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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/3013?offset=130</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30203/e-rga-enhanced-reference-guided-assembly-of-complex-genomes</guid>
	<pubDate>Mon, 19 Dec 2016 05:56:14 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30203/e-rga-enhanced-reference-guided-assembly-of-complex-genomes</link>
	<title><![CDATA[e-RGA: enhanced Reference Guided Assembly of Complex Genomes]]></title>
	<description><![CDATA[<p><span>Next Generation Sequencing has totally changed genomics: we are able to produce huge amounts of data at an incredibly low cost compared to Sanger sequencing. Despite this, some old problems have become even more difficult, de novo assembly being on top of this list. Despite efforts to design tools able to assemble, de novo, an organism sequenced with short reads, the results are still far from those achievable with long reads. In this paper, we propose a novel method that aims to improve de novo assembly in the presence of a closely related reference. The idea is to combine de novo and reference-guided assembly in order to obtain enhanced results.</span></p><p>Address of the bookmark: <a href="http://journal.embnet.org/index.php/embnetjournal/article/view/208" rel="nofollow">http://journal.embnet.org/index.php/embnetjournal/article/view/208</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30085/fqtools</guid>
	<pubDate>Thu, 08 Dec 2016 09:31:12 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30085/fqtools</link>
	<title><![CDATA[fqtools]]></title>
	<description><![CDATA[<p><code>fqtools</code><span>&nbsp;is a software suite for fast processing of&nbsp;</span><code>FASTQ</code><span>&nbsp;files. Various file manipulations are supported. See below for a full list of the subcommands available and a brief description of their purpose. Most of the individual subcommands will take either a single file or a pair of files as input. If no input file is specified, fqtools will attempt to read data from&nbsp;</span><code>stdin</code><span>. In this case, it is advisabe to specify the format of the data provided. For subcommands that generate FASTQ data, either a single file or a pair of files will be generated. If no&nbsp;</span><code>-o</code><span>&nbsp;argument is provided, single files will be writted to&nbsp;</span><code>stdout</code><span>.</span></p><p>Address of the bookmark: <a href="https://github.com/alastair-droop/fqtools" rel="nofollow">https://github.com/alastair-droop/fqtools</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/30104/structural-variation-the-hidden-genomic-treasure</guid>
	<pubDate>Sat, 10 Dec 2016 16:19:09 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/30104/structural-variation-the-hidden-genomic-treasure</link>
	<title><![CDATA[Structural variation: the hidden genomic treasure]]></title>
	<description><![CDATA[<p>Genome re-sequencing projects have revealed substantial amounts of genetic variation between individuals extending beyond single nucleotide polymorphisms (SNPs) and short indels. Structural Variations (SVs) and Copy Number Variations (CNVs) are a major source of genomic variation. However, compared to SNPs, accurate detection, genotyping and understanding of CNVs is lagging behind due to much greater analytical challenges related to SV/CNV detection and analysis. In our lab we analyse SVs/CNVs using high-throughput sequencing and different analytical approaches.&nbsp;The most‐studied structural variants are copy number variations (CNVs) which can be generated by several different mechanisms including non‐allelic homologous recombination, non‐homologous end‐joining and deoxyribonucleic acid (DNA) replication‐related fork stalling and template switching. CNVs are closely related to segmental duplications (SDs): SDs can stimulate the formation of CNVs and themselves started out as CNVs, but became fixed in a species. Structural variation can be neutral but has also influenced our phenotypic evolution, for example our susceptibility to disease and our ability to digest certain types of food. Our understanding of the extent of structural variation is increasing rapidly, but it will be much more difficult to understand its phenotypic consequences.