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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/36218?offset=40</link>
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	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36935/assemblytics-delta-file-to-analyze-alignments-of-an-assembly-to-another-assembly-or-a-reference-genome</guid>
	<pubDate>Thu, 14 Jun 2018 07:31:00 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36935/assemblytics-delta-file-to-analyze-alignments-of-an-assembly-to-another-assembly-or-a-reference-genome</link>
	<title><![CDATA[assemblytics: delta file to analyze alignments of an assembly to another assembly or a reference genome]]></title>
	<description><![CDATA[Download and install MUMmer
Align your assembly to a reference genome using nucmer (from MUMmer package)
$ nucmer -maxmatch -l 100 -c 500 REFERENCE.fa ASSEMBLY.fa -prefix OUT
Consult the MUMmer manual if you encounter problems

Optional: Gzip the delta file to speed up upload (usually 2-4X faster)
$ gzip OUT.delta
Then use the OUT.delta.gz file for upload.
Upload the .delta or delta.gz file (view example) to Assemblytics
Important: Use only contigs rather than scaffolds from the assembly. This will prevent false positives when the number of Ns in the scaffolded sequence does not match perfectly to the distance in the reference.

The unique sequence length required represents an anchor for determining if a sequence is unique enough to safely call variants from, which is an alternative to the mapping quality filter for read alignment.

http://assemblytics.com/<p>Address of the bookmark: <a href="http://assemblytics.com/" rel="nofollow">http://assemblytics.com/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39624/cogent-a-tool-for-reconstructing-the-coding-genome-using-high-quality-full-length-transcriptome-sequences</guid>
	<pubDate>Tue, 18 Jun 2019 05:33:04 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39624/cogent-a-tool-for-reconstructing-the-coding-genome-using-high-quality-full-length-transcriptome-sequences</link>
	<title><![CDATA[Cogent: a tool for reconstructing the coding genome using high-quality full-length transcriptome sequences.]]></title>
	<description><![CDATA[<div id="yui_3_14_1_1_1560853173251_3865">Cogent is a tool that identifies gene&nbsp;families and reconstructs the coding genome using high-quality transcriptome data without a reference genome, and can be used to check&nbsp;assemblies&nbsp;for the presence of&nbsp;these known coding sequences.</div>
<div>&nbsp;</div>
<div>
<p>Cogent is a tool for reconstructing the coding genome using high-quality full-length transcriptome sequences. It is designed to be used on&nbsp;<a href="https://github.com/PacificBiosciences/cDNA_primer/wiki">Iso-Seq data</a>&nbsp;and in cases where there is no reference genome or the ref genome is highly incomplete.</p>
<p>See a&nbsp;<a href="https://www.dropbox.com/s/mn6hwhguh0pqceu/20160106_Cogent_developers_conference_slides_Cuttlefish.pdf?dl=0">recent presentation</a>&nbsp;on Cogent being applied to the Cuttlefish Iso-Seq data.</p>
<p><a href="https://www.dropbox.com/s/kz0gi7qg0w82k9a/20161026_Cogent_manuscript_forGitHub.pdf?dl=0">Cogent preliminary draft paper (updated 2016Dec version)</a>,&nbsp;<a href="https://www.dropbox.com/s/37412o8glvnfhf9/20161026_Cogent_ManuscriptPlusSupplement_forGitHub.pdf?dl=0">Supplementary</a></p>
<p>Please see&nbsp;<a href="https://github.com/Magdoll/Cogent/wiki">wiki</a>&nbsp;for details on usage.</p>
</div><p>Address of the bookmark: <a href="https://github.com/Magdoll/Cogent" rel="nofollow">https://github.com/Magdoll/Cogent</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40994/biological-databases</guid>
	<pubDate>Wed, 12 Feb 2020 01:16:29 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40994/biological-databases</link>
	<title><![CDATA[Biological databases !]]></title>
	<description><![CDATA[<p>Now a days there are a lots of genomics databases available around the world. This bookmark is created to provide all links in one place ...</p>
