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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/40940?offset=210</link>
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	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38541/geneoverlap-an-r-package-to-test-and-visualize-gene-overlaps</guid>
	<pubDate>Thu, 27 Dec 2018 19:45:52 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38541/geneoverlap-an-r-package-to-test-and-visualize-gene-overlaps</link>
	<title><![CDATA[GeneOverlap: An R package to test and visualize gene overlaps]]></title>
	<description><![CDATA[<p>Overlapping gene lists can reveal biological meanings and may lead to novel hypotheses. For example, histone modification is an important cellular mechanism that can pack and re-pack chromatin. By making the chromatin structure more dense or loose, the gene expression can be turned on or off. Tri-methylation on lysine 4 of histone H3 (H3K4me3) is associated with gene activation and its genome-wide enrichment can be mapped by using ChIP-seq experiments. Because of its activating role, if we overlap the genes that are bound by H3K4me3 with the genes that are highly expressed, we should expect a positive association. Similary, we can perform such kind of overlapping between the gene lists of different histone modifications with that of various expression groups and establish each histone modification&rsquo;s role in gene regulation.</p><p>Address of the bookmark: <a href="https://bioconductor.org/packages/release/bioc/vignettes/GeneOverlap/inst/doc/GeneOverlap.pdf" rel="nofollow">https://bioconductor.org/packages/release/bioc/vignettes/GeneOverlap/inst/doc/GeneOverlap.pdf</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40591/modelstudio-a-package-automates-the-explanation-of-machine-learning-predictive-models</guid>
	<pubDate>Wed, 22 Jan 2020 23:58:11 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40591/modelstudio-a-package-automates-the-explanation-of-machine-learning-predictive-models</link>
	<title><![CDATA[modelStudio: a package automates the explanation of machine learning predictive models]]></title>
	<description><![CDATA[<p>The&nbsp;<code>modelStudio</code>&nbsp;package automates the explanation of machine learning predictive models. This package generates advanced interactive and animated model explanations in the form of a serverless HTML site.</p>
<p>It combines&nbsp;<strong>R</strong>&nbsp;with&nbsp;<strong>D3.js</strong>&nbsp;to produce plots and descriptions for various local and global explanations. Tools for model exploration unite with tools for EDA (Exploratory Data Analysis) to give a broad overview of the model behavior.&nbsp;<code>modelStudio</code>&nbsp;is a fast and condensed way to get all the answers without much effort. Break down your model and look into its ingredients with only a few lines of code.</p><p>Address of the bookmark: <a href="https://modeloriented.github.io/modelStudio/index.html" rel="nofollow">https://modeloriented.github.io/modelStudio/index.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41362/genemates-an-r-package-for-detecting-horizontal-gene-co-transfer-between-bacteria-using-gene-gene-associations-controlled-for-population-structure</guid>
	<pubDate>Sat, 07 Mar 2020 05:52:20 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41362/genemates-an-r-package-for-detecting-horizontal-gene-co-transfer-between-bacteria-using-gene-gene-associations-controlled-for-population-structure</link>
	<title><![CDATA[GeneMates: an R package for Detecting Horizontal Gene Co-transfer between Bacteria Using Gene-gene Associations Controlled for Population Structure]]></title>
	<description><![CDATA[<p><span>GeneMates is an R package implementing a network approach to identify horizontal gene co-transfer (HGcoT) between bacteria using whole-genome sequencing (WGS) data. It is particularly useful for investigating intra-species HGcoT, where presence-absence status of acquired genes is usually confounded by bacterial population structure due to clonal reproduction.</span></p>
