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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/42035?offset=20</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38579/genomeview-genome-browser-and-annotation-editor</guid>
	<pubDate>Wed, 02 Jan 2019 04:09:06 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38579/genomeview-genome-browser-and-annotation-editor</link>
	<title><![CDATA[GenomeView: genome browser and annotation editor]]></title>
	<description><![CDATA[<p><span>GenomeView is a genome browser and annotation editor that displays reference sequence, annotation, multiple alignments, short read alignments and graphs. Most major data formats are supported. Local and internet files can be loaded.</span><br><span>This project has moved to GitHub:&nbsp;</span><a href="https://github.com/GenomeView/genomeview" target="_blank">https://github.com/GenomeView/genomeview</a></p><p>Address of the bookmark: <a href="https://sourceforge.net/projects/genomeview/" rel="nofollow">https://sourceforge.net/projects/genomeview/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39869/mfannot-a-program-for-the-annotation-of-mitochondrial-and-plastid-genomes</guid>
	<pubDate>Mon, 26 Aug 2019 11:47:56 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39869/mfannot-a-program-for-the-annotation-of-mitochondrial-and-plastid-genomes</link>
	<title><![CDATA[MFannot : a program for the annotation of mitochondrial and plastid genomes]]></title>
	<description><![CDATA[<p><span>MFannot is a program for the annotation of mitochondrial and plastid genomes</span></p>
<p>MFannot is a program for the annotation of mitochondrial and plastid genomes. It is a PERL wrapper around a set of diverse, external independent tools.</p>
<p>It makes intense use of RNA/intron detection tools including&nbsp;<a href="http://hmmer.org/">HMMER</a>,&nbsp;<a href="https://github.com/nathanweeks/exonerate">Exonerate</a>,&nbsp;<a href="https://bioinformatics.ca/links_directory/tool/9822/erpin">Erpin</a>&nbsp;and others.</p>
<p><a href="http://megasun.bch.umontreal.ca/cgi-bin/mfannot/mfannotInterface.pl">http://megasun.bch.umontreal.ca/cgi-bin/mfannot/mfannotInterface.pl</a></p><p>Address of the bookmark: <a href="https://github.com/BFL-lab/Mfannot" rel="nofollow">https://github.com/BFL-lab/Mfannot</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41602/nucdiff-in-depth-characterization-and-annotation-of-differences-between-two-sets-of-dna-sequences</guid>
	<pubDate>Tue, 05 May 2020 10:35:48 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41602/nucdiff-in-depth-characterization-and-annotation-of-differences-between-two-sets-of-dna-sequences</link>
	<title><![CDATA[NucDiff: In-depth characterization and annotation of differences between two sets of DNA sequences]]></title>
	<description><![CDATA[<p>NucDiff locates and categorizes differences between two closely related nucleotide sequences. It is able to deal with very fragmented genomes, structural rearrangements and various local differences. These features make NucDiff to be perfectly suitable to compare assemblies with each other or with available reference genomes.</p>
<p>NucDiff provides information about the types of differences and their locations. It is possible to upload the results into genome browser for visualization and further inspection. It was written in Python and uses the NUCmer package from MUMmer[1] for sequence comparison.</p>
<p><br><br></p><p>Address of the bookmark: <a href="https://github.com/uio-cels/NucDiff" rel="nofollow">https://github.com/uio-cels/NucDiff</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43254/quasr-quantification-and-annotation-of-short-reads-in-r</guid>
	<pubDate>Fri, 13 Aug 2021 07:44:05 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43254/quasr-quantification-and-annotation-of-short-reads-in-r</link>
	<title><![CDATA[QuasR: Quantification and annotation of short reads in R]]></title>
