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<channel>
	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/44208?offset=0</link>
	<atom:link href="https://bioinformaticsonline.com/related/44208?offset=0" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31714/krona</guid>
	<pubDate>Wed, 22 Mar 2017 04:47:35 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31714/krona</link>
	<title><![CDATA[Krona]]></title>
	<description><![CDATA[<p>Krona allows hierarchical data to be explored with zooming, multi-layered pie charts. Krona charts can be created using an <a href="https://github.com/marbl/Krona/wiki/ExcelTemplate">Excel template</a> or <a href="https://github.com/marbl/Krona/wiki/KronaTools">KronaTools</a>, which includes support for several bioinformatics tools and raw data formats. The interactive charts are self-contained and can be viewed with any modern web browser (see <a href="https://github.com/marbl/Krona/wiki/Browser%20support">Browser support</a>).</p>
<p><a href="http://marbl.github.io/Krona/img/screen_mgrast.png"><img src="https://camo.githubusercontent.com/27b71b1f1832523723c3d14dec764e7ad098438c/687474703a2f2f6d6172626c2e6769746875622e696f2f4b726f6e612f696d672f7468756d625f6d67726173742e706e67" width="210" height="167" alt="image" style="border: 0px;"></a></p><p>Address of the bookmark: <a href="https://github.com/marbl/Krona/wiki" rel="nofollow">https://github.com/marbl/Krona/wiki</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/44284/tools-for-geospatial-data-analysis</guid>
	<pubDate>Wed, 22 Mar 2023 02:10:28 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/44284/tools-for-geospatial-data-analysis</link>
	<title><![CDATA[Tools for Geospatial data analysis !]]></title>
	<description><![CDATA[<div><div><div><div><div><div><div><div><div><div><p>Geospatial data is becoming increasingly important in many fields, including urban planning, environmental science, public health, and more. These tools can help you work with data from a variety of sources, including satellite imagery, GPS data, and other forms of spatial data. They can help you visualize data, perform complex analysis, and even create maps and other visualizations.</p><p>The list includes some of the most popular and widely used geospatial tools available in Python. These tools can help you work with data from a variety of sources and in a variety of formats. Some of the tools are focused on visualization, such as Cartopy, Folium, and Contextily, which allow you to create interactive maps and other visualizations. Other tools are more focused on data manipulation and analysis, such as Fiona, GeoPandas, and Rasterio, which allow you to manipulate and analyze spatial data in a variety of ways.</p><p>The list also includes some tools for working with specific types of geospatial data. For example, the H3 library is designed specifically for working with hexagonal grids, while PySAL is focused on spatial econometrics and spatial analysis. Whether you are a data scientist, GIS specialist, or geospatial enthusiast, these tools are sure to enhance your work and help you achieve your goals.</p><p>In summary, this list is an excellent resource for anyone working with geospatial data in Python. It contains a wide range of tools for working with different types of data, and can help you visualize data, perform complex analysis, and create maps and other visualizations. If you're looking to enhance your skills in geospatial analysis, this list is definitely worth checking out.</p></div></div></div><div><p>These tools are:</p><ul>
<li>ArcGIS - <a href="https://lnkd.in/dgC6sKJH" target="_new">https://lnkd.in/dgC6sKJH</a></li>
<li>Cartopy - <a href="https://lnkd.in/dc8ijXRg" target="_new">https://lnkd.in/dc8ijXRg</a></li>
<li>Contextily - <a href="https://lnkd.in/dTdQsmKX" target="_new">https://lnkd.in/dTdQsmKX</a></li>
