<?xml version='1.0'?><rss version="2.0" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:georss="http://www.georss.org/georss" xmlns:atom="http://www.w3.org/2005/Atom" >
<channel>
	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/42941?offset=100</link>
	<atom:link href="https://bioinformaticsonline.com/related/42941?offset=100" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35292/pgap-x-extension-on-pan-genome-analysis-pipeline</guid>
	<pubDate>Tue, 23 Jan 2018 11:41:43 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35292/pgap-x-extension-on-pan-genome-analysis-pipeline</link>
	<title><![CDATA[PGAP-X: Extension on pan-genome analysis pipeline]]></title>
	<description><![CDATA[<p>PGAP-X is a microbial comparative genomic analysis platform with graphic interface. Serials of algorithms and methodologies have been developed and integrated to analyze and visualize genomics structure variation, gene distribution with different conservative levels, and genetic variation from pan-genome sight. At the same time, analytical result data from many other programs, including genome alignment result and orthologs clusters, are also supported to be further analyzed or visualized in PGAP-X. The workflow and feature snapshot in PGAP-X were shown as Fig.1 and Fig.2.</p>
<div><img src="https://pgapx.ybzhao.com/image/f1.jpg" alt="image" style="border: 0px; border: 0px;"></div>
<div>&nbsp;</div>
<p>&nbsp;</p><p>Address of the bookmark: <a href="https://pgapx.ybzhao.com/" rel="nofollow">https://pgapx.ybzhao.com/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38762/katuali-is-a-flexible-consensus-pipeline-implemented-in-snakemake-to-basecall-assemble-and-polish-oxford-nanopore-technologies-sequencing-data</guid>
	<pubDate>Tue, 22 Jan 2019 06:26:55 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38762/katuali-is-a-flexible-consensus-pipeline-implemented-in-snakemake-to-basecall-assemble-and-polish-oxford-nanopore-technologies-sequencing-data</link>
	<title><![CDATA[Katuali is a flexible consensus pipeline implemented in Snakemake to basecall, assemble, and polish Oxford Nanopore Technologies&#039; sequencing data]]></title>
	<description><![CDATA[<ul>
<li>Run a pipeline processing fast5s to a consensus in a single command.</li>
<li>Recommended fixed "standard" and "fast" pipelines.</li>
<li>Interchange basecaller, assembler, and consensus components of the pipelines simply by changing the target filepath.</li>
<li>Seemless distribution of tasks over local or distributed compute.</li>
<li>Highly configurable.</li>
<li>Open source (Mozilla Public License 2.0).</li>
</ul>
<p>Documentation can be found at&nbsp;<a href="https://nanoporetech.github.io/katuali/">https://nanoporetech.github.io/katuali/</a>.</p><p>Address of the bookmark: <a href="https://github.com/nanoporetech/katuali" rel="nofollow">https://github.com/nanoporetech/katuali</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40604/gapfinisher-a-reliable-gap-filling-pipeline-for-sspace-longread-scaffolder-output</guid>
	<pubDate>Fri, 24 Jan 2020 06:04:40 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40604/gapfinisher-a-reliable-gap-filling-pipeline-for-sspace-longread-scaffolder-output</link>
	<title><![CDATA[gapFinisher: A reliable gap filling pipeline for SSPACE-LongRead scaffolder output]]></title>
	<description><![CDATA[<p><span>gapFinisher is based on the controlled use of a previously published gap filling tool FGAP and works on all standard Linux/UNIX command lines. They compare the performance of gapFinisher against two other published gap filling tools PBJelly and GMcloser. </span></p>
<p><span>gapFinisher can fill gaps in draft genomes quickly and reliably.</span></p><p>Address of the bookmark: <a href="https://github.com/kammoji/gapFinisher" rel="nofollow">https://github.com/kammoji/gapFinisher</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41893/sunbeam-a-robust-extensible-metagenomics-pipeline</guid>
	<pubDate>Thu, 18 Jun 2020 06:58:52 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41893/sunbeam-a-robust-extensible-metagenomics-pipeline</link>
	<title><![CDATA[sunbeam: A robust, extensible metagenomics pipeline]]></title>
