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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/36607?offset=310</link>
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	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36635/circlator-automated-circularization-of-genome-assemblies-using-long-sequencing-reads</guid>
	<pubDate>Tue, 15 May 2018 09:42:32 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36635/circlator-automated-circularization-of-genome-assemblies-using-long-sequencing-reads</link>
	<title><![CDATA[Circlator: automated circularization of genome assemblies using long sequencing reads]]></title>
	<description><![CDATA[A tool to circularize genome assemblies. The algorithm and benchmarks are described in the Genome Biology manuscript. 

Citation: "Circlator: automated circularization of genome assemblies using long sequencing reads", Hunt et al, Genome Biology 2015 Dec 29;16(1):294. doi: 10.1186/s13059-015-0849-0. PMID: 26714481.<p>Address of the bookmark: <a href="http://sanger-pathogens.github.io/circlator/" rel="nofollow">http://sanger-pathogens.github.io/circlator/</a></p>]]></description>
	<dc:creator>Poonam Mahapatra</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36758/pbalign-maps-pacbio-reads-to-reference-sequences-and-saves-alignments-to-a-bam-file</guid>
	<pubDate>Thu, 24 May 2018 10:06:52 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36758/pbalign-maps-pacbio-reads-to-reference-sequences-and-saves-alignments-to-a-bam-file</link>
	<title><![CDATA[pbalign: maps PacBio reads to reference sequences and saves alignments to a BAM file]]></title>
	<description><![CDATA[pbalign aligns PacBio reads to reference sequences, filters aligned reads according to user-specific filtering criteria, and converts the output to either the SAM format or PacBio Compare HDF5 (e.g., .cmp.h5) format. The output Compare HDF5 file will be compatible with Quiver if --forQuiver option is specified.<p>Address of the bookmark: <a href="https://github.com/PacificBiosciences/pbalign" rel="nofollow">https://github.com/PacificBiosciences/pbalign</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37211/jbrowse-embeddable-genome-browser-built-completely-with-javascript-and-html5</guid>
	<pubDate>Fri, 29 Jun 2018 09:19:56 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37211/jbrowse-embeddable-genome-browser-built-completely-with-javascript-and-html5</link>
	<title><![CDATA[JBrowse: Embeddable genome browser built completely with JavaScript and HTML5]]></title>
	<description><![CDATA[JBrowse is a fast, embeddable genome browser built completely with JavaScript and HTML5, with optional run-once data formatting tools written in Perl.

Headline Features:
Fast, smooth scrolling and zooming. Explore your genome with unparalleled speed.
Scales easily to multi-gigabase genomes and deep-coverage sequencing.
Quickly open and view data files on your computer without uploading them to any server.
Supports GFF3, BED, FASTA, Wiggle, BigWig, BAM, VCF (with either .tbi or .idx index), REST, and more.  BAM, BigBed, BigWig, and VCF data are displayed directly from chunks of the compressed binary files, no conversion needed.
Includes an optional “faceted” track selector (see demo) suitable for large installations with thousands of tracks.
Very light server resource requirements. In fact, JBrowse has no back-end server code, just tools for formatting data files to be read directly over HTTP. Serve huge datasets from a single low-cost cloud instance.
Can run as a stand-alone app on OSX and Windows using the Electron platform
Highly extensible plugin architecture, with a large plugin registry of existing examples here https://gmod.github.io/jbrowse-registry

https://jbrowse.org/<p>Address of the bookmark: <a href="https://github.com/GMOD/jbrowse" rel="nofollow">https://github.com/GMOD/jbrowse</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37759/pandaseq-is-a-program-to-align-illumina-reads-optionally-with-pcr-primers-embedded-in-the-sequence-and-reconstruct-an-overlapping-sequence</guid>
	<pubDate>Fri, 21 Sep 2018 10:19:52 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37759/pandaseq-is-a-program-to-align-illumina-reads-optionally-with-pcr-primers-embedded-in-the-sequence-and-reconstruct-an-overlapping-sequence</link>
	<title><![CDATA[PANDASEQ is a program to align Illumina reads, optionally with PCR primers embedded in the sequence, and reconstruct an overlapping sequence.]]></title>
	<description><![CDATA[<p>Development packages for zlib and libbz2 are needed, as well as a standard compiler environment. On Ubuntu, this can be installed via:</p>
<pre><code>sudo apt-get install build-essential libtool automake zlib1g-dev libbz2-dev pkg-config
</code></pre>
<p>On MacOS, the Apple Developer tools and Fink (or MacPorts or Brew) must be installed, then:</p>