	<description><![CDATA[<p>The <em><a href="https://bioconductor.org/packages/3.14/QuasR">QuasR</a></em> package (short for <em>Qu</em>antify and <em>a</em>nnotate <em>s</em>hort reads in <em>R</em>) integrates the functionality of several <strong>R</strong> packages (such as <em><a href="https://bioconductor.org/packages/3.14/IRanges">IRanges</a></em> <span>(Lawrence et al. 2013)</span> and <em><a href="https://bioconductor.org/packages/3.14/Rsamtools">Rsamtools</a></em>) and external software (e.g.&nbsp;<code>bowtie</code>, through the <em><a href="https://bioconductor.org/packages/3.14/Rbowtie">Rbowtie</a></em> package, and <code>HISAT2</code>, through the <em><a href="https://bioconductor.org/packages/3.14/Rhisat2">Rhisat2</a></em> package). The package aims to cover the whole analysis workflow of typical high throughput sequencing experiments, starting from the raw sequence reads, over pre-processing and alignment, up to quantification. A single <strong>R</strong> script can contain all steps of a complete analysis, making it simple to document, reproduce or share the workflow containing all relevant details.</p><p>Address of the bookmark: <a href="https://www.bioconductor.org/packages/devel/bioc/vignettes/QuasR/inst/doc/QuasR.html" rel="nofollow">https://www.bioconductor.org/packages/devel/bioc/vignettes/QuasR/inst/doc/QuasR.html</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38752/hgtector-an-automated-method-facilitating-genome-wide-discovery-of-putative-horizontal-gene-transfers</guid>
	<pubDate>Mon, 21 Jan 2019 06:50:05 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38752/hgtector-an-automated-method-facilitating-genome-wide-discovery-of-putative-horizontal-gene-transfers</link>
	<title><![CDATA[HGTector: an automated method facilitating genome-wide discovery of putative horizontal gene transfers]]></title>
	<description><![CDATA[<p>A computational pipeline for genome-wide detection of putative horizontal gene transfer (HGT) events based on sequence homology search hit distribution statistics</p>
<p>Authors: Qiyun Zhu (<a href="mailto:qiyunzhu@gmail.com">qiyunzhu@gmail.com</a>), Katharina Dittmar (<a href="mailto:katharinad@gmail.com">katharinad@gmail.com</a>)</p>
<p>Affiliation: Department of Biological Sciences, University at Buffalo, State University of New York, Buffalo, USA</p>
<p>Zhu Q, Kosoy M, Dittmar K. HGTector: an automated method facilitating genome-wide discovery of putative horizontal gene transfers.&nbsp;<em style="font-size: 12.8px;">BMC Genomics</em>. 2014. 15:717.</p>
<p>Usage: Simply execute&nbsp;<span style="font-size: 12.8px;">perl HGTector.pl</span>, or, open&nbsp;<span style="font-size: 12.8px;">GUI.html</span>&nbsp;in a web browser to see a step-by-step wizard.</p>
<p>Download&nbsp;<a href="https://github.com/DittmarLab/HGTector/archive/0.2.2.zip">HGTector 0.2.2</a>.</p><p>Address of the bookmark: <a href="https://github.com/DittmarLab/HGTector" rel="nofollow">https://github.com/DittmarLab/HGTector</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44595/squeezemeta-a-fully-automated-metagenomics-pipeline-from-reads-to-bins</guid>
	<pubDate>Sat, 06 Jul 2024 04:29:16 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44595/squeezemeta-a-fully-automated-metagenomics-pipeline-from-reads-to-bins</link>
	<title><![CDATA[SqueezeMeta: a fully automated metagenomics pipeline, from reads to bins]]></title>
	<description><![CDATA[<p dir="auto">SqueezeMeta is a full automatic pipeline for metagenomics/metatranscriptomics, covering all steps of the analysis. SqueezeMeta includes multi-metagenome support allowing the co-assembly of related metagenomes and the retrieval of individual genomes via binning procedures. Thus, SqueezeMeta features several unique characteristics:</p>
<ol dir="auto">
<li>Co-assembly procedure with read mapping for estimation of the abundances of genes in each metagenome</li>
<li>Co-assembly of a large number of metagenomes via merging of individual metagenomes</li>
<li>Includes binning and bin checking, for retrieving individual genomes</li>
<li>The results are stored in a database, where they can be easily exported and shared, and can be inspected anywhere using a web interface.</li>
<li>Internal checks for the assembly and binning steps inform about the consistency of contigs and bins, allowing to spot potential chimeras.</li>
<li>Metatranscriptomic support via mapping of cDNA reads against reference metagenomes</li>
