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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/38023?offset=140</link>
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	<description><![CDATA[]]></description>
	
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38758/roary-the-pan-genome-pipeline</guid>
	<pubDate>Tue, 22 Jan 2019 05:52:07 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38758/roary-the-pan-genome-pipeline</link>
	<title><![CDATA[Roary: the Pan Genome Pipeline]]></title>
	<description><![CDATA[<p><span>Roary is a high speed stand alone pan genome pipeline, which takes annotated assemblies in GFF3 format (produced by Prokka (Seemann, 2014)) and calculates the pan genome. Using a standard desktop PC, it can analyse datasets with thousands of samples, something which is computationally infeasible with existing methods, without compromising the quality of the results. 128 samples can be analysed in under 1 hour using 1 GB of RAM and a single processor. To perform this analysis using existing methods would take weeks and hundreds of GB of RAM. Roary is not intended for meta-genomics or for comparing extremely diverse sets of genomes.</span></p><p>Address of the bookmark: <a href="https://sanger-pathogens.github.io/Roary/" rel="nofollow">https://sanger-pathogens.github.io/Roary/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39269/ragoo-fast-reference-guided-scaffolding-of-genome-assembly-contigs</guid>
	<pubDate>Wed, 17 Apr 2019 19:45:22 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39269/ragoo-fast-reference-guided-scaffolding-of-genome-assembly-contigs</link>
	<title><![CDATA[RaGOO: Fast Reference-Guided Scaffolding of Genome Assembly Contigs]]></title>
	<description><![CDATA[<p>Alonge M, Soyk S, Ramakrishnan S, Wang X, Goodwin S, Sedlazeck FJ, Lippman ZB, Schatz MC:&nbsp;<a href="https://www.biorxiv.org/content/early/2019/01/13/519637">Fast and accurate reference-guided scaffolding of draft genomes</a>.&nbsp;<em>bioRxiv</em>&nbsp;2019.</p>
<p>RaGOO is a tool for coalescing genome assembly contigs into pseudochromosomes via minimap2 alignments to a closely related reference genome. The focus of this tool is on practicality and therefore has the following features:</p>
<ol>
<li>Good performance. On a MacBook Pro using Arabidopsis data, pseudochromosome construction takes less than a minute and the whole pipeline with SV calling takes ~2 minutes.</li>
<li>Intact ordering and orienting of contigs.</li>
<li><a href="https://github.com/malonge/RaGOO/wiki/Breaking-Chimeric-Contigs">Chimeric contig correction</a></li>
<li><a href="https://github.com/malonge/RaGOO/wiki/GFF-File-Lift-Over">GFF lift-over</a></li>
<li><a href="https://github.com/malonge/RaGOO/wiki/Calling-Structural-Variants">Structural variant calling with and integrated version of Assemblytics</a></li>
<li>Confidence scores associated with the grouping, localization, and orientation for each contig.</li>
</ol><p>Address of the bookmark: <a href="https://github.com/malonge/RaGOO" rel="nofollow">https://github.com/malonge/RaGOO</a></p>]]></description>
	<dc:creator>BioJoker</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40549/mgse-mapping-based-genome-size-estimation</guid>
	<pubDate>Fri, 17 Jan 2020 02:11:43 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40549/mgse-mapping-based-genome-size-estimation</link>
	<title><![CDATA[MGSE: Mapping-based Genome Size Estimation]]></title>
