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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/40940?offset=370</link>
	<atom:link href="https://bioinformaticsonline.com/related/40940?offset=370" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/35351/sam-to-bam-conversion</guid>
	<pubDate>Fri, 26 Jan 2018 02:36:18 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/35351/sam-to-bam-conversion</link>
	<title><![CDATA[sam to bam conversion !!]]></title>
	<description><![CDATA[<p>To do sam to bam conversion, follow the following commands :-&nbsp;</p><div><div>Code:</div><pre dir="ltr">$ samtools view -b -S file.sam &gt; file.bam</pre></div><p>Then you will need to use&nbsp;<br /><br /></p><div><div>Code:</div><pre dir="ltr">$ samtools sort file.bam file-sorted</pre></div><p>followed by<br /><br /></p><div><div>Code:</div><pre dir="ltr">$ samtools index  file-sorted.bam</pre></div><p>in order to get an indexed file.<br /><br />If you just type&nbsp;<br /><br /></p><div><div>Code:</div><pre dir="ltr">$ samtools</pre></div><p>or samtools followed by the name of one of the samtools commands, you will get a few lines of help giving the correct syntax for that command,</p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39450/apollo-first-instantaneous-collaborative-genomic-annotation-editor-available-on-the-web</guid>
	<pubDate>Fri, 31 May 2019 19:55:39 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39450/apollo-first-instantaneous-collaborative-genomic-annotation-editor-available-on-the-web</link>
	<title><![CDATA[Apollo: First instantaneous, collaborative genomic annotation editor available on the Web]]></title>
	<description><![CDATA[<ul>
<li>Apollo is a plug-in for the&nbsp;<a href="http://jbrowse.org/">JBrowse</a>&nbsp;Genome Viewer.</li>
<li>In addition to genes and pseudogenes, users can annotate ncRNAs (snRNA, snoRNA, tRNA, rRNA), miRNAs, repeat regions, and transposable elements; each annotation type has its own configuration of the &lsquo;Information Editor&rsquo;.</li>
<li>History tracking with undo/redo functions is available.</li>
<li>Users are able to directly set an annotation to a specific state, choosing from the &lsquo;History&rsquo; display.</li>
<li>Adding and updating PubMed IDs will prompt users with a publication title to confirm their submission.</li>
<li>Gene Ontology (GO) terms are supported and GO ID auto-completion has been incorporated.</li>
<li>Users may access a &lsquo;Recent Changes&rsquo; page.</li>
<li>Help page with Apollo specific content is available.</li>
</ul><p>Address of the bookmark: <a href="http://genomearchitect.github.io/" rel="nofollow">http://genomearchitect.github.io/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/21241/pacman</guid>
	<pubDate>Mon, 16 Feb 2015 12:15:17 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/21241/pacman</link>
	<title><![CDATA[Pacman]]></title>
	<description><![CDATA[<p><span>The pacman package is an R package management tool that combines the functionality of base library related functions into intuitively named functions. This package is ideally added to .Rprofile to increase workflow by reducing time recalling obscurely named functions, reducing code and integrating functionality of base functions to simultaneously perform multiple actions.<br /><br />Function names in the pacman package follow the format of p_xxx where &lsquo;xxx&rsquo; is the task the function performs. For instance the p_load function allows the user to load one or more packages as a more generic substitute for the library or require functions and if the package isn&rsquo;t available locally it will install it for you.<br /><br /></span></p><p><strong>Installation</strong></p><p><span>To download the development version of pacman:</span></p><p><span>Download the </span><a href="https://github.com/trinker/pacman/zipball/master">zip ball</a><span> or </span><a href="https://github.com/trinker/pacman/tarball/master">tar ball</a><span>, decompress and run </span><code>R CMD INSTALL</code><span> on it, or use th</span><span>e </span><strong>devtools</strong><span> package to install the development version:</span></p><pre title="">## Make sure your current packages are up to date
update.packages()
## devtools is required
devtools::install_github("trinker/pacman")