<pre><code>sudo fink install bzip2-dev pkgconfig</code></pre><p>Address of the bookmark: <a href="https://github.com/neufeld/pandaseq" rel="nofollow">https://github.com/neufeld/pandaseq</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37962/wtdbg2-a-de-novo-sequence-assembler-for-long-noisy-reads-produced-by-pacbio-or-oxford-nanopore</guid>
	<pubDate>Fri, 19 Oct 2018 08:48:43 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37962/wtdbg2-a-de-novo-sequence-assembler-for-long-noisy-reads-produced-by-pacbio-or-oxford-nanopore</link>
	<title><![CDATA[Wtdbg2: a de novo sequence assembler for long noisy reads produced by PacBio or Oxford Nanopore]]></title>
	<description><![CDATA[<p><span>Wtdbg2 is a&nbsp;</span><em>de novo</em><span>&nbsp;sequence assembler for long noisy reads produced by PacBio or Oxford Nanopore Technologies (ONT). It assembles raw reads without error correction and then builds the consensus from intermediate assembly output. Wtdbg2 is able to assemble the human and even the 32Gb&nbsp;</span><a href="https://www.nature.com/articles/nature25458">Axolotl</a><span>&nbsp;genome at a speed tens of times faster than&nbsp;</span><a href="https://github.com/marbl/canu">CANU</a><span>&nbsp;and&nbsp;</span><a href="https://github.com/PacificBiosciences/FALCON">FALCON</a><span>while producing contigs of comparable base accuracy.</span></p><p>Address of the bookmark: <a href="https://github.com/ruanjue/wtdbg2" rel="nofollow">https://github.com/ruanjue/wtdbg2</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39671/flye-fast-and-accurate-de-novo-assembler-for-single-molecule-sequencing-reads</guid>
	<pubDate>Sat, 06 Jul 2019 03:48:22 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39671/flye-fast-and-accurate-de-novo-assembler-for-single-molecule-sequencing-reads</link>
	<title><![CDATA[Flye: Fast and accurate de novo assembler for single molecule sequencing reads]]></title>
	<description><![CDATA[<p><span>Flye is a de novo assembler for single molecule sequencing reads, such as those produced by PacBio and Oxford Nanopore Technologies. It is designed for a wide range of datasets, from small bacterial projects to large mammalian-scale assemblies. The package represents a complete pipeline: it takes raw PB / ONT reads as input and outputs polished contigs. Flye also includes a special mode for metagenome assembly.</span></p><p>Address of the bookmark: <a href="https://github.com/fenderglass/Flye" rel="nofollow">https://github.com/fenderglass/Flye</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41030/slr-superscaffolder-a-scaffold-assemble-pipeline-for-stlfr-reads</guid>
	<pubDate>Fri, 14 Feb 2020 14:23:30 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41030/slr-superscaffolder-a-scaffold-assemble-pipeline-for-stlfr-reads</link>
	<title><![CDATA[SLR-superscaffolder: A scaffold assemble pipeline for stLFR reads.]]></title>
	<description><![CDATA[<p>This is a scaffold assembler designed for stLFR reads[1]. It uses the link-reads information from stLFR reads to assemble contigs to scaffolds.</p>
<p>Here is an illustration of this pipeline:</p>
<p>&nbsp;<img src="https://github.com/BGI-Qingdao/SLR-superscaffolder/raw/master/image.png" alt="image" style="border: 0px;"></p><p>Address of the bookmark: <a href="https://github.com/BGI-Qingdao/SLR-superscaffolder" rel="nofollow">https://github.com/BGI-Qingdao/SLR-superscaffolder</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41896/kad-assessing-genome-assemblies-using-k-mer-copies-in-assemblies-and-k-mer-abundance-in-illumina-reads</guid>
	<pubDate>Fri, 19 Jun 2020 07:34:12 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41896/kad-assessing-genome-assemblies-using-k-mer-copies-in-assemblies-and-k-mer-abundance-in-illumina-reads</link>
	<title><![CDATA[KAD: Assessing genome assemblies using K-mer copies in assemblies and K-mer abundance in Illumina reads]]></title>
	<description><![CDATA[<p>KAD is designed for evaluating the accuracy of nucleotide base quality of genome assemblies. Briefly, abundance of k-mers are quantified for both sequencing reads and assembly sequences. Comparison of the two values results in a single value per k-mer, K-mer Abundance Difference (KAD), which indicates how well the assembly matches read data for each k-mer.</p>
<p><a href="https://render.githubusercontent.com/render/math?math=KAD=log_{2}\begin{pmatrix}\frac{c%2Bm}{m(n%2B1)}\end{pmatrix}" target="_blank"><img src="https://render.githubusercontent.com/render/math?math=KAD=log_{2}\begin{pmatrix}\frac{c%2Bm}{m(n%2B1)}\end{pmatrix}" alt="image" style="border: 0px;"></a></p>
