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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/44616?offset=390</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31881/gbtools-interactive-visualization-of-metagenome-bins-in-r</guid>
	<pubDate>Sun, 26 Mar 2017 15:41:31 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31881/gbtools-interactive-visualization-of-metagenome-bins-in-r</link>
	<title><![CDATA[gbtools: Interactive Visualization of Metagenome Bins in R]]></title>
	<description><![CDATA[<p><span>We have developed gbtools, a software package that allows users to visualize metagenomic assemblies by plotting coverage (sequencing depth) and GC values of contigs, and also to annotate the plots with taxonomic information. Different sets of annotations, including taxonomic assignments from conserved marker genes or SSU rRNA genes, can be imported simultaneously; users can choose which annotations to plot. Bins can be manually defined from plots, or be imported from third-party binning tools and overlaid onto plots, such that results from different methods can be compared side-by-side. gbtools reports summary statistics of bins including marker gene completeness, and allows the user to add or subtract bins with each other.&nbsp;</span></p>
<p><span>Tool at&nbsp;https://github.com/kbseah/genome-bin-tools</span></p><p>Address of the bookmark: <a href="http://journal.frontiersin.org/article/10.3389/fmicb.2015.01451/full" rel="nofollow">http://journal.frontiersin.org/article/10.3389/fmicb.2015.01451/full</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35252/hgt-finder-a-new-tool-for-horizontal-gene-transfer-finding-and-application-to-aspergillus-genomes</guid>
	<pubDate>Wed, 17 Jan 2018 05:03:19 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35252/hgt-finder-a-new-tool-for-horizontal-gene-transfer-finding-and-application-to-aspergillus-genomes</link>
	<title><![CDATA[HGT-Finder: A New Tool for Horizontal Gene Transfer Finding and Application to Aspergillus genomes]]></title>
	<description><![CDATA[<p><span>HGT-Finder: </span></p>
<p><span>(i) can be used for HGT detection in both prokaryotes and eukaryotes, </span></p>
<p><span>(ii) can report a statistical&nbsp;</span><em>P</em><span>&nbsp;value for each gene to indicate how likely it is to be horizontally transferred, and </span></p>
<p><span>(iii) is fully automated (requires minimal human intervention), as well as very easy to install and run.&nbsp;</span></p><p>Address of the bookmark: <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4626719/" rel="nofollow">https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4626719/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39380/mgert-mobile-genetic-elements-retrieving-tool</guid>
	<pubDate>Sat, 18 May 2019 08:58:01 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39380/mgert-mobile-genetic-elements-retrieving-tool</link>
	<title><![CDATA[MGERT: Mobile Genetic Elements Retrieving Tool]]></title>
	<description><![CDATA[<p><em>MGERT</em><span>&nbsp;is a computational pipeline for easy retrieving of MGE's coding sequences of a particular family from genome assemblies.&nbsp;</span><em>MGERT</em><span>&nbsp;utilizes several established bioinformatic tools combined into single pipeline which hides different technical quirks from an inexperienced user.</span></p><p>Address of the bookmark: <a href="https://github.com/andrewgull/MGERT" rel="nofollow">https://github.com/andrewgull/MGERT</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44487/r-package-for-pca-analysis</guid>
	<pubDate>Sun, 24 Mar 2024 20:06:24 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44487/r-package-for-pca-analysis</link>
	<title><![CDATA[R Package for PCA Analysis]]></title>
	<description><![CDATA[<p><span>An R package for performing principal component analysis (PCA) of genomics data. The package performs PCA, generates the publication-ready plots, and identifies population-specific outlier individuals. The package can be accessed on GitHub:&nbsp;https://github.com/Devashish13/PopulationStructure</span></p><p>Address of the bookmark: <a href="https://rpubs.com/Devashish13/PCAGenomics" rel="nofollow">https://rpubs.com/Devashish13/PCAGenomics</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/45249/from-dna-chaos-to-a-clear-microbial-story</guid>
	<pubDate>Fri, 21 Aug 2026 11:22:54 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/45249/from-dna-chaos-to-a-clear-microbial-story</link>
	<title><![CDATA[From DNA Chaos to a Clear Microbial Story]]></title>
	<description><![CDATA[<p>Imagine opening a metagenomic dataset and finding millions of DNA fragments, each carrying a tiny piece of information about the microbial world inside a sample. The challenge is not generating the data &mdash; it is turning that data into a meaningful story.</p><p>This is where MeTAline comes in.</p><p>MeTAline is a reproducible workflow designed to simplify shotgun metagenomic analysis. It brings together important steps such as quality control, host-DNA removal, taxonomic profiling and functional analysis, using tools including Kraken2, MetaPhlAn4 and HUMAnN.</p><p>What makes it especially useful is its ability to handle large datasets while keeping analyses organized and reproducible. Built with Snakemake and supporting containerized environments, MeTAline can also be used on high-performance computing systems.</p><p>In simple terms, MeTAline helps researchers move from millions of confusing DNA fragments to a clearer picture of who is there, what they might be doing, and what the data could mean.</p><p>Sometimes, the biggest challenge in science isn't collecting more data &mdash; it's finding the story hidden inside it.</p><p>Read more at&nbsp;https://academic.oup.com/nargab/article/7/4/lqaf158/8340158?login=false</p>]]></description>