	<description><![CDATA[<p><span>Sunbeam is a pipeline written in&nbsp;</span><a href="http://snakemake.readthedocs.io/">snakemake</a><span>&nbsp;that simplifies and automates many of the steps in metagenomic sequencing analysis. It uses&nbsp;</span><a href="http://conda.io/">conda</a><span>&nbsp;to manage dependencies, so it doesn't have pre-existing dependencies or admin privileges, and can be deployed on most Linux workstations and clusters. To read more, check out&nbsp;</span><a href="https://microbiomejournal.biomedcentral.com/articles/10.1186/s40168-019-0658-x">our paper in Microbiome</a><span>.</span></p>
<p><span><a href="https://sunbeam.readthedocs.io/en/latest/">https://sunbeam.readthedocs.io/en/latest/</a></span></p><p>Address of the bookmark: <a href="https://github.com/sunbeam-labs/sunbeam" rel="nofollow">https://github.com/sunbeam-labs/sunbeam</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42946/aligngraph2-similar-genome-assisted-reassembly-pipeline-for-pacbio-long-reads</guid>
	<pubDate>Sun, 14 Mar 2021 09:42:47 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42946/aligngraph2-similar-genome-assisted-reassembly-pipeline-for-pacbio-long-reads</link>
	<title><![CDATA[AlignGraph2: similar genome-assisted reassembly pipeline for PacBio long reads]]></title>
	<description><![CDATA[<p><span>AlignGraph2 is the second version of&nbsp;</span><a href="https://github.com/baoe/AlignGraph">AlignGraph</a><span>&nbsp;for PacBio long reads. It extends and refines contigs assembled from the long reads with a published genome similar to the sequencing genome.</span></p>
<p><span>More at&nbsp;https://academic.oup.com/bib/advance-article-abstract/doi/10.1093/bib/bbab022/6146772</span></p><p>Address of the bookmark: <a href="https://github.com/huangs001/AlignGraph2" rel="nofollow">https://github.com/huangs001/AlignGraph2</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44375/phyloherb-a-high%E2%80%90throughput-phylogenomic-pipeline-for-processing-genome-skimming-data</guid>
	<pubDate>Wed, 06 Sep 2023 00:14:28 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44375/phyloherb-a-high%E2%80%90throughput-phylogenomic-pipeline-for-processing-genome-skimming-data</link>
	<title><![CDATA[PhyloHerb: A high‐throughput phylogenomic pipeline for processing genome skimming data]]></title>
	<description><![CDATA[<p dir="auto"><span>Phylo</span>genomic Analysis Pipeline for&nbsp;<span>Herb</span>arium Specimens</p>
<p dir="auto"><span>What is PhyloHerb</span>: PhyloHerb is a wrapper program to process&nbsp;<span>genome skimming</span>&nbsp;data collected from plant materials. The outcomes include the plastid genome (plastome) assemblies, mitochondrial genome assemblies, nuclear ribosomal DNAs (NTS+ETS+18S+ITS1+5.8S+ITS2+28S), alignments of gene and intergenic regions, and a species tree. It is designed to be a high throughput program dealing with lower quality data. Examples include&nbsp;<span>low-coverage (5x cpDNA) plastome phylogeny, recycling plastid genes from target enrichment data, retrieving low-copy nuclear genes from medium coverage (5x nucDNA) genome skimming</span>.</p>
<p dir="auto"><span>License</span>: GNU General Public License</p>
<p dir="auto"><span>Citation</span>:</p>
<ul dir="auto">
<li>Cai, Liming, Hongrui Zhang, and Charles C. Davis. 2022. PhyloHerb: A high‐throughput phylogenomic pipeline for processing genome‐skimming data. Applications in Plant Sciences 10(3): 1&ndash;9.&nbsp;<a href="https://doi.org/10.1002/aps3.11475">https://doi.org/10.1002/aps3.11475</a></li>
</ul><p>Address of the bookmark: <a href="https://github.com/lmcai/PhyloHerb/" rel="nofollow">https://github.com/lmcai/PhyloHerb/</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/27695/the-kingsley-lab</guid>
  <pubDate>Fri, 03 Jun 2016 09:55:10 -0500</pubDate>
  <link></link>
  <title><![CDATA[The Kingsley Lab]]></title>
  <description><![CDATA[
<p>The Molecular Basis of Vertebrate Evolution. Naturally occurring species show spectacular differences in morphology, physiology, behavior, disease susceptibility, and life span. Although the genomes of many organisms have now been completely sequenced, Kingsley lab still know relatively little about the specific DNA sequence changes that underlie interesting species-specific traits. Kingsley lab laboratory is using a combination of genetic and genomic approaches to identify the detailed molecular mechanisms that control evolutionary change in vertebrates.</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34416/miniasm-very-fast-olc-based-de-novo-assembler-for-noisy-long-reads</guid>
