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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/40792?offset=470</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27440/stampy</guid>
	<pubDate>Fri, 20 May 2016 19:13:32 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27440/stampy</link>
	<title><![CDATA[Stampy]]></title>
	<description><![CDATA[<p><strong>Stampy&nbsp;</strong><span>is a package for the mapping of short reads from illumina sequencing machines onto a reference genome. It's recommended for most workflows, including those for genomic resequencing, RNA-Seq and Chip-seq. Stampy excels in the mapping of reads containing that contain sequence variation relative to the reference, in particular for those containing insertions or deletions.</span></p><p>Address of the bookmark: <a href="http://www.well.ox.ac.uk/project-stampy" rel="nofollow">http://www.well.ox.ac.uk/project-stampy</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29614/art-set-of-simulation-tools</guid>
	<pubDate>Thu, 03 Nov 2016 08:28:25 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29614/art-set-of-simulation-tools</link>
	<title><![CDATA[ART: Set of Simulation Tools]]></title>
	<description><![CDATA[<p>ART is a set of simulation tools to generate synthetic next-generation sequencing reads. ART simulates sequencing reads by mimicking real sequencing process with empirical error models or quality profiles summarized from large recalibrated sequencing data. ART can also simulate reads using user own read error model or quality profiles. ART supports simulation of single-end, paired-end/mate-pair reads of three major commercial next-generation sequencing platforms: Illumina's Solexa, Roche's 454 and Applied Biosystems' SOLiD. ART can be used to test or benchmark a variety of method or tools for next-generation sequencing data analysis, including read alignment, de novo assembly, SNP and structure variation discovery. ART was used as a primary tool for the simulation study of the <span><a href="http://www.1000genomes.org/" target="_blank">1000 Genomes Project<span></span></a></span> . ART is implemented in C++ with optimized algorithms and is highly efficient in read simulation. ART outputs reads in the FASTQ format, and alignments in the ALN format. ART can also generate alignments in the SAM alignment or UCSC BED file format. ART can be used together with genome variants simulators (e.g. <span><a href="http://bioinform.github.io/varsim/" target="_blank">VarSim<span></span></a></span>) for evaluating variant calling tools or methods.</p><p>Address of the bookmark: <a href="http://www.niehs.nih.gov/research/resources/software/biostatistics/art/" rel="nofollow">http://www.niehs.nih.gov/research/resources/software/biostatistics/art/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34235/quorum-an-error-corrector-for-illumina-reads</guid>
	<pubDate>Wed, 08 Nov 2017 11:40:41 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34235/quorum-an-error-corrector-for-illumina-reads</link>
	<title><![CDATA[QuorUM: An Error Corrector for Illumina Reads]]></title>
	<description><![CDATA[<p><span><span>Illumina Sequencing data can provide high coverage of a genome by relatively short (most often 100 bp to 150 bp) reads at a low cost. Even with low (advertised 1%) error rate, 100 &times; coverage Illumina data on average has an error in some read at every base in the genome. These errors make handling the data more complicated because they result in a large number of low-count erroneous&nbsp;</span><em>k</em><span>-mers in the reads. However, there is enough information in the reads to correct most of the sequencing errors, thus making subsequent use of the data (e.g. for mapping or assembly) easier. Here we use the term &ldquo;error correction&rdquo; to denote the reduction in errors due to both changes in individual bases and trimming of unusable sequence. We developed an error correction software called QuorUM. QuorUM is mainly aimed at error correcting Illumina reads for subsequent assembly. It is designed around the novel idea of minimizing the number of distinct erroneous&nbsp;</span><em>k</em><span>-mers in the output reads and preserving the most true&nbsp;</span><em>k</em><span>-mers, and we introduce a composite statistic &pi; that measures how successful we are at achieving this dual goal. We evaluate the performance of QuorUM by correcting actual Illumina reads from genomes for which a reference assembly is available.</span></span></p>