&nbsp;</p><p><img src="http://www.nature.com/nmeth/journal/v9/n2/images/nmeth.1858-F3.jpg" alt="image" width="946" height="603" style="border: 0px; border: 0px;"></p><p>Structural variants (SVs) such as deletions, insertions, duplications, inversions and translocations litter genomes and are often associated with gene expression changes and severe phenotypes (ie. genetic diseases in humans). Recent studies on the functional aspects of different types of SVs have unveiled several cases of adaptive evolution. For example, inversions have been associated with ecological adaptations and may facilitate speciation. Due to their prevalent nature, SVs arguably have a large impact on genome evolution and should not be neglected when studying the genetics of adaptation and speciation.&nbsp;SVs were classically defined as chromosomal rearrangements larger than 1kb, but due to a higher resolution of new detection methods, smaller variants (between 50 and 1000 base pairs) can now be accurately assessed. Besides various methods of detection in next generation sequencing data (paired end mapping, split reads, and depth of coverage), array-based approaches have proven to be particularly useful for detecting copy number variations (CNVs). These technologies have enabled researchers to catalog a wide spectrum of SVs in many organisms and infer the effects of selection shaping their evolutionary trajectories.</p><p><strong>Structure variation sequencing signature (Source: NatRev Genetics)</strong></p><p><img src="http://www.nature.com/nrg/journal/v12/n5/images/nrg2958-f2.jpg" alt="image" width="800" height="824" style="border: 0px; border: 0px;"></p><p>Related tools, databases and publications are listed below. If you know any interesing papers, please let us know in comment section:</p><p><br /><strong>Key concepts</strong></p><p>Structural variation includes balanced variants such as inversions and translocations, and unbalanced ones such as duplications and deletions (copy number variations or CNVs).</p><p>Structural variants can arise by several mechanisms, including nonallelic homologous recombination (NAHR), nonhomologous end‐joining (NHEJ) and DNA replication‐based fork stalling and template switching (FoSTeS).</p><p>CNV is closely linked to segmental duplication, but is not exactly the same. Segmental duplications can stimulate CNV formation by NAHR, and themselves arise from CNVs that have become fixed.</p><p>Segmental duplications did not appear uniformly during the evolution of the Great Ape species, but rather during a burst of activity around the time of the divergence of gorilla from the human/chimpanzee ancestor.</p><p>Duplicated genes play a critical role in the evolution of a genome as they act as &lsquo;spare parts&rsquo; than can evolve to perform new or more specialized functions.</p><p>Effects of structural variation on gene expression can be identified but only a few examples of the consequences for species biology have been documented.</p><p><strong style="font-size: 12.8px;">Tools</strong></p><p><a href="http://sv.gersteinlab.org/cnvnator">CNVnator</a>a tool for CNV discovery and genotyping from depth of read mapping.<a href="http://www.ncbi.nlm.nih.gov/pubmed/21293372">2011a</a>,<a href="http://www.ncbi.nlm.nih.gov/pubmed/21324876">2011b</a></p><p><a href="http://sv.gersteinlab.org/age">AGE</a>a tools that implements an algorithm for optimal alignment of sequences with SVs.<a href="http://www.ncbi.nlm.nih.gov/pubmed/21233167">2011</a></p><p><a href="http://sv.gersteinlab.org/breakseq">BreakSeq</a>a pipeline for annotation, classification and analysis of SVs at single nucleotide resolution.<a href="http://www.ncbi.nlm.nih.gov/pubmed/20037582">2010</a></p><p><a href="http://sv.gersteinlab.org/pemer">PEMer</a>a computational and simulation framework for discovering SVs by paired-end read mapping.