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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/32465?offset=40</link>
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	<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>
</item>
<item>
	<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>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30355/meme-suite</guid>
	<pubDate>Fri, 23 Dec 2016 08:49:55 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30355/meme-suite</link>
	<title><![CDATA[MEME suite]]></title>
	<description><![CDATA[<p>Motif based sequence analysis suits&nbsp;</p>
<p>The MEME Suite allows the biologist to discover novel motifs in collections of unaligned nucleotide or protein sequences, and to perform a wide variety of other motif-based analyses.</p>
<p>The MEME Suite supports motif-based analysis of DNA, RNA and protein sequences. It provides motif discovery algorithms using both probabilistic (MEME) and discrete models (MEME), which have complementary strengths. It also allows discovery of motifs with arbitrary insertions and deletions (GLAM2). In addition to motif discovery, the MEME Suite provides tools for scanning sequences for matches to motifs (FIMO, MAST and GLAM2Scan), scanning for clusters of motifs (MCAST), comparing motifs to known motifs (Tomtom), finding preferred spacings between motifs (SpaMo), predicting the biological roles of motifs (GOMo), measuring the positional enrichment of sequences for known motifs (CentriMo), and analyzing ChIP-seq and other large datasets (MEME-ChIP).</p>
<p>The MEME Suite is comprised of a collection of tools that work together, as shown below. Not all the tools are available as webservices, so to get the full power of the MEME Suite you will need to&nbsp;<a href="http://meme-suite.org/doc/download.html">download</a>&nbsp;and&nbsp;<a href="http://meme-suite.org/doc/install.html">install</a>&nbsp;a local copy of the software. To see what has changed recently you can peruse the&nbsp;<a href="http://meme-suite.org/doc/release-notes.html">release notes</a>.</p>
<p>http://meme-suite.org/</p><p>Address of the bookmark: <a href="http://meme-suite.org/" rel="nofollow">http://meme-suite.org/</a></p>]]></description>
	<dc:creator>Bulbul</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30540/progressive-cactus</guid>
	<pubDate>Tue, 17 Jan 2017 03:40:06 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30540/progressive-cactus</link>
	<title><![CDATA[Progressive Cactus]]></title>
	<description><![CDATA[<h1><em style="font-size: 12.8px; font-weight: normal;">v0.0 by Glenn Hickey (<a href="mailto:hickey@soe.ucsc.edu">hickey@soe.ucsc.edu</a>)</em></h1>
<p>Progressive Cactus is a whole-genome alignment package.</p>
<h3><a href="https://github.com/glennhickey/progressiveCactus#requirements"></a>Requirements</h3>
<ul>
<li>git</li>
<li>gcc 4.2 or newer</li>
<li>python 2.7</li>
<li>wget</li>
<li>64bit processor and build environment</li>
<li>150GB+ of memory on at least one machine when aligning mammal-sized genomes; less memory is needed for smaller genomes.</li>
<li>Parasol or SGE for cluster support.</li>
<li>750M disk space</li>
</ul>
<h3><a href="https://github.com/glennhickey/progressiveCactus#instructions"></a>Instructions</h3>
<p>IMPORTANT NOTE: Progressive Cactus does not presently support installation into paths that contain spaces. Until this is resolved, you can use a softlink as a workaround: ln -s "path with spaces" "installation path without spaces"</p>
<p>In the parent directory of where you want Progressive Cactus installed:</p>
<pre><code>git clone git://github.com/glennhickey/progressiveCactus.git
cd progressiveCactus
git pull
git submodule update --init
make
</code></pre>
<p>It is also convenient to add the location of&nbsp;<code>progressiveCactus/bin</code>&nbsp;to your PATH environment variable. In order to run the included tools (ex hal2maf) in the submodules/ directory structure, first source&nbsp;<code>progressiveCactus/environment</code>&nbsp;to load the installed environment.</p>
<p>If any errors occur during the build process, you are unlikely to be able to use the tool. Please submit a GitHub issue so we can help out: not only will you help yourself, but others who wish to use the tool as well.</p>
<p><em>Note that all dependencies are also built and included in the submodules/ directory. This increases the size and build time but greatly simplifies installation and version management. The installation does not create or modify any files outside the progressiveCactus/ directory.</em></p><p>Address of the bookmark: <a href="https://github.com/glennhickey/progressiveCactus" rel="nofollow">https://github.com/glennhickey/progressiveCactus</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31087/bedtools</guid>