<p><span>QuorUM is distributed as an independent software package and as a module of the MaSuRCA assembly software. Both are available under the GPL open source license at&nbsp;</span><a href="http://www.genome.umd.edu/">http://www.genome.umd.edu</a><span>.</span></p><p>Address of the bookmark: <a href="http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0130821" rel="nofollow">http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0130821</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/44229/common-steps-for-reads-mapping</guid>
	<pubDate>Thu, 09 Mar 2023 02:48:02 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44229/common-steps-for-reads-mapping</link>
	<title><![CDATA[Common steps for reads mapping !]]></title>
	<description><![CDATA[<div><div><div><div><div><div><div><div><div><div><p>Mapping reads to a reference genome is an essential step in many types of genomic analysis, such as variant calling and gene expression analysis. Here are some general steps to follow for mapping reads to a genome:</p><ol>
<li>
<p>Choose a read mapper: There are many read mappers available, such as BWA, Bowtie, and HISAT2. Choose a mapper that is appropriate for your type of data and research question.</p>
</li>
<li>
<p>Index the reference genome: Before mapping reads, the reference genome needs to be indexed. This involves creating an index of the genome sequence that allows the mapper to quickly find matches to the reads. Most mappers have their own indexing tools.</p>
</li>
<li>
<p>Prepare the read data: The reads should be in a format that is compatible with the mapper. Most mappers accept FASTQ or BAM files. Depending on the quality of the data, it may need to be filtered or trimmed before mapping.</p>
</li>
<li>
<p>Run the mapper: The mapper is run with the command-line interface or using a graphical user interface. The specific command depends on the mapper being used, but typically involves specifying the input data, reference genome, and output file format.</p>
</li>
<li>
<p>Evaluate the mapping results: After the mapping is complete, the results should be evaluated. This includes assessing the quality of the mapping, such as the mapping rate, the number of mapped reads, and the mapping quality score.</p>
</li>
<li>
<p>Post-processing: Depending on the analysis being performed, post-processing of the mapped reads may be necessary. This can include filtering reads based on quality, removing duplicate reads, and calling variants.</p>
</li>
</ol><p>Overall, mapping reads to a reference genome is a complex process that requires careful consideration of the type of data, the research question, and the specific mapper being used.</p></div></div></div></div></div></div></div></div></div></div>]]></description>
	<dc:creator>BioStar</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/933/world-of-omics</guid>
	<pubDate>Tue, 16 Jul 2013 17:11:48 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/933/world-of-omics</link>
	<title><![CDATA[World of Omics]]></title>
	<description><![CDATA[<p>How many variants of "omics" techniques presently in use ?</p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/view/2044</guid>
	<pubDate>Mon, 12 Aug 2013 12:19:29 -0500</pubDate>
	<link>https://bioinformaticsonline.com/view/2044</link>
	<title><![CDATA[Does anyone have Nanopore latest updates?]]></title>
	<description><![CDATA[<p>There was a lot of buzz about&nbsp;<span>Oxford Nanopore Technologies&reg; is developing the GridION&trade; system and miniaturised MinION&trade; device. These are a new generation of electronic molecular analysis system for use in scientific research, personalised medicine, crop science, security/defence and more. The platform technology uses nanopores to analyse single molecules including DNA/RNA and proteins. With a broad patent portfolio, the Oxford Nanopore pipeline includes biological nanopores and solid-state nanopores.</span></p><p>Is this available, or still under trial mode?&nbsp;</p><p><a href="https://www.nanoporetech.com/">https://www.nanoporetech.com/</a></p><p><a href="https://www.nanoporetech.com/technology/the-minion-device-a-miniaturised-sensing-system/the-minion-device-a-miniaturised-sensing-system">https://www.nanoporetech.com/technology/the-minion-device-a-miniaturised-sensing-system/the-minion-device-a-miniaturised-sensing-system</a></p>]]></description>
