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<channel>
	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/38420?offset=140</link>
	<atom:link href="https://bioinformaticsonline.com/related/38420?offset=140" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39947/radar-charts-with-ggplot2</guid>
	<pubDate>Tue, 17 Sep 2019 23:01:28 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39947/radar-charts-with-ggplot2</link>
	<title><![CDATA[radar charts with ggplot2]]></title>
	<description><![CDATA[<p><code>ggradar</code>&nbsp;allows you to build radar charts with ggplot2. This package is based on&nbsp;<a href="http://rstudio-pubs-static.s3.amazonaws.com/5795_e6e6411731bb4f1b9cc7eb49499c2082.html">Paul Williamson&rsquo;s</a>&nbsp;code, with new aesthetics and compatibility with ggplot2 2.0.</p>
<p>It was inspired by&nbsp;<a href="http://www.buildingwidgets.com/blog/2015/12/9/week-49-d3radarr">d3radaR</a>, an htmlwidget built by&nbsp;<a href="https://github.com/timelyportfolio">timelyportfolio</a>.</p><p>Address of the bookmark: <a href="https://github.com/ricardo-bion/ggradar" rel="nofollow">https://github.com/ricardo-bion/ggradar</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40583/trelliscope-flexibly-visualize-large-complex-data-in-great-detail-from-within-the-r-statistical-programming-environment</guid>
	<pubDate>Tue, 21 Jan 2020 04:22:49 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40583/trelliscope-flexibly-visualize-large-complex-data-in-great-detail-from-within-the-r-statistical-programming-environment</link>
	<title><![CDATA[Trelliscope: flexibly visualize large, complex data in great detail from within the R statistical programming environment.]]></title>
	<description><![CDATA[<p>Trelliscope provides a way to flexibly visualize large, complex data in great detail from within the R statistical programming environment. Trelliscope is a component in the<span>&nbsp;</span><a href="http://deltarho.org/docs-trelliscope/deltarho.org">DeltaRho</a><span>&nbsp;</span>environment.</p>
<p>For those familiar with<span>&nbsp;</span><a href="http://cm.bell-labs.com/cm/ms/departments/sia/project/trellis/">Trellis Display</a>,<span>&nbsp;</span><a href="http://docs.ggplot2.org/0.9.3.1/facet_wrap.html">faceting in ggplot</a>, or the notion of<span>&nbsp;</span><a href="http://en.wikipedia.org/wiki/Small_multiple">small multiples</a>, Trelliscope provides a scalable way to break a set of data into pieces, apply a plot method to each piece, and then arrange those plots in a grid and interactively sort, filter, and query panels of the display based on metrics of interest. With Trelliscope, we are able to create multipanel displays on data with a very large number of subsets and view them in an interactive and meaningful way.</p><p>Address of the bookmark: <a href="http://deltarho.org/docs-trelliscope/#introduction" rel="nofollow">http://deltarho.org/docs-trelliscope/#introduction</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/41043/postdoctoral-scientist-genome-analytics-genome-bioinformatics-mf</guid>
  <pubDate>Sun, 16 Feb 2020 02:57:40 -0600</pubDate>
  <link></link>
  <title><![CDATA[Postdoctoral scientist genome analytics/ genome bioinformatics (m/f/*)]]></title>
  <description><![CDATA[
<p>https://www.uksh.de/jobs/Stellenangebote-nr-20190570-p-8.html<br />Your profile:<br />Degree in bioinformatics, biostatistics, or equivalent<br />Experience in the processing and analysis of large-scale genomics data using compute clusters / high-performance computing<br />Strong competence in working in Unix/Linux environments (shell)<br />Strong programming skills (in particular: Python, R, Perl)<br />Experience with using git and snakemake<br />Fluent English language skills, both spoken and written<br />Strong communication skills and motivation to work in a young, interdisciplinary, dynamic team</p>

<p>Additional Information:</p>

<p>If you have any questions about scientific aspects of this position, please contact Prof. Lars Bertram, head of LIGA (lars.bertram@uni-luebeck.de).</p>

