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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/37820?offset=90</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29008/circos-visualize</guid>
	<pubDate>Fri, 02 Sep 2016 08:29:26 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29008/circos-visualize</link>
	<title><![CDATA[CIRCOS Visualize !!]]></title>
	<description><![CDATA[<p>Before uploading a data file, check the&nbsp;<a href="http://mkweb.bcgsc.ca/tableviewer/samples">samples gallery</a>&nbsp;to make sure that your data format is compatible.</p>
<ul>
<li>Your file must be&nbsp;<strong>plain text</strong>.</li>
<li>Your data values must be&nbsp;<strong>non-negative integers</strong>.</li>
<li>Data must be space-separated (<strong>one or more</strong>&nbsp;tab or space, which will be collapsed).</li>
<li>No two rows or columns may have the same name.</li>
<li>Column and row names must&nbsp;<strong>begin with a letter</strong>&nbsp;(e.g. 'A', 'A0', 'A-0') and can only contain letters, numbers and _. No punctuation!</li>
<li>Maximum row + column total is 150 &mdash; if exceeded, rows and columns are limited to 75.</li>
<li>If you are using order, size and color rows/columns in combination they must appear in that order.</li>
</ul>
<p>Need help? Post questions to the&nbsp;<a href="https://groups.google.com/forum/#!forum/circos-data-visualization">Circos Google Group</a>.</p>
<p>http://mkweb.bcgsc.ca/tableviewer/visualize/</p><p>Address of the bookmark: <a href="http://mkweb.bcgsc.ca/tableviewer/visualize/" rel="nofollow">http://mkweb.bcgsc.ca/tableviewer/visualize/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29112/sybil</guid>
	<pubDate>Wed, 07 Sep 2016 03:20:44 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29112/sybil</link>
	<title><![CDATA[Sybil]]></title>
	<description><![CDATA[<p><span>The Sybil software package provides a primarily web-based front-end to comparative genome datasets warehoused in a chado relational database. It was developed by the bioinformatics department at The Institute for Genomic Research (</span><a href="http://www.tigr.org/">TIGR</a><span>) and development continues at the J. Craig Venter Institute (</span><a href="http://jcvi.org/">JCVI</a><span>) and the Institute for Genome Sciences (</span><a href="http://igs.umaryland.edu/">IGS</a><span>) at the University of Maryland: Baltimore. Sybil has been used at TIGR/JCVI, IGS, NYU, New York Medical College, Novartis Vaccines and University of Maryland: College Park to support a number of research projects that involve comparative genome analysis. The following sections provide some high-level technical details about the overall architecture and external dependencies of the Sybil package.</span></p><p>Address of the bookmark: <a href="http://sybil.sourceforge.net/" rel="nofollow">http://sybil.sourceforge.net/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29382/virmet</guid>
	<pubDate>Mon, 10 Oct 2016 08:27:19 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29382/virmet</link>
	<title><![CDATA[VirMet]]></title>
	<description><![CDATA[<p>Watch out: only a few files are counted in coverage statistics.</p>
<p>Full documentation on&nbsp;<a href="http://virmet.rtfd.org/en/latest/">Read the Docs</a>.</p>
<p>A set of tools for viral metagenomics.</p>
<p>virmet is called with a command subcommand syntax:&nbsp;<code>virmet fetch --viral n</code>, for example, downloads the bacterial database. Other available subcommands so far are</p>
<ul>
<li><code>fetch</code>&nbsp;download genomes</li>
<li><code>update</code>&nbsp;update viral/bacterial database</li>
<li><code>index</code>&nbsp;index genomes</li>
<li><code>wolfpack</code>&nbsp;analyze a Miseq run</li>
<li><code>covplot</code>&nbsp;plot coverage for a specific organism</li>
</ul>
<p>A short help is obtained with&nbsp;<code>virmet subcommand -h</code>.</p>
<p>More at&nbsp;https://github.com/ozagordi/VirMet</p><p>Address of the bookmark: <a href="https://github.com/ozagordi/VirMet" rel="nofollow">https://github.com/ozagordi/VirMet</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29628/links</guid>
	<pubDate>Fri, 04 Nov 2016 06:19:01 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29628/links</link>
	<title><![CDATA[LINKS]]></title>
	<description><![CDATA[<p>LINKS is a genomics application for scaffolding genome assemblies with long reads, such as those produced by Oxford Nanopore Technologies Ltd. It can be used to scaffold high-quality draft genome assemblies with any long sequences (eg. ONT reads, PacBio reads, another draft genomes, etc)</p>
<p>Paper at&nbsp;https://gigascience.biomedcentral.com/articles/10.1186/s13742-015-0076-3</p><p>Address of the bookmark: <a href="https://github.com/warrenlr/LINKS/" rel="nofollow">https://github.com/warrenlr/LINKS/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/file/view/29654/randomness-and-probability</guid>
	<pubDate>Tue, 08 Nov 2016 07:17:32 -0600</pubDate>
	<link>https://bioinformaticsonline.com/file/view/29654/randomness-and-probability</link>
	<title><![CDATA[Randomness and Probability]]></title>