	<dc:creator>Poonam Mahapatra</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/4164/two-major-breakthrough</guid>
	<pubDate>Mon, 02 Sep 2013 10:18:11 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/4164/two-major-breakthrough</link>
	<title><![CDATA[Two major breakthrough!!]]></title>
	<description><![CDATA[<p>"Scientists in Uruguay in colloboration with European partners sequenced the genome of the high-value Tannat grape, from which "the most healthy of red wines" are fermented.</p><p>A quick, $1 syphilis&nbsp;test in development by researchers from UNU-BIOLAC."</p><p><strong>Source</strong>:</p><p><a href="http://www.sciencedaily.com/releases/2013/09/130902101846.htm">http://www.sciencedaily.com/releases/2013/09/130902101846.htm</a></p><p><a href="http://www.eurekalert.org/pub_releases/2013-09/tca-ssg082613.php">http://www.eurekalert.org/pub_releases/2013-09/tca-ssg082613.php</a></p><p>&nbsp;</p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/9032/encode-sequencing-data-freely-available-to-download-and-use-for-academic-means</guid>
	<pubDate>Thu, 13 Mar 2014 18:18:08 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/9032/encode-sequencing-data-freely-available-to-download-and-use-for-academic-means</link>
	<title><![CDATA[Encode sequencing data freely available to download and use for academic means]]></title>
	<description><![CDATA[<p>In <span style="text-decoration: underline;"><strong>Encode</strong></span>,&nbsp;<span>regulatory elements investigated via DNA hypersensitivity assays, assays of DNA methylation, and chromatin immunoprecipitation (ChIP) of proteins that interact with DNA, including modified histones and transcription factors, followed by sequencing (ChIP-Seq).</span></p>
<p><span>More information:</span></p>
<p><span>https://genome.ucsc.edu/ENCODE/pilot.html</span></p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="https://genome.ucsc.edu/ENCODE/" rel="nofollow">https://genome.ucsc.edu/ENCODE/</a></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/10238/tsetse-fly-genome-sequenced</guid>
	<pubDate>Fri, 25 Apr 2014 10:48:35 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/10238/tsetse-fly-genome-sequenced</link>
	<title><![CDATA[Tsetse Fly Genome sequenced]]></title>
	<description><![CDATA[<p><span><span>As it&nbsp;</span><a href="http://www.sciencemag.org/content/344/6182/380" target="_blank">reported online today</a><span>&nbsp;in&nbsp;</span><em>Science</em><span>, the team used several sequencing approaches to tackle the tsetse fly's 366 million base genome.</span></span></p><p><span>The current study, and companion articles slated to appear in&nbsp;</span><em>PLOS One</em><span>,&nbsp;</span><em>PLOS Genetics</em><span>, and&nbsp;</span><em>PLOS Neglected Tropic Diseases</em><span>, are the result of &nbsp;nearly 150 researchers based in 18 countries.</span></p><p><span>Source:</span></p><p><span>http://www.genomeweb.com/sequencing/international-team-sequences-tsetse-fly-genome</span></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/10739/science-for-life-laboratory-scilifelab-sweden</guid>
  <pubDate>Sat, 10 May 2014 06:22:30 -0500</pubDate>
  <link></link>
  <title><![CDATA[Science for Life Laboratory (SciLifeLab)-Sweden]]></title>
  <description><![CDATA[
<p>Science for Life Laboratory (SciLifeLab) is a national center for molecular biosciences with focus on health and environmental research. The center combines frontline technical expertise with advanced knowledge of translational medicine and molecular bioscience. SciLifeLab is a national resource and a collaboration between four universities: Karolinska Institutet, KTH Royal Institute of Technology, Stockholm University and Uppsala University.</p>

<p>Webpage : https://www.scilifelab.se/about-us/<br />Opportunity: https://www.scilifelab.se/about-us/career/</p>
]]></description>
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