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	<title><![CDATA[BOL: All site bookmarks]]></title>
	<link>https://bioinformaticsonline.com/bookmarks/all?offset=300</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41991/sequence-ontology-bioinformatics-analysis-soba-tool-to-provide-a-simple-statistical-and-graphical-summary-of-an-annotated-genome</guid>
	<pubDate>Wed, 22 Jul 2020 10:11:13 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41991/sequence-ontology-bioinformatics-analysis-soba-tool-to-provide-a-simple-statistical-and-graphical-summary-of-an-annotated-genome</link>
	<title><![CDATA[Sequence Ontology Bioinformatics Analysis (SOBA) tool to provide a simple statistical and graphical summary of an annotated genome]]></title>
	<description><![CDATA[<p><span>We have developed the Sequence Ontology Bioinformatics Analysis (SOBA) tool to provide a simple statistical and graphical summary of an annotated genome. We envisage its use during annotation jamborees, genome comparison and for use by developers for rapid feedback during annotation software development and testing. SOBA also provides annotation consistency feedback to ensure correct use of terminology within annotations, and guides users to add new terms to the Sequence Ontology when required. SOBA is available at http://www.sequenceontology.org/cgi-bin/soba.cgi.</span></p>
<p><span>More at <a href="https://pubmed.ncbi.nlm.nih.gov/20494974/">https://pubmed.ncbi.nlm.nih.gov/20494974/</a></span></p><p>Address of the bookmark: <a href="http://www.sequenceontology.org/cgi-bin/soba.cgi" rel="nofollow">http://www.sequenceontology.org/cgi-bin/soba.cgi</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41969/shadowcaster-a-hybrid-approach-for-the-detection-of-horizontal-gene-transfer-events-in-prokaryotes</guid>
	<pubDate>Tue, 14 Jul 2020 06:42:10 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41969/shadowcaster-a-hybrid-approach-for-the-detection-of-horizontal-gene-transfer-events-in-prokaryotes</link>
	<title><![CDATA[ShadowCaster: a hybrid approach for the detection of horizontal gene transfer events in prokaryotes]]></title>
	<description><![CDATA[<p><span>ShadowCaster implements an evolutionary model to calculate Bayesian likelihoods for each &lsquo;alien genes&rsquo; with an unusual sequence composition according to the host genome background to detect HGT events in prokaryotes.</span></p>
<p><a href="https://www.mdpi.com/2073-4425/11/7/756/htm">https://www.mdpi.com/2073-4425/11/7/756/htm</a></p>
<p><a href="https://shadowcaster.readthedocs.io/en/latest/">https://shadowcaster.readthedocs.io/en/latest/</a></p>
<p><a href="https://github.com/dani2s/ShadowCaster_testData">https://github.com/dani2s/ShadowCaster_testData</a></p><p>Address of the bookmark: <a href="https://github.com/dani2s/ShadowCaster" rel="nofollow">https://github.com/dani2s/ShadowCaster</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41959/rna-bloom-a-fast-and-memory-efficient-de-novo-transcript-sequence-assembler</guid>
	<pubDate>Thu, 09 Jul 2020 03:13:06 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41959/rna-bloom-a-fast-and-memory-efficient-de-novo-transcript-sequence-assembler</link>
	<title><![CDATA[RNA-Bloom: a fast and memory-efficient de novo transcript sequence assembler]]></title>
	<description><![CDATA[<p><strong>RNA-Bloom</strong><span>&nbsp;</span>is a fast and memory-efficient<span>&nbsp;</span><em>de novo</em><span>&nbsp;</span>transcript sequence assembler. It is designed for the following sequencing data types:</p>
<ul>
<li>single-end/paired-end bulk RNA-seq (strand-specific/agnostic)</li>
<li>paired-end single-cell RNA-seq (strand-specific/agnostic)</li>
<li>nanopore RNA-seq (PCR cDNA/direct cDNA/direct RNA)</li>
</ul>
<p>Written by<span>&nbsp;</span><a>Ka Ming Nip</a><span>&nbsp;</span>✉️</p><p>Address of the bookmark: <a href="https://github.com/bcgsc/RNA-Bloom" rel="nofollow">https://github.com/bcgsc/RNA-Bloom</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41957/majiq-2-is-released</guid>