<p>ftp://ftp.ncbi.nih.gov/genomes/</p>
<p>https://hgdownload.soe.ucsc.edu/downloads.html</p><p>Address of the bookmark: <a href="ftp://ftp.ncbi.nih.gov/genomes/" rel="nofollow">ftp://ftp.ncbi.nih.gov/genomes/</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43711/vcf-compare</guid>
	<pubDate>Wed, 19 Jan 2022 10:30:14 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43711/vcf-compare</link>
	<title><![CDATA[VCF Compare !]]></title>
	<description><![CDATA[<h2><span>compare two&nbsp;<strong>BWA</strong>&nbsp;mapping methods with the online hg18-mapped data</span></h2>
<p>We first operate a rapid inspection of the different BAM files using&nbsp;<strong>samtools flagstat</strong>. Illumina provided chr21 read mapping obtained with their&nbsp;<strong>GA IIx</strong>&nbsp;deep sequencing platform &lt;<a href="ftp://webdata:webdata@ussd-ftp.illumina.com/Data/SequencingRuns/NA18507_GAIIx_100_chr21.bam" target="_blank">ftp://webdata:webdata@ussd-ftp.illumina.com/Data/SequencingRuns/NA18507_GAIIx_100_chr21.bam</a>&gt;, aligned to the b36/hg18 reference genome)</p><p>Address of the bookmark: <a href="https://wiki.bits.vib.be/index.php/NGS_Exercise.6#compare_aln_.26_mem_results_with_vcf-compare" rel="nofollow">https://wiki.bits.vib.be/index.php/NGS_Exercise.6#compare_aln_.26_mem_results_with_vcf-compare</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/19090/deeptools</guid>
	<pubDate>Sat, 08 Nov 2014 15:02:08 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/19090/deeptools</link>
	<title><![CDATA[deepTools]]></title>
	<description><![CDATA[<p>deepTools addresses the challenge of handling the large amounts of data that are now routinely generated from DNA sequencing centers. To do so, deepTools contains useful modules to process the mapped reads data to create coverage files in standard bedGraph and bigWig file formats. By doing so, deepTools allows the creation of normalized coverage files or the comparison between two files (for example, treatment and control). Finally, using such normalized and standardized files, multiple visualizations can be created to identify enrichments with functional annotations of the genome.<br /><br />Publicaton: http://nar.oxfordjournals.org/content/early/2014/05/05/nar.gku365.full<br /><br />Source Code and Wiki: https://github.com/fidelram/deepTools/wiki<br /><br />Galaxy Tool Shed repository: http://toolshed.g2.bx.psu.edu/view/bgruening/deeptools<br /><br />and example Galaxy workflows: http://toolshed.g2.bx.psu.edu/view/bgruening/deeptools_workflows</p>]]></description>
	<dc:creator>Martin Jones</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/28855/vcfr</guid>
	<pubDate>Fri, 19 Aug 2016 07:38:24 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/28855/vcfr</link>
	<title><![CDATA[vcfR]]></title>
	<description><![CDATA[<p><span>Most variant calling pipelines result in files containing large quantities of variant information. The&nbsp;</span><a href="http://samtools.github.io/hts-specs/" title="VCF format at hts-specs">variant call format (vcf)</a><span>&nbsp;is an increasingly popular format for this data. The format of these files and their content is discussed in the vignette &lsquo;vcf data.&rsquo; These files are typically intended to be post-processed (i.e., filtered) as an attempt to remove false positives or otherwise problematic sites. The R package vcfR provides tools to facilitate this filtering as well as to visualize the effects of choices made during this process.</span></p><p>Address of the bookmark: <a href="https://cran.r-project.org/web/packages/vcfR/vignettes/visualization_1.html" rel="nofollow">https://cran.r-project.org/web/packages/vcfR/vignettes/visualization_1.html</a></p>]]></description>
	<dc:creator>Archana Malhotra</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36592/lachesis-genome-assembly-with-hi-c-based-contact-probability-maps-lachesis</guid>
	<pubDate>Mon, 14 May 2018 04:26:30 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36592/lachesis-genome-assembly-with-hi-c-based-contact-probability-maps-lachesis</link>
