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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/38886?offset=160</link>
	<atom:link href="https://bioinformaticsonline.com/related/38886?offset=160" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37984/baum-%E2%80%93-improving-genome-assembly-by-adaptive-unique-mapping-and-local-overlap-layout-consensus</guid>
	<pubDate>Wed, 24 Oct 2018 23:35:09 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37984/baum-%E2%80%93-improving-genome-assembly-by-adaptive-unique-mapping-and-local-overlap-layout-consensus</link>
	<title><![CDATA[BAUM – Improving Genome Assembly by Adaptive Unique Mapping and Local Overlap-Layout-Consensus]]></title>
	<description><![CDATA[<p><span>BAUM, breaks the whole genome into regions by adaptive unique mapping; then the local OLC is used to assemble each region in parallel. BAUM can: (1) perform reference-assisted assembly based on the genome of a close species; (2) or improve the results of existing assemblies that are obtained based on short or long sequencing reads.&nbsp;</span></p><p>Address of the bookmark: <a href="http://www.zhanyuwang.xin/wordpress/index.php/2017/07/21/baum-improving-genome-assembly-by-adaptive-unique-mapping-and-local-overlap-layout-consensus/" rel="nofollow">http://www.zhanyuwang.xin/wordpress/index.php/2017/07/21/baum-improving-genome-assembly-by-adaptive-unique-mapping-and-local-overlap-layout-consensus/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40208/ragoo-fast-reference-guided-scaffolding-of-genome-assembly-contigs</guid>
	<pubDate>Sun, 27 Oct 2019 00:57:23 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40208/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/Misassembly-Correction">Misassembly 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>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41691/genobuntu-package-for-next-generation-sequencing-and-genome-assembly</guid>
	<pubDate>Mon, 18 May 2020 16:47:56 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41691/genobuntu-package-for-next-generation-sequencing-and-genome-assembly</link>
	<title><![CDATA[Genobuntu: Package for Next Generation Sequencing and Genome Assembly]]></title>
	<description><![CDATA[<div>
<p>Genobuntu is a software package containing more than 70 software and packages oriented towards NGS. In its current version, Genobuntu supports pre assembly tools, genome assemblers as well as post assembly tools.<br><br>Commonly used biological software and example script files for different assembly pipelines have also been provided, where the example script files can be updated to suit one&rsquo;s experimental needs. Genobuntu attempts to reduce the amount of time and energy needed to build software workstations and it can also act as a good teaching source for a class room setting.<br><br>Therefore, Genobuntu offers a well-tailored environment for both novices and experts working in the field of genome assembly.</p>
</div>
<div>
<h3>Features</h3>
<ul>
<li>Velvet</li>
<li>MiB</li>
<li>SSAKE</li>
<li>EULER</li>
<li>VCAKE</li>
<li>ABySS</li>
<li>ALLPATHS</li>
<li>Celera</li>
<li>SHARCGS</li>
<li>Allpaths</li>
<li>IDBA</li>
<li>TAIPAN</li>
<li>Edena</li>
<li>SOAPdenovo</li>
<li>Maq</li>
<li>IDBA-UD</li>
<li>No. of Reads present in the Ref. Seq.</li>
<li>ART NGS Reads Simulator</li>
<li>HiTEC, FASTQC</li>
<li>Minimum Description Length</li>
<li>SOAPaligner</li>
<li>Sequencing Read Archive Toolkit</li>
</ul>
</div><p>Address of the bookmark: <a href="https://sourceforge.net/projects/genobuntu/" rel="nofollow">https://sourceforge.net/projects/genobuntu/</a></p>]]></description>
	<dc:creator>BioStar</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/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/bookmarks/view/35543/genometools-the-versatile-open-source-genome-analysis-software</guid>
	<pubDate>Wed, 07 Feb 2018 10:44:18 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35543/genometools-the-versatile-open-source-genome-analysis-software</link>
	<title><![CDATA[GenomeTools: The versatile open source genome analysis software]]></title>
	<description><![CDATA[<p>The&nbsp;<em>GenomeTools</em>&nbsp;genome analysis system is a&nbsp;<a href="http://genometools.org/license.html">free</a>&nbsp;collection of bioinformatics&nbsp;<a href="http://genometools.org/tools.html">tools</a>&nbsp;(in the realm of genome informatics) combined into a single binary named&nbsp;<em>gt</em>. It is based on a C library named &ldquo;libgenometools&rdquo; which consists of several modules.</p>
<p>If you are interested in gene prediction, have a look at&nbsp;<a href="http://genomethreader.org/" title="GenomeThreader gene prediction        software"><em>GenomeThreader</em></a>.</p><p>Address of the bookmark: <a href="http://genometools.org/" rel="nofollow">http://genometools.org/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43273/understanding-kmer</guid>
	<pubDate>Wed, 18 Aug 2021 04:27:51 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43273/understanding-kmer</link>
	<title><![CDATA[Understanding kmer !]]></title>
