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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/43658?offset=50</link>
	<atom:link href="https://bioinformaticsonline.com/related/43658?offset=50" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39250/darwin-wga-a-co-processor-provides-increased-sensitivity-in-whole-genome-alignments-with-high-speedup</guid>
	<pubDate>Sat, 13 Apr 2019 08:55:31 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39250/darwin-wga-a-co-processor-provides-increased-sensitivity-in-whole-genome-alignments-with-high-speedup</link>
	<title><![CDATA[Darwin-WGA: A Co-processor Provides Increased Sensitivity in Whole Genome Alignments with High Speedup]]></title>
	<description><![CDATA[<p>Darwin-WGA, is the first hardware accelerator for whole genome alignment and accelerates the gapped filtering stage. Darwin-WGA also employs GACT-X, a novel algorithm used in the extension stage to align arbitrarily long genome sequences using a small on-chip memory, that provides better quality alignments at 2&times; improvement in memory and speed over the previously published GACT algorithm. Implemented on an FPGA, Darwin-WGA provides up to 24&times; improvement (performance/$) in WGA over iso-sensitive software.</p>
<p><a href="https://stanford.edu/~yatisht/pubs/darwin-wga.pdf">https://stanford.edu/~yatisht/pubs/darwin-wga.pdf</a></p><p>Address of the bookmark: <a href="https://github.com/gsneha26/Darwin-WGA" rel="nofollow">https://github.com/gsneha26/Darwin-WGA</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40573/de-novo-genome-assembly-for-illumina-data</guid>
	<pubDate>Mon, 20 Jan 2020 05:13:29 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40573/de-novo-genome-assembly-for-illumina-data</link>
	<title><![CDATA[De novo Genome Assembly for Illumina Data]]></title>
	<description><![CDATA[<p>Written and maintained by <a href="mailto:simon.gladman@unimelb.edu.au">Simon Gladman</a> - Melbourne Bioinformatics (formerly VLSCI)</p>
<p>Protocol Overview / Introduction</p>
<p>In this protocol we discuss and outline the process of de novo assembly for small to medium sized genomes.</p>
<p>https://www.melbournebioinformatics.org.au/tutorials/tutorials/assembly/assembly-protocol/</p><p>Address of the bookmark: <a href="https://www.melbournebioinformatics.org.au/tutorials/tutorials/assembly/assembly-protocol/" rel="nofollow">https://www.melbournebioinformatics.org.au/tutorials/tutorials/assembly/assembly-protocol/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<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/43110/quasimodo-quasispecies-metric-determination-on-omics</guid>
	<pubDate>Sat, 26 Jun 2021 15:22:56 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43110/quasimodo-quasispecies-metric-determination-on-omics</link>
	<title><![CDATA[QuasiModo - Quasispecies Metric Determination on Omics]]></title>
	<description><![CDATA[<p><span>This repository contains the scripts and pipeline that reproduces the results of the HCMV benchmarking study. In this study we evaluated genome assemblers and variant callers on 10 in vitro generated, mixed strain HCMV sequence samples, each consisting of two lab strains in different abundance ratios. This tool can also be used to evaluate assemblies and variant calling results on other similar datasets.</span></p>
<p><span>https://academic.oup.com/bib/article/22/3/bbaa123/5868070</span></p><p>Address of the bookmark: <a href="https://github.com/hzi-bifo/Quasimodo" rel="nofollow">https://github.com/hzi-bifo/Quasimodo</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43427/ogdraw-draw-organelle-genome-maps</guid>
	<pubDate>Tue, 05 Oct 2021 03:34:35 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43427/ogdraw-draw-organelle-genome-maps</link>
	<title><![CDATA[OGDRAW - Draw Organelle Genome Maps]]></title>
	<description><![CDATA[<p>OrganellarGenomeDRAW converts annotations in the&nbsp;<a href="https://www.ncbi.nlm.nih.gov/genbank/">GenBank</a>&nbsp;or&nbsp;<a href="https://www.ebi.ac.uk/ena">EMBL/ENA</a>&nbsp;format into graphical maps. The input has to be a&nbsp;<a href="https://www.ncbi.nlm.nih.gov/Sitemap/samplerecord.html">GenBank&nbsp;</a>or&nbsp;<a href="https://www.ebi.ac.uk/ena/submit/flat-file">EMBL/ENA flat file</a>&nbsp;wherase the output can vary among several types of files. The application is optimized to create detailed high-quality maps of organellar genomes (plastid and mitochondria). Nevertheless, you can upload most<span style="color: #0b0118;">&nbsp;database</span>&nbsp;entries.</p>