<p><a href="https://www.biorxiv.org/content/10.1101/2020.02.29.970970v1">https://www.biorxiv.org/content/10.1101/2020.02.29.970970v1</a></p><p>Address of the bookmark: <a href="https://github.com/wanyuac/GeneMates" rel="nofollow">https://github.com/wanyuac/GeneMates</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44414/reconplot-an-r-package-for-the-visualization-and-interpretation-of-genomic-rearrangements</guid>
	<pubDate>Thu, 14 Dec 2023 12:33:19 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44414/reconplot-an-r-package-for-the-visualization-and-interpretation-of-genomic-rearrangements</link>
	<title><![CDATA[ReConPlot: an R package for the visualization and interpretation of genomic rearrangements]]></title>
	<description><![CDATA[<p>ReConPlot (REarrangement and COpy Number PLOT), an R package that provides functionalities for the joint visualization of SCNAs and SVs across one or multiple chromosomes. ReConPlot is based on the popular ggplot2 package, thus allowing customization of plots and the generation of publication-quality figures with minimal effort.</p><p>Address of the bookmark: <a href="https://academic.oup.com/bioinformatics/article/39/12/btad719/7460198?login=false" rel="nofollow">https://academic.oup.com/bioinformatics/article/39/12/btad719/7460198?login=false</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/34702/run-miniasm-assembler-on-nanopore-reads</guid>
	<pubDate>Mon, 18 Dec 2017 04:07:50 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/34702/run-miniasm-assembler-on-nanopore-reads</link>
	<title><![CDATA[Run miniasm assembler on nanopore reads !]]></title>
	<description><![CDATA[<p>Miniasm is a very fast OLC-based&nbsp;<em>de novo</em>&nbsp;assembler for noisy long reads. It takes all-vs-all read self-mappings (typically by&nbsp;<a href="https://github.com/lh3/minimap">minimap</a>) as input and outputs an assembly graph in the&nbsp;<a href="https://github.com/pmelsted/GFA-spec/blob/master/GFA-spec.md">GFA</a>&nbsp;format. Different from mainstream assemblers, miniasm does not have a consensus step. It simply concatenates pieces of read sequences to generate the final&nbsp;<a href="http://wgs-assembler.sourceforge.net/wiki/index.php/Celera_Assembler_Terminology">unitig</a>&nbsp;sequences. Thus the per-base error rate is similar to the raw input reads.</p><p>Find the detail of the reads repeats:</p><blockquote><p>fq2fa ONT_A.fastq ONT_A.fasta&nbsp;<br /><br />minimap2 -xava-ont ONT_A.fasta ONT_A.fasta -t10 -X &gt; AONT.paf&nbsp;<br /><br />awk '{if($1==$6){print}}' AONT.paf &gt; AONTself.paf&nbsp;<br /><br />awk '$5=="-"' AONTself.paf | awk '{print $1}'| sort|uniq &gt; invertedrepeat.list</p></blockquote><p>Generated a few palindrome and repeats plots (highlighting only repeats largest than 10, 20 and 30 kb)</p><blockquote><p>minidot -f 5 -m 30000 AONTself.paf &gt; AONTself30000.eps&nbsp;<br />sed 's/_template_pass_FAH31515//' AONTself30000.eps &gt; AONTself30000final.eps&nbsp;<br /><br />minidot -f 5 -m 20000 AONTself.paf &gt; AONTself20000.eps&nbsp;<br />sed 's/_template_pass_FAH31515//' AONTself20000.eps &gt; AONTself20000final.eps&nbsp;<br /><br />minidot -f 5 -m 10000 AONTself.paf &gt; AONTself10000.eps&nbsp;<br />sed 's/_template_pass_FAH31515//' AONTself10000.eps &gt; AONTself10000final.eps&nbsp;</p></blockquote><p>Assemble with miniasm:</p><blockquote><p>miniasm -f ONT_A.fasta AONT.paf &gt; AONT.gfa&nbsp;</p><p>grep '^S' AONT.gfa |awk '{print "&gt;"$2"\n"$3}' &gt; AONT_miniasm.fasta&nbsp;<br /><br />minimap2 -xasm10 AONT_miniasm.fasta AONT_miniasm.fasta -t1 -X &gt; AONT_miniasm.paf&nbsp;<br /><br />awk '{if($1==$6){print}}' AONT_miniasm.paf &gt; AONT_miniasm_self.paf&nbsp;<br /><br />minidot -f 5 -m 10000 AONT_miniasm_self.paf &gt; AONT_miniasm_self10000.eps&nbsp;</p></blockquote><p>Njoy the assembly !</p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36607/tarean-a-computational-tool-for-identification-and-characterization-of-satellite-dna-from-unassembled-short-reads</guid>