	<description><![CDATA[<p>MGSE can harness the power of files generated in genome sequencing projects to predict the genome size. Required are the FASTA file containing a high continuity assembly and a BAM file with all available reads mapped to this assembly. The script construct_cov_file.py (https://doi.org/10.1186/s12864-018-5360-z) allows the generation of a COV file based on the (sorted) BAM file (also possible via MGSE directly). Next, this COV file can be used by MGSE to calculate the coverage in provided reference regions and to calculate the total number of mapped bases. Both values are subjected to the genome size estimation. Providing accurate reference regions is crucial for this genome size estimation.</p><p>Address of the bookmark: <a href="https://github.com/bpucker/MGSE" rel="nofollow">https://github.com/bpucker/MGSE</a></p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41604/synteny-and-rearrangement-identifier-syri</guid>
	<pubDate>Tue, 05 May 2020 10:37:10 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41604/synteny-and-rearrangement-identifier-syri</link>
	<title><![CDATA[Synteny and Rearrangement Identifier (SyRI)]]></title>
	<description><![CDATA[<p>SyRI is a comprehensive tool for predicting genomic differences between related genomes using whole-genome assemblies (WGA). The assemblies are aligned using whole-genome alignment tools, and these alignments are then used as input to SyRI. SyRI identifies syntenic path (longest set of co-linear regions), structural rearrangements (inversions, translocations, and duplications), local variations (SNPs, indels, CNVs etc) within syntenic and structural rearrangements, and un-aligned regions.</p><p>Address of the bookmark: <a href="https://schneebergerlab.github.io/syri/" rel="nofollow">https://schneebergerlab.github.io/syri/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42497/genome-assembly-training-tutorial-at-galaxy</guid>
	<pubDate>Sun, 27 Dec 2020 05:25:45 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42497/genome-assembly-training-tutorial-at-galaxy</link>
	<title><![CDATA[Genome assembly training tutorial at Galaxy !]]></title>
	<description><![CDATA[<p>In this tutorial we assemble and annotate the genome of <em>E. coli</em> strain <a href="http://cgsc2.biology.yale.edu/Strain.php?ID=8232">C-1</a>. This strain is routinely used in experimental evolution studies involving bacteriophages. For instance, now classic works by Holly Wichman and Jim Bull (<a href="https://training.galaxyproject.org/training-material/topics/assembly/tutorials/unicycler-assembly/tutorial.html#Bull1997">Bull 1997</a>, <a href="https://training.galaxyproject.org/training-material/topics/assembly/tutorials/unicycler-assembly/tutorial.html#Bull1998">Bull 1998</a>, <a href="https://training.galaxyproject.org/training-material/topics/assembly/tutorials/unicycler-assembly/tutorial.html#Wichman1999">Wichman 1999</a>) have been performed using this strain and bacteriophage phiX174.</p><p>Address of the bookmark: <a href="https://training.galaxyproject.org/training-material/topics/assembly/tutorials/unicycler-assembly/tutorial.html" rel="nofollow">https://training.galaxyproject.org/training-material/topics/assembly/tutorials/unicycler-assembly/tutorial.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43315/genome-assembly-workshop-2020</guid>
	<pubDate>Wed, 25 Aug 2021 04:30:32 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43315/genome-assembly-workshop-2020</link>
	<title><![CDATA[Genome Assembly Workshop 2020]]></title>
	<description><![CDATA[<p><span>Our team offers custom bioinformatics services to academic and private organizations. We have a strong academic background with a focus on cutting edge, open source software. We replicate standard analysis pipelines (best practices) when appropriate, and/or develop novel applications and pipelines when needed, however we always emphasize biological interpretation of the data.</span></p>
<p><span>More at&nbsp;https://ucdavis-bioinformatics-training.github.io/</span></p><p>Address of the bookmark: <a href="https://ucdavis-bioinformatics-training.github.io/2020-Genome_Assembly_Workshop/snakemake/snakemake_intro" rel="nofollow">https://ucdavis-bioinformatics-training.github.io/2020-Genome_Assembly_Workshop/snakemake/snakemake_intro</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/43559/job-offer-for-a-postdoctoral-researcher-in-genomics-bioinformatics-2-years</guid>
