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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/41893?offset=40</link>
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	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39843/dnapipete-a-pipeline-designed-to-find-annotate-and-quantify-transposable-elements</guid>
	<pubDate>Mon, 12 Aug 2019 21:56:08 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39843/dnapipete-a-pipeline-designed-to-find-annotate-and-quantify-transposable-elements</link>
	<title><![CDATA[dnaPipeTE: a pipeline designed to find, annotate and quantify Transposable Elements]]></title>
	<description><![CDATA[<p><span>dnaPipeTE (for de-novo assembly &amp; annotation Pipeline for Transposable Elements), is a pipeline designed to find, annotate and quantify Transposable Elements in small samples of NGS datasets. It is very useful to quantify the proportion of TEs in newly sequenced genomes since it does not require genome assembly and works on small datasets (&lt; 1X).</span></p>
<p><span><a href="https://github.com/clemgoub/dnaPipeTE/wiki/dnaPipeTE-WIKI-home">https://github.com/clemgoub/dnaPipeTE/wiki/dnaPipeTE-WIKI-home</a></span></p><p>Address of the bookmark: <a href="https://github.com/clemgoub/dnaPipeTE" rel="nofollow">https://github.com/clemgoub/dnaPipeTE</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40611/deepvariant-an-analysis-pipeline-that-uses-a-deep-neural-network-to-call-genetic-variants-from-next-generation-dna-sequencing-data</guid>
	<pubDate>Sat, 25 Jan 2020 13:28:09 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40611/deepvariant-an-analysis-pipeline-that-uses-a-deep-neural-network-to-call-genetic-variants-from-next-generation-dna-sequencing-data</link>
	<title><![CDATA[DeepVariant : an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data.]]></title>
	<description><![CDATA[<p><span>DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data.</span></p>
<p><span><span>DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data. DeepVariant relies on&nbsp;</span><a href="https://github.com/google/nucleus">Nucleus</a><span>, a library of Python and C++ code for reading and writing data in common genomics file formats (like SAM and VCF) designed for painless integration with the&nbsp;</span><a href="https://www.tensorflow.org/">TensorFlow</a><span>&nbsp;machine learning framework.</span></span></p>
<p><span><a href="https://ai.googleblog.com/2017/12/deepvariant-highly-accurate-genomes.html">https://ai.googleblog.com/2017/12/deepvariant-highly-accurate-genomes.html</a></span></p>
<p><span><a href="https://www.biorxiv.org/content/10.1101/092890v6">https://www.biorxiv.org/content/10.1101/092890v6</a></span></p>
<p><span><img src="https://4.bp.blogspot.com/-2KlXZO60sWE/WiGc8qlZfxI/AAAAAAAACOs/s1pNiKI8jsAvJLr1E_po5udDO8eObm_awCLcBGAs/s640/image3.png" width="640" height="427" alt="image" style="border: 0px;"></span></p><p>Address of the bookmark: <a href="https://github.com/google/deepvariant" rel="nofollow">https://github.com/google/deepvariant</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41998/wgddetector-a-pipeline-for-detecting-whole-genome-duplication-events-using-the-genome-or-transcriptome-annotations</guid>
	<pubDate>Thu, 23 Jul 2020 05:52:56 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41998/wgddetector-a-pipeline-for-detecting-whole-genome-duplication-events-using-the-genome-or-transcriptome-annotations</link>
	<title><![CDATA[WGDdetector: a pipeline for detecting whole genome duplication events using the genome or transcriptome annotations]]></title>
	<description><![CDATA[<p><span>WGDdetector pipeline that integrates all analyses including gene family constructing, dS estimating and phasing, and outputting the dS values of each paralogs pairs processed with only one command. We further chose four species (</span><em>Arabidopsis thaliana</em><span>,<span>&nbsp;</span></span><em>Juglans regia</em><span>,<span>&nbsp;</span></span><em>Populus trichocarpa</em><span><span>&nbsp;</span>and<span>&nbsp;</span></span><em>Xenopus laevis</em><span>) representing herb, wood and animal, to test its practicability. Our final results showed a high degree of accuracy with the previous studies using both genome and transcriptome data.</span></p>
