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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/38023?offset=50</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26375/ncbi-remap</guid>
	<pubDate>Thu, 11 Feb 2016 11:02:26 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26375/ncbi-remap</link>
	<title><![CDATA[NCBI Remap]]></title>
	<description><![CDATA[<p><span><span><strong>NCBI Remap</strong>. This tool is conceptually similar to liftOver in that in manages conversions between a pair of genome assemblies but it uses different methods to achieve these mappings. It is also available through a simple <a href="http://www.ncbi.nlm.nih.gov/genome/tools/remap">web interface</a> or you can use the <a href="http://www.ncbi.nlm.nih.gov/genome/tools/remap/docs/api">API for NCBI Remap</a>.</span></span></p>
<p><span><span>More at http://www.ncbi.nlm.nih.gov/genome/tools/remap</span></span></p>
<p><span><span>API http://www.ncbi.nlm.nih.gov/genome/tools/remap/docs/api</span></span></p><p>Address of the bookmark: <a href="http://www.ncbi.nlm.nih.gov/genome/tools/remap" rel="nofollow">http://www.ncbi.nlm.nih.gov/genome/tools/remap</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/33691/annotationsketch</guid>
	<pubDate>Sun, 25 Jun 2017 17:54:22 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/33691/annotationsketch</link>
	<title><![CDATA[AnnotationSketch]]></title>
	<description><![CDATA[<p><span>The&nbsp;</span><em>AnnotationSketch</em><span>&nbsp;module is a versatile and efficient C-based drawing library for GFF3-compatible genomic annotations. It is included in the&nbsp;</span><em>GenomeTools</em><span>&nbsp;</span><a href="http://genometools.org/pub">distribution</a><span>. Additionally, bindings to the&nbsp;</span><a href="http://www.lua.org/">Lua</a><span>,&nbsp;</span><a href="http://www.python.org/">Python</a><span>&nbsp;and&nbsp;</span><a href="http://www.ruby-lang.org/en">Ruby</a><span>programming languages are provided.</span></p>
<p><span>http://genometools.org/annotationsketch.html</span></p><p>Address of the bookmark: <a href="http://genometools.org/annotationsketch.html" rel="nofollow">http://genometools.org/annotationsketch.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38659/detail-annotation-of-genes</guid>
	<pubDate>Fri, 11 Jan 2019 05:23:33 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38659/detail-annotation-of-genes</link>
	<title><![CDATA[Detail annotation of genes !]]></title>
	<description><![CDATA[<p>gene_info recalculated daily<br>---------------------------------------------------------------------------<br> tab-delimited<br> one line per GeneID<br> Column header line is the first line in the file.<br> Note: subsets of gene_info are available in the DATA/GENE_INFO<br> directory (described later)<br>---------------------------------------------------------------------------</p>
<p>tax_id:<br> the unique identifier provided by NCBI Taxonomy<br> for the species or strain/isolate</p>
<p>GeneID:<br> the unique identifier for a gene<br> ASN1: geneid</p>
<p>Symbol:<br> the default symbol for the gene<br> ASN1: gene-&gt;locus</p>
<p>LocusTag:<br> the LocusTag value<br> ASN1: gene-&gt;locus-tag</p>
<p>Synonyms:<br> bar-delimited set of unofficial symbols for the gene</p>
<p>dbXrefs:<br> bar-delimited set of identifiers in other databases<br> for this gene. The unit of the set is database:value.<br> Note that HGNC and MGI include 'HGNC' and 'MGI', respectively,<br> in the value part of their identifier. Consequently,<br> dbXrefs for these databases will appear like:<br> HGNC:HGNC:1100<br> This would be interpreted as database='HGNC', value='HGNC:1100'<br> Example for MGI:<br> MGI:MGI:104537<br> This would be interpreted as database='MGI', value='MGI:104537'</p>
<p>chromosome:<br> the chromosome on which this gene is placed.<br> for mitochondrial genomes, the value 'MT' is used.</p>
<p>map location:<br> the map location for this gene</p>
<p>description:<br> a descriptive name for this gene</p>
<p>type of gene:<br> the type assigned to the gene according to the list of options<br> provided in https://www.ncbi.nlm.nih.gov/IEB/ToolBox/CPP_DOC/lxr/source/src/objects/entrezgene/entrezgene.asn</p>
