, when the coverage of the read set is at least 75&times;, the throughput of the new method is at least 20% higher.</span></p>
<blockquote>
<p><span>conda install -c atgc-montpellier lorma</span></p>
</blockquote><p>Address of the bookmark: <a href="https://gite.lirmm.fr/lorma/lorma-releases/wikis/home" rel="nofollow">https://gite.lirmm.fr/lorma/lorma-releases/wikis/home</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38304/lordfast-sensitive-and-fast-alignment-search-tool-for-long-noisy-read-sequencing-data</guid>
	<pubDate>Tue, 27 Nov 2018 04:43:57 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38304/lordfast-sensitive-and-fast-alignment-search-tool-for-long-noisy-read-sequencing-data</link>
	<title><![CDATA[lordFAST: sensitive and Fast Alignment Search Tool for LOng noisy Read sequencing Data]]></title>
	<description><![CDATA[<p><span>lordFAST is a sensitive tool for mapping long reads with high error rates. lordFAST is specially designed for aligning reads from PacBio sequencing technology but provides the user the ability to change alignment parameters depending on the reads and application.</span></p>
<p>lordFAST, a novel long-read mapper that is specifically designed to align reads generated by PacBio and potentially other SMS technologies to a reference. lordFAST not only has higher sensitivity than the available alternatives, it is also among the fastest and has a very low memory footprint.</p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="https://github.com/vpc-ccg/lordfast" rel="nofollow">https://github.com/vpc-ccg/lordfast</a></p>]]></description>
	<dc:creator>BioJoker</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39671/flye-fast-and-accurate-de-novo-assembler-for-single-molecule-sequencing-reads</guid>
	<pubDate>Sat, 06 Jul 2019 03:48:22 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39671/flye-fast-and-accurate-de-novo-assembler-for-single-molecule-sequencing-reads</link>
	<title><![CDATA[Flye: Fast and accurate de novo assembler for single molecule sequencing reads]]></title>
	<description><![CDATA[<p><span>Flye is a de novo assembler for single molecule sequencing reads, such as those produced by PacBio and Oxford Nanopore Technologies. It is designed for a wide range of datasets, from small bacterial projects to large mammalian-scale assemblies. The package represents a complete pipeline: it takes raw PB / ONT reads as input and outputs polished contigs. Flye also includes a special mode for metagenome assembly.</span></p><p>Address of the bookmark: <a href="https://github.com/fenderglass/Flye" rel="nofollow">https://github.com/fenderglass/Flye</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40701/fastgt-an-alignment-free-method-for-calling-common-snvs-directly-from-raw-sequencing-reads</guid>
	<pubDate>Tue, 28 Jan 2020 03:27:33 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40701/fastgt-an-alignment-free-method-for-calling-common-snvs-directly-from-raw-sequencing-reads</link>
	<title><![CDATA[FastGT: an alignment-free method for calling common SNVs directly from raw sequencing reads]]></title>
	<description><![CDATA[<p>FastGT is a program package for whole-genome genotyping of genome variants directly from raw sequencing reads. It is written in C and runs in Linux. FastGT uses a list of variant-specific k-mer pairs that are unique in human genome, counts the frequency of k-mers in sequencing data and predicts the genotype. All this takes less than 1 hour on average low-cost Linux server.</p>
<p><a href="http://bioinfo.ut.ee/FastGT/">http://bioinfo.ut.ee/FastGT/</a></p>
<p><strong><a href="https://github.com/bioinfo-ut/GenomeTester4/">https://github.com/bioinfo-ut/GenomeTester4/</a></strong></p><p>Address of the bookmark: <a href="http://bioinfo.ut.ee/FastGT/" rel="nofollow">http://bioinfo.ut.ee/FastGT/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42485/fastprongs-fast-preprocessing-of-next-generation-sequencing-reads</guid>
	<pubDate>Sat, 26 Dec 2020 08:35:21 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42485/fastprongs-fast-preprocessing-of-next-generation-sequencing-reads</link>
	<title><![CDATA[FastProNGS: fast preprocessing of next-generation sequencing reads]]></title>
	<description><![CDATA[<p><span>FastProNGS to integrate the quality control process with automatic adapter removal. Parallel processing was implemented to speed up the process by allocating multiple threads. Compared with similar up-to-date preprocessing tools, FastProNGS is by far the fastest.&nbsp;</span></p><p>Address of the bookmark: <a href="https://github.com/Megagenomics/FastProNGS" rel="nofollow">https://github.com/Megagenomics/FastProNGS</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/857/smyth-lab</guid>
  <pubDate>Sun, 14 Jul 2013 12:26:18 -0500</pubDate>
  <link></link>
  <title><![CDATA[Smyth Lab]]></title>
  <description><![CDATA[
<p>Statistical functional genomics in experimental medicine<br />The genome projects and the accelerated development of high-throughput genomic technologies such as microarrays have revolutionised biology. Making the most of this revolution requires the marriage of researchers from mathematical and biological backgrounds.</p>