<p>&nbsp;</p>
<p>Please take a look at our&nbsp;<a href="https://chlorobox.mpimp-golm.mpg.de/OGDraw-FAQ.html">FAQ section</a>&nbsp;and do not hesitate to report bugs or suggestions for improvements by&nbsp;<a href="mailto:chlorobox@mpimp-golm.mpg.de?subject=OGDRAW">email</a>.</p><p>Address of the bookmark: <a href="https://chlorobox.mpimp-golm.mpg.de/OGDraw.html" rel="nofollow">https://chlorobox.mpimp-golm.mpg.de/OGDraw.html</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
</item>
<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>
</item>
<item>
	<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>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/44371/steps-to-find-all-the-repeats-in-the-genome</guid>
	<pubDate>Thu, 31 Aug 2023 02:43:28 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/44371/steps-to-find-all-the-repeats-in-the-genome</link>
	<title><![CDATA[Steps to find all the repeats in the genome !]]></title>
	<description><![CDATA[<div><p>To find repeats in a genome from 2 to 9 length using a Perl script, you can use the RepeatMasker tool with the "--length" option<a href="https://mobilednajournal.biomedcentral.com/articles/10.1186/1759-8753-5-13" target="_blank">[0]</a>. Here's a step-by-step guide:</p></div><div><ol>
<li>Install RepeatMasker: First, you need to install RepeatMasker on your system. You can download it from the RepeatMasker website<a href="https://mobilednajournal.biomedcentral.com/articles/10.1186/1759-8753-5-13" target="_blank">[0]</a>.</li>
</ol></div><div><ol>
<li>Prepare the genome sequence: Make sure you have the genome sequence in a FASTA file format. Let's assume the file is named "genome.fasta".</li>
</ol><blockquote><p>./RepeatMasker -pa &lt;number_of_processors&gt; -nolow -norna -no_is -div &lt;divergence_value&gt; -lib RepeatMaskerLib.embl -gff -xsmall -small -poly -species &lt;species_name&gt; -dir &lt;output_directory&gt; -length &lt;min_length&gt;-&lt;max_length&gt; genome.fasta</p></blockquote><div><p>Replace the following placeholders with appropriate values:</p><ul>
<li><code>&lt;number_of_processors&gt;</code>: The number of processors/threads you want to use for parallel processing.</li>
<li><code>&lt;divergence_value&gt;</code>: The divergence value for the species you are analyzing. You can find divergence values for different species in the RepeatMasker documentation<a href="https://mobilednajournal.biomedcentral.com/articles/10.1186/1759-8753-5-13" target="_blank">[0]</a>.</li>
<li><code>&lt;species_name&gt;</code>: The name of the species you are analyzing.</li>
<li><code>&lt;output_directory&gt;</code>: The directory where you want the output files to be saved.</li>
<li><code>&lt;min_length&gt;</code>&nbsp;and&nbsp;<code>&lt;max_length&gt;</code>: The minimum and maximum lengths of the repeats you want to find (in this case, 2 and 9).</li>
</ul></div><div><ol>
<li>Analyze the output: RepeatMasker will generate several output files, including a .out file. You can parse this file to extract the information you need. There is a Perl tool called "one_code_to_find_them_all.pl" that can help you parse RepeatMasker output files<a href="https://mobilednajournal.biomedcentral.com/articles/10.1186/1759-8753-5-13" target="_blank">[0]</a>. You can download it from the source provided.</li>
</ol></div><div><ol>
<li>Use the provided Perl script: Once you have the "one_code_to_find_them_all.pl" script, you can run it to conveniently parse the RepeatMasker output files. Here's an example of how to use it:</li>
</ol><blockquote><p>perl one_code_to_find_them_all.pl --rm &lt;RepeatMasker_out_file&gt; --length &lt;length_file&gt;</p></blockquote></div><p>&nbsp;</p></div><div><div><p>Replace&nbsp;<code>&lt;RepeatMasker_out_file&gt;</code>&nbsp;with the path to your RepeatMasker .out file, and&nbsp;<code>&lt;length_file&gt;</code>&nbsp;with the path to a file containing the lengths of the reference elements.</p></div><div><p>This script will generate several output files, including .log.txt and .copynumber.csv, which contain quantitative information about the identified repeat elements.</p></div><div><p>Remember to adjust the parameters and options according to your specific needs and the characteristics of your genome.</p></div></div>]]></description>
	<dc:creator>Neel</dc:creator>
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