<a href="http://www.ncbi.nlm.nih.gov/pubmed/19236709">2009</a>,<a href="http://www.ncbi.nlm.nih.gov/pubmed/17901297">2007</a></p><p>GASV https://code.google.com/archive/p/gasv/</p><p>PAIROSCOPE http://pairoscope.sourceforge.net/</p><p>SVDetect&nbsp;http://svdetect.sourceforge.net/Site/Home.html</p><p>BreakPtr, discovery of unbalanced structural variants (copy-number variants) with tiling microarrays&nbsp;<a href="http://tiling.mbb.yale.edu/BreakPtr/" target="_top">Link</a>&nbsp;</p><p>R Package&nbsp;https://www.bioconductor.org/help/course-materials/2010/EMBL2010/Practical-4-StructuralVariants.pdf<br /><br />BreakSeq, structural variant genotyping using split reads&nbsp;<a href="http://sv.gersteinlab.org/breakseq/" target="_top">Link</a>&nbsp;<br /><br />CopySeq, genotyping of unbalanced structural variants (copy-number variants) using read-depth&nbsp;<a href="http://www.korbel.embl.de/CopySeq/" target="_top">Link</a>&nbsp;<br /><br />DELLY2, integrated structural variant discovery, genotyping and visualization in deep sequencing data&nbsp;<a href="https://github.com/dellytools/delly" target="_top">Link</a>&nbsp;<br /><br />PEMer, structural variant discovery in 454 sequencing data by paired-end mapping&nbsp;<a href="http://www.korbel.embl.de/PEMer/" target="_top">Link</a>&nbsp;<br /><br />TIGER, transduction inference in germline genomes using short read data&nbsp;<a href="https://github.com/jelena-tica/TIGER" target="_top">Link</a>&nbsp;</p><p>MANTA&nbsp;https://github.com/Illumina/manta</p><p>SV-Bay&nbsp;https://github.com/InstitutCurie/SV-Bay</p><p>BreakDancer&nbsp;http://breakdancer.sourceforge.net/</p><p>Variation Hunter&nbsp;http://compbio.cs.sfu.ca/software-variation-hunter</p><p>Lumpy&nbsp;https://github.com/arq5x/lumpy-sv</p><p>ForestSV&nbsp;http://sebatlab.ucsd.edu/index.php/software-data&nbsp;</p><p>PBSuites for long reads&nbsp;https://sourceforge.net/projects/pb-jelly/</p><p><strong>Visualization</strong></p><p>The SV visualization tool:&nbsp;<a href="http://genomesavant.com/savant/">http://genomesavant.com/savant/</a></p><p>InGAP-SV (<a href="http://ingap.sourceforge.net/">http://ingap.sourceforge.net/</a>) that is nice tools for both detection and visualisation of severals kind of structural variations (Large insertions, translocation, deletion, inversions....)&nbsp;</p><p>Tools table: http://www.nature.com/nbt/journal/v29/n8/fig_tab/nbt.1904_T2.html</p><p>Variation Viewer https://www.ncbi.nlm.nih.gov/variation/view/</p><p><strong style="font-size: 12.8px;">Papers</strong></p><p>http://www.nature.com/nmeth/journal/v9/n2/full/nmeth.1858.html</p><p>http://journal.frontiersin.org/researchtopic/1412/structural-variations-in-genomes-ecological-and-evolutionary-implications</p><p>http://www.mi.fu-berlin.de/wiki/pub/ABI/GenomicsLecture10Materials/structural-variation.pdf</p><p>http://bmcgenomics.biomedcentral.com/articles/10.1186/s12864-015-1479-3</p><p>https://www.ncbi.nlm.nih.gov/dbvar/content/overview/</p><p>http://www.nature.com/subjects/structural-variation</p><p>https://eichlerlab.gs.washington.edu/news/NatMeth_Feb2012.pdf</p><p>https://www.ncbi.nlm.nih.gov/pubmed/19477992 ***</p><p>https://www.ncbi.nlm.nih.gov/pubmed/22452995</p><p>http://biorxiv.org/content/early/2016/09/06/073833</p><p>https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4479793/</p><p>http://www.nature.com/articles/srep18501</p><p>http://www.genetics.org/content/202/1/351</p><p>http://www.cs.cmu.edu/~sssykim/teaching/s13/slides/Lecture_SVI.pdf</p><p>https://www.omicsonline.org/open-access/structural-variation-detection-from-next-generation-sequencing-2469-9853-S1-007.php?aid=69055</p><p>http://schatzlab.cshl.edu/presentations/2016/2016.01.12.PAG.Structural%20Variations.pdf</p><p>&nbsp;</p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30147/cisa-contig-integrator-for-sequence-assembly</guid>
	<pubDate>Thu, 15 Dec 2016 05:42:21 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30147/cisa-contig-integrator-for-sequence-assembly</link>
	<title><![CDATA[CISA: Contig Integrator for Sequence Assembly]]></title>