<p><br>Symbol from nomenclature authority:<br> when not '-', indicates that this symbol is from a<br> a nomenclature authority</p>
<p>Full name from nomenclature authority:<br> when not '-', indicates that this full name is from a<br> a nomenclature authority</p>
<p>Nomenclature status:<br> when not '-', indicates the status of the name from the <br> nomenclature authority (O for official, I for interim)</p>
<p>Other designations:<br> pipe-delimited set of some alternate descriptions that<br> have been assigned to a GeneID<br> '-' indicates none is being reported.</p>
<p>Modification date:<br> the last date a gene record was updated, in YYYYMMDD format</p>
<p>Feature type:<br> pipe-delimited set of annotated features and their classes or <br> controlled vocabularies, displayed as feature_type:feature_class <br> or feature_type:controlled_vocabulary, when appropriate; derived <br> from select feature annotations on RefSeq(s) associated with the <br> GeneID</p><p>Address of the bookmark: <a href="ftp://ftp.ncbi.nih.gov/gene/DATA/GENE_INFO/" rel="nofollow">ftp://ftp.ncbi.nih.gov/gene/DATA/GENE_INFO/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39881/apollo-a-sequence-annotation-editor</guid>
	<pubDate>Tue, 27 Aug 2019 08:08:47 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39881/apollo-a-sequence-annotation-editor</link>
	<title><![CDATA[Apollo: a sequence annotation editor]]></title>
	<description><![CDATA[<p><span>The well-established inaccuracy of purely computational methods for annotating genome sequences necessitates an interactive tool to allow biological experts to refine these approximations by viewing and independently evaluating the data supporting each annotation. Apollo was developed to meet this need, enabling curators to inspect genome annotations closely and edit them</span></p><p>Address of the bookmark: <a href="https://genomebiology.biomedcentral.com/articles/10.1186/gb-2002-3-12-research0082" rel="nofollow">https://genomebiology.biomedcentral.com/articles/10.1186/gb-2002-3-12-research0082</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42035/pannzer-a-fully-automated-service-for-functional-annotation-of-prokaryotic-and-eukaryotic-proteins-of-unknown-function</guid>
	<pubDate>Thu, 13 Aug 2020 09:57:24 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42035/pannzer-a-fully-automated-service-for-functional-annotation-of-prokaryotic-and-eukaryotic-proteins-of-unknown-function</link>
	<title><![CDATA[PANNZER: a fully automated service for functional annotation of prokaryotic and eukaryotic proteins of unknown function.]]></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.</p>
<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>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>BioStar</dc:creator>
</item>
<item>
	<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/33219/dbcan-a-web-server-and-database-for-automated-carbohydrate-active-enzyme-annotation</guid>
	<pubDate>Mon, 29 May 2017 05:39:29 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/33219/dbcan-a-web-server-and-database-for-automated-carbohydrate-active-enzyme-annotation</link>
	<title><![CDATA[dbCAN: a web server and DataBase for automated Carbohydrate-active enzyme ANnotation]]></title>
	<description><![CDATA[<p><a href="http://csbl.bmb.uga.edu/dbCAN/index.php">dbCAN</a>&nbsp;is a web server and&nbsp;<span style="text-decoration: underline;">D</span>ata<span style="text-decoration: underline;">B</span>ase for&nbsp;<a href="http://csbl.bmb.uga.edu/dbCAN/annotate.php"><strong>automated&nbsp;<span style="text-decoration: underline;">C</span>arbohydrate-active enzyme&nbsp;<span style="text-decoration: underline;">AN</span>notation</strong></a>, funded by the&nbsp;<a href="http://bioenergycenter.org/">BioEnergy Science Center of the DOE</a>. Similar resources on the web include&nbsp;<a href="http://www.cazy.org/" target="_blank">CAZy database</a>&nbsp;and&nbsp;<a href="http://cricket.ornl.gov/cgi-bin/cat.cgi" target="_blank">CAT</a>. All data in dbCAN are generated based on the family classification from&nbsp;<a href="http://www.cazy.org/" target="_blank">CAZy database</a>&nbsp;while it has the following&nbsp;<strong><span style="text-decoration: underline;">unique features</span></strong>&nbsp;compared with CAZy database and CAT:</p>
