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<channel>
	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/4590?offset=40</link>
	<atom:link href="https://bioinformaticsonline.com/related/4590?offset=40" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43867/genomeqc-a-quality-assessment-tool-for-genome-assemblies-and-gene-structure-annotations</guid>
	<pubDate>Thu, 19 May 2022 04:29:05 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43867/genomeqc-a-quality-assessment-tool-for-genome-assemblies-and-gene-structure-annotations</link>
	<title><![CDATA[GenomeQC: a quality assessment tool for genome assemblies and gene structure annotations]]></title>
	<description><![CDATA[<p><span>The GenomeQC web application is implemented in R/Shiny version 1.5.9 and Python 3.6 and is freely available at&nbsp;</span><a href="https://genomeqc.maizegdb.org/">https://genomeqc.maizegdb.org/</a><span>&nbsp;under the GPL license. All source code and a containerized version of the GenomeQC pipeline is available in the GitHub repository&nbsp;</span><a href="https://github.com/HuffordLab/GenomeQC">https://github.com/HuffordLab/GenomeQC</a><span>.</span></p>
<p>https://bmcgenomics.biomedcentral.com/articles/10.1186/s12864-020-6568-2</p><p>Address of the bookmark: <a href="https://github.com/HuffordLab/GenomeQC" rel="nofollow">https://github.com/HuffordLab/GenomeQC</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37211/jbrowse-embeddable-genome-browser-built-completely-with-javascript-and-html5</guid>
	<pubDate>Fri, 29 Jun 2018 09:19:56 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37211/jbrowse-embeddable-genome-browser-built-completely-with-javascript-and-html5</link>
	<title><![CDATA[JBrowse: Embeddable genome browser built completely with JavaScript and HTML5]]></title>
	<description><![CDATA[JBrowse is a fast, embeddable genome browser built completely with JavaScript and HTML5, with optional run-once data formatting tools written in Perl.

Headline Features:
Fast, smooth scrolling and zooming. Explore your genome with unparalleled speed.
Scales easily to multi-gigabase genomes and deep-coverage sequencing.
Quickly open and view data files on your computer without uploading them to any server.
Supports GFF3, BED, FASTA, Wiggle, BigWig, BAM, VCF (with either .tbi or .idx index), REST, and more.  BAM, BigBed, BigWig, and VCF data are displayed directly from chunks of the compressed binary files, no conversion needed.
Includes an optional “faceted” track selector (see demo) suitable for large installations with thousands of tracks.
Very light server resource requirements. In fact, JBrowse has no back-end server code, just tools for formatting data files to be read directly over HTTP. Serve huge datasets from a single low-cost cloud instance.
Can run as a stand-alone app on OSX and Windows using the Electron platform
Highly extensible plugin architecture, with a large plugin registry of existing examples here https://gmod.github.io/jbrowse-registry

https://jbrowse.org/<p>Address of the bookmark: <a href="https://github.com/GMOD/jbrowse" rel="nofollow">https://github.com/GMOD/jbrowse</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40465/airlift-a-methodology-and-tool-for-comprehensively-moving-mappings-and-annotations-from-one-genome-to-another-similar-genome</guid>
	<pubDate>Mon, 23 Dec 2019 10:20:13 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40465/airlift-a-methodology-and-tool-for-comprehensively-moving-mappings-and-annotations-from-one-genome-to-another-similar-genome</link>
	<title><![CDATA[AirLift, a methodology and tool for comprehensively moving mappings and annotations from one genome to another similar genome]]></title>
	<description><![CDATA[<p>We propose AirLift, a methodology and tool for comprehensively moving mappings and annotations from one genome to another similar genome while maintaining the accuracy of a full mapper.</p><p>Address of the bookmark: <a href="https://github.com/CMU-SAFARI/AirLift" rel="nofollow">https://github.com/CMU-SAFARI/AirLift</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36739/blasr-mapping-single-molecule-sequencing-reads-using-basic-local-alignment-with-successive-refinement-blasr-theory-and-application</guid>
	<pubDate>Wed, 23 May 2018 06:54:32 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36739/blasr-mapping-single-molecule-sequencing-reads-using-basic-local-alignment-with-successive-refinement-blasr-theory-and-application</link>