	<pubDate>Mon, 27 Nov 2017 07:58:49 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34416/miniasm-very-fast-olc-based-de-novo-assembler-for-noisy-long-reads</link>
	<title><![CDATA[miniasm: very fast OLC-based de novo assembler for noisy long reads]]></title>
	<description><![CDATA[<p>Miniasm is a very fast OLC-based&nbsp;<em>de novo</em>&nbsp;assembler for noisy long reads. It takes all-vs-all read self-mappings (typically by&nbsp;<a href="https://github.com/lh3/minimap">minimap</a>) as input and outputs an assembly graph in the&nbsp;<a href="https://github.com/pmelsted/GFA-spec/blob/master/GFA-spec.md">GFA</a>&nbsp;format. Different from mainstream assemblers, miniasm does not have a consensus step. It simply concatenates pieces of read sequences to generate the final&nbsp;<a href="http://wgs-assembler.sourceforge.net/wiki/index.php/Celera_Assembler_Terminology">unitig</a>&nbsp;sequences. Thus the per-base error rate is similar to the raw input reads.</p>
<p>So far miniasm is in early development stage. It has only been tested on a dozen of PacBio and Oxford Nanopore (ONT) bacterial data sets. Including the mapping step, it takes about 3 minutes to assemble a bacterial genome. Under the default setting, miniasm assembles 9 out of 12 PacBio datasets and 3 out of 4 ONT datasets into a single contig. The 12 PacBio data sets are&nbsp;<a href="https://github.com/PacificBiosciences/DevNet/wiki/E.-coli-Bacterial-Assembly">PacBio E. coli sample</a>,&nbsp;<a href="http://www.ebi.ac.uk/ena/data/view/ERS473430">ERS473430</a>,&nbsp;<a href="http://www.ebi.ac.uk/ena/data/view/ERS544009">ERS544009</a>,&nbsp;<a href="http://www.ebi.ac.uk/ena/data/view/ERS554120">ERS554120</a>,&nbsp;<a href="http://www.ebi.ac.uk/ena/data/view/ERS605484">ERS605484</a>,&nbsp;<a href="http://www.ebi.ac.uk/ena/data/view/ERS617393">ERS617393</a>,&nbsp;<a href="http://www.ebi.ac.uk/ena/data/view/ERS646601">ERS646601</a>,&nbsp;<a href="http://www.ebi.ac.uk/ena/data/view/ERS659581">ERS659581</a>,&nbsp;<a href="http://www.ebi.ac.uk/ena/data/view/ERS670327">ERS670327</a>,&nbsp;<a href="http://www.ebi.ac.uk/ena/data/view/ERS685285">ERS685285</a>,&nbsp;<a href="http://www.ebi.ac.uk/ena/data/view/ERS743109">ERS743109</a>&nbsp;and a&nbsp;<a href="https://github.com/PacificBiosciences/DevNet/wiki/E.-coli-20kb-Size-Selected-Library-with-P6-C4/ce0533c1d2a957488594f0b29da61ffa3e4627e8">deprecated PacBio E. coli data set</a>. ONT data are acquired from the&nbsp;<a href="http://lab.loman.net/2015/09/24/first-sqk-map-006-experiment/">Loman Lab</a>.</p>
<p>For a&nbsp;<em>C. elegans</em>&nbsp;<a href="https://github.com/PacificBiosciences/DevNet/wiki/C.-elegans-data-set">PacBio data set</a>&nbsp;(only 40X are used, not the whole dataset), miniasm finishes the assembly, including reads overlapping, in ~10 minutes with 16 CPUs. The total assembly size is 105Mb; the N50 is 1.94Mb. In comparison, the&nbsp;<a href="https://github.com/PacificBiosciences/Bioinformatics-Training/wiki/HGAP">HGAP3</a>produces a 104Mb assembly with N50 1.61Mb.&nbsp;<a href="http://lh3lh3.users.sourceforge.net/download/ce-miniasm.png">This dotter plot</a>&nbsp;gives a global view of the miniasm assembly (on the X axis) and the HGAP3 assembly (on Y). They are broadly comparable. Of course, the HGAP3 consensus sequences are much more accurate. In addition, on the whole data set (assembled in ~30 min), the miniasm N50 is reduced to 1.79Mb. Miniasm still needs improvements.</p>
<p>Miniasm confirms that at least for high-coverage bacterial genomes, it is possible to generate long contigs from raw PacBio or ONT reads without error correction. It also shows that&nbsp;<a href="https://github.com/lh3/minimap">minimap</a>&nbsp;can be used as a read overlapper, even though it is probably not as sensitive as the more sophisticated overlapers such as&nbsp;<a href="https://github.com/marbl/MHAP">MHAP</a>&nbsp;and&nbsp;<a href="https://github.com/thegenemyers/DALIGNER">DALIGNER</a>. Coupled with long-read error correctors and consensus tools, miniasm may also be useful to produce high-quality assemblies.</p>
<p>Minimap and miniasm are ultrafast tools for (i) mapping and (ii) assembly. Designed for long, noisy reads, they do not have a correction or consensus step, and therefore the resulting assemblies are contiguous (i.e. long) but very noisy (i.e. full of errors)</p>
<p>We start with an all against all comparison:</p>
