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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/30093?offset=60</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32709/cabog-celera-assembler-with-best-overlap-graph</guid>
	<pubDate>Mon, 15 May 2017 05:04:39 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32709/cabog-celera-assembler-with-best-overlap-graph</link>
	<title><![CDATA[CABOG: Celera Assembler with Best Overlap Graph]]></title>
	<description><![CDATA[<p>CABOG (Celera Assembler with Best Overlap Graph) is scientific software for&nbsp;<a href="http://bioinformatics.oxfordjournals.org/content/24/24/2818.abstract">DNA research</a>. CABOG has been a critical component of many genome sequencing projects. CABOG operates on small genomes such as bacterial as well as large genomes such as mammalian. CABOG is an extension of the Celera Assembler software that was originally developed at&nbsp;<a href="http://www.celera.com/">Celera</a>&nbsp;for the 2001 publication of the first draft human genome sequence. The software was released to the public domain in 2004. Its open source&nbsp;<a href="http://wgs-assembler.sf.net/">repository</a>&nbsp;on Source Forge is an internet resource for scientists around the world.&nbsp;</p>
<p>CABOG is one of many software programs called genome assemblers. These programs exist to overcome the fundamental limitation of all sequencing machines, namely, that they read out very few DNA letters at a time. These programs reconstruct genomes that are billions of letters long from the hundreds of letters per read that modern sequencers provide. What these programs do is often described as a scaled up version of a family solving a jigsaw puzzle.</p>
<p>The CABOG software was the first to accomplish many scientific goals. It was the first to assemble the genome of a multicellular organism (<em>Drosophila melanogaster</em>, 2000). It was the first to assemble both parental haplotypes of one human genome (J. Craig Venter, 2007). It was the first to assemble environmental sequence from the oceans (Sargasso Sea in 2004 and Global Ocean Sampling in 2007). It was first to combine reads from first-generation Sanger sequencing machines and second-generation pyrosequencing machines (Marine microbes, 2006). Today, CABOG is one of the leading assembly programs for data sets that include paired end data from the Roche 454 line of sequencing machines.</p><p>Address of the bookmark: <a href="http://www.jcvi.org/cms/research/projects/cabog/overview/" rel="nofollow">http://www.jcvi.org/cms/research/projects/cabog/overview/</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36594/fragscaff-genome-assembly-with-contiguity-preserving-transposition</guid>
	<pubDate>Mon, 14 May 2018 04:28:14 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36594/fragscaff-genome-assembly-with-contiguity-preserving-transposition</link>
	<title><![CDATA[fragScaff: Genome Assembly with Contiguity Preserving Transposition]]></title>
	<description><![CDATA[<p>Contiguity preserving transposition and sequencing (CPT-seq) is an entirely in vitro means of generating libraries comprised of 9216 indexed pools, each of which contains thousands of sparsely sequenced long fragments ranging from 5 kilobases to &gt;1 megabase. This software, fragScaff, leverages coincidences between the content of different pools as a source of contiguity information for scaffolding de novo genome assemblies. FragScaff is complementary to Lachesis, providing midrange contiguity to support robust, accurate chromosome-scale de novo genome assemblies without the need for laborious in vivo cloning steps.</p>
<p>Further information about fragScaff, including source code, is available at:<a href="https://sourceforge.net/projects/fragscaff/files/">https://sourceforge.net/projects/fragscaff/files</a>.</p>
<p>Manuscript describing fragScaff was published as: Adey A, Kitzman JO, Burton JN, Daza R, Kumar A, Christiansen L, Ronaghi M, Amini S, L Gunderson K, Steemers FJ, Shendure J#.&nbsp;<em>In vitro, long-range sequence information for de novo genome assembly via transposase contiguity.</em>&nbsp;Genome Research 2014 Dec;24(12):2041-9. doi:&nbsp;<a href="http://dx.doi.org/10.1101/gr.178319.114">10.1101/gr.178319.114</a>. PubMed PMID:&nbsp;<a href="http://www.ncbi.nlm.nih.gov/pubmed/25327137">25327137</a>.</p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="https://sourceforge.net/projects/fragscaff/files/" rel="nofollow">https://sourceforge.net/projects/fragscaff/files/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31100/vaguevelvet-assembler-graphical-front-end</guid>
