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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/41046?offset=40</link>
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	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38762/katuali-is-a-flexible-consensus-pipeline-implemented-in-snakemake-to-basecall-assemble-and-polish-oxford-nanopore-technologies-sequencing-data</guid>
	<pubDate>Tue, 22 Jan 2019 06:26:55 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38762/katuali-is-a-flexible-consensus-pipeline-implemented-in-snakemake-to-basecall-assemble-and-polish-oxford-nanopore-technologies-sequencing-data</link>
	<title><![CDATA[Katuali is a flexible consensus pipeline implemented in Snakemake to basecall, assemble, and polish Oxford Nanopore Technologies&#039; sequencing data]]></title>
	<description><![CDATA[<ul>
<li>Run a pipeline processing fast5s to a consensus in a single command.</li>
<li>Recommended fixed "standard" and "fast" pipelines.</li>
<li>Interchange basecaller, assembler, and consensus components of the pipelines simply by changing the target filepath.</li>
<li>Seemless distribution of tasks over local or distributed compute.</li>
<li>Highly configurable.</li>
<li>Open source (Mozilla Public License 2.0).</li>
</ul>
<p>Documentation can be found at&nbsp;<a href="https://nanoporetech.github.io/katuali/">https://nanoporetech.github.io/katuali/</a>.</p><p>Address of the bookmark: <a href="https://github.com/nanoporetech/katuali" rel="nofollow">https://github.com/nanoporetech/katuali</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/39827/prof-dr-med-andreas-ramming</guid>
  <pubDate>Wed, 07 Aug 2019 03:25:48 -0500</pubDate>
  <link></link>
  <title><![CDATA[Prof. Dr. med. Andreas Ramming]]></title>
  <description><![CDATA[
<p>In many autoimmune diseases, a misdirected immune response leads to chronic inflammation and subsequently to fibrotic and degenerative tissue remodeling. Therapeutic options are available for inflammatory joint diseases, but only about 40% of patients respond to these existing therapies on a permanent basis. In the remaining cases, these therapies miss their target from the beginning or later during the course of treatment failure. There are currently no causal therapies available for the treatment of fibrotic autoimmune diseases such as systemic sclerosis. Therefore, there is an urgent need to develop new therapeutic options for the treatment of fibrotic and synovitic autoimmune diseases. His group is therefore deal with the molecular mechanisms of these misdirected signaling pathways for the development of novel, targeted therapies</p>

<p>http://www.medizin3.uk-erlangen.de/forschung/arbeitsgruppen/matrixbiologie-entzuendliche-signalwege-in-arthritis-und-fibrose/</p>
]]></description>
</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/41599/haslr-a-hybrid-assembler-which-uses-both-second-and-third-generation-sequencing-reads</guid>
	<pubDate>Mon, 04 May 2020 02:04:03 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41599/haslr-a-hybrid-assembler-which-uses-both-second-and-third-generation-sequencing-reads</link>
	<title><![CDATA[HASLR: a hybrid assembler which uses both second and third generation sequencing reads]]></title>
	<description><![CDATA[<p><span>HASLR, a hybrid assembler which uses both second and third generation sequencing reads to efficiently generate accurate genome assemblies. Our experiments show that HASLR is not only the fastest assembler but also the one with the lowest number of misassemblies on all the samples compared to other tested assemblers. Furthermore, the generated assemblies in terms of contiguity and accuracy are on par with the other tools on most of the samples. Availability. HASLR is an open source tool available at https://github.com/vpc-ccg/haslr.</span></p><p>Address of the bookmark: <a href="https://github.com/vpc-ccg/haslr" rel="nofollow">https://github.com/vpc-ccg/haslr</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43801/smudgeplot-inference-of-ploidy-and-heterozygosity-structure-using-whole-genome-sequencing-data</guid>
	<pubDate>Fri, 25 Feb 2022 04:42:09 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43801/smudgeplot-inference-of-ploidy-and-heterozygosity-structure-using-whole-genome-sequencing-data</link>
	<title><![CDATA[Smudgeplot: Inference of ploidy and heterozygosity structure using whole genome sequencing data]]></title>
	<description><![CDATA[<p dir="auto">This tool extracts heterozygous kmer pairs from kmer count databases and performs gymnastics with them. We are able to disentangle genome structure by comparing the sum of kmer pair coverages (CovA + CovB) to their relative coverage (CovB / (CovA + CovB)). Such an approach also allows us to analyze obscure genomes with duplications, various ploidy levels, etc.</p>
<p dir="auto">Smudgeplots are computed from raw or even better from trimmed reads and show the haplotype structure using heterozygous kmer pairs. For example:</p>