  <pubDate>Fri, 22 Oct 2021 04:44:33 -0500</pubDate>
  <link></link>
  <title><![CDATA[Job offer for a postdoctoral researcher in genomics / bioinformatics (2 years)]]></title>
  <description><![CDATA[
<p>Ongoing research in the group of Karine Van Doninck involves topics at the core of<br />evolutionary biology, including the evolution of sex, genome maintenance,<br />recombination and extreme stress resistance on different eukaryotic systems,<br />including rotifers, amoeba and Corbicula clams. We are employing different tools<br />(including experimental ecology, population genetics, phylogeny, comparative<br />genomics, transcriptomics, bioinformatics, molecular and cellular biology) to study<br />evolutionary processes at the level of populations, both experimental and natural, and<br />genomes.</p>

<p>Offer<br />We offer a full-time contract for two years. The contract starts between October 2021<br />and December 2021. The position involves no or extremely light teaching load, if the<br />candidate is interested. Salaries are competitive at the European level. The recruited<br />person will benefit from the Belgian social insurance scheme (health care, etc.) without<br />additional expenses.</p>

<p>Profile<br />Applicants are expected to show outstanding commitment to research and must have<br />obtained a PhD by the start of the position. A strong expertise in genomics is required.<br />More specifically, solid competences in bioinformatics (e.g. scripting pipelines) and in<br />genome evolution are needed. Knowledge or interest regarding recombination,<br />metazoan evolution, phylogenomics and population genomics is an added-value.</p>

<p>Application<br />Applications should be submitted via email to karine.van.doninck@ulb.be. The<br />application package should contain the following documents:<br />- A curriculum vitae with the complete list of publications<br />- A cover letter mentioning why the candidate is interested in the position<br />- Minimum 2 recommendation letters<br />Interviews: Interviews will be conducted with the selected candidates. Selected<br />candidates could also be invited to give a seminar to MBE ULB.<br />For any additional information, please contact karine.van.doninck@ulb.be</p>
]]></description>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/43670/useful-bioinformatics-analysis-tools</guid>
	<pubDate>Thu, 23 Dec 2021 23:10:02 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/43670/useful-bioinformatics-analysis-tools</link>
	<title><![CDATA[Useful Bioinformatics Analysis Tools !]]></title>
	<description><![CDATA[<h3><a href="http://sun.aei.polsl.pl/REFRESH/index.php?page=projects&amp;project=cometa&amp;subpage=about">CoMeta</a></h3><p><strong>Classificier of reads from metagenomic sequencing experiments.</strong></p><p><span>&bull;&nbsp;&nbsp;Kawulok, J., Deorowicz, S.,&nbsp;</span><em>CoMeta: Classification of Metagenomes Using k-mers</em><span>,&nbsp;</span><a href="http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0121453">PLOS ONE,&nbsp;</a><span>2015; 10(4):1&ndash;23,</span></p><h3><a href="http://sun.aei.polsl.pl/REFRESH/index.php?page=projects&amp;project=CoMSA&amp;subpage=about">CoMSA</a></h3><p><strong>Compressor of multiple sequence alignments of proteins.</strong></p><p><span>&bull;&nbsp;&nbsp;Deorowicz, S., Walczyszyn, J., Debudaj-Grabysz, A.,&nbsp;</span><em>CoMSA: compression of protein multiple sequence alignment files</em><span>,&nbsp;</span><a href="https://doi.org/10.1093/bioinformatics/bty619">Bioinformatics,&nbsp;</a><span>2019; 35(2):22&ndash;234,</span></p><h3><a href="http://sun.aei.polsl.pl/REFRESH/index.php?page=projects&amp;project=dsrc&amp;subpage=about">DSRC</a></h3><p><strong>Compressor of sequencing reads.