	<pubDate>Fri, 24 Feb 2017 08:56:49 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31100/vaguevelvet-assembler-graphical-front-end</link>
	<title><![CDATA[VAGUE:Velvet Assembler Graphical Front End]]></title>
	<description><![CDATA[<p>VAGUE is a vague acronym for "Velvet Assembler Graphical Front End", which means it is a GUI for the Velvet <em>de novo</em> assembler. The command line version of Velvet can be complicated for beginners to use, but VAGUE makes it clear and simple</p>
<p>More at&nbsp;http://www.vicbioinformatics.com/software.vague.shtml</p><p>Address of the bookmark: <a href="http://www.vicbioinformatics.com/software.vague.shtml" rel="nofollow">http://www.vicbioinformatics.com/software.vague.shtml</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/28842/repeatmodeler</guid>
	<pubDate>Thu, 18 Aug 2016 09:57:15 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/28842/repeatmodeler</link>
	<title><![CDATA[RepeatModeler]]></title>
	<description><![CDATA[<p><span>RepeatModeler is a de-novo repeat family identification and modeling package. At the heart of RepeatModeler are two de-novo repeat finding programs ( RECON and RepeatScout ) which employ complementary computational methods for identifying repeat element boundaries and family relationships from sequence data. RepeatModeler assists in automating the runs of RECON and RepeatScout given a genomic database and uses the output to build, refine and classify consensus models of putative interspersed repeats.</span></p><p>Address of the bookmark: <a href="http://www.repeatmasker.org/RepeatModeler.html" rel="nofollow">http://www.repeatmasker.org/RepeatModeler.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/28884/tgnet</guid>
	<pubDate>Wed, 24 Aug 2016 05:36:36 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/28884/tgnet</link>
	<title><![CDATA[TGNet]]></title>
	<description><![CDATA[<p><span>Recent technological progress has greatly facilitated&nbsp;</span><em>de novo</em><span>&nbsp;genome sequencing. However,&nbsp;</span><em>de novo</em><span>&nbsp;assemblies consist in many pieces of contiguous sequence (contigs) arranged in thousands of scaffolds instead of small numbers of chromosomes. Confirming and improving the quality of such assemblies is critical for subsequent analysis.&nbsp;</span></p>
<p>Visualization and quality assessment of de novo genome assemblies</p>
<p>Citation</p>
<p>This software is fully described in the paper:<br>Riba-Grognuz, Keller, Falquet, Xenarios &amp; Wurm (2011) Visualization and quality assessment of de novo genome assemblies.</p>
<p>In brief, our scripts create Cytoscape files to visualize transcript evidence that suggests adjacency between scaffolds and contigs.</p>
<p>Software requirements</p>
<p>BLAT (tested with Standalone BLAT v. 32&times;1). Source Binaries .<br>Cytoscape (tested with versions 2.7.0, 2.8.2)<br>a UNIX machine (tested on Mac OS X 10.6 and CentOS 4.6)</p><p>Address of the bookmark: <a href="https://github.com/ksanao/TGNet" rel="nofollow">https://github.com/ksanao/TGNet</a></p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/28915/useful-bioinformatics-tools</guid>
	<pubDate>Mon, 29 Aug 2016 04:08:12 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/28915/useful-bioinformatics-tools</link>
	<title><![CDATA[Useful Bioinformatics Tools]]></title>
	<description><![CDATA[<p>Collections of few handy tools for bioinformatician</p>
<p>http://molbiol-tools.ca/Convert.htm</p><p>Address of the bookmark: <a href="http://molbiol-tools.ca/Convert.htm" rel="nofollow">http://molbiol-tools.ca/Convert.htm</a></p>]]></description>
	<dc:creator>Poonam Mahapatra</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/28997/braker-pipeline-for-fully-automated-prediction-of-protein-coding-genes-with-genemark-eset-and-augustus-in-novel-eukaryotic-genomes</guid>
