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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/44541?offset=160</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37527/nanopack-visualizing-and-processing-long-read-sequencing-data</guid>
	<pubDate>Fri, 10 Aug 2018 18:41:34 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37527/nanopack-visualizing-and-processing-long-read-sequencing-data</link>
	<title><![CDATA[NanoPack: visualizing and processing long-read sequencing data]]></title>
	<description><![CDATA[<p>The NanoPack tools are written in Python3 and released under the GNU GPL3.0 License. The source code can be found at&nbsp;<a href="https://github.com/wdecoster/nanopack" target="">https://github.com/wdecoster/nanopack</a>, together with links to separate scripts and their documentation. The scripts are compatible with Linux, Mac OS and the MS Windows 10 subsystem for Linux and are available as a graphical user interface, a web service at&nbsp;<a href="http://nanoplot.bioinf.be/" target="">http://nanoplot.bioinf.be</a>&nbsp;and command line tools.</p>
<p>&nbsp;https://academic.oup.com/bioinformatics/article/34/15/2666/4934939</p><p>Address of the bookmark: <a href="https://github.com/wdecoster/nanoQC" rel="nofollow">https://github.com/wdecoster/nanoQC</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38505/allhic-phasing-and-scaffolding-polyploid-genomes-based-on-hi-c-data</guid>
	<pubDate>Thu, 20 Dec 2018 12:03:32 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38505/allhic-phasing-and-scaffolding-polyploid-genomes-based-on-hi-c-data</link>
	<title><![CDATA[ALLHiC: Phasing and scaffolding polyploid genomes based on Hi-C data]]></title>
	<description><![CDATA[<p><span>The major problem of scaffolding polyploid genome is that Hi-C signals are frequently detected between allelic haplotypes and any existing stat of art Hi-C scaffolding program links the allelic haplotypes together. To solve the problem, we developed a new Hi-C scaffolding pipeline, called ALLHIC, specifically tailored to the polyploid genomes. ALLHIC pipeline contains a total of 5 steps:&nbsp;</span><em>prune</em><span>,&nbsp;</span><em>partition</em><span>,&nbsp;</span><em>rescue</em><span>,&nbsp;</span><em>optimize</em><span>&nbsp;and&nbsp;</span><em>build</em><span>.</span></p><p>Address of the bookmark: <a href="https://github.com/tangerzhang/ALLHiC/wiki" rel="nofollow">https://github.com/tangerzhang/ALLHiC/wiki</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38623/kallisto-a-program-for-quantifying-abundances-of-transcripts-from-bulk-and-single-cell-rna-seq-data</guid>
	<pubDate>Mon, 07 Jan 2019 10:35:14 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38623/kallisto-a-program-for-quantifying-abundances-of-transcripts-from-bulk-and-single-cell-rna-seq-data</link>
	<title><![CDATA[kallisto: a program for quantifying abundances of transcripts from bulk and single-cell RNA-Seq data]]></title>
	<description><![CDATA[<p><strong>kallisto</strong>&nbsp;is a program for quantifying abundances of transcripts from bulk and single-cell RNA-Seq data, or more generally of target sequences using high-throughput sequencing reads. It is based on the novel idea of&nbsp;<em>pseudoalignment</em>&nbsp;for rapidly determining the compatibility of reads with targets, without the need for alignment. On benchmarks with standard RNA-Seq data,&nbsp;<strong>kallisto</strong>&nbsp;can quantify 30 million human reads in less than 3 minutes on a Mac desktop computer using only the read sequences and a transcriptome index that itself takes less than 10 minutes to build. Pseudoalignment of reads preserves the key information needed for quantification, and&nbsp;<strong>kallisto</strong>&nbsp;is therefore not only fast, but also as accurate as existing quantification tools. In fact, because the pseudoalignment procedure is robust to errors in the reads, in many benchmarks&nbsp;<strong>kallisto</strong>&nbsp;significantly outperforms existing tools.&nbsp;<strong>kallisto</strong>&nbsp;is described in detail in:</p>
<p>Nicolas L Bray, Harold Pimentel, P&aacute;ll Melsted and Lior Pachter,&nbsp;<a href="http://www.nature.com/nbt/journal/v34/n5/full/nbt.3519.html">Near-optimal probabilistic RNA-seq quantification</a>, Nature Biotechnology&nbsp;<strong>34</strong>, 525&ndash;527 (2016), doi:10.1038/nbt.3519</p><p>Address of the bookmark: <a href="https://pachterlab.github.io/kallisto/about" rel="nofollow">https://pachterlab.github.io/kallisto/about</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40525/heatmaply-popular-graphical-method-for-visualizing-high-dimensional-data</guid>