</strong></p><p><span>&bull;&nbsp;&nbsp;Roguski, L., Deorowicz, S.,&nbsp;</span><em>DSRC 2: Industry-oriented compression of FASTQ files</em><span>,&nbsp;</span><a href="http://bioinformatics.oxfordjournals.org/content/30/15/2213">Bioinformatics,&nbsp;</a><span>2014; 30(15):2213&ndash;2215,</span><br /><span>&bull;&nbsp;&nbsp;Deorowicz, S., Grabowski, Sz.,&nbsp;</span><em>Compression of DNA sequences in FASTQ format</em><span>,&nbsp;</span><a href="http://bioinformatics.oxfordjournals.org/">Bioinformatics,&nbsp;</a><span>2011; 27(6):860&ndash;862,</span></p><h3><a href="http://sun.aei.polsl.pl/REFRESH/index.php?page=projects&amp;project=famsa&amp;subpage=about">FAMSA</a></h3><p><strong>Multiple sequence alignment designed for huge families of proteins (even containing hundreds of thousands of sequences).</strong></p><p><span>&bull;&nbsp;&nbsp;Deorowicz, S., Debudaj-Grabysz, A., Gudys, A.,&nbsp;</span><em>FAMSA: Fast and accurate multiple sequence alignment of huge protein families</em><span>,&nbsp;</span><a href="http://www.nature.com/articles/srep33964">Scientific Reports,&nbsp;</a><span>2016; 6(33964):</span></p><h3><a href="http://sun.aei.polsl.pl/REFRESH/index.php?page=projects&amp;project=fastore&amp;subpage=about">FaStore</a></h3><p><strong>Compressor of FASTQ files.</strong></p><p><span>&bull;&nbsp;&nbsp;Roguski, L., Ochoa, I., Hernaez, M., Deorowicz, S.,&nbsp;</span><em>FaStore - a space-saving solution for raw sequencing data</em><span>,&nbsp;</span><a href="https://doi.org/10.1093/bioinformatics/bty205">Bioinformatics,&nbsp;</a><span>2018; 34(16):2748&ndash;2756,</span></p><h3><a href="http://sun.aei.polsl.pl/REFRESH/index.php?page=projects&amp;project=fqsqueezer&amp;subpage=about">FQSqueezer</a></h3><p><strong>Experimental high-end compressor of FASTQ files.</strong></p><p><span>&bull;&nbsp;&nbsp;Deorowicz, S.,&nbsp;</span><em>FQSqueezer: k-mer-based compression of sequencing data</em><span>,&nbsp;</span><a href="https://www.nature.com/articles/s41598-020-57452-6">Scientific Reports,&nbsp;</a><span>2020; 10(578):</span></p><h3><a href="http://sun.aei.polsl.pl/REFRESH/index.php?page=projects&amp;project=gdc&amp;subpage=about">GDC</a></h3><p><strong>Compressor of collections of genome sequences.</strong></p><p><span>&bull;&nbsp;&nbsp;Deorowicz, S., Danek, A., Niemiec, M.,&nbsp;</span><em>GDC 2: Compression of large collections of genomes</em><span>,&nbsp;</span><a href="http://www.nature.com/srep/2015/150625/srep11565/full/srep11565.html">Scientific Reports,&nbsp;</a><span>2015; 5(11565):1&ndash;12,</span><br /><span>&bull;&nbsp;&nbsp;Deorowicz, S., Grabowski, Sz.,&nbsp;</span><em>Robust relative compression of genomes with random access</em><span>,&nbsp;</span><a href="http://sun.aei.polsl.pl/REFRESH/bioinformatics.oxfordjournals.org/content/27/21/2979.abstract">Bioinformatics,&nbsp;</a><span>2011; 27(21):2979&ndash;2986,</span></p><h3><a href="http://sun.aei.polsl.pl/REFRESH/index.php?page=projects&amp;project=gtc&amp;subpage=about">GTC</a></h3><p><strong>Genotype databases compressor with support for fast queries.</strong></p><p><span>&bull;&nbsp;&nbsp;Danek, A., Deorowicz, S.,&nbsp;</span><em>GTC: how to maintain huge genotype collections in a compressed form</em><span>,&nbsp;</span><a href="https://doi.org/10.1093/bioinformatics/bty023">Bioinformatics,&nbsp;</a><span>2018; 34(11):1834&ndash;1840,</span></p><h3><a href="http://sun.aei.polsl.pl/REFRESH/index.php?page=projects&amp;project=gtshark&amp;subpage=about">GTShark</a></h3><p><strong>Genotypes compressor.</strong></p><p><span>&bull;&nbsp;&nbsp;Deorowicz, S., Danek, A.,&nbsp;</span><em>GTShark: Genotype compression in large projects</em><span>,&nbsp;</span><a href="https://doi.org/10.1093/bioinformatics/btz508">Bioinformatics,&nbsp;</a><span>2019; 35(22):4791&ndash;4793,</span></p><h3><a href="http://sun.aei.polsl.pl/REFRESH/index.php?page=projects&amp;project=kmc&amp;subpage=about">KMC</a></h3><p><strong>Memory frugal&nbsp;<em>k</em>-mer counter.