	<title><![CDATA[BlasR Mapping single molecule sequencing reads using Basic Local Alignment with Successive Refinement (BLASR): Theory and Application,]]></title>
	<description><![CDATA[<p><span>BLASR (Basic Local Alignment with Successive Refinement) for mapping Single Molecule Sequencing (SMS) reads that are thousands to tens of thousands of bases long with divergence between the read and genome dominated by insertion and deletion error.</span></p>
<p>Here is how I use the blasr to align PacBio reads to the contigs (target.fasta). The &ldquo;target.fasta.sa&rdquo; is the suffix array from &ldquo;target.fasta&rdquo; generated by sawriter.</p>
<blockquote>
<p>blasr query.fa ./target.fasta -sa ./target.fasta.sa -bestn 40 -maxScore -500 -m 4 -nproc 24 -out target.m4 -maxLCPLength 15</p>
</blockquote>
<p>the output format option &ldquo;-m 4&Prime; generate the alignment coordinate. Not fully documented, but I can explain that to you.&nbsp;</p>
<p>I use a 24 cores / 48G ram server for the alignment. It took about 2 to 3 hours aligning 3G PacBio Reads to 10^6 sequences of short read contigs with a mean 3.5kbp length.</p><p>Address of the bookmark: <a href="http://bix.ucsd.edu/projects/blasr/" rel="nofollow">http://bix.ucsd.edu/projects/blasr/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/1897/genetic-test-in-india</guid>
	<pubDate>Sun, 11 Aug 2013 10:54:35 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/1897/genetic-test-in-india</link>
	<title><![CDATA[Genetic Test in India]]></title>
	<description><![CDATA[<p>1.<strong>Xcode Life Sciences Pvt. Ltd.</strong><br /><span>6B, Eldorado,&nbsp;</span><br /><span>112, Nungambakkam High Road,</span><br /><span>Nungambakkam, Chennai 600034</span><br /><span>Tamil Nadu, India&nbsp;</span></p><p>2.<span><strong>Mapmygenome&trade;</strong><br /></span><span>Royal Demeure,HUDA Techno Enclave,<br />Plot No. 12/2, Sector-1 500 081&nbsp;<br />Madhapur,Hyderabad<br />AP, India</span></p><p>3.<strong>&nbsp;DNA Labs India</strong></p><p><strong><a href="http://www.dnalabsindia.com/lab.php">http://www.dnalabsindia.com/lab.php</a></strong></p><p>&nbsp;</p><p>4.<strong>MedGenome Labs Pvt Ltd</strong><br /><span>(Division of SciGenom Labs Pvt Ltd.)</span><br /><span>Plot no: 43A,SDF, 3rd floor</span><br /><span>A Block,CSEZ, Kakanad, Cochin</span><br /><span>Kerala - 682037&nbsp;</span><br /><span>Phone: 0484 - 2413399</span><br /><span>Fax: 0484 - 2413398</span><br /><span>Email:&nbsp;</span><a href="mailto:info@medgenome.com">info@medgenome.com</a></p><p>5.<strong>Narayana Nethralaya</strong></p><p><span>Narayana Hrudayalaya Campus</span><br /><span>Narayana Health City</span><br /><span># 258/A, Bommasandra, Hosur Road,&nbsp;</span><br /><span>Bangalore - 560 099 - INDIA.</span><br /><span>TEL: +91-80-66660655-0658&nbsp;</span><br /><span>FAX: +91-80-66660650&nbsp;</span><br /><span>Mobile: 9902 821128 (Emergency Only)</span><br /><span>e-mail:&nbsp;</span><a href="mailto:info@narayananethralaya.com">info@narayananethralaya.com</a></p><p>6.<strong>BioAxis DNA Research Centre Private Limited</strong><br />13-51,Sri Lakshmi Nagar colony,<br />Besides Big Bazar, Near Kamineni Hospitals<br />GSI Post BandalGuda (L B Nagar) Hydeabad-500068<br />Andhra Pradesh (<strong>India</strong>).<br />Phone :&nbsp;+91-40-24034503/+91-9246338983</p><p>7.<strong>Gene Guiide</strong></p><p>8th Floor, Embassy Towers, 7 Bungalows Rd, Versova, Andheri West, Mumbai-61&nbsp;<br />&nbsp;09167 117799&nbsp;<br />&nbsp;<a href="mailto:info@geneguiide.com" target="_blank">info@geneguiide.com</a>&nbsp;</p><p>See more at: http://www.geneguiide.com</p><p>8.<strong>INDIAN BIOSCIENCES</strong><br />Regd. Office:<br />G-2 (Ground Floor Rear), Kailash Colony, New Delhi - 110048, India.<br />Phone: +91 (0)11 29236088, Email: info@inbdna.com.</p><p>9.<strong>SRL Limited</strong></p><p>GP-26, MARUTI INDUSTRIAL ESTATE,</p><p>UDYOG VIHAR,SECTOR-18,</p><p>GURGAON - 122015</p><p>Tel: 0124-3001243 / 0124-3001209</p><p><strong>SRL Limited</strong><br />VASANT VIHAR, 8, PALAM MARG,<br />NEW DELHI - 110057<br />Tel: 011 - 4229 5333&nbsp;</p><p><strong>Website:</strong>&nbsp;<a href="http://www.srlworld.com/" target="_blank">http://www.srlworld.com</a><br /><strong>National Customer care number:</strong><br />Call Toll Free : 1800-222-660/1800-102-8282&nbsp;<br /><strong>E-mail id:</strong>&nbsp;<a href="mailto:customercare@srl.in">customercare@srl.in</a></p><p>10.<strong>Tata Memorial Centre</strong>,</p><p>Advanced Centre for Treatment, Research and Education in Cancer</p><p>Kharghar, Navi Mumbai - 410 210, INDIA.</p><p>Tel: +91-22-2740 5000</p><p>Fax: +91-22-2740 5085</p><p>E-mail: mail@actrec.gov.in</p><p style="text-align: center;">&nbsp;</p><p style="text-align: center;"><span style="font-size: large;"><a href="mailto:office@actrec.gov.in"></a></span></p><p>&nbsp;</p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/14011/dynamic-chromosome-breakpoints</guid>