<p><span>More at <a href="https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-019-2670-3">https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-019-2670-3</a></span></p><p>Address of the bookmark: <a href="https://github.com/yongzhiyang2012/wgddetector" rel="nofollow">https://github.com/yongzhiyang2012/wgddetector</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42946/aligngraph2-similar-genome-assisted-reassembly-pipeline-for-pacbio-long-reads</guid>
	<pubDate>Sun, 14 Mar 2021 09:42:47 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42946/aligngraph2-similar-genome-assisted-reassembly-pipeline-for-pacbio-long-reads</link>
	<title><![CDATA[AlignGraph2: similar genome-assisted reassembly pipeline for PacBio long reads]]></title>
	<description><![CDATA[<p><span>AlignGraph2 is the second version of&nbsp;</span><a href="https://github.com/baoe/AlignGraph">AlignGraph</a><span>&nbsp;for PacBio long reads. It extends and refines contigs assembled from the long reads with a published genome similar to the sequencing genome.</span></p>
<p><span>More at&nbsp;https://academic.oup.com/bib/advance-article-abstract/doi/10.1093/bib/bbab022/6146772</span></p><p>Address of the bookmark: <a href="https://github.com/huangs001/AlignGraph2" rel="nofollow">https://github.com/huangs001/AlignGraph2</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/43634/illumina-based-assembly-pipeline-steps</guid>
	<pubDate>Fri, 10 Dec 2021 06:22:54 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/43634/illumina-based-assembly-pipeline-steps</link>
	<title><![CDATA[Illumina based assembly pipeline steps !]]></title>
	<description><![CDATA[<h3 id="illumina">Illumina<a href="https://nf-co.re/viralrecon#illumina"><span></span></a></h3><ol>
<li>Merge re-sequenced FastQ files (<a href="http://www.linfo.org/cat.html"><code>cat</code></a>)</li>
<li>Read QC (<a href="https://www.bioinformatics.babraham.ac.uk/projects/fastqc/"><code>FastQC</code></a>)</li>
<li>Adapter trimming (<a href="https://github.com/OpenGene/fastp"><code>fastp</code></a>)</li>
<li>Removal of host reads (<a href="http://ccb.jhu.edu/software/kraken2/"><code>Kraken 2</code></a>; <em>optional</em>)</li>
<li>Variant calling<ol>
<li>Read alignment (<a href="http://bowtie-bio.sourceforge.net/bowtie2/index.shtml"><code>Bowtie 2</code></a>)</li>
<li>Sort and index alignments (<a href="https://sourceforge.net/projects/samtools/files/samtools/"><code>SAMtools</code></a>)</li>
<li>Primer sequence removal (<a href="https://github.com/andersen-lab/ivar"><code>iVar</code></a>; <em>amplicon data only</em>)</li>
<li>Duplicate read marking (<a href="https://broadinstitute.github.io/picard/"><code>picard</code></a>; <em>optional</em>)</li>
<li>Alignment-level QC (<a href="https://broadinstitute.github.io/picard/"><code>picard</code></a>, <a href="https://sourceforge.net/projects/samtools/files/samtools/"><code>SAMtools</code></a>)</li>
<li>Genome-wide and amplicon coverage QC plots (<a href="https://github.com/brentp/mosdepth/"><code>mosdepth</code></a>)</li>
<li>Choice of multiple variant calling and consensus sequence generation routes (<a href="https://github.com/andersen-lab/ivar"><code>iVar variants and consensus</code></a>; <em>default for amplicon data</em> <em>||</em> <a href="http://samtools.github.io/bcftools/bcftools.html"><code>BCFTools</code></a>, <a href="https://github.com/arq5x/bedtools2/"><code>BEDTools</code></a>; <em>default for metagenomics data</em>)
<ul>
<li>Variant annotation (<a href="http://snpeff.sourceforge.net/SnpEff.html"><code>SnpEff</code></a>, <a href="http://snpeff.sourceforge.net/SnpSift.html"><code>SnpSift</code></a>)</li>
<li>Consensus assessment report (<a href="http://quast.sourceforge.net/quast"><code>QUAST</code></a>)</li>
<li>Lineage analysis (<a href="https://github.com/cov-lineages/pangolin"><code>Pangolin</code></a>)</li>
<li>Clade assignment, mutation calling and sequence quality checks (<a href="https://github.com/nextstrain/nextclade"><code>Nextclade</code></a>)</li>
<li>Individual variant screenshots with annotation tracks (<a href="https://asciigenome.readthedocs.io/en/latest/"><code>ASCIIGenome</code></a>)</li>
