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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/39441?offset=270</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26322/liftover</guid>
	<pubDate>Mon, 08 Feb 2016 15:45:03 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26322/liftover</link>
	<title><![CDATA[liftover]]></title>
	<description><![CDATA[<p><span>Convenient conversions between genome assemblie.&nbsp;The liftover package makes it easy to remap genomic coordinates to a different genome assembly. </span></p>
<p><span>More at https://github.com/aaronwolen/liftover<br></span></p>
<p><span>https://www.bioconductor.org/help/workflows/liftOver/</span></p><p>Address of the bookmark: <a href="https://github.com/aaronwolen/liftover" rel="nofollow">https://github.com/aaronwolen/liftover</a></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27113/picard</guid>
	<pubDate>Fri, 29 Apr 2016 08:21:54 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27113/picard</link>
	<title><![CDATA[Picard]]></title>
	<description><![CDATA[<p>Picard is a set of command line tools for manipulating high-throughput sequencing (HTS) data and formats such as SAM/BAM/CRAM and VCF. These file formats are defined in the <a href="http://samtools.github.io/hts-specs/">Hts-specs</a> repository. See especially the <a href="http://samtools.github.io/hts-specs/SAMv1.pdf">SAM specification</a> and the <a href="http://samtools.github.io/hts-specs/VCFv4.3.pdf">VCF specification</a>.</p>
<p>Note that the information on this page is targeted at end-users. For developers, the source code, building instructions and implementation/development resources are available on <a href="https://github.com/broadinstitute/picard">GitHub</a>.</p>
<p>The Picard toolkit is open-source under the <a href="https://tldrlegal.com/license/mit-license">MIT license</a> and free for all uses.</p>
<p>Enjoy!</p><p>Address of the bookmark: <a href="http://broadinstitute.github.io/picard/" rel="nofollow">http://broadinstitute.github.io/picard/</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27110/easyfig</guid>
	<pubDate>Fri, 29 Apr 2016 05:49:39 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27110/easyfig</link>
	<title><![CDATA[Easyfig]]></title>
	<description><![CDATA[<p>Easyfig has moved to github, for newer releases of Easyfig please visit our new webpage - https://mjsull.github.io/Easyfig.&nbsp; Easyfig is a Python application for creating linear comparison figures of multiple genomic loci with an easy-to-use graphical user interface (GUI).</p>
<p>More at http://easyfig.sourceforge.net/</p><p>Address of the bookmark: <a href="http://easyfig.sourceforge.net/" rel="nofollow">http://easyfig.sourceforge.net/</a></p>]]></description>
	<dc:creator>Poonam Mahapatra</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26968/scalce</guid>
	<pubDate>Fri, 15 Apr 2016 05:09:51 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26968/scalce</link>
	<title><![CDATA[SCALCE]]></title>
	<description><![CDATA[<p><span>SCALCE (</span><code>/skeɪlz/</code><span>, a.k.a. boosting&nbsp;</span><span style="text-decoration: underline;">S</span><span>equence&nbsp;</span><span style="text-decoration: underline;">C</span><span>ompression&nbsp;</span><span style="text-decoration: underline;">A</span><span>lgorithms using&nbsp;</span><span style="text-decoration: underline;">L</span><span>ocally&nbsp;</span><span style="text-decoration: underline;">C</span><span>onsistent</span><span style="text-decoration: underline;">E</span><span>ncoding) is a tool for compressing FASTQ files. It is designed specifically for the Illumina-generated FASTQ files, but supports any valid FASTQ with consistent read lengths.&nbsp;</span></p>
<p><span>More at&nbsp;http://sfu-compbio.github.io/scalce/</span></p><p>Address of the bookmark: <a href="http://sfu-compbio.github.io/scalce/" rel="nofollow">http://sfu-compbio.github.io/scalce/</a></p>]]></description>
	<dc:creator>Surabhi Chaudhary</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27035/spades</guid>
	<pubDate>Tue, 19 Apr 2016 08:37:08 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27035/spades</link>
	<title><![CDATA[SPAdes]]></title>
	<description><![CDATA[<p>SPAdes &ndash; St. Petersburg genome assembler &ndash; is intended for both standard isolates and single-cell MDA bacteria assemblies. This manual will help you to install and run SPAdes. SPAdes version 3.7.1 was released under GPLv2 on March 8, 2016 and can be downloaded from <a href="http://bioinf.spbau.ru/en/spades" target="_blank">http://bioinf.spbau.ru/en/spades</a>.</p>
<p>Manual at http://spades.bioinf.spbau.ru/release3.7.1/manual.html</p><p>Address of the bookmark: <a href="http://bioinf.spbau.ru/spades" rel="nofollow">http://bioinf.spbau.ru/spades</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27078/homer-software-for-motif-discovery-and-next-gen-sequencing-analysis</guid>
	<pubDate>Tue, 26 Apr 2016 03:48:23 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27078/homer-software-for-motif-discovery-and-next-gen-sequencing-analysis</link>
	<title><![CDATA[HOMER:  Software for motif discovery and next-gen sequencing analysis]]></title>
	<description><![CDATA[<p><span>This tutorial covers topics independently of HOMER, and represents knowledge which is important to know before diving head first into more advanced analysis tools such as HOMER.</span></p>
<ol>
<li><a href="http://homer.salk.edu/homer/basicTutorial/computerSetup.html">Setting up your computing environment</a></li>
<li><a href="http://homer.salk.edu/homer/basicTutorial/retrieveFiles.html">Retrieving and storing sequencing files</a>&nbsp;(your own data or from public sources)</li>