</ol><p>Address of the bookmark: <a href="https://github.com/jtamames/SqueezeMeta" rel="nofollow">https://github.com/jtamames/SqueezeMeta</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40699/kevler-reference-free-variant-discovery-in-large-eukaryotic-genomes</guid>
	<pubDate>Tue, 28 Jan 2020 03:21:53 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40699/kevler-reference-free-variant-discovery-in-large-eukaryotic-genomes</link>
	<title><![CDATA[Kevler: Reference-free variant discovery in large eukaryotic genomes]]></title>
	<description><![CDATA[<p><span>Welcome to&nbsp;</span><span>kevlar</span><span>, software for predicting&nbsp;</span><em>de novo</em><span>&nbsp;genetic variants without mapping reads to a reference genome! kevlar's&nbsp;</span><em>k</em><span>-mer abundance based method calls single nucleotide variants (SNVs), multinucleotide variants (MNVs), insertion/deletion variants (indels), and structural variants (SVs) simultaneously with a single simple model.&nbsp;</span></p>
<p><span>More at&nbsp;<a href="https://kevlar.readthedocs.io/en/latest/">https://kevlar.readthedocs.io/en/latest/</a></span></p>
<p><span><a href="https://www.cell.com/iscience/pdf/S2589-0042(19)30259-7.pdf">https://www.cell.com/iscience/pdf/S2589-0042(19)30259-7.pdf</a></span></p><p>Address of the bookmark: <a href="https://github.com/kevlar-dev/kevlar" rel="nofollow">https://github.com/kevlar-dev/kevlar</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27479/biogps</guid>
	<pubDate>Mon, 23 May 2016 03:15:46 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27479/biogps</link>
	<title><![CDATA[BioGPS]]></title>
	<description><![CDATA[<p>A free&nbsp;<em>extensible</em>&nbsp;and&nbsp;<em>customizable</em>&nbsp;<strong>gene annotation portal</strong>, a complete resource for learning about&nbsp;<strong>gene and protein function</strong>.</p>
<p>http://biogps.org/#goto=welcome</p><p>Address of the bookmark: <a href="http://biogps.org/#goto=welcome" rel="nofollow">http://biogps.org/#goto=welcome</a></p>]]></description>
	<dc:creator>Anjana</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27475/polyphen-2-prediction-of-functional-effects-of-human-nssnps</guid>
	<pubDate>Mon, 23 May 2016 02:27:25 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27475/polyphen-2-prediction-of-functional-effects-of-human-nssnps</link>
	<title><![CDATA[PolyPhen-2: Prediction of functional effects of human nsSNPs]]></title>
	<description><![CDATA[<p><strong>PolyPhen-2</strong> (<strong>Poly</strong>morphism <strong>Phen</strong>otyping v<strong>2</strong>) is a tool which predicts possible impact of an amino acid substitution on the structure and function of a human protein using straightforward physical and comparative considerations.</p><p>Address of the bookmark: <a href="http://genetics.bwh.harvard.edu/pph2/" rel="nofollow">http://genetics.bwh.harvard.edu/pph2/</a></p>]]></description>
	<dc:creator>Anjana</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37980/csbfinder-discovery-of-colinear-syntenic-blocks-across-thousands-of-prokaryotic-genomes</guid>
	<pubDate>Wed, 24 Oct 2018 22:12:27 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37980/csbfinder-discovery-of-colinear-syntenic-blocks-across-thousands-of-prokaryotic-genomes</link>
	<title><![CDATA[CSBFinder: Discovery of colinear syntenic blocks across thousands of prokaryotic genomes]]></title>
	<description><![CDATA[<p>CSBFinder is a standalone Desktop java application with a graphical user interface, that can also be executed via command line.</p>
<p>CSBFinder implements a novel methodology for the discovery, ranking, and taxonomic distribution analysis of colinear syntenic blocks (<span>CSBs</span>) - groups of genes that are consistently located close to each other, in the same order, across a wide range of taxa. CSBFinder incorporates an efficient algorithm that identifies CSBs in large genomic datasets. The discovered CSBs are ranked according to a probabilistic score and clustered to families according to their gene content similarity.</p><p>Address of the bookmark: <a href="https://github.com/dinasv/CSBFinder" rel="nofollow">https://github.com/dinasv/CSBFinder</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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