</pre><p>Note: Windows users need <a href="http://www.murdoch-sutherland.com/Rtools/">Rtools</a> and <a href="http://CRAN.R-project.org/package=devtools">devtools</a> to install this way.</p><p>More at https://github.com/trinker/pacman</p><p>&nbsp;</p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27850/clusterprofiler</guid>
	<pubDate>Thu, 16 Jun 2016 18:57:03 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27850/clusterprofiler</link>
	<title><![CDATA[clusterProfiler]]></title>
	<description><![CDATA[<p>statistical analysis and visulization of functional profiles for genes and gene clusters<br><br>Bioconductor version: Release (3.3)<br><br>This package implements methods to analyze and visualize functional profiles (GO and KEGG) of gene and gene clusters.<br><br>Author: Guangchuang Yu &lt;guangchuangyu at gmail.com&gt; with contributions from Li-Gen Wang and Giovanni Dall'Olio.<br><br>Maintainer: Guangchuang Yu &lt;guangchuangyu at gmail.com&gt;<br><br>Citation (from within R, enter citation("clusterProfiler")):<br><br>Yu G, Wang L, Han Y and He Q (2012). &ldquo;clusterProfiler: an R package for comparing biological themes among gene clusters.&rdquo; OMICS: A Journal of Integrative Biology, 16(5), pp. 284-287.<br>Installation<br><br>To install this package, start R and enter:<br><br>## try http:// if https:// URLs are not supported<br>source("https://bioconductor.org/biocLite.R")<br>biocLite("clusterProfiler")</p>
<p>https://www.bioconductor.org/packages/devel/bioc/vignettes/clusterProfiler/inst/doc/clusterProfiler.html</p><p>Address of the bookmark: <a href="https://www.bioconductor.org/packages/devel/bioc/vignettes/clusterProfiler/inst/doc/clusterProfiler.html" rel="nofollow">https://www.bioconductor.org/packages/devel/bioc/vignettes/clusterProfiler/inst/doc/clusterProfiler.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41169/instructions-for-creating-your-own-r-package</guid>
	<pubDate>Wed, 19 Feb 2020 01:22:48 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41169/instructions-for-creating-your-own-r-package</link>
	<title><![CDATA[Instructions for Creating Your Own R Package]]></title>
	<description><![CDATA[<p>The following is a step-by-step guide to creating your own R package.&nbsp; Even beyond this course, youmay find this useful for storing functions you create for your own research or for editing existingR packages to suit your needs.</p>
<p>This guide contains three different sets of instructions.&nbsp; If you use RStudio, you can follow the &ldquo;Ba-sic Instructions&rdquo; in Section 2 which involve using RStudio&rsquo;s interface.&nbsp; </p><p>Address of the bookmark: <a href="http://web.mit.edu/insong/www/pdf/rpackage_instructions.pdf" rel="nofollow">http://web.mit.edu/insong/www/pdf/rpackage_instructions.pdf</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35437/dupradar-package</guid>
	<pubDate>Sun, 04 Feb 2018 14:28:57 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35437/dupradar-package</link>
	<title><![CDATA[dupRadar package]]></title>
	<description><![CDATA[<p><span>The&nbsp;</span><em>dupRadar</em><span>&nbsp;package gives an insight into the duplication problem by graphically relating the gene expression level and the duplication rate present on it. Thus, failed experiments can be easily identified at a glance</span></p><p>Address of the bookmark: <a href="https://bioconductor.org/packages/3.7/bioc/vignettes/dupRadar/inst/doc/dupRadar.html" rel="nofollow">https://bioconductor.org/packages/3.7/bioc/vignettes/dupRadar/inst/doc/dupRadar.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38420/regioner-an-r-package-for-the-management-and-comparison-of-genomic-regions</guid>
	<pubDate>Tue, 11 Dec 2018 08:43:51 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38420/regioner-an-r-package-for-the-management-and-comparison-of-genomic-regions</link>
	<title><![CDATA[regioneR: an R package for the management and comparison of genomic regions]]></title>
	<description><![CDATA[<p><span>Regioner is an R package for the management and comparison of genomic regions. It offers a set of function for basic manipulation of region sets extending the functionality of GenomicRanges and a powerful and customizable permutation test framework. With it, it's possible to study the association of a set of regions with other sets of regions, functions defined over the genome or essentially any user defined function.</span></p>
<p><span>http://gattaca.imppc.org/regioner/</span></p><p>Address of the bookmark: <a href="http://gattaca.imppc.org/regioner/" rel="nofollow">http://gattaca.imppc.org/regioner/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39244/chromomap-an-r-package-for-interactive-visualization-and-annotation-of-chromosomes</guid>