	<pubDate>Thu, 09 Jul 2020 03:06:26 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41957/majiq-2-is-released</link>
	<title><![CDATA[MAJIQ 2 is released !]]></title>
	<description><![CDATA[<p>&nbsp;</p>
<p>Ability to detect, quantify, and visualize complex and de-novo splicing variations from RNASeq.</p>
<p>MAJIQ&rsquo;s accuracy compares favorably to other algorithms.</p>
<p>MAJIQ 2 is *way* faster, more memory and I/O efficient</p>
<p>New visualization (VOILA 2.0) Ability to analyze hundreds and thousands of samples Why so negative? (Support for a confident negative set)</p>
<p><span>Finally, a major reason we are excited about MAJIQ 2.0 is that it sets the code base for many new exciting algorithmic and visualization improvements, with application to new research questions so stay tuned!</span></p>
<p><span>More at <a href="https://biociphers.wordpress.com/2019/04/01/majiq-2-is-out/">https://biociphers.wordpress.com/2019/04/01/majiq-2-is-out/</a></span></p><p>Address of the bookmark: <a href="https://majiq.biociphers.org/" rel="nofollow">https://majiq.biociphers.org/</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41948/predict-gene-ontology-with-sequences</guid>
	<pubDate>Wed, 08 Jul 2020 04:59:28 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41948/predict-gene-ontology-with-sequences</link>
	<title><![CDATA[Predict Gene Ontology with sequences !]]></title>
	<description><![CDATA[<p><strong>PANNZER</strong>&nbsp;(Protein ANNotation with Z-scoRE) is a fully automated service for functional annotation of prokaryotic and eukaryotic proteins of unknown function. The tool is designed to predict the functional description (DE) and GO classes.</p>
<p>PANNZER2 processes bacterial proteomes in minutes and eukaryotic proteomes in an hour. You can use&nbsp;<a href="http://ekhidna2.biocenter.helsinki.fi/AAI/">AAI-profiler</a>&nbsp;to summarize a proteome's species neighbors and reveal taxonomic identity or contamination.</p>
<p>http://ekhidna2.biocenter.helsinki.fi/sanspanz/</p>
<p>IterPro is for the beginners</p>
<p><a href="https://www.ebi.ac.uk/interpro/">h</a><a href="https://www.ebi.ac.uk/interpro/">ttps://www.ebi.ac.uk/interpro/</a></p>
<p>You can find other comparative info at&nbsp;<a href="https://academic.oup.com/view-large/118391389">https://academic.oup.com/view-large/118391389</a></p><p>Address of the bookmark: <a href="http://ekhidna2.biocenter.helsinki.fi/sanspanz/" rel="nofollow">http://ekhidna2.biocenter.helsinki.fi/sanspanz/</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41941/svengine-allele-specific-and-haplotype-aware-structural-variants-simulator</guid>
	<pubDate>Sat, 04 Jul 2020 05:52:34 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41941/svengine-allele-specific-and-haplotype-aware-structural-variants-simulator</link>
	<title><![CDATA[SVEngine: Allele Specific and Haplotype Aware Structural Variants Simulator]]></title>
	<description><![CDATA[<p>SVEngine (Structural Variants Engine)</p>
<ul>
<li>SVEngine is a multi-purpose and self-contained simulator for whole genome scale spike-in of thousands of SV events of various types in both single-sample and matched sample scenarios.</li>
<li>SVEngine takes as input reference contigs in FASTA files, variant meta distribution as specified in META files (see Manual) or specific variant information as specified in VAR files (see Manual) and NEWICK files for specifying clonal phylogenetic trees in cancer.</li>
<li>SVEngine outpus alterred contigs in FASTA files, spiked-in variants in VAR files (see Manual), simulated short read in FASTQ files and aligned short reads in BAM files.</li>
</ul>
<p>&nbsp;</p><p>Address of the bookmark: <a href="https://bitbucket.org/charade/svengine/src/master/" rel="nofollow">https://bitbucket.org/charade/svengine/src/master/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41937/merqury-evaluate-genome-assemblies-with-k-mers</guid>