<p>Please contact Ms. Anna Wolbert for further questions about administrative details (recruiting@uksh.de).</p>

<p>Weitere Informationen erhalten Sie auch unter www.uksh.de/karriere.</p>

<p>Wir freuen uns auf Ihre Bewerbung bis zum 15.03.2020 unter Angabe unserer Ausschreibungsnummer 20190570.119.CL.</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43254/quasr-quantification-and-annotation-of-short-reads-in-r</guid>
	<pubDate>Fri, 13 Aug 2021 07:44:05 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43254/quasr-quantification-and-annotation-of-short-reads-in-r</link>
	<title><![CDATA[QuasR: Quantification and annotation of short reads in R]]></title>
	<description><![CDATA[<p>The <em><a href="https://bioconductor.org/packages/3.14/QuasR">QuasR</a></em> package (short for <em>Qu</em>antify and <em>a</em>nnotate <em>s</em>hort reads in <em>R</em>) integrates the functionality of several <strong>R</strong> packages (such as <em><a href="https://bioconductor.org/packages/3.14/IRanges">IRanges</a></em> <span>(Lawrence et al. 2013)</span> and <em><a href="https://bioconductor.org/packages/3.14/Rsamtools">Rsamtools</a></em>) and external software (e.g.&nbsp;<code>bowtie</code>, through the <em><a href="https://bioconductor.org/packages/3.14/Rbowtie">Rbowtie</a></em> package, and <code>HISAT2</code>, through the <em><a href="https://bioconductor.org/packages/3.14/Rhisat2">Rhisat2</a></em> package). The package aims to cover the whole analysis workflow of typical high throughput sequencing experiments, starting from the raw sequence reads, over pre-processing and alignment, up to quantification. A single <strong>R</strong> script can contain all steps of a complete analysis, making it simple to document, reproduce or share the workflow containing all relevant details.</p><p>Address of the bookmark: <a href="https://www.bioconductor.org/packages/devel/bioc/vignettes/QuasR/inst/doc/QuasR.html" rel="nofollow">https://www.bioconductor.org/packages/devel/bioc/vignettes/QuasR/inst/doc/QuasR.html</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44362/biostats-book</guid>
	<pubDate>Mon, 14 Aug 2023 03:11:39 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44362/biostats-book</link>
	<title><![CDATA[Biostats book !]]></title>
	<description><![CDATA[<p>https://practical-stats-med-r.netlify.app/</p><p>Address of the bookmark: <a href="https://practical-stats-med-r.netlify.app/" rel="nofollow">https://practical-stats-med-r.netlify.app/</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36720/dupcar-reconstructing-contiguous-ancestral-regions-with-duplications</guid>
	<pubDate>Mon, 21 May 2018 11:09:02 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36720/dupcar-reconstructing-contiguous-ancestral-regions-with-duplications</link>
	<title><![CDATA[DUPCAR: Reconstructing Contiguous Ancestral Regions with Duplications]]></title>
	<description><![CDATA[we propose a heuristic algorithm, called DUPCAR, for reconstructing ancestral genomic orders with duplications. The method starts from the order of genes in modern genomes and predicts predecessor and successor relationships in the ancestor. Then a greedy algorithm is used to reconstruct the ancestral orders by connecting genes into contiguous regions based on predicted adjacencies. Computer simulation was used to validate the algorithm. We also applied the method to reconstruct the ancestral chromosome X of placental mammals and the ancestral genomes of the ciliate Paramecium tetraurelia.<p>Address of the bookmark: <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3205822/" rel="nofollow">https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3205822/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/34221/alignment-free-sequence-comparison-tools-available-for-next-generation-sequencing-data-analysis</guid>
	<pubDate>Tue, 07 Nov 2017 05:33:33 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/34221/alignment-free-sequence-comparison-tools-available-for-next-generation-sequencing-data-analysis</link>