	<pubDate>Fri, 24 Feb 2017 04:50:44 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31087/bedtools</link>
	<title><![CDATA[bedtools]]></title>
	<description><![CDATA[<p>Collectively, the&nbsp;<strong>bedtools</strong>&nbsp;utilities are a swiss-army knife of tools for a wide-range of genomics analysis tasks. The most widely-used tools enable&nbsp;<em>genome arithmetic</em>: that is, set theory on the genome. For example,&nbsp;<strong>bedtools</strong>&nbsp;allows one to<em>intersect</em>,&nbsp;<em>merge</em>,&nbsp;<em>count</em>,&nbsp;<em>complement</em>, and&nbsp;<em>shuffle</em>&nbsp;genomic intervals from multiple files in widely-used genomic file formats such as BAM, BED, GFF/GTF, VCF. While each individual tool is designed to do a relatively simple task (e.g.,&nbsp;<em>intersect</em>&nbsp;two interval files), quite sophisticated analyses can be conducted by combining multiple bedtools operations on the UNIX command line.</p>
<p><strong>bedtools</strong>&nbsp;is developed in the&nbsp;<a href="http://quinlanlab.org/">Quinlan laboratory</a>&nbsp;at the&nbsp;<a href="http://www.utah.edu/">University of Utah</a>&nbsp;and benefits from fantastic contributions made by scientists worldwide.</p><p>Address of the bookmark: <a href="http://bedtools.readthedocs.io/en/latest/index.html" rel="nofollow">http://bedtools.readthedocs.io/en/latest/index.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31156/splitbam-splits-a-bam-by-chromosomes</guid>
	<pubDate>Tue, 28 Feb 2017 09:01:28 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31156/splitbam-splits-a-bam-by-chromosomes</link>
	<title><![CDATA[splitbam: splits a BAM by chromosomes]]></title>
	<description><![CDATA[<p><strong>splitbam</strong>&nbsp;splits a BAM by chromosomes.</p>
<p>Using the reference sequence dictionary (<code>*.dict</code>), it also creates some empty BAM files if no sam record was found for a chromosome. A pair of 'mock' SAM-Records can also be added to those empty BAMs to avoid some tools (like samtools) to crash.</p>
<h1>Usage</h1>
<p><code>java -jar splitbam.jar -p OUT/__CHROM__/__CHROM__.bam -R ref.fasta (bam|sam|stdin)</code></p>
<h1>Options</h1>
<ul>
<li>-h help; This screen.</li>
<li>-R (indexed reference file) REQUIRED.</li>
<li>-u (unmapped chromosome name): default:Unmapped</li>
<li>-e | --empty : generate EMPTY bams for chromosome having no read mapped</li>
<li>-m | --mock : if option '-e', add a mock pair of sam records to the empty bam</li>
<li>-p (output file/bam pattern) REQUIRED. MUST contain&nbsp;<strong><code>__CHROM__</code></strong>&nbsp;and end with .bam</li>
<li>-s assume input is sorted.</li>
<li>-x | --index create index.</li>
<li>-t | --tmp (dir) tmp file directory</li>
<li>-G (file) chrom-group file (see below)</li>
</ul><p>Address of the bookmark: <a href="https://code.google.com/archive/p/jvarkit/wikis/SplitBam.wiki" rel="nofollow">https://code.google.com/archive/p/jvarkit/wikis/SplitBam.wiki</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31351/maxbin-software-for-binning-assembled-metagenomic-sequences-based-on-an-expectation-maximization-algorithm</guid>
	<pubDate>Mon, 06 Mar 2017 04:03:38 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31351/maxbin-software-for-binning-assembled-metagenomic-sequences-based-on-an-expectation-maximization-algorithm</link>
	<title><![CDATA[MaxBin: software for binning assembled metagenomic sequences based on an Expectation-Maximization algorithm.]]></title>
	<description><![CDATA[<p><span>MaxBin is software for binning assembled metagenomic sequences based on an Expectation-Maximization algorithm. Users can understand the underlying bins (genomes) of the microbes in their metagenomes by simply providing assembled metagenomic sequences and the reads coverage information or sequencing reads. For users' convenience MaxBin will report genome-related statistics, including estimated completeness, GC content and genome size in the binning summary page.</span><br><br><span>Users can use MEGAN or similar software on MaxBin bins to find the taxonomy of each bin after the binning process is finished.</span></p>