	<pubDate>Sat, 11 Jan 2020 07:34:14 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40525/heatmaply-popular-graphical-method-for-visualizing-high-dimensional-data</link>
	<title><![CDATA[heatmaply: popular graphical method for visualizing high-dimensional data]]></title>
	<description><![CDATA[<p>This work is based on ggplot2 and plotly.js engine. It produces similar heatmaps as d3heatmap, with the advantage of speed (plotly.js is able to handle larger size matrix), and the ability to zoom from the dendrogram.</p>
<p>heatmaply also provides an interface based around the&nbsp;<a href="https://cran.r-project.org/package=plotly">plotly R package</a>. This interface can be used by choosing&nbsp;<code>plot_method = "plotly"</code>&nbsp;instead of the default&nbsp;<code>plot_method = "ggplot"</code>. This interface can provide smaller objects and faster rendering to disk in many cases and provides otherwise almost identical features.</p>
<p>Documentation for this package is also available as a&nbsp;<a href="https://cran.r-project.org/package=pkgdown">pkgdown</a>&nbsp;site:&nbsp;<a href="http://talgalili.github.io/heatmaply/">http://talgalili.github.io/heatmaply/</a></p><p>Address of the bookmark: <a href="http://talgalili.github.io/heatmaply/articles/heatmaply.html" rel="nofollow">http://talgalili.github.io/heatmaply/articles/heatmaply.html</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40946/free-genomics-data</guid>
	<pubDate>Fri, 07 Feb 2020 14:08:31 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40946/free-genomics-data</link>
	<title><![CDATA[Free Genomics data !]]></title>
	<description><![CDATA[<p><span>The specimens were collected by the Oxford Wytham Woods and Edinburgh Lohse lab teams. DNA extraction and sequencing was carried out by the Sanger Institute Scientific Operations teams. Assemblies were carried out by the Tree of Life team (Shane McCarthy) and colleagues in Pacific Biosciences (Jonas Korlach).</span></p>
<p><a href="https://www.darwintreeoflife.org/an-initial-set-of-raw-genome-assemblies-from-the-darwin-tree-of-life-project/">https://www.darwintreeoflife.org/an-initial-set-of-raw-genome-assemblies-from-the-darwin-tree-of-life-project/</a></p><p>Address of the bookmark: <a href="https://www.darwintreeoflife.org/an-initial-set-of-raw-genome-assemblies-from-the-darwin-tree-of-life-project/" rel="nofollow">https://www.darwintreeoflife.org/an-initial-set-of-raw-genome-assemblies-from-the-darwin-tree-of-life-project/</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/41562/submit-your-sars-cov-2-sequence-data-to-genbank</guid>
	<pubDate>Thu, 09 Apr 2020 18:28:25 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/41562/submit-your-sars-cov-2-sequence-data-to-genbank</link>
	<title><![CDATA[Submit your SARS-CoV-2 sequence data to GenBank]]></title>
	<description><![CDATA[<div dir="auto">Submit your SARS-CoV-2 sequence data to GenBank and SRA with our new submission landing page. Submission is simple and streamlined *and* there&rsquo;s a rapid turnaround. <span><a href="https://l.facebook.com/l.php?u=https%3A%2F%2Fsubmit.ncbi.nlm.nih.gov%2Fsarscov2%2F%3Ffbclid%3DIwAR3p-OzZPe2yx4CZMoZxiWMF3kUQjXyVVduNQhBdehWmFTJ3cPBstsOLypI&amp;h=AT2d-umit7ciXRW-nrRYVL3gJSLKY4Hte8W8cXw8Wl94n6PGmoHmVqvvhgQj-mTo6A5lpMP9JDV_lRSq9RRLT5KeVVAAfcuRgJOeA6QhApIB2B9nFxUfDCD3sio4HYidpRwpmng&amp;__tn__=-UK-R&amp;c[0]=AT2zWGa1K5EvV4UcnB0b7HHvkBtX-wAyh7AF8_fZ9uI2y-02nOHQHT_Um3xgnto5KEZ26wRG0xNgUWTA1W-7HF0E25E23XtIL5XGOhloBXaDIcHw30AVjTCkQi7aFk4dN7aBCmVJeSbH37urtbM2kmMfyTCbdTvMU8FGlnX-DNVuCaZr4XfXnf_jvPNdxe9sBH84oXJ-uJz5kbqlHGAHDoqK" target="_blank">https://submit.ncbi.nlm.nih.gov/sarscov2/</a></span></div><div dir="auto">&nbsp;</div><div dir="auto"><span><span>Quickly and easily add your SARS-CoV-2 sequence data to the growing public archive with new, special features and support from NCBI. </span><a href="https://submit.ncbi.nlm.nih.gov/sarscov2/">new SARS-CoV-2 sequence submission landing page</a><span>&nbsp;will help you get started. GenBank submissions are accessioned and released in approximately 1-2 working days, and&nbsp;</span><a href="https://www.ncbi.nlm.nih.gov/sra" target="_blank">Sequence Read Archive</a><span>&nbsp;(SRA) submissions typically processed and released within hours. Submission is simple!