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	<title><![CDATA[BOL: All site bookmarks]]></title>
	<link>https://bioinformaticsonline.com/bookmarks/all?offset=660</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37502/alignqc-a-tool-for-assessing-an-alignment-and-generating-reports-that-are-easy-to-share</guid>
	<pubDate>Tue, 07 Aug 2018 04:41:07 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37502/alignqc-a-tool-for-assessing-an-alignment-and-generating-reports-that-are-easy-to-share</link>
	<title><![CDATA[AlignQC: A tool for assessing an alignment, and generating reports that are easy to share]]></title>
	<description><![CDATA[<p><span>Long read alignment analysis. Generate a reports on sequence alignments for mappability vs read sizes, error patterns, annotations and rarefraction curve analysis. The most basic analysis only requires a BAM file, and outputs a web browser compatible xhtml to visualize/share/store/extract analysis results.</span></p>
<p>https://f1000research.com/articles/6-100/</p>
<p>https://github.com/jason-weirather/AlignQC</p><p>Address of the bookmark: <a href="https://www.healthcare.uiowa.edu/labs/au/AlignQC/" rel="nofollow">https://www.healthcare.uiowa.edu/labs/au/AlignQC/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37498/nextsv-a-meta-caller-for-structural-variants-from-low-coverage-long-read-sequencing-data</guid>
	<pubDate>Mon, 06 Aug 2018 17:24:53 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37498/nextsv-a-meta-caller-for-structural-variants-from-low-coverage-long-read-sequencing-data</link>
	<title><![CDATA[NextSV: a meta-caller for structural variants from low-coverage long-read sequencing data]]></title>
	<description><![CDATA[<p>NextSV, a meta SV caller and a computational pipeline to perform SV calling from low coverage long-read sequencing data. NextSV integrates three aligners and three SV callers and generates two integrated call sets (sensitive/stringent) for different analysis purpose. The output of NextSV is in ANNOVAR-compatible bed format. Users can easily perform downstream annotation using ANNOVAR and disease gene discovery using Phenolyzer.</p>
<p>&nbsp;</p>
<h2>&nbsp;</h2><p>Address of the bookmark: <a href="https://github.com/Nextomics/NextSV" rel="nofollow">https://github.com/Nextomics/NextSV</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37496/gsearch-a-fast-and-flexible-general-search-tool-for-whole-genome-sequencing</guid>
	<pubDate>Mon, 06 Aug 2018 17:19:15 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37496/gsearch-a-fast-and-flexible-general-search-tool-for-whole-genome-sequencing</link>
	<title><![CDATA[gSearch: a fast and flexible general search tool for whole-genome sequencing]]></title>
	<description><![CDATA[<p><span>gSearch compares sequence variants in the Genome Variation Format (GVF) or Variant Call Format (VCF) with a pre-compiled annotation or with variants in other genomes. Its search algorithms are subsequently optimized and implemented in a multi-threaded manner.&nbsp;</span></p><p>Address of the bookmark: <a href="http://ml.ssu.ac.kr/gSearch/index.html" rel="nofollow">http://ml.ssu.ac.kr/gSearch/index.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37493/fastq-stats-in-emoji</guid>
	<pubDate>Mon, 06 Aug 2018 10:20:20 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37493/fastq-stats-in-emoji</link>
	<title><![CDATA[Fastq stats in Emoji :)]]></title>
	<description><![CDATA[<p>Read one or more FASTQ files,&nbsp;<a href="https://fastqe.com/">fastqe</a>&nbsp;will compute quality stats for each file and print those stats as emoji... for some reason.</p>
<p>Given a fastq file in Illumina 1.8+/Sanger format, calculate the mean (rounded) score for each position and print a corresponding emoji!</p>
<p><a href="https://github.com/lonsbio/fastqe/blob/master/docs/img/fastqe_binned.png" target="_blank"><img src="https://github.com/lonsbio/fastqe/raw/master/docs/img/fastqe_binned.png" alt="Example" style="border: 0px;"></a></p>