	<pubDate>Tue, 15 May 2018 02:53:11 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36607/tarean-a-computational-tool-for-identification-and-characterization-of-satellite-dna-from-unassembled-short-reads</link>
	<title><![CDATA[TAREAN: A computational tool for identification and characterization of satellite DNA from unassembled short reads]]></title>
	<description><![CDATA[<p><strong>TA</strong>ndem&nbsp;<strong>RE</strong>peat&nbsp;<strong>AN</strong>alyzer -TAREAN &ndash; is a computational pipeline for&nbsp;<strong>unsupervised identification of satellite repeats</strong>&nbsp;from unassembled sequence reads. The pipeline uses low-pass whole genome sequence reads and performs their graph-based clustering. Resulting clusters, representing all types of repeats, are then examined for the presence of circular structures and putative satellite repeats are reported.</p>
<p><em><strong>How to use TAREAN</strong></em>:</p>
<ul>
<li>Install a local instance of the pipeline using its source code available from&nbsp;<a href="https://bitbucket.org/petrnovak/repex_tarean" target="_blank" title="TAREAN source code">bitbucket repository</a>.</li>
<li>Use&nbsp; public Galaxy-based server at&nbsp;<a href="https://repeatexplorer-elixir.cerit-sc.cz/" target="_blank">https://repeatexplorer-elixir.cerit-sc.cz/</a>. The server is provided in frame of the&nbsp;<a href="https://www.elixir-czech.cz/" target="_blank">Elixir CZ project</a>&nbsp;and is maintained by&nbsp;<a href="https://www.cesnet.cz/" target="_blank">CESNET</a>&nbsp;and&nbsp;<a href="https://www.cerit-sc.cz/en/index.html" target="_blank">CERIT-SC</a>. Simple registration is required to use this service.</li>
</ul>
<p>Development of TAREAN was supported by&nbsp;<a href="https://www.elixir-czech.cz/" target="_blank" title="ELIXIR-CZ">ELIXIR CZ</a>&nbsp;research infrastructure project (MEYS Grant No: LM2015047).</p>
<p><strong><em>References</em></strong></p>
<p>Novak, P., Avila Robledillo, L., Koblizkova, A., Vrbova, I., Neumann, P., Macas, J. (2017) &ndash;&nbsp;<a href="https://academic.oup.com/nar/article/3574061/" target="_blank">TAREAN: a computational tool for identification and characterization of satellite DNA from unassembled short reads</a>.&nbsp;<em>Nucleic Acids Res.</em>, doi:10.1093/nar/gkx257</p><p>Address of the bookmark: <a href="https://bitbucket.org/petrnovak/repex_tarean" rel="nofollow">https://bitbucket.org/petrnovak/repex_tarean</a></p>]]></description>
	<dc:creator>Surabhi Chaudhary</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36739/blasr-mapping-single-molecule-sequencing-reads-using-basic-local-alignment-with-successive-refinement-blasr-theory-and-application</guid>
	<pubDate>Wed, 23 May 2018 06:54:32 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36739/blasr-mapping-single-molecule-sequencing-reads-using-basic-local-alignment-with-successive-refinement-blasr-theory-and-application</link>
	<title><![CDATA[BlasR Mapping single molecule sequencing reads using Basic Local Alignment with Successive Refinement (BLASR): Theory and Application,]]></title>
	<description><![CDATA[<p><span>BLASR (Basic Local Alignment with Successive Refinement) for mapping Single Molecule Sequencing (SMS) reads that are thousands to tens of thousands of bases long with divergence between the read and genome dominated by insertion and deletion error.</span></p>
<p>Here is how I use the blasr to align PacBio reads to the contigs (target.fasta). The &ldquo;target.fasta.sa&rdquo; is the suffix array from &ldquo;target.fasta&rdquo; generated by sawriter.</p>
<blockquote>
<p>blasr query.fa ./target.fasta -sa ./target.fasta.sa -bestn 40 -maxScore -500 -m 4 -nproc 24 -out target.m4 -maxLCPLength 15</p>
</blockquote>
<p>the output format option &ldquo;-m 4&Prime; generate the alignment coordinate. Not fully documented, but I can explain that to you.&nbsp;</p>
