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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/30234?offset=30</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29586/eforgev12</guid>
	<pubDate>Fri, 28 Oct 2016 09:06:59 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29586/eforgev12</link>
	<title><![CDATA[eFORGE.v1.2]]></title>
	<description><![CDATA[<p><span>The eFORGE tool provides a method to view the tissue specific regulatory component of a set of EWAS DMPs. eFORGE analysis takes a set of DMPs, such as those hits above genome-wide significance threshold in an EWAS study, and analyses whether there is enrichment for overlap of putative functional elements compared to matched background DMPs. It assesses enrichment on a per cell type basis, since functional elements are differentially active in different cell types, and hence can expose tissue-specific signals of enrichment for the given test DMP set. This can reveal the sites of action underlying the EWAS signal, and provide confirmation of the validity of the EWAS where a tissue-specific mechanism is known or expected for the phenotype. Conversely unknown tissue involvements can also be revealed.</span></p><p>Address of the bookmark: <a href="http://eforge.cs.ucl.ac.uk/eFORGE.v1.2/?documentation" rel="nofollow">http://eforge.cs.ucl.ac.uk/eFORGE.v1.2/?documentation</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30074/minia</guid>
	<pubDate>Thu, 08 Dec 2016 05:07:00 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30074/minia</link>
	<title><![CDATA[Minia]]></title>
	<description><![CDATA[<p>Minia is a short-read assembler based on a de Bruijn graph, capable of assembling a human genome on a desktop computer in a day. The output of Minia is a set of contigs. Minia produces results of similar contiguity and accuracy to other de Bruijn assemblers (e.g. Velvet).</p>
<h3>Download</h3>
<p><a href="https://github.com/GATB/minia/releases/download/v2.0.7/minia-v2.0.7-bin-Linux.tar.gz">Minia 2.0.7 Linux 64-bits binaries</a>&nbsp;(<a href="https://github.com/GATB/minia/releases/download/v2.0.7/minia-v2.0.7-Source.tar.gz">Source code</a>)&nbsp;<span>(<a href="http://minia.genouest.org/files/minia-1.6906.tar.gz">Legacy codebase</a>)</span></p>
<h3>For the impatient</h3>
<p>A typical Minia command line looks like:</p>
<pre>./minia -in <span>reads.fa</span> -kmer-size <span>31</span> -abundance-min <span>3</span> -out <span>output_prefix</span></pre>
<p>Type</p>
<pre>./minia</pre>
<p><span>for a quick explanation of the parameters.</span></p>
<p>For more information, refer to the&nbsp;<a href="http://minia.genouest.org/files/minia.pdf">manual</a>.</p>
<p><a href="http://kmergenie.bx.psu.edu/">KmerGenie</a>&nbsp;can be used to determine the best k-mer size, minimum abundance of correct k-mers, and genome size estimation for your dataset.</p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="http://minia.genouest.org/" rel="nofollow">http://minia.genouest.org/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<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>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30144/bima-v3-an-aligner-customized-for-mate-pair-library-sequencing</guid>
	<pubDate>Wed, 14 Dec 2016 15:20:00 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30144/bima-v3-an-aligner-customized-for-mate-pair-library-sequencing</link>
	<title><![CDATA[BIMA V3: an aligner customized for mate pair library sequencing]]></title>
	<description><![CDATA[<p>Summary: Mate pair library sequencing is an effective and economical method for detecting genomic structural variants and chromosomal abnormalities. Unfortunately, the mapping and alignment of mate pair read pairs to a reference genome is a challenging and <br>time consuming process for most NGS alignment programs. Large insert sizes, introduction of library preparation protocol artifacts (biotin junction reads, paired-end read contamination, chimeras, etc.), and presence of structural variant breakpoints within reads increases mapping and alignment complexity. We describe an algorithm that is up to 20 times faster and 25% more accurate than popular NGS alignment programs when processing mate pair sequencing. <br>Availability: http://bioinformaticstools.mayo.edu/research/bima/ <br>Contact: vasmatzis.george@mayo.edu</p><p>Address of the bookmark: <a href="http://bioinformatics.oxfordjournals.org/content/early/2014/02/12/bioinformatics.btu078.full.pdf" rel="nofollow">http://bioinformatics.oxfordjournals.org/content/early/2014/02/12/bioinformatics.btu078.full.pdf</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30205/garmgenome-assembly-reconciliation-and-merging</guid>
	<pubDate>Mon, 19 Dec 2016 06:03:02 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30205/garmgenome-assembly-reconciliation-and-merging</link>
	<title><![CDATA[GARM:Genome Assembly, Reconciliation and Merging]]></title>
	<description><![CDATA[<p><span>The pipeline is based mainly implemented using Perl scripts and modules and third-party open source software like the AMOS (Myers et al., 2000) and MUMmer (Kurtz et al., 2004) packages. The pipeline was tested on Debian, Ubuntu, Fedora and BioLinux distributions. The method merges contigs or scaffolds from different assemblers using the same or different sequencing technologies. When scaffolds are provided, a process of finding probable compressions or extensions (CE) problems in the assemblies can be per-formed; contigs are joined back into scaffolds after gap recalculation</span></p><p>Address of the bookmark: <a href="http://garm-meta-assem.sourceforge.net/" rel="nofollow">http://garm-meta-assem.sourceforge.net/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30216/quickmerge-a-simple-and-fast-metassembler-and-assembly-gap-filler-designed-for-long-molecule-based-assemblies</guid>