	<description><![CDATA[<p>Randomness and Probability</p><p>Randomness and probability are two differnet concepts: probaility is a measure (according to measure theory) which measures the randomness. Randomness is the object to be measured by probability.&nbsp;For example, probability is a mapping from randomness to the real number between 0 and 1. The similar examples are that the entropy measures the uncertanity; product of length and width measures the area of rectangle etc.</p><p><strong>Please see &ldquo;A mathematical theory of ability measure&rdquo; by N. Kong ets for more examples to answer&nbsp;this question.</strong></p>]]></description>
	<dc:creator>Jit</dc:creator>
	<enclosure url="https://bioinformaticsonline.com/file/download/29654" length="598559" type="application/pdf" />
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29693/bioistats-online-course</guid>
	<pubDate>Thu, 10 Nov 2016 04:22:51 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29693/bioistats-online-course</link>
	<title><![CDATA[Bioistats Online course]]></title>
	<description><![CDATA[<p><span>One of our primary focuses will be to develop an understanding of the various ways in which we can assign a probability to some chance event. We'll also learn the&nbsp;</span><strong>fundamental&nbsp;</strong><span><strong>properties of probability</strong>, investigate how probability behaves, and learn how to calculate the probability of a new chance event.</span></p>
<p><span>This book is handy understanding basic concepts.</span></p><p>Address of the bookmark: <a href="https://onlinecourses.science.psu.edu/stat414/node/287" rel="nofollow">https://onlinecourses.science.psu.edu/stat414/node/287</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30002/excavator2tool</guid>
	<pubDate>Wed, 30 Nov 2016 04:09:19 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30002/excavator2tool</link>
	<title><![CDATA[EXCAVATOR2tool]]></title>
	<description><![CDATA[<p><span>EXCAVATOR2 is a collection of bash, R and Fortran scripts and codes that analyses Whole Exome Sequencing (WES) data to identify CNVs. EXCAVATOR2 enhances the identification of all genomic CNVs, both overlapping and non-overlapping targeted exons by integrating the analysis of In-targets and Off- targets reads. Specifically, it improves the precision of calling CNVs overlapping targeted exons from WES data and enlarges the spectrum of detectable CNVs to off-target events.</span><br><span>EXCAVATOR2 can be effectively employed for the identification of CNVs in small as well as large-scale re-sequencing population and cancer studies. Lastly, it&rsquo;s of particular interest that all WES experiments can be re-analysed using our method with the beneficial effect to identify novelCNVs in extra-exonic regions by having the full-genome CN profile.</span></p><p>Address of the bookmark: <a href="https://sourceforge.net/projects/excavator2tool/" rel="nofollow">https://sourceforge.net/projects/excavator2tool/</a></p>]]></description>
	<dc:creator>Bulbul</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/bookmarks/view/30130/scaffmatch</guid>
	<pubDate>Tue, 13 Dec 2016 10:23:56 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30130/scaffmatch</link>
	<title><![CDATA[ScaffMatch]]></title>
	<description><![CDATA[<p>caffMatch is a novel scaffolding tool based on Maximum-Weight Matching able to produce high-quality scaffolds from NGS data (reads and contigs). The tool is written in Python 2.7. It also includes a bash script wrapper that calls aligner in case one needs to first map reads to contigs (instead of providing .sam files).</p>
<p>The arguments accepted by ScaffMatch are:</p>
<p>&nbsp; -w) Working directory -- this is the directory where ScaffMatch files are stored. These are .sam files produced after mapping reads to contigs and the resulting scaffolds file `scaffolds.fa` fasta file;</p>
<p>&nbsp; -c) Contig fasta file;</p>
<p>&nbsp; -m) Command line argument with no options. It is used when .sam files are used instead of reads .fastq files. Do not use this option if you provide reads files;</p>
<p>&nbsp; -1) (Comma separated list of) either .fastq or .sam file(s) corresponding to the first read of the read pair;</p>
<p>&nbsp; -2) (Comma separated list of) either .fastq or .sam file(s) corresponding to the second read of the read pair;</p>
<p>&nbsp; -i) (Comma separated list of) insert size(s) of the library(-ies);</p>
<p>&nbsp; -s) (Comma separated list of) library(-ies) standard deviation(s) of insert size(s);</p>
<p>&nbsp; -t) Bundle threshold. Pairs of contigs supported by number of read pairs less than the value of this argument are discarded. Optional argument, by default it is equal to 5;</p>
<p>&nbsp; -g) Matching heuristics: use `max_weight` for Maximum Weight Matching heuristics with the Insertion step, use `backbone` for Maximum Weight Matching heuristics without the Insertion step, use `greedy` for Greedy Matching heuristics;</p>
<p>&nbsp; -l) Log file - where to store the logs. Optional argument. By default, stdout is used.</p><p>Address of the bookmark: <a href="http://alan.cs.gsu.edu/NGS/?q=content/scaffmatch" rel="nofollow">http://alan.cs.gsu.edu/NGS/?q=content/scaffmatch</a></p>]]></description>
	<dc:creator>Jit</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>

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