	<pubDate>Wed, 13 Aug 2014 18:38:10 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/14011/dynamic-chromosome-breakpoints</link>
	<title><![CDATA[Dynamic chromosome breakpoints !!!]]></title>
	<description><![CDATA[<p>Cell division involves the distribution of identical genetic material, DNA, to two daughters&rsquo; cells. During this process, duplicated deoxyribonucleic acid (DNA) goes through a condensation and decondensation process. This is followed by nuclear envelope dissolution, mitotic spindle assembly, migration of the sister chromatid pairs to the metaphase plate, division and segregation of identical sets of chromosomes into daughter nuclei and nuclear envelope reformation.</p><p>The vital metaphase stage of cell division, when the sister chromatids migrated to the centre and lined up in a row, and pulled apart using attached microtubules in such a way that half the DNA ends up in each daughter cell. However, before the mitotic spindle‐mediated movement gets start and pulled DNA apart, the chromosomes are free to undergo <strong>recombination </strong>which involves the exchange of genetic material either between multiple chromosomes or between different regions of the same chromosome.</p><p><img src="http://www.sciencelearn.org.nz/var/sciencelearn/storage/images/contexts/uniquely-me/sci-media/images/chromosomes-crossing-over/464438-1-eng-NZ/Chromosomes-crossing-over.jpg" alt="image" width="504" height="342" style="border: 0px; border: 0px;"></p><p>During recombination, the precise breakage of each strand, exchange between the strands, and sealing of the resulting recombined molecules happens. The &ldquo;<strong>chromosomal breakpoints</strong>&rdquo; refers to these places where they break. Mostly, this process occurs with a high degree of accuracy at high frequency in both eukaryotic and prokaryotic cells. But occasionally this &ldquo;break and sealing/ break and reattach&rdquo; process goes wrong and the reattachment happens in the wrong place which usually create disaster (with few exceptions).These chromosome disaster or abnormalities involve the gain, loss or rearrangement of visible amounts of genetic material during cell division. These abnormalities are of two type, the first one is numerical abnormalities &nbsp;where severe disorders are caused by the loss or gain of whole chromosomes, which affect the copy number of hundreds or even thousands of genes. The second are structural abnormalities which can be unbalanced or balanced. The former are similar to numerical abnormalities in that genetic material is either gained or lost. The natural defects in chromosome segregation are linked to cancer and several genetic diseases (http://en.wikipedia.org/wiki/List_of_genetic_disorders). Therefore, the enzymes involved in regulating cell division are still the attractive drug targets for many diseases.</p><p>&nbsp;</p><p>&nbsp;</p><p><img src="http://upload.wikimedia.org/wikipedia/commons/4/4a/Chromosomal_translocations.svg" alt="image" width="424" height="331" style="border: 0px; border: 0px;"></p><p>&nbsp;</p><p>Apart from certain chromosome abnormalities, these &ldquo;crossing over&rdquo; of segments of maternal and paternal chromosomes to form hybrid chromosomes have some evolutionary importance and considered as a driver of genetic variation. Moreover, the chromosome breakage in evolution is considered to be non-random in nature(http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.0020014). In addition the study of breakpoint regions and non-breakpoint (stable) regions of chromosomes indicates both the regions evolved in distinctly different ways ( http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2675965/). These breakage may lead to genetic diseases or participate to chromosomal rearranmgnets and contributed in development of new species.</p><p>I will try to explain the genome hotspots/Evolutionary Breakpoint Regions(EBRs)/fragile regions/weak fragments/&nbsp; in my next blog.