	<pubDate>Mon, 19 Dec 2016 10:23:36 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30216/quickmerge-a-simple-and-fast-metassembler-and-assembly-gap-filler-designed-for-long-molecule-based-assemblies</link>
	<title><![CDATA[quickmerge: A simple and fast metassembler and assembly gap filler designed for long molecule based assemblies.]]></title>
	<description><![CDATA[<p><span>quickmerge uses a simple concept to improve contiguity of genome assemblies based on long molecule sequences, often with dramatic outcomes. The program uses information from assemblies made with illumina short reads and PacBio long reads to improve contiguities of an assembly generated with PacBio long reads alone. This is counterintuitive because illumina short reads are not typically considered to cover genomic regions which PacBio long reads cannot. Although we have not evaluated this program for assemblies generated with Oxford nanopore sequences, the program should work with ONP-assemblies too.&nbsp;</span></p><p>Address of the bookmark: <a href="https://github.com/mahulchak/quickmerge" rel="nofollow">https://github.com/mahulchak/quickmerge</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30304/mcscan</guid>
	<pubDate>Thu, 22 Dec 2016 03:53:58 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30304/mcscan</link>
	<title><![CDATA[MCscan]]></title>
	<description><![CDATA[<p><span>MCscan is a computer program that can simultaneously scan multiple genomes to identify homologous chromosomal regions and subsequently align these regions using genes as anchors. This is the toolset for generating the synteny correspondences in&nbsp;</span><a href="http://chibba.agtec.uga.edu/duplication">Plant Genome Duplication Database</a><span>. It is intended as an easy-to-use and quick way to identify conserved gene arrays both within the same genome and across different genomes.</span></p>
<p><span>More at&nbsp;http://chibba.agtec.uga.edu/duplication/mcscan/</span></p><p>Address of the bookmark: <a href="http://chibba.agtec.uga.edu/duplication/mcscan/" rel="nofollow">http://chibba.agtec.uga.edu/duplication/mcscan/</a></p>]]></description>
	<dc:creator>Bulbul</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31300/clgenomics</guid>
	<pubDate>Fri, 03 Mar 2017 09:57:28 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31300/clgenomics</link>
	<title><![CDATA[CLgenomics]]></title>
	<description><![CDATA[<p>CLgenomics is a standalone desktop software specifically designed for bacterial genome analysis. This program has a powerful multi-genome browser, which enables rapid and responsive exploration of bacterial genomes.</p>
<p>To use CLgenomics, individual genome data (genome sequences + annotation details) are compiled and saved in a specially formatted file called CLG (ChunLab Genomics).&nbsp;Each CLG file corresponds with one bacterial genome. If multiple genomes are being considered and compared, multiple CLG files are needed. ChunLab offers &gt;40,000 CLG files of publicly available Bacterial and Archaeal genomes.</p><p>Address of the bookmark: <a href="https://chunlab.wordpress.com/clgenomics-software/" rel="nofollow">https://chunlab.wordpress.com/clgenomics-software/</a></p>]]></description>
	<dc:creator>Radha Agarkar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26587/last</guid>
	<pubDate>Wed, 09 Mar 2016 14:27:01 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26587/last</link>
	<title><![CDATA[LAST]]></title>
	<description><![CDATA[<p style="text-align: center;"><img src="http://last.cbrc.jp/lastwebfig.png" alt="sketch of  similar regions in sequences" style="border: 0px;"></p>
<p>LAST can:</p>
<ul>
<li>Handle <strong>big</strong> sequence data, e.g:
<ul>
<li>Compare two vertebrate genomes</li>
<li>Align billions of DNA reads to a genome</li>
</ul>
</li>
<li>Indicate the <a href="http://lastweb.cbrc.jp/about.html">reliability</a> of each aligned column.</li>
<li>Use sequence quality data <a href="http://nar.oxfordjournals.org/content/38/7/e100.abstract">properly</a>.</li>
<li>Compare DNA to proteins, with frameshifts.</li>
<li>Compare PSSMs to sequences</li>
<li>Calculate the likelihood of chance similarities between random sequences.</li>
<li>Do split and spliced alignment.</li>
<li><a href="http://last.cbrc.jp/doc/last-train.html">Train</a> alignment parameters for unusual kinds of sequence (e.g. nanopore).</li>
</ul><p>Address of the bookmark: <a href="http://last.cbrc.jp/" rel="nofollow">http://last.cbrc.jp/</a></p>]]></description>
	<dc:creator>Archana Malhotra</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31353/concoct-clustering-contigs-with-coverage-and-composition</guid>
	<pubDate>Mon, 06 Mar 2017 04:08:16 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31353/concoct-clustering-contigs-with-coverage-and-composition</link>
	<title><![CDATA[CONCOCT: Clustering cONtigs with COverage and ComposiTion]]></title>
	<description><![CDATA[<p>A program for unsupervised binning of metagenomic contigs by using nucleotide composition, coverage data in multiple samples and linkage data from paired end reads.</p>
<p>Warning! This software is to be considered under development. Functionality and the user interface may still change significantly from one version to another. If you want to use this software, please stay up to date with the list of known issues:<a href="https://github.com/BinPro/CONCOCT/issues">https://github.com/BinPro/CONCOCT/issues</a></p><p>Address of the bookmark: <a href="https://github.com/BinPro/CONCOCT" rel="nofollow">https://github.com/BinPro/CONCOCT</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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