	<description><![CDATA[<p><a href="https://en.wikipedia.org/wiki/k-mer">What is a&nbsp;<em>k-mer</em>&nbsp;anyway?</a><span>&nbsp;A&nbsp;</span><em>k-mer</em><span>&nbsp;is just a sequence of&nbsp;</span><em>k</em><span>&nbsp;characters in a string (or nucleotides in a DNA sequence). Now, it is important to remember that to get&nbsp;</span><em>all k-mers</em><span>&nbsp;from a sequence you need to get the first&nbsp;</span><em>k</em><span>&nbsp;characters, then move just a single character for the start of the next&nbsp;</span><em>k-mer</em><span>&nbsp;and so on. Effectively, this will create sequences that overlap in&nbsp;</span><code>k-1</code><span>&nbsp;positions.</span></p><p>Address of the bookmark: <a href="https://bioinfologics.github.io/post/2018/09/17/k-mer-counting-part-i-introduction/" rel="nofollow">https://bioinfologics.github.io/post/2018/09/17/k-mer-counting-part-i-introduction/</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43711/vcf-compare</guid>
	<pubDate>Wed, 19 Jan 2022 10:30:14 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43711/vcf-compare</link>
	<title><![CDATA[VCF Compare !]]></title>
	<description><![CDATA[<h2><span>compare two&nbsp;<strong>BWA</strong>&nbsp;mapping methods with the online hg18-mapped data</span></h2>
<p>We first operate a rapid inspection of the different BAM files using&nbsp;<strong>samtools flagstat</strong>. Illumina provided chr21 read mapping obtained with their&nbsp;<strong>GA IIx</strong>&nbsp;deep sequencing platform &lt;<a href="ftp://webdata:webdata@ussd-ftp.illumina.com/Data/SequencingRuns/NA18507_GAIIx_100_chr21.bam" target="_blank">ftp://webdata:webdata@ussd-ftp.illumina.com/Data/SequencingRuns/NA18507_GAIIx_100_chr21.bam</a>&gt;, aligned to the b36/hg18 reference genome)</p><p>Address of the bookmark: <a href="https://wiki.bits.vib.be/index.php/NGS_Exercise.6#compare_aln_.26_mem_results_with_vcf-compare" rel="nofollow">https://wiki.bits.vib.be/index.php/NGS_Exercise.6#compare_aln_.26_mem_results_with_vcf-compare</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31568/pacbio-long-reads-compatible-software-and-tools</guid>
	<pubDate>Wed, 15 Mar 2017 14:19:01 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31568/pacbio-long-reads-compatible-software-and-tools</link>
	<title><![CDATA[Pacbio Long Reads Compatible Software and Tools]]></title>
	<description><![CDATA[<p>The following software packages are known to be compatible with PacBio&reg; data, in addition to PacBio's own SMRT&reg; Analysis suite. All packages are believed to be open source or freely available for non-commercial use. See the individual project sites for up-to-date license information. A separate page lists&nbsp;<a href="http://pacb.com/community/partner_program/current_partners/">commercial software</a>.</p>
<p>Know of any other open source software for PacBio data?&nbsp;<a href="mailto:devnet@pacificbiosciences.com">Email us</a>.</p>
<p>Software categories:</p>
<ul>
<li><a href="https://github.com/PacificBiosciences/DevNet/wiki/Compatible-Software#denovo">De novo assembly</a></li>
<li><a href="https://github.com/PacificBiosciences/DevNet/wiki/Compatible-Software#svdetection">Structural Variations Detection</a></li>
<li><a href="https://github.com/PacificBiosciences/DevNet/wiki/Compatible-Software#aligners">Reference-based alignment</a></li>
<li><a href="https://github.com/PacificBiosciences/DevNet/wiki/Compatible-Software#variants">Consensus and variant calling</a></li>
<li><a href="https://github.com/PacificBiosciences/DevNet/wiki/Compatible-Software#RNA">RNA analysis</a></li>
<li><a href="https://github.com/PacificBiosciences/DevNet/wiki/Compatible-Software#basemods">Epigenetic base modifications and methylation</a></li>
<li><a href="https://github.com/PacificBiosciences/DevNet/wiki/Compatible-Software#barcoding">Barcoding</a></li>
<li><a href="https://github.com/PacificBiosciences/DevNet/wiki/Compatible-Software#browsers">Genome Browsers</a></li>
<li><a href="https://github.com/PacificBiosciences/DevNet/wiki/Compatible-Software#qc">Run QC</a></li>
<li><a href="https://github.com/PacificBiosciences/DevNet/wiki/Compatible-Software#frameworks">Frameworks and APIs</a></li>
</ul><p>Address of the bookmark: <a href="https://github.com/PacificBiosciences/DevNet/wiki/Compatible-Software" rel="nofollow">https://github.com/PacificBiosciences/DevNet/wiki/Compatible-Software</a></p>]]></description>
	<dc:creator>Archana Malhotra</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36950/salsa-a-tool-to-scaffold-long-read-assemblies-with-hi-c</guid>
	<pubDate>Fri, 15 Jun 2018 04:01:15 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36950/salsa-a-tool-to-scaffold-long-read-assemblies-with-hi-c</link>
	<title><![CDATA[SALSA: A tool to scaffold long read assemblies with Hi-C]]></title>
	<description><![CDATA[This code is used to scaffold your assemblies using Hi-C data. This version implements some improvements in the original SALSA algorithm. If you want to use the old version, it can be found in the old_salsa branch.

To use the latest version, first run the following commands:

  cd SALSA
  make
To run the code, you will need Python 2.7, BOOST libraries and Networkx(version lower than 1.2).

If you consider using this tool, please cite our publication which describes the methods used for scaffolding.

Ghurye, J., Pop, M., Koren, S., Bickhart, D., &amp; Chin, C. S. (2017). Scaffolding of long read assemblies using long range contact information. BMC genomics, 18(1), 527. Link

Ghurye, J., Rhie, A., Walenz, B.P., Schmitt, A., Selvaraj, S., Pop, M., Phillippy, A.M. and Koren, S., 2018. Integrating Hi-C links with assembly graphs for chromosome-scale assembly. bioRxiv, p.261149 Link

For any queries, please either ask on github issue page or send an email to Jay Ghurye (jayg@cs.umd.edu).<p>Address of the bookmark: <a href="https://github.com/machinegun/SALSA" rel="nofollow">https://github.com/machinegun/SALSA</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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