<li><a href="http://homer.salk.edu/homer/basicTutorial/fastqFiles.html">Checking sequence quality, trimming, general sequence manipulation</a></li>
<li><a href="http://homer.salk.edu/homer/basicTutorial/mapping.html">Mapping reads to a reference genome</a></li>
<li><a href="http://homer.salk.edu/homer/basicTutorial/samfiles.html">Manipulating SAM/BAM alignment files</a></li>
<li><a href="http://homer.salk.edu/homer/basicTutorial/genomeBrowsers.html">Visualizing data in a genome browser</a></li>
</ol>
<p><br>RNA-Seq</p>
<ol>
<li><a href="http://homer.salk.edu/homer/basicTutorial/rnaseqCufflinks.html">De novo transcript discovery and differential analysis with Cufflinks</a></li>
<li><a href="http://homer.salk.edu/homer/basicTutorial/rnaseqR.html">Differential expression analysis with R/Bioconductor</a></li>
<li><a href="http://homer.salk.edu/homer/basicTutorial/clustering.html">Clustering of large expression datasets (microarray or RNA-Seq)</a></li>
</ol>
<p><br><span>Microarray</span></p>
<ol>
<li><a href="http://homer.salk.edu/homer/basicTutorial/affymetrix.html">Basic analysis of Affymetrix Gene Expression Arrays using R/Bioconductor</a></li>
</ol>
<p><span>General Tips for Data Analysis</span></p>
<ol>
<li><a href="http://homer.salk.edu/homer/basicTutorial/excelTips.html">Excel workarounds, adding gene annotation, X-Y plots tips, etc.</a></li>
</ol><p>Address of the bookmark: <a href="http://homer.salk.edu/homer/basicTutorial/" rel="nofollow">http://homer.salk.edu/homer/basicTutorial/</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27094/smash-an-alignment-free-method-to-find-and-visualise-rearrangements-between-pairs-of-dna-sequences</guid>
	<pubDate>Tue, 26 Apr 2016 12:18:49 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27094/smash-an-alignment-free-method-to-find-and-visualise-rearrangements-between-pairs-of-dna-sequences</link>
	<title><![CDATA[Smash: An alignment-free method to find and visualise rearrangements between pairs of DNA sequences]]></title>
	<description><![CDATA[<p><strong>Smash is a completely alignment-free method/tool to find and visualise genomic rearrangements</strong><span>. The detection is based on&nbsp;</span><strong>conditional exclusive compression</strong><span>, namely using a FCM (Markov model), of high context order (typically 20). For visualisation, Smash outputs a&nbsp;</span><strong>SVG image</strong><span>, with an&nbsp;</span><strong>ideogram</strong><span>output architecture, where the patterns are represented with several&nbsp;</span><strong>HSV values</strong><span>&nbsp;(only value varies). The method can perform both in small- and large-scale. Nevertheless is more directed to large-scale since that the main aim of the research is to&nbsp;</span><strong>know where the large-scale [chromosomal by chromosome] of several primates was equal/different, having at a glance a map of the entire genomes</strong><span>.</span></p><p>Address of the bookmark: <a href="http://bioinformatics.ua.pt/software/smash/" rel="nofollow">http://bioinformatics.ua.pt/software/smash/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27323/cutadapt</guid>
	<pubDate>Fri, 13 May 2016 04:54:50 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27323/cutadapt</link>
	<title><![CDATA[cutadapt]]></title>
	<description><![CDATA[<p>Cutadapt finds and removes adapter sequences, primers, poly-A tails and other types of unwanted sequence from your high-throughput sequencing reads.</p>
<p>Cleaning your data in this way is often required: Reads from small-RNA sequencing contain the 3&rsquo; sequencing adapter because the read is longer than the molecule that is sequenced. Amplicon reads start with a primer sequence. Poly-A tails are useful for pulling out RNA from your sample, but often you don&rsquo;t want them to be in your reads.</p>
<p>Cutadapt helps with these trimming tasks by finding the adapter or primer sequences in an error-tolerant way. It can also modify and filter reads in various ways. Adapter sequences can contain IUPAC wildcard characters. Also, paired-end reads and even colorspace data is supported. If you want, you can also just demultiplex your input data, without removing adapter sequences at all.</p>
<p>Cutadapt comes with an extensive suite of automated tests and is available under the terms of the MIT license.</p>
<p>If you use cutadapt, please cite <a href="http://dx.doi.org/10.14806/ej.17.1.200">DOI:10.14806/ej.17.1.200</a> .</p><p>Address of the bookmark: <a href="https://cutadapt.readthedocs.io/en/stable/installation.html#quickstart" rel="nofollow">https://cutadapt.readthedocs.io/en/stable/installation.html#quickstart</a></p>]]></description>
	<dc:creator>Radha Agarkar</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/35418/karyoploter-plot-whole-genomes-with-arbitrary-data</guid>
	<pubDate>Fri, 02 Feb 2018 03:24:28 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35418/karyoploter-plot-whole-genomes-with-arbitrary-data</link>
	<title><![CDATA[karyoploteR: plot whole genomes with arbitrary data]]></title>
	<description><![CDATA[<p><span><a href="http://bioconductor.org/packages/karyoploteR">karyoploteR</a></span><span>&nbsp;is an R package to create karyoplots, that is, representations of whole genomes with arbitrary data plotted on them. It is inspired by the R base graphics system and does not depend on other graphics packages. The aim of karyoploteR is to offer the user an easy way to plot data along the genome to get broad genome-wide view to facilitate the identification of genome wide relations and distributions.</span></p><p>Address of the bookmark: <a href="https://bernatgel.github.io/karyoploter_tutorial/" rel="nofollow">https://bernatgel.github.io/karyoploter_tutorial/</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>

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