</ul>
</li>
<li>Intersect variants across callers (<a href="http://samtools.github.io/bcftools/bcftools.html"><code>BCFTools</code></a>)</li>
</ol></li>
<li><em>De novo</em> assembly<ol>
<li>Primer trimming (<a href="https://cutadapt.readthedocs.io/en/stable/guide.html"><code>Cutadapt</code></a>; <em>amplicon data only</em>)</li>
<li>Choice of multiple assembly tools (<a href="http://cab.spbu.ru/software/spades/"><code>SPAdes</code></a> <em>||</em> <a href="https://github.com/rrwick/Unicycler"><code>Unicycler</code></a> <em>||</em> <a href="https://github.com/GATB/minia"><code>minia</code></a>)
<ul>
<li>Blast to reference genome (<a href="https://blast.ncbi.nlm.nih.gov/Blast.cgi?PAGE_TYPE=BlastSearch"><code>blastn</code></a>)</li>
<li>Contiguate assembly (<a href="https://www.sanger.ac.uk/science/tools/pagit"><code>ABACAS</code></a>)</li>
<li>Assembly report (<a href="https://github.com/BU-ISCIII/plasmidID"><code>PlasmidID</code></a>)</li>
<li>Assembly assessment report (<a href="http://quast.sourceforge.net/quast"><code>QUAST</code></a>)</li>
</ul>
</li>
</ol></li>
<li>Present QC and visualisation for raw read, alignment, assembly and variant calling results (<a href="http://multiqc.info/"><code>MultiQC</code></a>)</li>
</ol>]]></description>
	<dc:creator>Surabhi Chaudhary</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44561/bactopia-a-flexible-pipeline-for-complete-analysis-of-bacterial-genomes</guid>
	<pubDate>Sat, 08 Jun 2024 16:25:08 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44561/bactopia-a-flexible-pipeline-for-complete-analysis-of-bacterial-genomes</link>
	<title><![CDATA[Bactopia: a flexible pipeline for complete analysis of bacterial genomes]]></title>
	<description><![CDATA[<p>Bactopia is a flexible pipeline for complete analysis of bacterial genomes. The goal of Bactopia is process your data with a broad set of tools, so that you can get to the fun part of analyses quicker!</p>
<p>Bactopia was inspired by&nbsp;<a href="https://staphopia.github.io/">Staphopia</a>, a workflow we (Tim Read and myself) released that is targeted towards&nbsp;<em>Staphylococcus aureus</em>&nbsp;genomes. Using what we learned from Staphopia and user feedback, Bactopia was developed from scratch with usability, portability, and speed in mind from the start.</p>
<p>Bactopia uses&nbsp;<a href="https://www.nextflow.io/">Nextflow</a>&nbsp;to manage the workflow, allowing for support of many types of environments (e.g. cluster or cloud). Bactopia allows for the usage of many public datasets as well as your own datasets to further enhance the analysis of your sequencing. Bactopia only uses software packages available from&nbsp;<a href="https://bioconda.github.io/">Bioconda</a>&nbsp;and&nbsp;<a href="https://conda-forge.org/">Conda-Forge</a>&nbsp;to make installation as simple as possible for&nbsp;<em>all</em>&nbsp;users.</p>
<p>To highlight the use of&nbsp;<a href="https://bactopia.github.io/latest/full-guide/">Bactopia</a>&nbsp;and&nbsp;<a href="https://bactopia.github.io/latest/bactopia-tools/">Bactopia Tools</a>, we performed an analysis of 1,664 public&nbsp;<em>Lactobacillus</em>&nbsp;genomes, focusing on&nbsp;<em>Lactobacillus crispatus</em>, a species that is a common part of the human vaginal microbiome. The results from this analysis are published in mSystems under the title:&nbsp;<em><a href="https://doi.org/10.1128/mSystems.00190-20">Bactopia: a flexible pipeline for complete analysis of bacterial genomes</a></em></p>
<p><a href="https://bactopia.github.io/latest/assets/bactopia-workflow.png"><img src="https://bactopia.github.io/latest/assets/bactopia-workflow.png" alt="Bactopia Workflow" style="border: 0px;"></a></p><p>Address of the bookmark: <a href="https://bactopia.github.io/latest/" rel="nofollow">https://bactopia.github.io/latest/</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44628/uncovar-workflow-for-transparent-and-robust-virus-variant-calling-genome-reconstruction-and-lineage-assignment</guid>
	<pubDate>Mon, 05 Aug 2024 23:01:29 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44628/uncovar-workflow-for-transparent-and-robust-virus-variant-calling-genome-reconstruction-and-lineage-assignment</link>