<li>Descartes - <a href="https://lnkd.in/dCJykxwW" target="_new">https://lnkd.in/dCJykxwW</a></li>
<li>Fiona - <a href="https://lnkd.in/d8sJ3Q5a" target="_new">https://lnkd.in/d8sJ3Q5a</a></li>
<li>Folium - <a href="https://lnkd.in/dfSsE-MB" target="_new">https://lnkd.in/dfSsE-MB</a></li>
<li>GDAL - <a href="https://lnkd.in/dYBJBaAY" target="_new">https://lnkd.in/dYBJBaAY</a></li>
<li>Geohash - <a href="https://lnkd.in/d_NxJ4_M" target="_new">https://lnkd.in/d_NxJ4_M</a></li>
<li>GeoJSON - <a href="https://lnkd.in/daGs2WYq" target="_new">https://lnkd.in/daGs2WYq</a></li>
<li>GeoPandas - <a href="https://lnkd.in/dBTFKKV3" target="_new">https://lnkd.in/dBTFKKV3</a></li>
<li>Geopy - <a href="https://lnkd.in/dfAzR8Xa" target="_new">https://lnkd.in/dfAzR8Xa</a></li>
<li>Gevent - <a href="http://www.gevent.org/" target="_new">http://www.gevent.org</a></li>
<li>H3 - <a href="https://h3geo.org/docs/" target="_new">https://h3geo.org/docs/</a></li>
<li>OSMnx - <a href="https://lnkd.in/dm3pHgUS" target="_new">https://lnkd.in/dm3pHgUS</a></li>
<li>PyQGIS - <a href="https://lnkd.in/dShWyWVr" target="_new">https://lnkd.in/dShWyWVr</a></li>
<li>PySAL - <a href="https://pysal.org/" target="_new">https://pysal.org</a></li>
<li>Pydeck - <a href="https://lnkd.in/dGBFu-iw" target="_new">https://lnkd.in/dGBFu-iw</a></li>
<li>Pyproj - <a href="https://lnkd.in/dNG9fdkm" target="_new">https://lnkd.in/dNG9fdkm</a></li>
<li>RTree - <a href="https://lnkd.in/dURMiYpU" target="_new">https://lnkd.in/dURMiYpU</a></li>
<li>Rasterio - <a href="https://lnkd.in/dEMC6ve6" target="_new">https://lnkd.in/dEMC6ve6</a></li>
<li>Scikit-mobility - <a href="https://lnkd.in/dpHhaX2J" target="_new">https://lnkd.in/dpHhaX2J</a></li>
<li>Shapely - <a href="https://lnkd.in/d568datK" target="_new">https://lnkd.in/d568datK</a></li>
</ul><p>These tools offer a wide range of capabilities for working with geospatial data, from visualizing and manipulating data to performing complex analysis and modeling. Whether you are a data scientist, GIS specialist, or geospatial enthusiast, these tools are sure to enhance your work and help you achieve your goals.</p></div></div></div></div></div></div></div></div>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40937/shinycircos-an-rshiny-application-for-interactive-creation-of-circos-plot</guid>
	<pubDate>Fri, 07 Feb 2020 03:26:58 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40937/shinycircos-an-rshiny-application-for-interactive-creation-of-circos-plot</link>
	<title><![CDATA[shinyCircos: an R/Shiny application for interactive creation of Circos plot]]></title>
	<description><![CDATA[<p><span>shinyCircos, a graphical user interface for interactive creation of Circos plot. shinyCircos can be easily installed either on computers for personal use or on local or public servers to provide online use to the community. Furthermore, various types of Circos plots could be easily generated and decorated with simple mouse-click.</span></p>
<p>Tutorial&nbsp;<a href="http://shinycircos.ncpgr.cn/shinyCircos_Help_Manual.pdf">http://shinycircos.ncpgr.cn/shinyCircos_Help_Manual.pdf</a></p>
<p>Github&nbsp;<a href="https://github.com/venyao/shinyCircos">https://github.com/venyao/shinyCircos</a></p><p>Address of the bookmark: <a href="http://150.109.59.144:3838/shinyCircos/" rel="nofollow">http://150.109.59.144:3838/shinyCircos/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27427/rcircos-an-r-package-for-circos-2d-track-plots</guid>
	<pubDate>Fri, 20 May 2016 11:01:13 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27427/rcircos-an-r-package-for-circos-2d-track-plots</link>
	<title><![CDATA[RCircos: an R package for Circos 2D track plots]]></title>