<p>Research Area:<br />Linear models for microarray data<br />Digital gene expression technologies<br />Detection of molecular pathways<br />Bioinformatics resources for medical research</p>

<p>Link @ http://www.wehi.edu.au/faculty_members/professor_gordon_smyth/</p>
]]></description>
</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/44648/modern-statistics-with-r</guid>
	<pubDate>Thu, 22 Aug 2024 04:44:06 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44648/modern-statistics-with-r</link>
	<title><![CDATA[Modern Statistics with R]]></title>
	<description><![CDATA[<p>This is the online version of the second edition of&nbsp;<em>Modern Statistics with R</em>. It is free to use, and always will be.&nbsp;<a href="https://www.routledge.com/Modern-Statistics-with-R-From-Wrangling-and-Exploring-Data-to-Inference-and-Predictive-Modelling/Thulin/p/book/9781032512440">Printed copies</a>&nbsp;are available from CRC Press.</p>
<p><span>Live&nbsp;<a href="https://statistikakademin.se/in-english-r/">online courses on statistics with R</a></span>&nbsp;based on this book, led by the author, are offered regularly; see&nbsp;<a href="https://statistikakademin.se/in-english-r/">this page</a>&nbsp;for more information and dates.</p>
<p>The past decades have transformed the world of statistical data analysis, with new methods, new types of data, and new computational tools. The aim of&nbsp;<em>Modern Statistics with R</em>&nbsp;is to introduce you to key parts of the modern statistical toolkit. It teaches you:</p>
<ul>
<li><span>Data wrangling</span>&nbsp;- importing, formatting, reshaping, merging, and filtering data in R.</li>
<li><span>Exploratory data analysis</span>&nbsp;- using visualisations and multivariate techniques to explore datasets.</li>
<li><span>Statistical inference</span>&nbsp;- modern methods for testing hypotheses and computing confidence intervals.</li>
<li><span>Predictive modelling</span>&nbsp;- regression models and machine learning methods for prediction, classification, and forecasting.</li>
<li><span>Simulation</span>&nbsp;- using simulation techniques for sample size computations and evaluations of statistical methods.</li>
<li><span>Ethics in statistics</span>&nbsp;- ethical issues and good statistical practice.</li>
<li><span>R programming</span>&nbsp;- writing code that is fast, readable, and (hopefully!) free from bugs.</li>
</ul>
<p>The book includes plenty of examples and more than 200 exercises with worked solutions.&nbsp;<a href="http://www.modernstatisticswithr.com/data.zip">The datasets used for the examples and the exercises can be downloaded here.</a></p><p>Address of the bookmark: <a href="https://www.modernstatisticswithr.com/" rel="nofollow">https://www.modernstatisticswithr.com/</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43957/gfastats-the-swiss-army-knife-for-genome-assembly</guid>
	<pubDate>Thu, 08 Sep 2022 06:03:05 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43957/gfastats-the-swiss-army-knife-for-genome-assembly</link>
	<title><![CDATA[gfastats: The swiss army knife for genome assembly.]]></title>
	<description><![CDATA[<p><span>gfastats</span><span>&nbsp;is a single fast and exhaustive tool for&nbsp;</span><span>summary statistics</span><span>&nbsp;and simultaneous *fa* (fasta, fastq, gfa [.gz]) genome assembly file&nbsp;</span><span>manipulation</span><span>.&nbsp;</span><span>gfastats</span><span>&nbsp;also allows seamless fasta&lt;&gt;fastq&lt;&gt;gfa[.gz] conversion. It has been tested in genomes even &gt;100Gbp.</span></p><p>Address of the bookmark: <a href="https://github.com/vgl-hub/gfastats" rel="nofollow">https://github.com/vgl-hub/gfastats</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35619/tallymer-method-to-compute-k-mer-frequencies-and-its-application-to-annotate-large-repetitive-plant-genomes</guid>
	<pubDate>Thu, 15 Feb 2018 10:21:02 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35619/tallymer-method-to-compute-k-mer-frequencies-and-its-application-to-annotate-large-repetitive-plant-genomes</link>
	<title><![CDATA[Tallymer: method to compute K-mer frequencies and its application to annotate large repetitive plant genomes]]></title>
	<description><![CDATA[<p>Tallymer is based on enhanced suffix arrays. This gives a much larger flexibility concerning the choice of the&nbsp;<span>k</span>-mer size. Tallymer can process large data sizes of several billion bases. We used it in a variety of applications to study the genomes of maize and other plant species. In particular, Tallymer was used to index a set whole genome shotgun sequences from maize (B73) (total size 10<sup>9</sup>&nbsp;bp).&nbsp;<br>Tallymer was effective in a variety of applications to aid genome annotation in maize, despite limitations imposed by the relatively low coverage of sequence available.</p>
<p>A manual can be found&nbsp;<a href="https://www.zbh.uni-hamburg.de/fileadmin/gi/tallymer/tallymer.pdf" target="_blank" title="tallymer.pdf (111 KB)">here</a>.</p><p>Address of the bookmark: <a href="https://www.zbh.uni-hamburg.de/forschung/arbeitsgruppe-genominformatik/software/tallymer.html" rel="nofollow">https://www.zbh.uni-hamburg.de/forschung/arbeitsgruppe-genominformatik/software/tallymer.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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