	<title><![CDATA[UnCoVar: Workflow for Transparent and Robust Virus Variant Calling, Genome Reconstruction and Lineage Assignment]]></title>
	<description><![CDATA[<p>UnCoVar: Workflow for Transparent and Robust Virus Variant Calling, Genome Reconstruction and Lineage Assignment</p>
<ul>
<li>
<p>Using state of the art tools, easily extended for other viruses</p>
</li>
<li>
<p>Tool and database updates for critical components via Conda</p>
</li>
<li>
<p>Built using modern design patterns with Conda and Snakemake</p>
</li>
<li>
<p>Extensible and easy to customize</p>
</li>
<li>
<p>Submission Ready Genomes</p>
</li>
<li>
<p>Customizable reporting with comprehensive visualization</p>
</li>
</ul>
<p>https://ikim-essen.github.io/uncovar/</p>
<p>Github&nbsp;https://github.com/IKIM-Essen/uncovar</p>
<p>&nbsp;</p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="https://ikim-essen.github.io/uncovar/" rel="nofollow">https://ikim-essen.github.io/uncovar/</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/4211/socbin-bioinformatics-2014</guid>
  <pubDate>Tue, 03 Sep 2013 18:50:20 -0500</pubDate>
  <link></link>
  <title><![CDATA[SocBiN Bioinformatics 2014]]></title>
  <description><![CDATA[
<p>14th annual conference in Bioinformatics</p>

<p>Date : June 10-13</p>

<p>Organizers: The Society for Bioinformatics in Northern European countries (SocBiN) and the Norwegian Bioinformatics Platform / ELIXIR.NO </p>

<p>Venue: Department of Informatics, University of Oslo, Norway</p>

<p>Topics:<br />Tools and technologies for integrative bioinformatics<br />Metagenomics<br />Comparative genomics and phylogeny<br />Post-ENCODE bioinformatics<br />Gene regulation<br />Cancer genomes<br />Marine genomics</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38212/megahit-an-ultra-fast-single-node-solution-for-large-and-complex-metagenomics-assembly-via-succinct-de-bruijn-graph</guid>
	<pubDate>Wed, 14 Nov 2018 04:50:27 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38212/megahit-an-ultra-fast-single-node-solution-for-large-and-complex-metagenomics-assembly-via-succinct-de-bruijn-graph</link>
	<title><![CDATA[MEGAHIT: an ultra-fast single-node solution for large and complex metagenomics assembly via succinct de Bruijn graph]]></title>
	<description><![CDATA[<p><span>MEGAHIT is a single node assembler for large and complex metagenomics NGS reads, such as soil. It makes use of succinct&nbsp;</span><em>de Bruijn</em><span>&nbsp;graph (SdBG) to achieve low memory assembly. MEGAHIT can&nbsp;</span><span>optionally</span><span>&nbsp;utilize a CUDA-enabled GPU to accelerate its SdBG contstruction. The GPU-accelerated version of MEGAHIT has been tested on NVIDIA GTX680 (4G memory) and Tesla K40c (12G memory) with CUDA 5.5, 6.0 and 6.5. MEGAHIT v1.0 or greater also supports IBM Power PC and has been tested on IBM POWER8.</span></p>
<p><span>https://academic.oup.com/bioinformatics/article/31/10/1674/177884</span></p><p>Address of the bookmark: <a href="https://github.com/voutcn/megahit" rel="nofollow">https://github.com/voutcn/megahit</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43048/coverm-read-coverage-calculator-for-metagenomics</guid>
	<pubDate>Thu, 29 Apr 2021 23:39:14 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43048/coverm-read-coverage-calculator-for-metagenomics</link>
	<title><![CDATA[CoverM: Read coverage calculator for metagenomics]]></title>
	<description><![CDATA[<p>CoverM aims to be a configurable, easy to use and fast DNA read coverage and relative abundance calculator focused on metagenomics applications.</p>
<p>CoverM calculates coverage of genomes/MAGs&nbsp;<code>coverm genome</code>&nbsp;(<a href="https://wwood.github.io/CoverM/coverm-genome.html">help</a>) or individual contigs&nbsp;<code>coverm contig</code>&nbsp;(<a href="https://wwood.github.io/CoverM/coverm-contig.html">help</a>). Calculating coverage by read mapping, its input can either be BAM files sorted by reference, or raw reads and reference genomes in various formats.</p><p>Address of the bookmark: <a href="https://github.com/wwood/CoverM" rel="nofollow">https://github.com/wwood/CoverM</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>

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