	<dc:creator>BioStar</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/34141/rami-a-tool-for-identification-and-characterization-of-phylogenetic-clusters-in-microbial-communities</guid>
	<pubDate>Mon, 07 Aug 2017 18:49:27 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34141/rami-a-tool-for-identification-and-characterization-of-phylogenetic-clusters-in-microbial-communities</link>
	<title><![CDATA[RAMI: a tool for identification and characterization of phylogenetic clusters in microbial communities]]></title>
	<description><![CDATA[<p>RAMI, which clusters related nodes in a phylogenetic tree based on the patristic distance. RAMI also produces indices of cluster properties and other indices used in population and community studies on-the-fly.</p>
<p><strong>Availability:</strong>&nbsp;RAMI is licensed under GNU GPL and can be run or downloaded from&nbsp;<a href="http://www.acgt.se/online.html" target="">http://www.acgt.se/online.html</a>.</p><p>Address of the bookmark: <a href="https://academic.oup.com/bioinformatics/article-lookup/doi/10.1093/bioinformatics/btp051" rel="nofollow">https://academic.oup.com/bioinformatics/article-lookup/doi/10.1093/bioinformatics/btp051</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34594/synima-synteny-imaging-tool</guid>
	<pubDate>Sun, 10 Dec 2017 17:03:48 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34594/synima-synteny-imaging-tool</link>
	<title><![CDATA[Synima: Synteny Imaging tool]]></title>
	<description><![CDATA[<p><span>Synteny Imaging tool (Synima) written in Perl, which uses the graphical features of R. Synima takes orthologues computed from reciprocal best BLAST hits or OrthoMCL, and DAGchainer, and outputs an overview of genome-wide synteny in PDF. Each of these programs are included with the Synima package, and a pipeline for their use. Synima has a range of graphical parameters including size, colours, order, and labels, which are specified in a config file generated by the first run of Synima &ndash; and can be subsequently edited. Synima runs quickly on a command line to generate informative and publication quality figures. Synima is open source and freely available from&nbsp;</span><span><a href="https://github.com/rhysf/Synima"><span>https://github.com/rhysf/Synima</span></a></span><span>&nbsp;under the MIT License.</span></p><p>Address of the bookmark: <a href="https://github.com/rhysf/Synima" rel="nofollow">https://github.com/rhysf/Synima</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36271/heap-a-highly-sensitive-and-accurate-snp-detection-tool-for-low-coverage-high-throughput-sequencing-data</guid>
	<pubDate>Thu, 19 Apr 2018 08:06:03 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36271/heap-a-highly-sensitive-and-accurate-snp-detection-tool-for-low-coverage-high-throughput-sequencing-data</link>
	<title><![CDATA[Heap: a highly sensitive and accurate SNP detection tool for low-coverage high-throughput sequencing data]]></title>
	<description><![CDATA[<p><span>Heap, that enables robustly sensitive and accurate calling of SNPs, particularly with a low coverage NGS data, which must be aligned to the reference genome sequences in advance. To reduce false positive SNPs, Heap determines genotypes and calls SNPs at each site except for sites at the both end of reads or containing a minor allele supported by only one read. Performance comparison with existing tools showed that Heap achieved the highest F-scores with low coverage (7X) restriction-site associated DNA sequencing reads of sorghum and rice individuals. This will facilitate cost-effective GWAS and GP studies in this NGS era. Code and documentation of Heap are freely available from&nbsp;</span><a href="https://github.com/meiji-bioinf/heap">https://github.com/meiji-bioinf/heap</a><span>&nbsp;and our web site (</span><a href="http://bioinf.mind.meiji.ac.jp/lab/en/tools.html">http://bioinf.mind.meiji.ac.jp/lab/en/tools.html</a><span>).</span></p><p>Address of the bookmark: <a href="https://github.com/meiji-bioinf/heap" rel="nofollow">https://github.com/meiji-bioinf/heap</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36861/eagler-a-scaffolding-tool-for-long-reads</guid>
	<pubDate>Mon, 04 Jun 2018 05:26:03 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36861/eagler-a-scaffolding-tool-for-long-reads</link>
	<title><![CDATA[EAGLER: a scaffolding tool for long reads.]]></title>
	<description><![CDATA[<p>EAGLER is a scaffolding tool for long reads. The scaffolder takes as input a draft genome created by any NGS assembler and a set of long reads. The long reads are used to extend the contigs present in the NGS draft and possibly join overlapping contigs. EAGLER supports both PacBio and Oxford Nanopore reads.</p>
<p>The tool should be compatible with most UNIX flavors and has been successfully tested on the following operating systems:</p>
<ul>
<li>Mac OS X 10.11.1</li>
<li>Mac OS X 10.10.3</li>
<li>Ubuntu 14.04 LTS</li>
</ul>

https://bib.irb.hr/datoteka/844447.Diplomski_2015_Luka_terbi.pdf<p>Address of the bookmark: <a href="https://github.com/mculinovic/EAGLER" rel="nofollow">https://github.com/mculinovic/EAGLER</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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