</strong></p><p><span>&bull;&nbsp;&nbsp;Kokot, M., Długosz, M., Deorowicz, S.,&nbsp;</span><em>KMC 3: counting and manipulating k -mer statistics</em><span>,&nbsp;</span><a href="https://doi.org/10.1093/bioinformatics/btx304">Bioinformatics,&nbsp;</a><span>2017; 33(17):2759&ndash;2761,</span><br /><span>&bull;&nbsp;&nbsp;Deorowicz, S., Kokot, M., Grabowski, Sz., Debudaj-Grabysz, A.,&nbsp;</span><em>KMC 2: Fast and resource-frugal k-mer counting</em><span>,&nbsp;</span><a href="https://doi.org/10.1093/bioinformatics/btv022">Bioinformatics,&nbsp;</a><span>2015; 31(10):1569&ndash;1576,</span><br /><span>&bull;&nbsp;&nbsp;Deorowicz, S., Debudaj-Grabysz, A., Grabowski, Sz.,&nbsp;</span><em>Disk-based k-mer counting on a PC</em><span>,&nbsp;</span><a href="http://www.biomedcentral.com/1471-2105/14/160">BMC Bioinformatics,&nbsp;</a><span>2013; 14():Article no. 160,</span></p><h3><a href="http://sun.aei.polsl.pl/REFRESH/index.php?page=projects&amp;project=kmer-db&amp;subpage=about">Kmer-db</a></h3><p><strong>Tool for estimation of evolutionary distances in a collection of genomes.</strong></p><p><span>&bull;&nbsp;&nbsp;Deorowicz, S., Gudys, A., Dlugosz, M., Kokot, M., Danek, A.,&nbsp;</span><em>Kmer-db: instant evolutionary distance estimation</em><span>,&nbsp;</span><a href="https://doi.org/10.1093/bioinformatics/bty610">Bioinformatics,&nbsp;</a><span>2019; 35(1):133&ndash;136,</span></p><h3><a href="http://sun.aei.polsl.pl/REFRESH/index.php?page=projects&amp;project=mugi&amp;subpage=about">MuGI</a></h3><p><strong>Index allowing queries for a collection of multiple genome sequences.</strong></p><p><span>&bull;&nbsp;&nbsp;Danek, A., Deorowicz, S., Grabowski, Sz.,&nbsp;</span><em>Indexes of Large Genome Collections on a PC</em><span>,&nbsp;</span><a href="http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0109384">PLOS ONE,&nbsp;</a><span>2014; 9(10):e109384,</span></p><h3><a href="http://sun.aei.polsl.pl/REFRESH/index.php?page=projects&amp;project=orcom&amp;subpage=about">ORCOM</a></h3><p><strong>Experimental compressor of sequencing reads.</strong></p><p><span>&bull;&nbsp;&nbsp;Grabowski, Sz., Deorowicz, S., Roguski, L.,&nbsp;</span><em>Disk-based compression of data from genome sequencing</em><span>,&nbsp;</span><a href="http://bioinformatics.oxfordjournals.org/content/early/2014/12/22/bioinformatics.btu844.abstract">Bioinformatics,&nbsp;</a><span>2014; 31(9):1389&ndash;1395,</span></p><h3><a href="http://sun.aei.polsl.pl/REFRESH/index.php?page=projects&amp;project=pgsa&amp;subpage=about">PgSA</a></h3><p><strong>Index allowing queries for a collection of sequencing reads.</strong></p><p><span>&bull;&nbsp;&nbsp;Kowalski, T., Grabowski, Sz., Deorowicz, S.,&nbsp;</span><em>Indexing arbitrary-length k-mers in sequencing reads</em><span>,&nbsp;</span><a href="http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0133198">PLOS ONE,&nbsp;</a><span>2015; 10(7):1&ndash;16,</span></p><h3><a href="http://sun.aei.polsl.pl/REFRESH/index.php?page=projects&amp;project=quickprobs&amp;subpage=about">QuickProbs</a></h3><p><strong>Multiple sequence alignment designed especially for GPU.</strong></p><p><span>&bull;&nbsp;&nbsp;Gudys, A., Deorowicz, S.,&nbsp;</span><em>QuickProbs 2: towards rapid construction of high-quality alignments of large protein families</em><span>,&nbsp;</span><a href="http://www.nature.com/articles/srep41553">Scientific Reports,&nbsp;</a><span>2017; 7(41553):</span><br /><span>&bull;&nbsp;&nbsp;Gudys, A., Deorowicz, S.,&nbsp;</span><em>QuickProbs &ndash; A Fast Multiple Sequence Alignment Algorithm Designed for Graphics Processors</em><span>,&nbsp;</span><a href="http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0088901">PLOS ONE,&nbsp;</a><span>2014; 9(2):e88901,</span></p><h3><a href="http://sun.aei.polsl.pl/REFRESH/index.php?page=projects&amp;project=reckoner&amp;subpage=about">RECKONER</a></h3><p><strong>Read error corrector.