	<description><![CDATA[<p>RCircos package provides a simple and flexible way to make Circos 2D track plots with R and could be easily integrated into other R data processing and graphic manipulation pipelines for presenting large-scale multi-sample genomic research data. It can also serve as a base tool to generate complex Circos images.</p>
<p>More at https://bitbucket.org/henryhzhang/rcircos/src</p><p>Address of the bookmark: <a href="https://bitbucket.org/henryhzhang/rcircos/src" rel="nofollow">https://bitbucket.org/henryhzhang/rcircos/src</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36109/sankeynetwork-with-networkd3</guid>
	<pubDate>Fri, 06 Apr 2018 12:07:55 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36109/sankeynetwork-with-networkd3</link>
	<title><![CDATA[sankeyNetwork with networkD3]]></title>
	<description><![CDATA[<p><span>You can also create&nbsp;</span><a href="http://en.wikipedia.org/wiki/Sankey_diagram">Sankey diagrams</a><span>&nbsp;with&nbsp;</span><code>sankeyNetwork</code><span>. Here is an example using downloaded JSON data:</span></p>
<p><span>https://en.wikipedia.org/wiki/Sankey_diagram</span></p><p>Address of the bookmark: <a href="https://christophergandrud.github.io/networkD3/#sankey" rel="nofollow">https://christophergandrud.github.io/networkD3/#sankey</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/1182/installing-perl-gd-module</guid>
	<pubDate>Mon, 22 Jul 2013 14:02:01 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/1182/installing-perl-gd-module</link>
	<title><![CDATA[Installing Perl GD Module]]></title>
	<description><![CDATA[<div><p>In comparative genome analysis work, we usually compare more than two genomes and looks for syntenic regions amongst them. In my research I used Evolution Highway (RH) <a href="http://eh-demo.ncsa.uiuc.edu/">http://eh-demo.ncsa.uiuc.edu/</a>, which is a collaborative project designed to provide a visual means for simultaneously comparing genomes of multiple amniote species. The tool removes the burden of manually aligning these maps and allows cognitive skills to be used toward something more valuable than preparation and transformation of data. In addition to EH, attractive Circos (<a href="http://circos.ca/">http://circos.ca/</a>) is also very popular for this kind of analysis.</p><p>The EH is available online, and can be easily access and use, whereas Circos installation is not entirely straightforward. One of the most difficult parts of the installation involves installing the GD library. Since there weren't good instructions for installing this library on the internet I decided to post instructions here in case they are useful to anyone else.</p><p><strong>Following are the steps to install GD modules in Mac OS</strong><br /><br />1. Setup<br /><br />Create a folder for the files:<br /><br />$ mkdir -p /SourceCache<br />$ cd /SourceCache<br /><br />Get and unpack the required Jpeg-6b and GD libraries:<br />Download Jpeg-6b (<a href="http://code.google.com/p/google-desktop-for-linux-mirror/downloads/detail?name=jpeg-6b.tar.gz&amp;can=2&amp;q">http://code.google.com/p/google-desktop-for-linux-mirror/downloads/detail?name=jpeg-6b.tar.gz&amp;can=2&amp;q</a>)<br />Download GD (<a href="http://search.cpan.org/%7Elds/GD-2.46/">http://search.cpan.org/~lds/GD-2.46/</a>)<br /><br />Place the "tar.gz" files in "/SourceCache" and double click to unpack.<br /><br />2. Install libjpeg<br /><br />Copy the "config.sub" and "config.guess" files to "/SourceCache". Note that your "config.sub" and ""config.guess" files may be in a slightly different location. The commands below show where they were on my machine:<br /><br />$ cd /SourceCache/jpeg-6b/src<br />$ cp /usr/share/libtool/config/config.sub .<br />$ cp /usr/share/libtool/config/config.guess .<br /><br />Configure libjpeg as follows. Note that this was installed on a 64 bit machine. However, this method may configure it in a 32 bit format. This may not be the best way to configure the installation but it works.