	<description><![CDATA[<p>A plethora of algorithmic assemblers have been proposed for the <em>de novo</em> assembly of genomes, however, no individual assembler guarantees the optimal assembly for diverse species. Optimizing various parameters in an assembler is often performed in order to generate the most optimal assembly. However, few efforts have been pursued to take advantage of multiple assemblies to yield an assembly of high accuracy. In this study, we employ various state-of-the-art assemblers to generate different sets of contigs for bacterial genomes. A tool, named CISA, has been developed to integrate the assemblies into a hybrid set of contigs, resulting in assemblies of superior contiguity and accuracy, compared with the assemblies generated by the state-of-the-art assemblers and the hybrid assemblies merged by existing tools. This tool is implemented in Python and requires MUMmer and BLAST+ to be installed on the local machine. The source code of CISA and examples of its use are available at <a href="http://sb.nhri.org.tw/CISA/">http://sb.nhri.org.tw/CISA/</a>.</p><p>Address of the bookmark: <a href="http://sb.nhri.org.tw/CISA/en/CISA" rel="nofollow">http://sb.nhri.org.tw/CISA/en/CISA</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30168/gene-synteny-database</guid>
	<pubDate>Fri, 16 Dec 2016 11:09:39 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30168/gene-synteny-database</link>
	<title><![CDATA[Gene Synteny Database]]></title>
	<description><![CDATA[<p>Comparative genomics remains a pivotal strategy to study the evolution of gene organization, and this primacy is reinforced by the growing number of full genome sequences available in public repositories. Despite this growth, bioinformatic tools available to visualize and compare genomes and to infer evolutionary events remain restricted to two or three genomes at a time, thus limiting the breadth and the nature of the question that can be investigated. Here we present Genomicus, a new synteny browser that can represent and compare unlimited numbers of genomes in a broad phylogenetic view. In addition, Genomicus includes reconstructed ancestral gene organization, thus greatly facilitating the interpretation of the data.</p>
<p><strong>Availability:</strong>&nbsp;Genomicus is freely available for online use at&nbsp;<a href="http://www.dyogen.ens.fr/genomicus" target="pmc_ext">http://www.dyogen.ens.fr/genomicus</a>&nbsp;while data can be downloaded at&nbsp;<a href="ftp://ftp.biologie.ens.fr/pub/dyogen/genomicus" target="pmc_ext">ftp://ftp.biologie.ens.fr/pub/dyogen/genomicus</a></p>
<p><strong>Contact:</strong>&nbsp;<a href="mailto:dev@null">rf.sne.eigoloib@crh</a></p><p>Address of the bookmark: <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2853686/" rel="nofollow">https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2853686/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30214/megamerge-a-tool-to-merge-assembled-contigs-long-reads-from-metagenomic-sequencing-runs</guid>
	<pubDate>Mon, 19 Dec 2016 09:42:15 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30214/megamerge-a-tool-to-merge-assembled-contigs-long-reads-from-metagenomic-sequencing-runs</link>
	<title><![CDATA[MeGAMerge: A tool to merge assembled contigs, long reads from metagenomic sequencing runs]]></title>
	<description><![CDATA[<p>MeGAMerge</p>
<p>MeGAMerge (A tool to merge assembled contigs, long reads from metagenomic sequencing runs)</p>
<p>Description</p>
<p>MeGAMerge is a perl based wrapper/tool that can accept any number of sequence (FASTA) files containing assembled contigs of any length in Multi-FASTA format to produce an improved contig set based on OLC based assembly. All overlap parameters (Minimum Overlap Length, Identity, etc) are user-declarable at runtime. It is written to run on Linux.</p>
<p>Requirements:</p>
<p>You will need to have the following tools installed and in $PATH, or added to $binpath in the tool:</p>
<p>Newbler (specifically runAssembly)<br>Minimus2 (part of AMOS, also requires MUMmer)</p><p>Address of the bookmark: <a href="https://github.com/LANL-Bioinformatics/MeGAMerge" rel="nofollow">https://github.com/LANL-Bioinformatics/MeGAMerge</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/30245/venkatesh-lab</guid>
  <pubDate>Tue, 20 Dec 2016 04:38:01 -0600</pubDate>
  <link></link>
  <title><![CDATA[Venkatesh Lab]]></title>
  <description><![CDATA[
<p>We are using a comparative genomics approach to better understand the structure, function and evolution of the human genome. Our group is one of the pioneers in the field of comparative genomics. We proposed the compact genome of the fugu (Takifugu rubripes) as a model vertebrate genome in 1993 (Nature 366: 265-268, 1993) and determined its whole genome sequence in 2002 (Science 297: 1301-1310, 2002).</p>