	<pubDate>Fri, 12 Apr 2019 05:30:41 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39244/chromomap-an-r-package-for-interactive-visualization-and-annotation-of-chromosomes</link>
	<title><![CDATA[chromoMap-An R package for Interactive Visualization and Annotation of Chromosomes]]></title>
	<description><![CDATA[<p>Provides interactive, configurable and elegant graphics visualization of the chromosomes or chromosome regions of any living organism allowing users to map chromosome elements (like genes, SNPs etc.) on the chromosome plot. It introduces a special plot viz. the "chromosome heatmap" that, in addition to mapping elements, can visualize the data associated with chromosome elements (like gene expression) in the form of heat colors which can be highly advantageous in the scientific interpretations and research work. The package provide multiple features like visualizing multiple sets, chromosome heat-maps, group annotations, adding hyperlinks, and labelling. The plots can be saved as HTML documents that can be customized and shared easily. In addition, you can include them in R Markdown or in R 'Shiny' applications.</p><p>Address of the bookmark: <a href="https://cran.r-project.org/web/packages/chromoMap/vignettes/chromoMap.html" rel="nofollow">https://cran.r-project.org/web/packages/chromoMap/vignettes/chromoMap.html</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41006/netgo-r-shiny-package-for-network-integrated-pathway-enrichment-analysis</guid>
	<pubDate>Wed, 12 Feb 2020 12:40:54 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41006/netgo-r-shiny-package-for-network-integrated-pathway-enrichment-analysis</link>
	<title><![CDATA[netGO: R-Shiny package for network-integrated pathway enrichment analysis]]></title>
	<description><![CDATA[<p>netGO is an R/Shiny package for network-integrated pathway enrichment analysis.<br>netGO provides user-interactive visualization of enrichment analysis results and related networks.</p>
<p>Currently, netGO supports analysis for four species (<em><a href="https://github.com/unistbig/netGO-Data/tree/master/Human">Human</a>,&nbsp;<a href="https://github.com/unistbig/netGO-Data/tree/master/Mouse">Mouse</a>,&nbsp;<a href="https://github.com/unistbig/netGO-Data/tree/master/Arabidopsis">Arabidopsis thaliana</a>,and&nbsp;<a href="https://github.com/unistbig/netGO-Data/tree/master/Yeast">Yeast</a></em>)<br>These data are available from&nbsp;<a href="https://github.com/unistbig/netGO-Data">netGO-Data</a>&nbsp;repository.</p>
<p><a href="https://academic.oup.com/bioinformatics/advance-article/doi/10.1093/bioinformatics/btaa077/5728635">https://academic.oup.com/bioinformatics/advance-article/doi/10.1093/bioinformatics/btaa077/5728635</a></p><p>Address of the bookmark: <a href="https://github.com/unistbig/netGO" rel="nofollow">https://github.com/unistbig/netGO</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42299/platypus-%E2%80%93-r-package-for-object-detection-and-image-segmentation</guid>
	<pubDate>Mon, 09 Nov 2020 02:56:25 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42299/platypus-%E2%80%93-r-package-for-object-detection-and-image-segmentation</link>
	<title><![CDATA[Platypus – R package for object detection and image segmentation.]]></title>
	<description><![CDATA[<p><a href="https://github.com/maju116/platypus" target="_blank">platypus</a>&nbsp;is an R package for object detection and semantic segmentation. Currently using&nbsp;</p>
<div>platypus&nbsp;you can perform:</div>
<ul>
<li>multi-class semantic segmentation using&nbsp;U-Net&nbsp;architecture</li>
<li>multi-class object detection using&nbsp;YOLOv3&nbsp;architecture</li>
</ul>
<p>You can install the latest version of&nbsp;platypus&nbsp;with&nbsp;remotes&nbsp;package:</p>
<div>
<div>
<div>
<div>remotes::install_github("maju116/platypus")</div>
</div>
</div>
</div>
<p>Note that in order to install&nbsp;platypus&nbsp;you need to install&nbsp;keras&nbsp;and&nbsp;tensorflow&nbsp;packages and&nbsp;Tensorflow&nbsp;version&nbsp;&gt;= 2.0.0&nbsp;(&nbsp;Tensorflow 1.x&nbsp;will not be supported!)</p><p>Address of the bookmark: <a href="https://github.com/maju116/platypus" rel="nofollow">https://github.com/maju116/platypus</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>

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