	<title><![CDATA[Alignment-free sequence comparison tools available for next-generation sequencing data analysis]]></title>
	<description><![CDATA[<div><p><span>kallisto</span></p></div><div><p>Transcript abundance quantification from RNA-seq data (uses pseudoalignment for rapid determination of read compatibility with targets)</p><p>Software (C++)</p><p><a href="https://pachterlab.github.io/kallisto/">https://pachterlab.github.io/kallisto/</a></p><p>Sailfish</p><p>Estimation of isoform abundances from reference sequences and RNA-seq data (<em>k</em>-mer based)</p><p>Software (C++)</p><p><a href="http://www.cs.cmu.edu/~ckingsf/software/sailfish/">http://www.cs.cmu.edu/~ckingsf/software/sailfish/</a></p><p>Salmon</p><p>Quantification of the expression of transcripts using RNA-seq data (uses&nbsp;<em>k</em>-mers)</p><p><a href="https://combine-lab.github.io/salmon/">https://combine-lab.github.io/salmon/</a></p><p>RNA-Skim</p><p>RNA-seq quantification at transcript-level (partitions the transcriptome into disjoint transcript clusters; uses&nbsp;<em>sig</em>-mers, a special type of&nbsp;<em>k</em>-mers)</p><p>Software (C++)</p><p><a href="http://www.csbio.unc.edu/rs/">http://www.csbio.unc.edu/rs/</a></p><p>Variant calling</p><p>ChimeRScope</p><p>Fusion transcript prediction using gene&nbsp;<em>k</em>-mers profiles of the RNA-seq paired-end reads</p><p>Software (Java)</p><p><a href="https://github.com/ChimeRScope/ChimeRScope/wiki">https://github.com/ChimeRScope/ChimeRScope/wiki</a></p><p>FastGT</p><p>Genotyping of known SNV/SNP variants directly from raw NGS sequence reads by counting unique&nbsp;<em>k</em>-mers</p><p>Software (C)</p><p><a href="https://github.com/bioinfo-ut/GenomeTester4/">https://github.com/bioinfo-ut/GenomeTester4/</a></p><p>Phy-Mer</p><p>Reference-independent mitochondrial haplogroup classifier from NGS data (<em>k</em>-mer based)</p><p>Software (Python)</p><p><a href="https://github.com/danielnavarrogomez/phy-mer">https://github.com/danielnavarrogomez/phy-mer</a></p><p>LAVA</p><p>Genotyping of known SNPs (dbSNP and Affymetrix's Genome-Wide Human SNP Array) from raw NGS reads (<em>k</em>-mer based)</p><p>Software (C)</p><p><a href="http://lava.csail.mit.edu/">http://lava.csail.mit.edu/</a></p><p>MICADo</p><p>Detection of mutations in targeted third-generation NGS data (can distinguish patients&rsquo; specific mutations; algorithm uses&nbsp;<em>k</em>-mers and is based on colored de Bruijn graphs)</p><p>Software (Python)</p><p><a href="http://github.com/cbib/MICADo">http://github.com/cbib/MICADo</a></p><p>General mapper</p><p>Minimap</p><p>Lightweight and fast read mapper and read overlap detector (uses the concept of &ldquo;minimazers&rdquo;, a special type of&nbsp;<em>k</em>-mers)</p><p>Software (C)</p><p><a href="https://github.com/lh3/minimap">https://github.com/lh3/minimap</a></p><p>Assembly</p><p>De novo genome assembly</p><p>MHAP</p><p>Produces highly continuous assembly (fully resolved chromosome arms) from third-generation long and noisy reads (10 kbp) using a dimensionality reduction technique MinHash</p><p>Software (Java)</p><p><a href="https://github.com/marbl/MHAP">https://github.com/marbl/MHAP</a></p><p>Miniasm</p><p>Assembler of long noisy reads (SMRT, ONT) using the Overlap-Layout Consensus (OLC) approach without the necessity of an error correction stage (uses minimap)</p><p>Software (C)</p><p><a href="https://github.com/lh3/miniasm">https://github.com/lh3/miniasm</a></p><p>LINKS</p><p>Scaffolding genome assembly with error-containing long sequence (e.g., ONT or PacBio reads, draft genomes)</p><p>Software (Perl)</p><p><a href="https://github.com/warrenlr/LINKS/">https://github.com/warrenlr/LINKS/</a></p><p>Read clustering</p><p>afcluster</p><p>Clustering of reads from different genes and different species based on&nbsp;<em>k</em>-mer counts</p><p>Software (C++)</p><p><a href="https://github.com/luscinius/afcluster">https://github.com/luscinius/afcluster</a></p><p>QCluster</p><p>Clustering of reads with alignment-free measures (<em>k</em>-mer based) and quality values</p><p>Software (C++)</p><p><a