<p>More at <br />https://zfin.org/ZDB-LAB-110408-1<br />http://www.imcb.a-star.edu.sg/php/venkatesh.php</p>
]]></description>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/30331/16th-congress-of-the-european-society-for-evolutionary-biology-eseb</guid>
  <pubDate>Thu, 22 Dec 2016 08:08:37 -0600</pubDate>
  <link></link>
  <title><![CDATA[16th Congress of the European Society for Evolutionary Biology (ESEB)]]></title>
  <description><![CDATA[
<p>Abstract submissions for our upcoming symposium on the Genomics of Adaptation that will take place as part of the 16th Congress of the European Society for Evolutionary Biology (ESEB). The conference will take place from August 20th - August 25th, 2017 in Groningen, the Netherlands. </p>

<p>SYMPOSIUM DESCRIPTION: Genomics of Adaptation [S16] Model organisms for life-history research are mainly studied in the lab where functional genetics is assessable. In general, however, knowledge about their eco-evolutionary dynamics, such as biotic interactions, is rare. By contrast, in organisms for which the ecology and adaptation strategies in the field are well known, we typically lack the appropriate genetic tools to investigate functionality. Advances in genomics and statistics as well as investments in evolutionary model organisms are now providing access to putatively adaptive genome-wide variation within species from across the tree of life. In this symposium, we focus on integrating life-history biology, genetics and evolutionary ecology in the genomics era. </p>

<p>We wish to (1) highlight the role of genetic architecture of complex traits, such as adaptations to biotic interactions or life-history traits; (2) contrast this to morphological traits which are generally thought to have a less complex genetic architecture; and (3) discuss the opportunities and drawbacks of specific model systems. </p>

<p>INVITED SPEAKERS: Josephine Pemberton, University of Cambridge (http://bit.ly/2hJWytJ ) Peter Tiffin, University of Minnesota (http://bit.ly/2hK7HuS ) </p>

<p>ABSTRACT SUBMISSION The deadline for abstract submission is January 10, 2017. For more information and to submit abstracts online, please visit: http://bit.ly/2fBXlvN We look forward to an exciting symposium and seeing you all in Groningen! Sincerely, Ben Blackman, UC Berkeley Maaike de Jong, University of Bristol Bart Pannebakker, Wageningen University Noah Whiteman, UC Berkeley Jelle Zandveld, Wageningen University</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/30364/bioinformatics-contest-2017</guid>
	<pubDate>Fri, 23 Dec 2016 14:03:37 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/30364/bioinformatics-contest-2017</link>
	<title><![CDATA[Bioinformatics Contest 2017!]]></title>
	<description><![CDATA[<p><a href="http://contest.bioinf.me" target="_blank">Bioinformatics Contest 2017</a>! Rosalind is co-organizer.<br /> Compete with thousands of people worldwide on bioinformatics problem solving.<br /> Everything is online. Qualification round starts on <strong>January 23, 2017</strong>. Final is on <span><span>Feb 18</span></span>.</p><p>You will need to solve bioinformatics problems using programming. The goal is to correctly solve as many problems as possible within 24 hours. Some of them will be approximation problems and will have partial grades. All rounds will be held online, submissions will be auto-graded in real time.</p><p>Check more at http://contest.bioinf.me/</p><p>Good luck!</p>]]></description>
	<dc:creator>Neel</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30538/gkno</guid>
	<pubDate>Tue, 17 Jan 2017 03:35:34 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30538/gkno</link>
	<title><![CDATA[GKNO]]></title>
	<description><![CDATA[<p><span>gkno opens the world of complex bioinformatic analysis to people of all level of computational expertise. This site contains documentation, tutorials and information on all the tools that comprise gkno.</span></p>
<p><span>More at&nbsp;http://gkno.me/</span></p><p>Address of the bookmark: <a href="http://gkno.me/" rel="nofollow">http://gkno.me/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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