	<pubDate>Thu, 01 Sep 2016 08:02:59 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/28997/braker-pipeline-for-fully-automated-prediction-of-protein-coding-genes-with-genemark-eset-and-augustus-in-novel-eukaryotic-genomes</link>
	<title><![CDATA[BRAKER: pipeline for fully automated prediction of protein coding genes with GeneMark-ES/ET and AUGUSTUS in novel eukaryotic genomes]]></title>
	<description><![CDATA[<p><span>Gene finding in eukaryotic genomes is notoriously difficult to automate. The task is to design a work flow with a minimal set of tools that would reach state-of-the-art performance across a wide range of species. GeneMark-ET is a gene prediction tool that incorporates RNA-Seq data into unsupervised training and subsequently generates ab initio gene predictions. AUGUSTUS is a gene finder that usually requires supervised training and uses information from RNA-Seq reads in the prediction step. Complementary strengths of GeneMark-ET and AUGUSTUS provided motivation for designing a new combined tool for automatic gene prediction.</span></p>
<p>http://www.ncbi.nlm.nih.gov/pubmed/26559507</p><p>Address of the bookmark: <a href="http://bioinf.uni-greifswald.de/bioinf/braker/" rel="nofollow">http://bioinf.uni-greifswald.de/bioinf/braker/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29384/phymmbl</guid>
	<pubDate>Mon, 10 Oct 2016 08:56:34 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29384/phymmbl</link>
	<title><![CDATA[PHYMMBL]]></title>
	<description><![CDATA[<p><span>Metagenomics sequencing projects collect samples of DNA from uncharacterized environments that may contain hundreds or even thousands of species. One of the main challenges in analyzing a metagenome is phylogenetic classification of raw sequence reads into groups representing the same or similar species. Such classification is a useful prerequisite for genome assembly and for analysis of the biological diversity present in a sample. The newest sequencing technologies have simultaneously made metagenomics easier, by making the sequencing process faster, and more difficult, by producing shorter read lengths than previous technologies. Methods for classifying sequences as short as 100 base pairs (bp) have until now been relatively inaccurate, requiring metagenomics projects to use older, long-read technologies.&nbsp;</span><strong>Phymm</strong><span>, a new classification approach for metagenomics data which uses interpolated Markov models (IMMs) to taxonomically classify DNA sequences, can accurately classify reads as short as 100 bp. Its accuracy for short reads represents a significant leap forward over previous composition-based classification methods.&nbsp;</span><strong>PhymmBL</strong><span>&nbsp;(rhymes with "thimble"), the hybrid classifier included in this distribution which combines analysis from both Phymm and&nbsp;</span><a href="http://www.ncbi.nlm.nih.gov/BLAST">BLAST</a><span>, produces even higher accuracy.</span></p><p>Address of the bookmark: <a href="http://www.cbcb.umd.edu/software/phymm/" rel="nofollow">http://www.cbcb.umd.edu/software/phymm/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<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>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30212/pear</guid>
	<pubDate>Mon, 19 Dec 2016 09:28:30 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30212/pear</link>
	<title><![CDATA[PEAR]]></title>
	<description><![CDATA[<p><strong>PEAR</strong>&nbsp;is an ultrafast, memory-efficient and highly accurate pair-end read merger. It is fully parallelized and can run with as low as just a few kilobytes of memory.</p>
<p>PEAR evaluates all possible paired-end read overlaps and without requiring the target fragment size as input. In addition, it implements a statistical test for minimizing false-positive results. Together with a highly optimized implementation, it can merge millions of paired end reads within a couple of minutes on a standard desktop computer.</p><p>Address of the bookmark: <a href="http://sco.h-its.org/exelixis/web/software/pear/doc.html" rel="nofollow">http://sco.h-its.org/exelixis/web/software/pear/doc.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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