</p><p><strong>Software for recombination detection:</strong></p><p><strong>RAT</strong> http://cbr.jic.ac.uk/dicks/software/RAT/</p><p><strong>Breakpointer</strong> https://github.com/ruping/Breakpointer</p><p><strong>DRP</strong> http://web.cbio.uct.ac.za/~darren/rdp.html</p><p><strong>RB-finder</strong> http://www.ncbi.nlm.nih.gov/pubmed/18707535</p><p><strong>LDhat2.0</strong> http://ldhat.sourceforge.net/LDhat2.0/instructions.shtml</p><p><strong>Reference:</strong></p><p>http://www.nature.com/scitable/topicpage/genetic-recombination-514#</p><p>Image: Wikipedia , sciencelearn.org.nz</p><p><strong>Recommended Articles:</strong></p><p>http://www.friendshipcircle.org/blog/2012/05/22/13-chromosomal-disorders-youve-never-heard-of/</p><p>http://web.udl.es/usuaris/e4650869/docencia/segoncicle/genclin98/recursos_classe_%28pdf%29/revisionsPDF/chromosyndromes.pdf</p><p>http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2775595/table/T2/</p><p>http://learn.genetics.utah.edu/content/disorders/chromosomal/</p><p>http://www.ncert.nic.in/html/learning_basket/biology/cc&amp;cd.pdf</p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30111/eager</guid>
	<pubDate>Sat, 10 Dec 2016 18:07:23 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30111/eager</link>
	<title><![CDATA[EAGER]]></title>
	<description><![CDATA[<p><span>The automated reconstruction of genome sequences in ancient genome analysis is a multifaceted process.</span></p>
<p><span>EAGER encompasses both state-of-the-art tools for each step as well as new complementary tools tailored for ancient DNA data within a single integrated solution in an easily accessible format.</span></p>
<p>https://genomebiology.biomedcentral.com/articles/10.1186/s13059-016-0918-z</p><p>Address of the bookmark: <a href="https://github.com/apeltzer/EAGER-GUI" rel="nofollow">https://github.com/apeltzer/EAGER-GUI</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/31566/software-and-tools-to-detect-structure-variation-with-long-reads</guid>
	<pubDate>Wed, 15 Mar 2017 14:31:09 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/31566/software-and-tools-to-detect-structure-variation-with-long-reads</link>
	<title><![CDATA[Software and Tools to detect structure variation with long reads !!]]></title>
	<description><![CDATA[<p>Uncovering the connection between genetics and heritable diseases requires an approach that looks at all the variant bases and types in a genome. While a PacBio&nbsp;<em>de novo</em>&nbsp;assembly resolves the most novel SV variants. 8-10X PacBio coverage of single genomes or trios reveals triple the SVs detectable by short-read data.</p><p>With&nbsp;<span style="text-decoration: underline;"><a href="http://www.pacb.com/smrt-science/">Single Molecule, Real-Time (SMRT) Sequencing</a></span>, you can access structural variations having a broad range of sizes, types, and GC content with the ability to:</p><ul>
<li>Uncover missing heritability linked to structural variation</li>
<li>Unambiguously identify genomic context and variant breakpoints at the sequence level to unravel the genetic etiology of disease</li>
<li>Resolve structural variation across the complete size spectrum with basepair resolution</li>
</ul><p>Following are the SV tools, which can assist you to achieve your goal.</p><p><strong>Sniffles:</strong>&nbsp;Structural variation caller using third generation sequencing</p><p>Sniffles is a structural variation caller using third generation sequencing (PacBio or Oxford Nanopore). It detects all types of SVs using evidence from split-read alignments, high-mismatch regions, and coverage analysis. Please note the current version of Sniffles requires sorted output from BWA-MEM (use -M and -x parameter) or NGM-LR with the optional SAM attributes enabled!&nbsp;</p><p>More at&nbsp;https://github.com/fritzsedlazeck/Sniffles</p><p><strong style="font-size: 12.8px;"><br />MultiBreak-SV:</strong> It identifies structural variants from next-generation paired end data, third-generation long read data, or data from a combination of sequencing platforms.</p><p>There are two pieces of software in this release: (1) a pre-processor that takes machineformat (.m5) BLASR files, and (2) MultiBreak-SV. For installation and usage instructions, see doc/MultiBreakSV-Manual.txt.</p><p>More at&nbsp;https://github.com/raphael-group/multibreak-sv</p><p><strong style="font-size: 12.8px;"><br />Parliament:</strong>&nbsp;A Structural Variation Tool. Why ask a single sv-detection approach to find every variant when you can have a parliament of tools deciding?