	<title><![CDATA[LACHESIS: Genome Assembly with Hi-C-based Contact Probability Maps (LACHESIS)]]></title>
	<description><![CDATA[<p>LACHESIS is method that exploits contact probability map data (e.g. from Hi-C) for chromosome-scale&nbsp;<em>de novo</em>&nbsp;genome assembly.</p>
<p>Further information about LACHESIS, including source code, documentation and a user's guide are available at:&nbsp;<a href="http://shendurelab.github.io/LACHESIS/">http://shendurelab.github.io/LACHESIS</a>.</p>
<p>Manuscript describing LACHESIS was published as: Burton JN#, Adey A, Patwardhan RP, Qiu R, Kitzman JO, Shendure J#.&nbsp;<em>Chromosome-scale scaffolding of de novo genome assemblies based on chromatin interactions.</em>&nbsp;Nature Biotechnology 2013 Dec;31(12):1119-25. doi:&nbsp;<a href="http://dx.doi.org/10.1038/nbt.2727">10.1038/nbt.272</a>. PubMed PMID:&nbsp;<a href="http://www.ncbi.nlm.nih.gov/pubmed/24185095">24185095</a>.</p>
<p>&nbsp;</p>
<p>http://shendurelab.github.io/LACHESIS/</p><p>Address of the bookmark: <a href="http://shendurelab.github.io/LACHESIS/" rel="nofollow">http://shendurelab.github.io/LACHESIS/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44322/genome-context-viewer-gcv</guid>
	<pubDate>Sun, 21 May 2023 19:33:43 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44322/genome-context-viewer-gcv</link>
	<title><![CDATA[Genome Context Viewer (GCV)]]></title>
	<description><![CDATA[<p><span>The Genome Context Viewer (GCV) is a web-app that visualizes genomic context data provided by third party services. Specifically, it uses functional annotations as a unit of search and comparison. By adopting a common set of annotations, data-store operators can deploy federated instances of GCV, allowing users to compare genomes from different providers in a single interface.</span></p><p>Address of the bookmark: <a href="https://github.com/legumeinfo/gcv" rel="nofollow">https://github.com/legumeinfo/gcv</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26559/microscope</guid>
	<pubDate>Fri, 04 Mar 2016 05:26:31 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26559/microscope</link>
	<title><![CDATA[Microscope]]></title>
	<description><![CDATA[<p>Microscope Platform user documentation.</p>
<p>The MicroScope platform is available at this URL:</p>
<p><a href="https://www.genoscope.cns.fr/agc/microscope">https://www.genoscope.cns.fr/agc/microscope</a></p><p>Address of the bookmark: <a href="http://microscope.readthedocs.org/en/latest/index.html" rel="nofollow">http://microscope.readthedocs.org/en/latest/index.html</a></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42661/3d-genome-browser-explore-chromatin-interaction-data-such-as-hi-c-chia-pet-capture-hi-c-plac-seq-and-more</guid>
	<pubDate>Fri, 22 Jan 2021 20:19:32 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42661/3d-genome-browser-explore-chromatin-interaction-data-such-as-hi-c-chia-pet-capture-hi-c-plac-seq-and-more</link>
	<title><![CDATA[3D Genome Browser: explore chromatin interaction data, such as Hi-C, ChIA-PET, Capture Hi-C, PLAC-Seq, and more]]></title>
	<description><![CDATA[<p><span>Beside visualizing chromatin interaction data, you can also seamlessly browse other omics data such as ChIP-Seq or RNA-Seq for the same genomic region, and gain a complete view of both regulatory landscape and 3D genome structure for any given gene. You can also check the expression of any queried gene across hundreds of tissue/cell types measured by the ENCODE consortium. Finally, please check out the virtual 4C page, where we provide multiple methods to link distal cis-regulatory elements with their potential target genes, including virtual 4C, ChIA-PET and cross-cell-type correlation of proximal and distal DHSs.</span></p><p>Address of the bookmark: <a href="http://3dgenome.fsm.northwestern.edu/index.html" rel="nofollow">http://3dgenome.fsm.northwestern.edu/index.html</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>

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