<br /><br />$ .configure --enable-shared<br />$ make<br /><br />Check to see if the following directories exist on your machine. Create the missing directories in the following manner:<br /><br />$ mkdir -p /usr/local/include<br />$ mkdir -p /usr/local/bin<br />$ mkdir -p /usr/local/lib<br />$ mkdir -p /usr/local/man/man1<br /><br />Finish making and installing libjpeg:<br /><br />$ make install<br /><br />3. Install GD<br /><br />$ cd /SourceCache/GD-2.46/GD/<br />$ perl Makefile.PL<br />$ make<br />$ make test (optional)<br />$ make html (optional)<br />$ make install</p><p><strong>Other way for Mac OS</strong><br />The easiest way to get a lot of these is with a program called Fink, which is similar in nature to the CPAN installer, but installs common GNU utilities. Fink is available from &lt;<a href="http://sourceforge.net/projects/fink/%3E">http://sourceforge.net/projects/fink/&gt;</a>.<br /><br />Follow the instructions for setting up Fink. Once it's installed, you'll want to run the following as root: fink install gd<br /><br />It will prompt you for a number of dependencies, type 'y' and hit enter to install all of the dependencies. Then watch it work.<br /><br />To prevent creating conflicts with the software that Apple installs by default, Fink creates its own directory tree at /sw where it installs most of the software that it installs. This means your libraries and headers for libgd will be at /sw/lib and /sw/include instead of /usr/lib and /usr/local/include. Because of these changed locations for the libraries, the Perl GD module will not install directly via CPAN, because it looks for the specific paths instead of getting them from your environment. But there's a way around that :-)<br /><br />Instead of typing "install GD" at the cpan&gt; prompt, type look GD. This should go through the motions of downloading the latest version of the GD module, then it will open a shell and drop you into the build directory. Apply below patch to the Makefile.PL file (save the patch into a file and use the command patch &lt; patchfile.)<br /><br />Then, run these commands to finish the installation of the GD module:<br /><br />perl Makefile.PL<br />make<br />make test<br />make install<br />And don't forget to run exit to get back to CPAN.</p><p>&nbsp;</p><p><strong>Install on MS Window, using PPM</strong></p><p>C:\Documents and Settings\Owner&gt;ppm<br />PPM interactive shell (2.2.0) - type 'help' for available commands.<br />PPM&gt; install GD<br />Install package 'GD?' (y/N): y<br />Installing package 'GD'...<br />Downloading <a href="http://ppm.ActiveState.com/PPMPackages/5.6plus/MSW">http://ppm.ActiveState.com/PPMPackages/5.6plus/MSW</a>. ...<br />Installing C:\Perl\site\lib\auto\GD\GD.bs<br />Installing C:\Perl\site\lib\auto\GD\GD.dll<br />Installing C:\Perl\site\lib\auto\GD\GD.exp<br />Installing C:\Perl\site\lib\auto\GD\GD.lib<br />Installing C:\Perl\html\site\lib\GD.html<br />Installing C:\Perl\site\lib\GD.pm<br />Installing C:\Perl\site\lib\qd.pl<br />Installing C:\Perl\site\lib\auto\GD\autosplit.ix<br />PPM&gt;<br /><br /><br />If you can't install it from ppm. You can download it:<br /><a href="http://ppm.ActiveState.com/PPMPackages/5.6plus/MSW">http://ppm.ActiveState.com/PPMPackages/5.6plus/MSW</a>.<br /><br /><br />BTW,All Perl 5.6.1 Modules are located at:<br /><br /><a href="http://ppm.ActiveState.com/PPMPackages/5.6plus/MSW">http://ppm.ActiveState.com/PPMPackages/5.6plus/MSW</a>.