</p><p>Publication about the algorithm and &ldquo;&hellip;the first long-read characterization of structural variation in a diploid human personal genome&hellip;&rdquo; (HS1011) -&nbsp;<a href="http://www.biomedcentral.com/1471-2164/16/286">&ldquo;Assessing structural variation in a personal genome&mdash;towards a human reference diploid genome&rdquo;</a></p><p>More at&nbsp;https://sourceforge.net/projects/parliamentsv/</p><p>https://www.dnanexus.com/papers/Parliament_Info_Sheet.pdf</p><p><br /><strong>PBHoney:</strong>&nbsp;the structural variation discovery tool&nbsp;<br /><br />PBHoney is an implementation of two variant-identification approaches designed to exploit the high mappability of long reads (i.e., greater than 10,000 bp). PBHoney considers both intra-read discordance and soft-clipped tails of long reads to identify structural variants.</p><p>Read The Paper&nbsp;<a href="http://www.biomedcentral.com/1471-2105/15/180/abstract" target="_blank">http://www.biomedcentral.com/1471-2105/15/180/abstract</a></p><p>More at&nbsp;https://sourceforge.net/projects/pb-jelly/</p><p><strong><br />SMRT-SV:</strong> Structural variant and indel caller for PacBio reads</p><p>Structural variant (SV) and indel caller for PacBio reads based on methods from&nbsp;<a href="http://www.nature.com/nature/journal/vaop/ncurrent/full/nature13907.html">Chaisson et al. 2014</a>.</p><p>SMRT-SV provides an official software package for tools described in&nbsp;<a href="http://www.nature.com/nature/journal/vaop/ncurrent/full/nature13907.html">Chaisson et al. 2014</a>&nbsp;and adds several key features including the following.</p><ul>
<li>Unified variant calling user interface with built-in cluster compute support</li>
<li>Small indel calling (2-49 bp)</li>
<li>Improved inversion calling (<code>screenInversions</code>)</li>
<li>Quality metric for SV calls based on number of local assemblies supporting each call</li>
<li>Higher sensitivity for SV calls using tiled local assemblies across the entire genome instead of "signature" regions</li>
<li>Genotyping of SVs with Illumina paired-end reads from WGS samples</li>
</ul><p>More at&nbsp;https://github.com/EichlerLab/pacbio_variant_caller</p>]]></description>
	<dc:creator>Archana Malhotra</dc:creator>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/32713/salzberg-lab</guid>
  <pubDate>Mon, 15 May 2017 05:14:01 -0500</pubDate>
  <link></link>
  <title><![CDATA[Salzberg lab]]></title>
  <description><![CDATA[
<p>We are a computational biology lab that develops novel methods for analysis of DNA and RNA sequences. Our research includes software for aligning and assembling RNA-seq data, whole-genome assembly, and microbiome analysis. We work closely with biomedical scientists to apply these methods to current problems arising in a broad spectrum of biological and medical research areas. We’re also part of the Center for Computational Biology, a group of 20+ faculty members and their labs at Johns Hopkins working on computational, statistical, and mathematical methods that can turn massive genomic data sets into biologically and clinically useful information.</p>

<p>https://salzberg-lab.org/</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42359/dnasp-dna-sequence-polymorphism-is-a-software-package-for-the-analysis-of-dna-polymorphisms</guid>
	<pubDate>Wed, 25 Nov 2020 19:51:38 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42359/dnasp-dna-sequence-polymorphism-is-a-software-package-for-the-analysis-of-dna-polymorphisms</link>
	<title><![CDATA[DnaSP: DNA Sequence Polymorphism, is a software package for the analysis of DNA polymorphisms]]></title>
	<description><![CDATA[<p><span>DnaSP, DNA Sequence Polymorphism, is a software package for the analysis of DNA polymorphisms using data from a single locus (a multiple sequence aligned -MSA data), or from several loci (a Multiple-MSA data, such as formats generated by some assembler RAD-seq software). DnaSP can estimate several measures of DNA sequence variation within and between populations in noncoding, synonymous or nonsynonymous sites, or in various sorts of codon positions), as well as linkage disequilibrium, recombination, gene flow and gene conversion parameters.</span></p><p>Address of the bookmark: <a href="http://www.ub.edu/dnasp/" rel="nofollow">http://www.ub.edu/dnasp/</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
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