<p>I use a 24 cores / 48G ram server for the alignment. It took about 2 to 3 hours aligning 3G PacBio Reads to 10^6 sequences of short read contigs with a mean 3.5kbp length.</p><p>Address of the bookmark: <a href="http://bix.ucsd.edu/projects/blasr/" rel="nofollow">http://bix.ucsd.edu/projects/blasr/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36918/p-rna-scaffolder-a-fast-and-accurate-genome-scaffolder-using-paired-end-rna-sequencing-reads</guid>
	<pubDate>Tue, 12 Jun 2018 08:14:41 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36918/p-rna-scaffolder-a-fast-and-accurate-genome-scaffolder-using-paired-end-rna-sequencing-reads</link>
	<title><![CDATA[P_RNA_scaffolder: a fast and accurate genome scaffolder using paired-end RNA-sequencing reads]]></title>
	<description><![CDATA[P_RNA_scaffolder, a fast and accurate tool using paired-end RNA-sequencing reads to scaffold genomes. This tool aims to improve the completeness of both protein-coding and non-coding genes. After this tool was applied to scaffolding human contigs, the structures of both protein-coding genes and circular RNAs were almost completely recovered and equivalent to those in a complete genome, especially for long proteins and long circular RNAs.<p>Address of the bookmark: <a href="http://www.fishbrowser.org/software/P_RNA_scaffolder/" rel="nofollow">http://www.fishbrowser.org/software/P_RNA_scaffolder/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37574/simlord-a-read-simulator-for-third-generation-sequencing-reads</guid>
	<pubDate>Wed, 22 Aug 2018 10:40:27 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37574/simlord-a-read-simulator-for-third-generation-sequencing-reads</link>
	<title><![CDATA[SimLoRD: A read simulator for third generation sequencing reads]]></title>
	<description><![CDATA[<p>SimLoRD is a read simulator for third generation sequencing reads and is currently focused on the Pacific Biosciences SMRT error model.</p>
<p>Reads are simulated from both strands of a provided or randomly generated reference sequence.</p>
<div id="rst-header-features">
<ul>
<li>The reference can be read from a FASTA file or randomly generated with a given GC content. It can consist of several chromosomes, whose structure is respected when drawing reads. (Simulation of genome rearrangements may be incorporated at a later stage.)</li>
<li>The read lengths can be determined in four ways: drawing from a log-normal distribution (typical for genomic DNA), sampling from an existing FASTQ file (typical for RNA), sampling from a a text file with integers (RNA), or using a fixed length</li>
<li>Quality values and number of passes depend on fragment length.</li>
<li>Provided subread error probabilities are modified according to number of passes</li>
<li>Outputs reads in FASTQ format and alignments in SAM format</li>
</ul>
</div><p>Address of the bookmark: <a href="https://bitbucket.org/genomeinformatics/simlord/" rel="nofollow">https://bitbucket.org/genomeinformatics/simlord/</a></p>]]></description>
	<dc:creator>Aaryan Lokwani</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37737/rebaler-program-for-conducting-reference-based-assemblies-using-long-reads</guid>
	<pubDate>Tue, 18 Sep 2018 07:52:41 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37737/rebaler-program-for-conducting-reference-based-assemblies-using-long-reads</link>
	<title><![CDATA[Rebaler: program for conducting reference-based assemblies using long reads.]]></title>
	<description><![CDATA[<p>Rebaler is a program for conducting reference-based assemblies using long reads. It relies mainly on&nbsp;<a href="https://github.com/lh3/minimap2">minimap2</a>&nbsp;for alignment and&nbsp;<a href="https://github.com/isovic/racon">Racon</a>&nbsp;for making consensus sequences.</p>
<p>I made Rebaler for bacterial genomes (specifically for the task of&nbsp;<a href="https://github.com/rrwick/Basecalling-comparison">testing basecallers</a>). It should in principle work for non-bacterial genomes as well, but I haven't tested it.</p><p>Address of the bookmark: <a href="https://github.com/rrwick/Rebaler" rel="nofollow">https://github.com/rrwick/Rebaler</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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