<p dir="auto"><a href="https://user-images.githubusercontent.com/8181573/45959760-f1032d00-c01a-11e8-8576-ff0512c33da9.png" target="_blank"><img src="https://user-images.githubusercontent.com/8181573/45959760-f1032d00-c01a-11e8-8576-ff0512c33da9.png" alt="smudgeexample" style="border: 0px;"></a></p><p>Address of the bookmark: <a href="https://github.com/KamilSJaron/smudgeplot" rel="nofollow">https://github.com/KamilSJaron/smudgeplot</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/19087/dcgor</guid>
	<pubDate>Sat, 08 Nov 2014 14:54:28 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/19087/dcgor</link>
	<title><![CDATA[dcGOR]]></title>
	<description><![CDATA[<p>An R package for analysing ontologies and protein domain annotations has been published in PLoS Computational Biology (http://dx.doi.org/10.1371/journal.pcbi.1003929). The package is distributed as part of CRAN (http://cran.r-project.org/package=dcGOR), and also at GitHub for version control.<br /><br />The dedicated website is available in http://supfam.org/dcGOR, from which several demos are also provided:<br /><br />1. Analysing SCOP domains: http://supfam.org/dcGOR/demo-Fang.html<br /><br />2. Analysing Pfam domains: http://supfam.org/dcGOR/demo-Basu.html<br /><br />3. Analysing InterPro domains: http://supfam.org/dcGOR/demo-Customisation.html<br /><br />&nbsp;</p>]]></description>
	<dc:creator>Martin Jones</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27090/canu-assembling-large-genomes-with-single-molecule-sequencing-and-locality-sensitive-hashing</guid>
	<pubDate>Tue, 26 Apr 2016 11:38:10 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27090/canu-assembling-large-genomes-with-single-molecule-sequencing-and-locality-sensitive-hashing</link>
	<title><![CDATA[CANU: Assembling Large Genomes with Single-Molecule Sequencing and Locality Sensitive Hashing.]]></title>
	<description><![CDATA[<p>Canu is a fork of the&nbsp;<a href="http://wgs-assembler.sourceforge.net/wiki/index.php?title=Main_Page" title="Celera Assembler">Celera Assembler</a>&nbsp;designed for high-noise single-molecule sequencing (such as the PacBio RSII or Oxford Nanopore MinION). The software is currently alpha level, feel free to use and report issues encountered.</p>
<p>Canu is a hierachical assembly pipeline which runs in four steps:</p>
<ul>
<li>Detect overlaps in high-noise sequences using&nbsp;<a href="https://github.com/marbl/MHAP" title="MHAP">MHAP</a></li>
<li>Generate corrected sequence consensus</li>
<li>Trim corrected sequences</li>
<li>Assemble trimmed corrected sequences</li>
</ul>
<p>Read the&nbsp;<a href="http://canu.readthedocs.org/" title="docs">documentation</a></p>
<p>New release https://github.com/marbl/canu/releases</p><p>Address of the bookmark: <a href="https://github.com/marbl/canu" rel="nofollow">https://github.com/marbl/canu</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/27344/orffinder-with-smart-blast</guid>
	<pubDate>Tue, 17 May 2016 01:43:15 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/27344/orffinder-with-smart-blast</link>
	<title><![CDATA[ORFfinder with smart BLAST]]></title>
	<description><![CDATA[<p><span>ORF Finder</span></p><p><span><a href="http://www.ncbi.nlm.nih.gov/orffinder">ORFfinder</a><span>&nbsp;is a graphical analysis tool for finding open reading frames (ORFs). We&rsquo;ve been working on a few updates, and we&rsquo;d like to find out what you think about them. Read on to find out what you can do with the new ORFfinder.</span></span></p><p>Smart BLAST (https://ncbiinsights.ncbi.nlm.nih.gov/2015/07/29/smartblast/)</p><p>Select one or a group of ORFs and BLAST several databases at once, and use the newly developed&nbsp;<a href="http://blast.ncbi.nlm.nih.gov/smartblast/">SmartBLAST</a>&nbsp;to verify protein names.&nbsp;Looking for the traditional results from&nbsp;<a href="http://blast.ncbi.nlm.nih.gov/Blast.cgi">BLAST</a>? They&rsquo;re there too.</p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/27799/bbmapbbtools-package-multipurpose-tool-designed-for-converting-reads-or-other-nucleotide-data-between-different-formats</guid>
	<pubDate>Mon, 13 Jun 2016 05:47:21 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/27799/bbmapbbtools-package-multipurpose-tool-designed-for-converting-reads-or-other-nucleotide-data-between-different-formats</link>
	<title><![CDATA[BBMap/BBTools package: Multipurpose tool designed for converting reads or other nucleotide data between different formats.]]></title>