</strong></p><p><span>&bull;&nbsp;&nbsp;Maciej Długosz, M., Deorowicz, S.,&nbsp;</span><em>RECKONER: read error corrector based on KMC</em><span>,&nbsp;</span><a href="https://academic.oup.com/bioinformatics/article-abstract/33/7/1086/2843893/RECKONER-read-error-corrector-based-on-KMC">Bioinformatics,&nbsp;</a><span>2017; 33(7):1086&ndash;1089,</span></p><h3><a href="http://sun.aei.polsl.pl/REFRESH/index.php?page=projects&amp;project=tgc&amp;subpage=about">TGC</a></h3><p><strong>Compressor of collections of genomes given in Variant Call Format (VCF) files.</strong></p><p><span>&bull;&nbsp;&nbsp;Deorowicz, S., Danek, A., Grabowski, Sz.,&nbsp;</span><em>Genome compression: a novel approach for large collections</em><span>,&nbsp;</span><a href="http://bioinformatics.oxfordjournals.org/content/early/2013/08/29/bioinformatics.btt460">Bioinformatics,&nbsp;</a><span>2013; 29(20):2572&ndash;2578,</span></p><h3><a href="http://sun.aei.polsl.pl/REFRESH/index.php?page=projects&amp;project=vcfshark&amp;subpage=about">VCFShark</a></h3><p><strong>Compressor of VCF files.</strong></p><p><span>&bull;&nbsp;&nbsp;Deorowicz, S., Danek, A.,&nbsp;</span><em>GTShark: Genotype compression in large projects</em><span>,&nbsp;</span><a href="https://www.biorxiv.org/content/10.1101/2020.12.18.423437v1">biorxiv.org,&nbsp;</a><span>2020; ():</span></p><h3><a href="http://sun.aei.polsl.pl/REFRESH/index.php?page=projects&amp;project=whisper&amp;subpage=about">Whisper</a></h3><p><strong>Experimental mapper of whole genome sequencing data.</strong></p><p><span>&bull;&nbsp;&nbsp;Deorowicz, S., Gudys, A.,&nbsp;</span><em>Whisper 2: indel-sensitive short read mapping</em><span>,&nbsp;</span><a href="https://doi.org/10.1101/2019.12.18.881292">bioRxiv.org,&nbsp;</a><span>2019; :</span><br /><span>&bull;&nbsp;&nbsp;Deorowicz, S., Debudaj-Grabysz, A., Gudys, A., Grabowski, Sz.,&nbsp;</span><em>Whisper: read sorting allows robust robust mapping of DNA sequencing data</em><span>,&nbsp;</span><a href="https://doi.org/10.1093/bioinformatics/bty927">Bioinformatics,&nbsp;</a><span>2019; 35(12):2043&ndash;2050,</span><br /><span>&bull;&nbsp;&nbsp;Deorowicz, S., Debudaj-Grabysz, A., Gudys, A., Grabowski, Sz.,&nbsp;</span><em>Robust mapping of whole genome sequencing data</em><span>,&nbsp;</span><a href="https://meetings.cshl.edu/abstracts.aspx?meet=GENOME&amp;year=17">Poster at The Biology of Genomes Conference,&nbsp;</a><span>2017;</span></p>]]></description>
	<dc:creator>Neel</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43799/kast</guid>
	<pubDate>Wed, 23 Feb 2022 08:28:36 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43799/kast</link>
	<title><![CDATA[KAST]]></title>
	<description><![CDATA[<p><span>Perform Alignment-free k-tuple frequency comparisons from sequences. This can be in the form of two input files (e.g. a reference and a query) or a single file for pairwise comparisons to be made.</span></p><p>Address of the bookmark: <a href="https://github.com/martinjvickers/KAST" rel="nofollow">https://github.com/martinjvickers/KAST</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44223/ale-assembly-likelihood-estimator</guid>
	<pubDate>Wed, 08 Mar 2023 01:39:33 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44223/ale-assembly-likelihood-estimator</link>
	<title><![CDATA[ALE: Assembly Likelihood Estimator]]></title>
	<description><![CDATA[<p>Just import the assembly, bam and ALE scores. You can convert the .ale file to a set of .wig files with ale2wiggle.py and IGV can read those directly.&nbsp; Depending on your genome size you may want to convert the .wig files to the BigWig format.</p><p>Address of the bookmark: <a href="https://github.com/sc932/ALE" rel="nofollow">https://github.com/sc932/ALE</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>

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