<ul>
<li>dbCAN provides the capability of&nbsp;<a href="http://csbl.bmb.uga.edu/dbCAN/annotate.php">automated and comprehensive CAZyme annotation</a>&nbsp;of a given genome submitted by the user;</li>
<li>dbCAN provides an explicitly defined&nbsp;<span style="text-decoration: underline;">signature domain</span>&nbsp;for each and every CAZyme family along with its location in all the relevant full-length CAZyme proteins in all sequenced&nbsp;<a href="http://csbl.bmb.uga.edu/dbCAN/genome.php">genomes</a>;</li>
<li>dbCAN provides the most complete set of&nbsp;<span style="text-decoration: underline;">metagenomic CAZyme</span>&nbsp;genes published so far and represents the first step towards discovering novel CAZyme catalysts in metagenomes;</li>
<li>dbCAN provides a&nbsp;<span style="text-decoration: underline;">subfamily classification</span>&nbsp;of the existing CAZyme families based on sequence similarities;</li>
<li>dbCAN make all pre-computed data freely available to the public, including sequence alignments,&nbsp;<a href="http://csbl.bmb.uga.edu/dbCAN/download/">hidden markov models (HMMs)</a>&nbsp;and phylogenies of the signature domain regions in each and every CAZyme family and subfamily.</li>
</ul>
<p><a href="http://csbl.bmb.uga.edu/dbCAN/help.php">dbCAN</a>&nbsp;is updated regularly when&nbsp;<a href="http://www.cazy.org/" target="_blank">CAZy database</a>&nbsp;created new families based on latest literature.</p><p>Address of the bookmark: <a href="http://csbl.bmb.uga.edu/dbCAN/index.php" rel="nofollow">http://csbl.bmb.uga.edu/dbCAN/index.php</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36817/kwip-the-k-mer-weighted-inner-product-a-de-novo-estimator-of-genetic-similarity</guid>
	<pubDate>Tue, 29 May 2018 08:37:53 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36817/kwip-the-k-mer-weighted-inner-product-a-de-novo-estimator-of-genetic-similarity</link>
	<title><![CDATA[kWIP: The k-mer weighted inner product, a de novo estimator of genetic similarity]]></title>
	<description><![CDATA[<p>The k-mer Weighted Inner Product.</p>
<p>This software implements a <em>de novo</em>, <em>alignment free</em> measure of sample genetic dissimilarity which operates upon raw sequencing reads. It is able to calculate the genetic dissimilarity between samples without any reference genome, and without assembling one.</p>
<p> </p>

De novo estimates of genetic relatedness from next-gen sequencing data https://kwip.readthedocs.org<p>Address of the bookmark: <a href="https://github.com/kdmurray91/kwip" rel="nofollow">https://github.com/kdmurray91/kwip</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37554/finishersca-repeat-aware-tool-for-upgrading-de-novo-assembly-using-long-reads</guid>
	<pubDate>Mon, 20 Aug 2018 04:08:50 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37554/finishersca-repeat-aware-tool-for-upgrading-de-novo-assembly-using-long-reads</link>
	<title><![CDATA[FinisherSC:a repeat-aware tool for upgrading de novo assembly using long reads]]></title>
	<description><![CDATA[<p><br>Here is the command to run the tool:</p>
<pre><code>python finisherSC.py destinedFolder mummerPath
</code></pre>
<p>If you are running on server computer and would like to use multiple threads, then the following commands can generate 20 threads to run FinisherSC.</p>
<pre><code>python finisherSC.py -par 20 destinedFolder mummerPath
</code></pre>
<p>Sometimes, if the names of raw reads and contigs consists of special characters/formats, FinisherSC/MUMmer may not parse them correctly. In that case, you want to have a quick renaming of the names of contigs/reads in contigs.fasta or raw_reads.fasta using the following command.</p>
<pre><code>    perl -pe 's/&gt;[^\$]*$/"&gt;Seg" . ++$n ."\n"/ge' raw_reads.fasta &gt; newRaw_reads.fasta
    cp newRaw_reads.fasta raw_reads.fasta
    perl -pe 's/&gt;[^\$]*$/"&gt;Seg" . ++$n ."\n"/ge' contigs.fasta &gt; newContigs.fasta
    cp newContigs.fasta contigs.fasta</code></pre><p>Address of the bookmark: <a href="https://github.com/kakitone/finishingTool" rel="nofollow">https://github.com/kakitone/finishingTool</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>

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