	<description><![CDATA[<div id="post_message_148585"><a href="https://sourceforge.net/projects/bbmap/" target="_blank">Reformat</a>is a member of the <a href="https://sourceforge.net/projects/bbmap/" target="_blank">BBMap/BBTools package</a>. It is a multipurpose tool designed for converting reads or other nucleotide data between different formats. It supports, and can inter-convert:<br /> <br /> fastq<br /> fasta<br /> fasta+qual<br /> sam<br /> scarf (an old Illumina format)<br /> bam (if samtools is installed)<br /> gzip<br /> zip<br /> ascii-33 (sanger)<br /> ascii-64 (old Illumina)<br /> paired files<br /> interleaved files<br /> <br /> It is multithreaded and can process data at over 500 megabytes per second, and can accept streams from standard in and write to standard out, allowing it to be easily dropped into the middle of a pipeline for format conversion. Reformat autodetects formats based on file extensions and content, making it very easy to use; and the autodetection can be overridden, allowing flexibility for people who don't like to follow naming conventions, or out-of-spec fastq files with qualities values like -17 or 120.<br /> <br /> The program has been gradually expanded, and can now perform various other functions. None of these will break pairing, if the input is paired.<br /> <br /> Quality trimming (either or both ends)<br /> Quality filtering<br /> Fixed-length trimming<br /> Generation of histograms (base composition, quality, etc)<br /> Subsampling (to a fraction of input reads, or an exact number of reads or bases)<br /> Changing fasta line-wrapping length<br /> Reverse-complementing (all reads or only read 2)<br /> Adding /1 and /2 suffix to read names<br /> GC-content filtering<br /> Length-filtering<br /> Testing for corrupted interleaved files<br /> <br /> Reformat is compatible with any platform that supports Java 1.7 or higher. It also has a bash shellscript for simpler invocation. Typical usage examples:<br /> <br /> Reformat fastq into fasta:<br /> <strong>reformat.sh in=x.fq out=y.fa</strong><br /> <br /> Interleave paired reads:<br /> <strong>reformat.sh in1=x1.fq in2=x2.fq out=y.fq</strong><br /> <br /> Note - you can actually use a shortcut if paired read files have the same name with a 1 and a 2. This is equivalent to the above command:<br /> <strong>reformat.sh in=x#.fq out=y.fq</strong><br /> <br /> De-interleave reads:<br /> <strong>reformat.sh in=x.fq out1=y1.fq out2=y2.fq</strong><br /> <br /> Verify that interleaving appears correct, assuming Illumina namimg conventions:<br /> <strong>reformat.sh in=x.fq vint</strong><br /> <br /> Convert ASCII-33 to ASCII-64:<br /> <strong>reformat.sh in=x.fq out=y.fq qin=33 qout=64</strong><br /> <br /> Quality-trim paired reads to Q10 on the left and right ends and discard reads shorter than 50bp after trimming:<br /> <strong>reformat.sh in1=x1.fq in2=x2.fq out1=y1.fq out2=y2.fq outsingle=singletons.fq qtrim=rl trimq=10 minlength=50</strong><br /> <br /> Subsample 10% of the first 20000 pairs in an interleaved file:<br /> <strong>reformat.sh in=x.fq out=y.fq reads=20000 samplerate=0.1 int=t</strong><br /> (in this case "int=t" overrides interleaving autodetection, to ensure reads are treated as pairs)<br /> <br /> Pipe in a gzipped sam file and pipe out fasta:<br /> <strong>reformat.sh in=stdin.sam.gz out=stdout.fa</strong><br /> <br /> Reverse-complement reads:<br /> <strong>reformat.sh in=x.fq out=y.fq rcomp</strong><br /> <br /> For reformatting a file with very long sequences, Reformat will need more memory; just add the additional flag "-Xmx2g". For example, to change the line-wrapping length on the human genome (which has individual sequences over 200Mbp long) to 70 characters:<br /> <strong>reformat.sh -Xmx2g in=HG19.fa.gz out=HG19_wrapped.fa.gz fastawrap=70</strong><br /> <br /> For additional functions, please run the shellscript with no arguments, or just read it with a text editor. If you have any questions, please post them in this thread.<br /> <br /> For people using a non-bash terminal, you may need to type "bash reformat.sh" instead of just "reformat.sh".<br /> For users of Windows or other platforms that do not support bash shellscripts, replace "reformat.sh" with "java -ea -Xmx200m /path/to/bbmap/current/ jgi.ReformatReads"<br /> for example,<br /> <strong>java -ea -Xmx200m C:\bbmap\current\ jgi.ReformatReads in=x.fq out=y.fa</strong><br /> <br /> Reformat can be downloaded with BBTools here:<br /> <a href="https://sourceforge.net/projects/bbmap/" target="_blank">https://sourceforge.net/projects/bbmap/</a></div>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30680/easybuild</guid>
	<pubDate>Fri, 27 Jan 2017 16:00:43 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30680/easybuild</link>
	<title><![CDATA[EasyBuild]]></title>
	<description><![CDATA[<p><a href="https://github.com/hpcugent/easybuild">EasyBuild</a><span>&nbsp;is a software build and installation framework that allows you to manage (scientific) software on High Performance Computing (HPC) systems in an efficient way.</span><br><span>A full list of supported software packages is available&nbsp;</span><a href="http://easybuild.readthedocs.io/en/latest/version-specific/Supported_software.html">here</a><span>.</span></p><p>Address of the bookmark: <a href="https://hpcugent.github.io/easybuild/" rel="nofollow">https://hpcugent.github.io/easybuild/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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