<p><a href="https://fastqe.com/">https://fastqe.com/</a></p><p>Address of the bookmark: <a href="https://github.com/lonsbio/fastqe" rel="nofollow">https://github.com/lonsbio/fastqe</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37473/lsc-a-long-read-error-correction-tool</guid>
	<pubDate>Thu, 02 Aug 2018 07:39:46 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37473/lsc-a-long-read-error-correction-tool</link>
	<title><![CDATA[LSC :a long read error correction tool]]></title>
	<description><![CDATA[<h2>Getting Started</h2>
<p>These simple steps will help you integrate LSC into your transcriptomics analysis pipeline.</p>
<ul>
<li>Read the&nbsp;<a href="https://www.healthcare.uiowa.edu/labs/au/LSC/LSC_requirements.asp">LSC_requirements</a>&nbsp;for running LSC.</li>
<li><a href="https://www.healthcare.uiowa.edu/labs/au/LSC/LSC_download.asp">Download</a>&nbsp;and set-up the LSC package.</li>
<li>Follow the&nbsp;<a href="https://www.healthcare.uiowa.edu/labs/au/LSC/LSC_tutorial.asp">tutorial</a>&nbsp;to see how LSC works on some example data.</li>
<li>Read the&nbsp;<a href="https://www.healthcare.uiowa.edu/labs/au/LSC/LSC_manual.asp">manual</a>&nbsp;if anything is unclear.</li>
<li>You're ready, Happy LSCing!</li>
</ul>
<h2>Latest publication</h2>
<p><span>Kin Fai Au, Jason Underwood, Lawrence Lee and Wing Hung Wong&nbsp;</span><br><strong>Improving PacBio Long Read Accuracy by Short Read Alignment&nbsp;</strong><span>[</span><a href="http://journals.plos.org/plosone/article?id=10.1371%2Fjournal.pone.0046679">Manuscript</a><span>]&nbsp;</span><br><em>PLoS ONE</em><span>&nbsp;2012. 7(10): e46679. doi:10.1371/journal.pone.0046679</span></p><p>Address of the bookmark: <a href="https://www.healthcare.uiowa.edu/labs/au/LSC/" rel="nofollow">https://www.healthcare.uiowa.edu/labs/au/LSC/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37460/revigo-reduced-visualize-gene-ontology</guid>
	<pubDate>Tue, 31 Jul 2018 05:28:42 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37460/revigo-reduced-visualize-gene-ontology</link>
	<title><![CDATA[REVIGO: Reduced Visualize gene ontology]]></title>
	<description><![CDATA[<div>REViGO can take long lists of Gene Ontology terms and summarize them by removing redundant GO terms. The remaining terms can be visualized in semantic similarity-based scatterplots, interactive graphs, or tag clouds.&nbsp;<a href="http://dx.doi.org/10.1371/journal.pone.0021800">More about REViGO...</a>&nbsp;|&nbsp;<a href="http://revigo.irb.hr/about_hr.jsp"><img src="http://revigo.irb.hr/gfx/croatian-wCrown.png" alt="In Croatian" title="" width="12" height="15" style="border: 0px;"></a></div>
<div>Please enter a list of Gene Ontology IDs below, each on its own line. The GO IDs may be followed by p-values or another quantity which describes the GO term in a way meaningful to you.&nbsp;<img src="http://revigo.irb.hr/gfx/qmark.png" alt="For instance, you may provide a p-value          (statistical significance), a fold change, enrichment, or some          directly measured quantity such as average signal intensity from          microarrays, ion count from mass spec, or read count from RNA-seq.          You may also provide more than one value per line, although only the          first value will be used in GO term selection/clustering." title="" width="16" height="15" style="border: 0px;"></div><p>Address of the bookmark: <a href="http://revigo.irb.hr/" rel="nofollow">http://revigo.irb.hr/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37457/nanofilt-filtering-and-trimming-of-long-read-sequencing-data</guid>
	<pubDate>Mon, 30 Jul 2018 12:01:52 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37457/nanofilt-filtering-and-trimming-of-long-read-sequencing-data</link>
	<title><![CDATA[nanofilt: Filtering and trimming of long read sequencing data]]></title>
	<description><![CDATA[<p>Filtering on quality and/or read length, and optional trimming after passing filters.<br>Reads from stdin, writes to stdout.</p>