</span></span></div><div><div dir="auto">&nbsp;</div><div dir="auto">More information is available on NCBI Insights. <span><a href="https://l.facebook.com/l.php?u=https%3A%2F%2Fncbiinsights.ncbi.nlm.nih.gov%2F2020%2F04%2F09%2Fsars-cov2-data-streamlined-submission-rapid-turnaround%2F%3Ffbclid%3DIwAR1OuLu3oDjz3VX4fDq5Jg316td9foTOUGNqnoN1eI2nFXTf4EBv28JiXD4&amp;h=AT0ah_epxwAc-nM6QiPBYvKSQ-kWmiPgHKO1w7SnxnnRiTI4etJJfNAWyzcR7snIdtxtcErAFRdHPBH2j0EY77gUPDdnBVnAsxnVbSgZnrrOPfnni331A37Xvytgnye0ArnUuWk&amp;__tn__=-UK-R&amp;c[0]=AT2zWGa1K5EvV4UcnB0b7HHvkBtX-wAyh7AF8_fZ9uI2y-02nOHQHT_Um3xgnto5KEZ26wRG0xNgUWTA1W-7HF0E25E23XtIL5XGOhloBXaDIcHw30AVjTCkQi7aFk4dN7aBCmVJeSbH37urtbM2kmMfyTCbdTvMU8FGlnX-DNVuCaZr4XfXnf_jvPNdxe9sBH84oXJ-uJz5kbqlHGAHDoqK" target="_blank">https://ncbiinsights.ncbi.nlm.nih.gov/2020/04/09/sars-cov2-data-streamlined-submission-rapid-turnaround/</a></span></div></div>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42271/mcclintock-meta-pipeline-to-identify-transposable-element-insertions-using-next-generation-sequencing-data</guid>
	<pubDate>Tue, 27 Oct 2020 00:21:18 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42271/mcclintock-meta-pipeline-to-identify-transposable-element-insertions-using-next-generation-sequencing-data</link>
	<title><![CDATA[McClintock: Meta-pipeline to identify transposable element insertions using next generation sequencing data]]></title>
	<description><![CDATA[<p><span>an integrated bioinformatics pipeline for the detection of TE insertions in whole-genome shotgun data, called McClintock (</span><a href="https://github.com/bergmanlab/mcclintock">https://github.com/bergmanlab/mcclintock</a><span>), which automatically runs and standardizes output for multiple TE detection methods. We demonstrate the utility of McClintock by evaluating six TE detection methods using simulated and real genome data from the model microbial eukaryote,&nbsp;</span><em>Saccharomyces cerevisiae</em><span>.&nbsp;</span></p><p>Address of the bookmark: <a href="https://github.com/bergmanlab/mcclintock" rel="nofollow">https://github.com/bergmanlab/mcclintock</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42806/graphunzip-phases-an-assembly-graph-using-hi-c-data-andor-long-reads</guid>
	<pubDate>Fri, 05 Feb 2021 21:22:24 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42806/graphunzip-phases-an-assembly-graph-using-hi-c-data-andor-long-reads</link>
	<title><![CDATA[GraphUnzip: Phases an assembly graph using Hi-C data and/or long reads.]]></title>
	<description><![CDATA[<p>GraphUnzip, a fast, memory-efficient and accurate tool to unzip assembly graphs into their constituent haplotypes using long reads and/or Hi-C data. As GraphUnzip only connects sequences in the assembly graph that already had a potential link based on overlaps, it yields high-quality gap-less supercontigs. To demonstrate the efficiency of GraphUnzip, we tested it on a simulated diploid Escherichia coli genome, and on two real datasets for the genomes of the rotifer Adineta vaga and the potato Solanum tuberosum. In all cases, GraphUnzip yielded highly continuous phased assemblies.</p>
<p>https://www.biorxiv.org/content/biorxiv/early/2021/02/01/2021.01.29.428779.full.pdf</p><p>Address of the bookmark: <a href="https://github.com/nadegeguiglielmoni/GraphUnzip" rel="nofollow">https://github.com/nadegeguiglielmoni/GraphUnzip</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43645/corona-virus-genome-and-data-download</guid>
	<pubDate>Sun, 12 Dec 2021 23:34:54 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43645/corona-virus-genome-and-data-download</link>
	<title><![CDATA[Corona Virus Genome and Data Download !]]></title>
	<description><![CDATA[<p>Genes and its related metadata could be found on&nbsp;https://www.ncbi.nlm.nih.gov/datasets/coronavirus/genomes/</p><p>Address of the bookmark: <a href="https://www.ncbi.nlm.nih.gov/datasets/coronavirus/genomes/" rel="nofollow">https://www.ncbi.nlm.nih.gov/datasets/coronavirus/genomes/</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44252/orange-data-mining</guid>
	<pubDate>Mon, 13 Mar 2023 12:42:29 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44252/orange-data-mining</link>
	<title><![CDATA[Orange: Data mining]]></title>
	<description><![CDATA[<div>
<p>Open source machine learning and data visualization.</p>
<p>Build data analysis workflows visually, with a large, diverse toolbox.</p>
<p>&nbsp;</p>
</div><p>Address of the bookmark: <a href="https://orangedatamining.com/" rel="nofollow">https://orangedatamining.com/</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
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