</p><p>&nbsp;</p><p><strong>Install the Perl GD Module on Linux</strong><br /><br />$ sudo perl -MCPAN -e shell<br /><br />Since it was the first time I had run this command on this particular machine I had to answer a lot of questions but simply selected the defaults for everything as this usually works for me. Once in the CPAN shell I entered<br /><br />$ install Bundle::CPAN<br /><br />and selected all of the defaults again. Once the CPAN bundle had finished installing I tried to install GD::Graph by typing<br /><br />$ install GD::Graph<br /><br />but it failed with hundreds of errors &ndash; the first of which was<br /><br />GD.xs:7:16: error: gd.h: No such file or directory<br /><br />This was fixed with the following apt-get command (in the bash shell)<br /><br />$ sudo apt-get install libgd2-xpm-dev<br /><br />back in the CPAN shell I still couldn&rsquo;t get GD::Graph to build and I guessed this was because of some left over files from the failed build. I don&rsquo;t know the command to clean things up inside the CPAN shell and am too lazy to read the docs so I simply went into the .cpan/build directory in my home directory and deleted anything that started with GD &ndash; eg<br /><br />$ rm -rf GD-2.35-HC_vkB<br /><br />$ rm -rf GDGraph-1.44-Evfibe<br /><br />and so on. Those strings at the end (VkB and so on) look random so they might be different on your machine. Then I went back into the CPAN shell and ran<br /><br />$ install GD::Graph<br /><br />There were a few dependencies which the script fetched and installed for me but everything worked smoothly.</p><p>Manual and other Perl Module instalation are mentioned in my previous blog @ <a href="http://bioinformaticsonline.com/blog/view/710/how-to-install-perl-modules-manually-using-cpan-command-and-other-quick-ways">http://bioinformaticsonline.com/blog/view/710/how-to-install-perl-modules-manually-using-cpan-command-and-other-quick-ways</a></p></div>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26319/n50plottingtools</guid>
	<pubDate>Mon, 08 Feb 2016 15:39:04 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26319/n50plottingtools</link>
	<title><![CDATA[n50PlottingTools]]></title>
	<description><![CDATA[<p><span>Tools to create plots showing N-statistics for genome assemblies </span></p>
<p><span>More at https://github.com/dentearl/n50PlottingTools</span></p><p>Address of the bookmark: <a href="https://github.com/dentearl/n50PlottingTools" rel="nofollow">https://github.com/dentearl/n50PlottingTools</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<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>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29635/r-graphs</guid>
	<pubDate>Fri, 04 Nov 2016 10:48:00 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29635/r-graphs</link>
	<title><![CDATA[R Graphs !!]]></title>
	<description><![CDATA[<p><span>The blog is a collection of script examples with example data and output plots. R produce excellent quality graphs for data analysis, science and business presentation, publications and other purposes. Self-help codes and examples are provided. Enjoy nice graphs !!</span></p><p>Address of the bookmark: <a href="http://rgraphgallery.blogspot.be/" rel="nofollow">http://rgraphgallery.blogspot.be/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30971/hiveplot</guid>
	<pubDate>Thu, 16 Feb 2017 11:39:34 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30971/hiveplot</link>
	<title><![CDATA[HivePlot]]></title>
	<description><![CDATA[<p>The&nbsp;<em>hive plot</em>&nbsp;is a rational visualization method for drawing networks. Nodes are mapped to and positioned on radially distributed linear axes &mdash; this mapping is based on network structural properties. Edges are drawn as curved links. Simple and interpretable.</p>
<p>The purpose of the hive plot is to establish a new baseline for visualization of large networks &mdash; a method that is both general and tunable and useful as a starting point in visually exploring network structure.</p>
<p>More at&nbsp;http://www.hiveplot.com/</p><p>Address of the bookmark: <a href="http://www.hiveplot.com/" rel="nofollow">http://www.hiveplot.com/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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