<p>where,&nbsp;<em>c</em>&nbsp;is the count of a k-mer from reads,&nbsp;<em>m</em>&nbsp;is the mode of counts of read k-mers, and&nbsp;<em>n</em>&nbsp;is the copy of the k-mer in the assembly.</p><p>Address of the bookmark: <a href="https://github.com/liu3zhenlab/KAD" rel="nofollow">https://github.com/liu3zhenlab/KAD</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42477/hifiasm-a-haplotype-resolved-assembler-for-accurate-hifi-reads</guid>
	<pubDate>Thu, 24 Dec 2020 10:03:36 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42477/hifiasm-a-haplotype-resolved-assembler-for-accurate-hifi-reads</link>
	<title><![CDATA[Hifiasm: a haplotype-resolved assembler for accurate Hifi reads]]></title>
	<description><![CDATA[<p><span>Hifiasm is a fast haplotype-resolved de novo assembler for PacBio Hifi reads. It can assemble a human genome in several hours and works with the California redwood genome, one of the most complex genomes sequenced so far. Hifiasm can produce primary/alternate assemblies of quality competitive with the best assemblers. It also introduces a new graph binning algorithm and achieves the best haplotype-resolved assembly given trio data.</span></p><p>Address of the bookmark: <a href="https://github.com/chhylp123/hifiasm" rel="nofollow">https://github.com/chhylp123/hifiasm</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/43260/bioinformatics-tools-for-telomere-to-telomere-assembly</guid>
	<pubDate>Tue, 17 Aug 2021 13:17:09 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/43260/bioinformatics-tools-for-telomere-to-telomere-assembly</link>
	<title><![CDATA[Bioinformatics tools for telomere to telomere assembly !]]></title>
	<description><![CDATA[<p>●&nbsp;<a href="https://github.com/arangrhie/merfin" target="_blank">Merfin</a>&nbsp;&ndash; k-mer-based assembly and variant calling evaluation for improved consensus accuracy (Arang Rhie)<br />●&nbsp;<a href="https://www.biorxiv.org/content/10.1101/2020.11.11.378133v1" target="_blank">PanGenie</a>&nbsp;&ndash; algorithm that leverages a pangenome reference built from haplotype-resolved genome assemblies in conjunction with k-mer count information from raw, short-read sequencing data to genotype a wide spectrum of genetic variation (Tobias Marschall)<br />●&nbsp;<a href="https://github.com/ConesaLab/SQANTI3" target="_blank">SQANTI3</a>&nbsp;&ndash; an automated pipeline for the classification of long-read transcripts that can assess the quality of data and the preprocessing pipeline (Roc&iacute;o Amor&iacute;n de Heged&uuml;s&nbsp;<a href="https://twitter.com/rocioadh" target="_blank">@rocioadh</a>)<br />●&nbsp;<a href="https://github.com/GenomeRIK/tama" target="_blank">tama</a>&nbsp;(Transcriptome Annotation by Modular Algorithms) &ndash; software designed for processing Iso-Seq data and other long-read transcriptome data (Richard Kuo&nbsp;<a href="https://twitter.com/GenomeRIK" target="_blank">@GenomeRIK</a>)<br />●&nbsp;<a href="https://github.com/PacificBiosciences/pbAA" target="_blank">pbaa</a>&nbsp;(PacBio Amplicon Analysis) &ndash; separates complex mixtures of amplicon targets from genomic samples to cluster and generate high-quality consensus sequences from HiFi reads (Zev Kronenberg&nbsp;<a href="https://twitter.com/zevkronenberg" target="_blank">@zevkronenberg</a>)<br />●&nbsp;<a href="https://github.com/yuanyuan929/bellerophon" target="_blank">bellerophon</a>&nbsp;&ndash; analyzes MHC typing and other low-complexity gene amplicon data; performs allele calling while detecting polymorphic sites within the sequences and removing potential chimeric sequence variants (Yuanyuan Cheng&nbsp;<a href="https://twitter.com/Yuanyuan929" target="_blank">@Yuanyuan929</a>)<br />●&nbsp;<a href="https://github.com/amwenger/svpack" target="_blank">svpack</a>&nbsp;&ndash; tools for filtering, comparing, and annotating structural variant (SV) calls in VCF format (Aaron Wenger)<br />●&nbsp;<a href="https://github.com/AntonBankevich/jumboDB" target="_blank">JumboDB</a>&nbsp;&ndash; tool for de Bruijn graph construction (Anton Bankevich&nbsp;<a href="https://twitter.com/AntonBankevich" target="_blank">@AntonBankevich</a>)<br />●&nbsp;<a href="https://github.com/ksahlin/ultra" target="_blank">uLTRA</a>&nbsp;&ndash; tool for splice alignment of long transcriptomic reads to a genome, guided by a database of exon annotations. (Kristoffer Sahlin&nbsp;<a href="https://twitter.com/krsahlin" target="_blank">@krsahlin</a>)<br />●&nbsp;<a href="https://www.biorxiv.org/content/10.1101/2021.01.25.428044v1.full.pdf" target="_blank">LeafGo</a>&nbsp;&ndash; workflow to rapidly produce high-quality de novo plant genomes (Luca Ermini&nbsp;<a href="https://twitter.com/ermini_luca" target="_blank">@ermini_luca</a>)</p><p>Reference:</p><p>https://www.pacb.com/blog/young-investigators-share-stellar-science-career-advice-and-bioinformatics-tools-at-smrt-leiden-2021/</p><p>&nbsp;</p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>

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