href="http://www.dei.unipd.it/~ciompin/main/qcluster.html">http://www.dei.unipd.it/~ciompin/main/qcluster.html</a></p><p>Reads error correction</p><p>Lighter</p><p>Correction of sequencing errors in raw, whole genome sequencing reads (<em>k</em>-mer based)</p><p>Software (C++)</p><p><a href="https://github.com/mourisl/Lighter">https://github.com/mourisl/Lighter</a></p><p>QuorUM</p><p>Error corrector for Illumina reads using k-mers</p><p>Software (C++)</p><p><a href="https://github.com/gmarcais/Quorum">https://github.com/gmarcais/Quorum</a></p><p>Trowel</p><p>Software (C++)</p><p><a href="https://sourceforge.net/projects/trowel-ec/">https://sourceforge.net/projects/trowel-ec/</a></p><p>Metagenomics</p><p>Assembly-free phylogenomics</p><p>AAF</p><p>Phylogeny reconstruction directly from unassembled raw sequence data from whole genome sequencing projects; provides bootstrap support to assess uncertainty in the tree topology (<em>k</em>-mer based)</p><p>Software (Python)</p><p><a href="https://github.com/fanhuan/AAF">https://github.com/fanhuan/AAF</a></p><p>kSNP v3</p><p>Reference-free SNP identification and estimation of phylogenetic trees using SNPs (based on&nbsp;<em>k</em>-mer analysis)</p><p>Software (C)</p><p><a href="https://sourceforge.net/projects/ksnp/files/">https://sourceforge.net/projects/ksnp/files/</a></p><p>NGS-MC</p><p>Phylogeny of species based on NGS reads using alignment-free sequence dissimilarity measures d2* and d2&nbsp;S&nbsp;under different Markov chain models (using&nbsp;<em>k</em>-words)</p><p>R package</p><p><a href="http://www-rcf.usc.edu/~fsun/Programs/NGS-MC/NGS-MC.html">http://www-rcf.usc.edu/~fsun/Programs/NGS-MC/NGS-MC.html</a></p><p>Species identification/taxonomic profiling</p><p>CLARK</p><p>Taxonomic classification of metagenomic reads to known bacterial genomes using&nbsp;<em>k</em>-mer search and LCA assignment</p><p>Software (C++)</p><p><a href="http://clark.cs.ucr.edu/">http://clark.cs.ucr.edu/</a></p><p>FOCUS</p><p>Reports organisms present in metagenomic samples and profiles their abundances (uses composition-based approach and non-negative least squares for prediction)</p><p>Web service Software (Python)</p><p><a href="http://edwards.sdsu.edu/FOCUS/">http://edwards.sdsu.edu/FOCUS/</a></p><p>GSM</p><p>Estimation of abundances of microbial genomes in metagenomic samples (<em>k</em>-mer based)</p><p>Software (Go)</p><p><a href="https://github.com/pdtrang/GSM">https://github.com/pdtrang/GSM</a></p><p>Mash</p><p>Species identification using assembled or unassembled Illumina, PacBio, and ONT data (based on MinHash dimensionality-reduction technique)</p><p>Software (C++)</p><p><a href="https://github.com/marbl/mash">https://github.com/marbl/mash</a></p><p>Kraken</p><p>Taxonomic assignment in metagenome analysis by exact&nbsp;<em>k</em>-mer search; LCA assignment of short reads based on a comprehensive sequence database</p><p>Software (C++)</p><p><a href="https://ccb.jhu.edu/software/kraken/">https://ccb.jhu.edu/software/kraken/</a></p><p>LMAT</p><p>Assignment of taxonomic labels to reads by&nbsp;<em>k</em>-mers searches in precomputed database</p><p>Software (C++/Python)</p><p><a href="https://sourceforge.net/projects/lmat/">https://sourceforge.net/projects/lmat/</a></p><p>stringMLST</p><p><em>k</em>-mer-based tool for MLST directly from the genome sequencing reads</p><p>Software (Python)</p><p><a href="http://jordan.biology.gatech.edu/page/software/stringMLST">http://jordan.biology.gatech.edu/page/software/stringMLST</a></p><p>Taxonomer</p><p><em>k</em>-mer-based ultrafast metagenomics tool for assigning taxonomy to sequencing reads from clinical and environmental samples</p><p>Web service</p><p><a href="http://taxonomer.iobio.io/">http://taxonomer.iobio.io/</a></p><p>Other</p><p>d2-tools</p><p>Word-based (<em>k</em>-tuple) comparison (pairwise dissimilarity matrix using d2S measure) of metatranscriptomic samples from NGS reads</p><p>Software (Python/R)</p><p><a href="https://code.google.com/p/d2-tools/">https://code.google.com/p/d2-tools/</a></p><p>VirHostMatcher</p><p>Prediction of hosts from metagenomic viral