<div>
<pre><code>minimap -Sw5 -L100 -m0 -t8 reads.fq reads.fq | gzip -1 &gt; reads.paf.gz
</code></pre>
</div>
<p>Then we can assemble</p>
<div>
<pre><code>miniasm -f reads.fq reads.paf.gz &gt; reads.gfa
</code></pre>
</div>
<p>Convert GFA to FASTA:</p>
<div>
<pre><code>awk <span>'/^S/{print "&gt;"$2"\n"$3}'</span> reads.gfa | fold &gt; reads.fa
</code></pre>
</div>
<p>And then count how many contigs:</p>
<div>
<pre><code>grep <span>"&gt;"</span> reads.fa | wc -l</code></pre>
</div>
<p>&nbsp;</p>
<pre><span><span>#</span> Download sample PacBio from the PBcR website</span>
wget -O- http://www.cbcb.umd.edu/software/PBcR/data/selfSampleData.tar.gz <span>|</span> tar zxf -
ln -s selfSampleData/pacbio_filtered.fastq reads.fq
<span><span>#</span> Install minimap and miniasm (requiring gcc and zlib)</span>
git clone https://github.com/lh3/minimap <span>&amp;&amp;</span> (cd minimap <span>&amp;&amp;</span> make)
git clone https://github.com/lh3/miniasm <span>&amp;&amp;</span> (cd miniasm <span>&amp;&amp;</span> make)
<span><span>#</span> Overlap</span>
minimap/minimap -Sw5 -L100 -m0 -t8 reads.fq reads.fq <span>|</span> gzip -1 <span>&gt;</span> reads.paf.gz
<span><span>#</span> Layout</span>
miniasm/miniasm -f reads.fq reads.paf.gz <span>&gt;</span> reads.gfa</pre><p>Address of the bookmark: <a href="https://github.com/lh3/miniasm" rel="nofollow">https://github.com/lh3/miniasm</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34618/mashmap-a-fast-and-approximate-software-for-mapping-long-reads-pacbioont-or-assembly-to-reference-genomes</guid>
	<pubDate>Tue, 12 Dec 2017 17:23:31 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34618/mashmap-a-fast-and-approximate-software-for-mapping-long-reads-pacbioont-or-assembly-to-reference-genomes</link>
	<title><![CDATA[MashMap: a fast and approximate software for mapping long reads (PacBio/ONT) or assembly to reference genome(s)]]></title>
	<description><![CDATA[<p><span>MashMap is a fast and approximate software for mapping long reads (PacBio/ONT) or assembly to reference genome(s). It maps a query sequence against a reference region if and only if its estimated alignment identity is above a specified threshold. It does not compute the alignments explicitly, but rather estimates a&nbsp;</span><em>k</em><span>-mer based&nbsp;</span><a href="https://en.wikipedia.org/wiki/Jaccard_index">Jaccard similarity</a><span>&nbsp;using a combination of&nbsp;</span><a href="http://www.cs.princeton.edu/courses/archive/spr05/cos598E/bib/p76-schleimer.pdf">Winnowing</a><span>&nbsp;and&nbsp;</span><a href="https://en.wikipedia.org/wiki/MinHash">MinHash</a><span>. This is then converted to an estimate of sequence identity using the&nbsp;</span><a href="http://mash.readthedocs.org/">Mash</a><span>&nbsp;distance. An appropriate&nbsp;</span><em>k</em><span>-mer sampling rate is automatically determined given minimum local alignment length and identity thresholds. The efficiency of the algorithm improves as both of these thresholds are increased.</span></p><p>Address of the bookmark: <a href="https://github.com/marbl/MashMap" rel="nofollow">https://github.com/marbl/MashMap</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35345/rgfa-powerful-and-convenient-handling-of-assembly-graphs</guid>
	<pubDate>Thu, 25 Jan 2018 05:47:53 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35345/rgfa-powerful-and-convenient-handling-of-assembly-graphs</link>
	<title><![CDATA[RGFA: powerful and convenient handling of assembly graphs]]></title>
	<description><![CDATA[<p><span>RGFA, an implementation of the proposed GFA specification in Ruby. It allows the user to conveniently parse, edit and write GFA files. Complex operations such as the separation of the implicit instances of repeats and the merging of linear paths can be performed. A typical application of RGFA is the editing of a graph, to finish the assembly of a sequence, using information not available to the assembler. We illustrate a use case, in which the assembly of a repetitive metagenomic fosmid insert was completed using a script based on RGFA.</span></p>
<p><span>https://github.com/ggonnella/rgfa</span></p><p>Address of the bookmark: <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5103826/" rel="nofollow">https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5103826/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>

</channel>
</rss>