	<pubDate>Fri, 03 Jul 2020 19:29:34 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41937/merqury-evaluate-genome-assemblies-with-k-mers</link>
	<title><![CDATA[merqury: Evaluate genome assemblies with k-mers]]></title>
	<description><![CDATA[<p><span>Often, genome assembly projects have illumina whole genome sequencing reads available for the assembled individual. The k-mer spectrum of this read set can be used for independently evaluating assembly quality without the need of a high quality reference. Merqury provides a set of tools for this purpose.</span></p>
<p><span>More at&nbsp;<a href="https://www.biorxiv.org/content/10.1101/2020.03.15.992941v1.full">https://www.biorxiv.org/content/10.1101/2020.03.15.992941v1.full</a></span></p><p>Address of the bookmark: <a href="https://github.com/marbl/merqury" rel="nofollow">https://github.com/marbl/merqury</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41920/liftoff-an-accurate-tool-that-maps-annotations-in-gff-or-gtf-between-assemblies</guid>
	<pubDate>Tue, 30 Jun 2020 21:40:52 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41920/liftoff-an-accurate-tool-that-maps-annotations-in-gff-or-gtf-between-assemblies</link>
	<title><![CDATA[Liftoff: an accurate tool that maps annotations in GFF or GTF between assemblies]]></title>
	<description><![CDATA[<p><span>&nbsp;Liftoff, an accurate tool that maps annotations in GFF or GTF between assemblies of the same, or closely-related species. Unlike current coordinate lift-over tools which require a pre-generated &ldquo;chain&rdquo; file as input, Liftoff is a standalone tool that takes two genome assemblies and a reference annotation as input and outputs an annotation of the target genome.&nbsp;</span></p><p>Address of the bookmark: <a href="https://github.com/agshumate/Liftoff" rel="nofollow">https://github.com/agshumate/Liftoff</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41918/phispy-phispy-identifies-prophages-in-bacterial-and-probably-archaeal-genomes</guid>
	<pubDate>Tue, 30 Jun 2020 21:36:19 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41918/phispy-phispy-identifies-prophages-in-bacterial-and-probably-archaeal-genomes</link>
	<title><![CDATA[PhiSpy: PhiSpy identifies prophages in Bacterial (and probably Archaeal) genomes]]></title>
	<description><![CDATA[<p>PhiSpy identifies prophages in Bacterial (and probably Archaeal) genomes. Given an annotated genome it will use several approaches to identify the most likely prophage regions.</p>
<p>Initial versions of PhiSpy were written by</p>
<p>Sajia Akhter (<a href="mailto:sajia@stanford.edu">sajia@stanford.edu</a>)&nbsp;<a href="http://edwards.sdsu.edu/research/">Edwards Bioinformatics Lab</a></p>
<p>Improvements, bug fixes, and other changes were made by</p>
<p>Katelyn McNair&nbsp;<a href="http://edwards.sdsu.edu/research/">Edwards Bioinformatics Lab</a>&nbsp;and Przemyslaw Decewicz&nbsp;<a href="http://ddlemb.com/">DEMB at the University of Warsaw</a></p><p>Address of the bookmark: <a href="https://github.com/linsalrob/PhiSpy" rel="nofollow">https://github.com/linsalrob/PhiSpy</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41916/truvari-structural-variant-comparison-tool-for-vcfs</guid>
	<pubDate>Tue, 30 Jun 2020 21:30:44 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41916/truvari-structural-variant-comparison-tool-for-vcfs</link>
	<title><![CDATA[truvari: Structural variant comparison tool for VCFs]]></title>
	<description><![CDATA[<p>Structural variant comparison tool for VCFs</p>
<p>Given benchmark and comparsion sets of SVs, calculate the recall, precision, and f-measure.</p>
<p><a href="https://github.com/spiralgenetics/www.spiralgenetics.com">Spiral Genetics</a></p>
<p><a href="https://docs.google.com/presentation/d/17mvC1XOpOm7khAbZwF3SgtG2Rl4M9Mro37yF2nN7GhE/edit">Motivation</a></p><p>Address of the bookmark: <a href="https://github.com/spiralgenetics/truvari" rel="nofollow">https://github.com/spiralgenetics/truvari</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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