<p>Intended to be used:</p>
<ul>
<li>directly after fastq extraction</li>
<li>prior to mapping</li>
<li>in a stream between extraction and mapping</li>
</ul>
<p>https://github.com/wdecoster/nanofilt</p><p>Address of the bookmark: <a href="https://github.com/wdecoster/nanofilt" rel="nofollow">https://github.com/wdecoster/nanofilt</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37416/gfinisher-a-new-strategy-to-refine-and-finish-bacterial-genome-assemblies</guid>
	<pubDate>Thu, 26 Jul 2018 09:31:55 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37416/gfinisher-a-new-strategy-to-refine-and-finish-bacterial-genome-assemblies</link>
	<title><![CDATA[GFinisher: a new strategy to refine and finish bacterial genome assemblies]]></title>
	<description><![CDATA[<p>GFinisher is an application tools for refinement and finalization of prokaryotic genomes assemblies using the bias of GC Skew to identify assembly errors and organizes the contigs/scaffolds with genomes references.</p>
<pre>java -Xms2G -Xmx4G -jar GenomeFinisher.jar  \
    -i target_contigs.fasta  \
    -ds alternative_assemblies.fasta -ref reference.fasta  \
    -o outputDirectory</pre><p>Address of the bookmark: <a href="http://gfinisher.sourceforge.net" rel="nofollow">http://gfinisher.sourceforge.net</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37414/arc-pipeline-which-facilitates-iterative-reference-guided-de-novo-assemblies</guid>
	<pubDate>Thu, 26 Jul 2018 09:20:26 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37414/arc-pipeline-which-facilitates-iterative-reference-guided-de-novo-assemblies</link>
	<title><![CDATA[ARC: pipeline which facilitates iterative, reference guided de novo assemblies]]></title>
	<description><![CDATA[<p>ARC is a pipeline which facilitates iterative, reference guided&nbsp;<em>de novo</em>&nbsp;assemblies with the intent of:</p>
<ol>
<li>Reducing time in analysis and increasing accuracy of results by only considering those reads which should assemble together.</li>
<li>Reducing/removing reference bias as compared to mapping based approaches.</li>
</ol>
<p><span>The software is designed to work in situations where a whole-genome assembly is not the objective, but rather when the researcher wishes to assemble discreet 'targets' contained within next-generation shotgun sequence data. ARC decomplexifies the traditionally difficult problem of assembly by breaking the reads into small, manageable subsets which can then be assembled quickly and efficiently in parallel. Applications include those in which the researcher wishes to&nbsp;</span><em>de novo</em><span>&nbsp;assemble specific content and a set of semi-similar reference targets is available to initialize the assembly process.</span></p>
<p>https://ibest.github.io/ARC/</p><p>Address of the bookmark: <a href="https://ibest.github.io/ARC/" rel="nofollow">https://ibest.github.io/ARC/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37409/nanopolis-polish-a-genome-assembly</guid>
	<pubDate>Thu, 26 Jul 2018 04:51:28 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37409/nanopolis-polish-a-genome-assembly</link>
	<title><![CDATA[Nanopolis: polish a genome assembly]]></title>
	<description><![CDATA[<p><span>Software package for signal-level analysis of Oxford Nanopore sequencing data. Nanopolish can calculate an improved consensus sequence for a draft genome assembly, detect base modifications, call SNPs and indels with respect to a reference genome and more (see Nanopolish modules, below).</span></p>
<p>Quickstart</p>
<p>http://nanopolish.readthedocs.io/en/latest/quickstart_consensus.html</p>
<p>Algorithms</p>
<p>http://simpsonlab.github.io/2017/06/30/nanopolish-v0.7.0/</p><p>Address of the bookmark: <a href="https://github.com/jts/nanopolish" rel="nofollow">https://github.com/jts/nanopolish</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>

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