<p>https://academic.oup.com/bioinformatics/article/32/4/605/1744462/MaxBin-2-0-an-automated-binning-algorithm-to<br><br><span>The most recent version of MaxBin is 2.2, which supports the analysis of coassemblies of multiple samples. It is available at this JBEI downloads sites as well as&nbsp;</span><a href="https://sourceforge.net/projects/maxbin/" target="_blank">MaxBin</a><span>&nbsp;and&nbsp;</span><a href="https://sourceforge.net/projects/maxbin2/" target="_blank">MaxBin 2.0</a><span>&nbsp;sourceforge sites.</span></p><p>Address of the bookmark: <a href="http://downloads.jbei.org/data/microbial_communities/MaxBin/MaxBin.html" rel="nofollow">http://downloads.jbei.org/data/microbial_communities/MaxBin/MaxBin.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31377/groopm-metagenomic-binning-toolset</guid>
	<pubDate>Tue, 07 Mar 2017 08:59:45 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31377/groopm-metagenomic-binning-toolset</link>
	<title><![CDATA[GroopM: Metagenomic binning toolset]]></title>
	<description><![CDATA[<p>GroopM is a metagenomic binning toolset. It leverages spatio-temoral<br>dynamics (differential coverage) to accurately (and almost automatically)<br>extract population genomes from multi-sample metagenomic datasets.</p>
<p>GroopM is largely parameter-free. Use: groopm -h for more info.</p>
<p>For installation and usage instructions see : http://ecogenomics.github.io/GroopM/</p><p>Address of the bookmark: <a href="https://github.com/ecogenomics/GroopM" rel="nofollow">https://github.com/ecogenomics/GroopM</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32048/json</guid>
	<pubDate>Tue, 04 Apr 2017 08:02:39 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32048/json</link>
	<title><![CDATA[JSON]]></title>
	<description><![CDATA[<p><strong>JSON</strong>&nbsp;(JavaScript Object Notation) is a lightweight data-interchange format. It is easy for humans to read and write. It is easy for machines to parse and generate. It is based on a subset of the&nbsp;<a href="http://javascript.crockford.com/">JavaScript Programming Language</a>,&nbsp;<a href="http://www.ecma-international.org/publications/files/ecma-st/ECMA-262.pdf">Standard ECMA-262 3rd Edition - December 1999</a>. JSON is a text format that is completely language independent but uses conventions that are familiar to programmers of the C-family of languages, including C, C++, C#, Java, JavaScript, Perl, Python, and many others. These properties make JSON an ideal data-interchange language.</p>
<p>JSON is built on two structures:</p>
<ul>
<li>A collection of name/value pairs. In various languages, this is realized as an&nbsp;<em>object</em>, record, struct, dictionary, hash table, keyed list, or associative array.</li>
<li>An ordered list of values. In most languages, this is realized as an&nbsp;<em>array</em>, vector, list, or sequence.</li>
</ul>
<p>These are universal data structures. Virtually all modern programming languages support them in one form or another. It makes sense that a data format that is interchangeable with programming languages also be based on these structures.</p><p>Address of the bookmark: <a href="http://json.org/" rel="nofollow">http://json.org/</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32483/cla-contig-layout-authenticator</guid>
	<pubDate>Fri, 05 May 2017 05:58:36 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32483/cla-contig-layout-authenticator</link>
	<title><![CDATA[CLA: Contig-Layout-Authenticator]]></title>
	<description><![CDATA[<p><span>To improve upon the shortcomings associated with the construction of draft genomes with Illumina paired-end sequencing, we developed Contig-Layout-Authenticator (CLA). The CLA pipeline can scaffold reference-sorted contigs based on paired reads, resulting in better assembled genomes. Moreover, CLA also hints at probable misassemblies and contaminations, for the users to cross-check before constructing the consensus draft. The CLA pipeline was designed and trained extensively on various bacterial genome datasets for the ordering and scaffolding of large repetitive contigs. The tool has been validated and compared favorably with other widely-used scaffolding and ordering tools using both simulated and real sequence datasets. CLA is a user friendly tool that requires a single command line input to generate ordered scaffolds.</span></p>
<p><span>Script&nbsp;https://sourceforge.net/projects/c-l-authenticator/files/</span></p><p>Address of the bookmark: <a href="http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0155459" rel="nofollow">http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0155459</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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