sequences based on ONF using various distance measures (e.g., d2)</p><p>Software (C++)</p><p><a href="https://github.com/jessieren/VirHostMatcher">https://github.com/jessieren/VirHostMatcher</a></p><p>MetaFast</p><p>Statistics calculation of metagenome sequences and the distances between them based on assembly using de Bruijn graphs and Bray&ndash;Curtis dissimilarity measure</p><p>Software (Java)</p><p><a href="https://github.com/ctlab/metafast">https://github.com/ctlab/metafast</a></p></div>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37820/s-plot2-rapid-visual-and-statistical-analysis-of-genomic-sequences</guid>
	<pubDate>Tue, 02 Oct 2018 17:57:27 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37820/s-plot2-rapid-visual-and-statistical-analysis-of-genomic-sequences</link>
	<title><![CDATA[S-plot2: Rapid Visual and Statistical Analysis of Genomic Sequences]]></title>
	<description><![CDATA[<p><span>S-plot2 creates an interactive, two-dimensional heatmap capturing the similarities and dissimilarities in nucleotide usage between genomic sequences (partial or complete). In S-plot2, whole eukaryotic chromosomes and smaller prokaryotic genomes can be efficiently compared. The tool includes functionality to extract, analyze, and automate BLAST queries of regions of interest within the heatmap. This facilitates the investigation of quickly evolving coding regions, novel coding regions, and laterally transferred elements.</span></p><p>Address of the bookmark: <a href="https://bitbucket.org/lkalesinskas/splot" rel="nofollow">https://bitbucket.org/lkalesinskas/splot</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44555/ultra-ultra-locates-tandemly-repetitive-areas-effective-labeling-of-repetitive-genomic-sequence</guid>
	<pubDate>Sat, 08 Jun 2024 16:03:39 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44555/ultra-ultra-locates-tandemly-repetitive-areas-effective-labeling-of-repetitive-genomic-sequence</link>
	<title><![CDATA[ULTRA (ULTRA Locates Tandemly Repetitive Areas) : Effective Labeling of Repetitive Genomic Sequence]]></title>
	<description><![CDATA[<p dir="auto">ULTRA is a tool to find and annotate tandem repeats inside genomic sequence. It is able to find repeats of any length and of any period (up to a maximum period of 4000). It can find highly decayed repeats missed by other software, and it will also be able to find very large repeats in highly repetitive sequence, regardless of the size of sequence or length of repeats. ULTRA offers meaningful annotation scores and can produce annotation P-values at user request.</p>
<p dir="auto">More at&nbsp;https://www.biorxiv.org/content/10.1101/2024.06.03.597269v1</p><p>Address of the bookmark: <a href="https://github.com/TravisWheelerLab/ULTRA" rel="nofollow">https://github.com/TravisWheelerLab/ULTRA</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/33983/web-apollo-a-web-based-genomic-annotation-editing-platform</guid>
	<pubDate>Fri, 28 Jul 2017 04:48:17 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/33983/web-apollo-a-web-based-genomic-annotation-editing-platform</link>
	<title><![CDATA[Web Apollo: a web-based genomic annotation editing platform]]></title>
	<description><![CDATA[<p><span>Web Apollo is the first instantaneous, collaborative genomic annotation editor available on the web. One of the natural consequences following from current advances in sequencing technology is that there are more and more researchers sequencing new genomes. These researchers require tools to describe the functional features of their newly sequenced genomes. With Web Apollo researchers can use any of the common browsers (for example, Chrome or Firefox) to jointly analyze and precisely describe the features of a genome in real time, whether they are in the same room or working from opposite sides of the world.</span></p><p>Address of the bookmark: <a href="http://genomearchitect.github.io/" rel="nofollow">http://genomearchitect.github.io/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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