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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/43090?offset=180</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/33976/goldgenomes-online-database</guid>
	<pubDate>Wed, 26 Jul 2017 07:49:29 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/33976/goldgenomes-online-database</link>
	<title><![CDATA[GOLD:Genomes Online Database]]></title>
	<description><![CDATA[<p><span>GOLD</span><span>:Genomes Online Database, is a World Wide Web resource for comprehensive access to information regarding genome and metagenome sequencing projects, and their associated metadata, around the world.</span></p>
<p>https://gold.jgi.doe.gov/</p><p>Address of the bookmark: <a href="https://gold.jgi.doe.gov/" rel="nofollow">https://gold.jgi.doe.gov/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44599/p10k-the-protist-10000-genomes</guid>
	<pubDate>Sat, 06 Jul 2024 08:29:30 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44599/p10k-the-protist-10000-genomes</link>
	<title><![CDATA[P10K: The Protist 10,000 Genomes]]></title>
	<description><![CDATA[<p><span>The Protist 10,000 Genomes (P10K) Project aims to decipher the genome sequences and construct a comprehensive database resource containing over 10,000 species of protists, encompassing representatives from every major clade. Samples were collected from diverse habitats, and the genome information was acquired through de novo sequencing, genome re-annotation, and integration of publicly available data. Serving as a centralized data portal for the project, the P10K database primarily focuses on delivering high-quality curation and facilitating efficient retrieval of protist genome data.</span></p><p>Address of the bookmark: <a href="https://ngdc.cncb.ac.cn/p10k/" rel="nofollow">https://ngdc.cncb.ac.cn/p10k/</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34377/genomicus-genome-browser-that-enables-users-to-navigate-in-genomes-in-several-dimensions</guid>
	<pubDate>Sat, 18 Nov 2017 16:10:16 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34377/genomicus-genome-browser-that-enables-users-to-navigate-in-genomes-in-several-dimensions</link>
	<title><![CDATA[Genomicus: genome browser that enables users to navigate in genomes in several dimensions]]></title>
	<description><![CDATA[<p>Genomicus is a genome browser that enables users to navigate in genomes in several dimensions: linearly along chromosome axes, transversaly across different species, and chronologicaly along evolutionary time.</p>
<p>Once a query gene has been entered, it is displayed in its genomic context in parallel to the genomic context of all its orthologous and paralogous copies in all the other sequenced metazoan genomes. Moreover, Genomicus stores and displays the predicted ancestral genome structure in all the ancestral species within the phylogenetic range of interest.</p>
<p>All the data on extant species displayed in this browser are from&nbsp;<a href="http://www.ensembl.org/">Ensembl</a>.</p><p>Address of the bookmark: <a href="http://genomicus.biologie.ens.fr/genomicus-90.01/cgi-bin/search.pl" rel="nofollow">http://genomicus.biologie.ens.fr/genomicus-90.01/cgi-bin/search.pl</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36736/checkmassessing-the-quality-of-microbial-genomes-recovered-from-isolates-single-cells-and-metagenomes</guid>
	<pubDate>Wed, 23 May 2018 04:39:26 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36736/checkmassessing-the-quality-of-microbial-genomes-recovered-from-isolates-single-cells-and-metagenomes</link>
	<title><![CDATA[CheckM:Assessing the quality of microbial genomes recovered from isolates, single cells, and metagenomes]]></title>
	<description><![CDATA[<p><span>CheckM provides a set of tools for assessing the quality of genomes recovered from isolates, single cells, or metagenomes. It provides robust estimates of genome completeness and contamination by using collocated sets of genes that are ubiquitous and single-copy within a phylogenetic lineage. Assessment of genome quality can also be examined using plots depicting key genomic characteristics (e.g., GC, coding density) which highlight sequences outside the expected distributions of a typical genome. CheckM also provides tools for identifying genome bins that are likely candidates for merging based on marker set compatibility, similarity in genomic characteristics, and proximity within a reference genome tree.</span></p><p>Address of the bookmark: <a href="http://ecogenomics.github.io/CheckM/" rel="nofollow">http://ecogenomics.github.io/CheckM/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37957/base-a-practical-de-novo-assembler-for-large-genomes-using-long-ngs-reads</guid>
	<pubDate>Fri, 19 Oct 2018 07:25:21 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37957/base-a-practical-de-novo-assembler-for-large-genomes-using-long-ngs-reads</link>
	<title><![CDATA[BASE: a practical de novo assembler for large genomes using long NGS reads]]></title>
	<description><![CDATA[<p><span>new&nbsp;</span><em>de novo</em><span>&nbsp;assembler called BASE. It enhances the classic seed-extension approach by indexing the reads efficiently to generate adaptive seeds that have high probability to appear uniquely in the genome. Such seeds form the basis for BASE to build extension trees and then to use reverse validation to remove the branches based on read coverage and paired-end information, resulting in high-quality consensus sequences of reads sharing the seeds. Such consensus sequences are then extended to contigs.</span></p><p>Address of the bookmark: <a href="https://github.com/dhlbh/BASE" rel="nofollow">https://github.com/dhlbh/BASE</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40409/haplotypo-a-variant-calling-pipeline-for-phased-genomes</guid>
	<pubDate>Thu, 19 Dec 2019 07:33:40 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40409/haplotypo-a-variant-calling-pipeline-for-phased-genomes</link>
	<title><![CDATA[HaploTypo: a variant-calling pipeline for phased genomes]]></title>
	<description><![CDATA[<p>An increasing number of phased (i.e. with resolved haplotypes) reference genomes are available. However, most genetic variant calling tools do not explicitly account for haplotype structure. Here, we present HaploTypo, a pipeline tailored to resolve haplotypes in genetic variation analyses. HaploTypo infers the haplotype correspondence for each heterozygous variant called on a phased reference genome.</p>
<div>Availability and Implementation</div>
<p>HaploTypo is implemented in Python 2.7 and Python 3.5, and is freely available at&nbsp;<a href="https://github.com/gabaldonlab/haplotypo" target="">https://github.com/gabaldonlab/haplotypo</a>, and as a Docker image.</p><p>Address of the bookmark: <a href="https://github.com/gabaldonlab/haplotypo" rel="nofollow">https://github.com/gabaldonlab/haplotypo</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42357/irscope-an-online-program-to-visualize-the-junction-sites-of-chloroplast-genomes</guid>
	<pubDate>Wed, 25 Nov 2020 19:44:46 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42357/irscope-an-online-program-to-visualize-the-junction-sites-of-chloroplast-genomes</link>
	<title><![CDATA[IRscope: an online program to visualize the junction sites of chloroplast genomes]]></title>
	<description><![CDATA[<p><span>eMPRess, a software program for phylogenetic tree reconciliation under the duplication-transfer-loss model that systematically addresses the problems of choosing event costs and selecting representative solutions, enabling users to make more robust inferences.</span></p><p>Address of the bookmark: <a href="https://sites.google.com/g.hmc.edu/empress/home" rel="nofollow">https://sites.google.com/g.hmc.edu/empress/home</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44561/bactopia-a-flexible-pipeline-for-complete-analysis-of-bacterial-genomes</guid>
	<pubDate>Sat, 08 Jun 2024 16:25:08 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44561/bactopia-a-flexible-pipeline-for-complete-analysis-of-bacterial-genomes</link>
	<title><![CDATA[Bactopia: a flexible pipeline for complete analysis of bacterial genomes]]></title>
	<description><![CDATA[<p>Bactopia is a flexible pipeline for complete analysis of bacterial genomes. The goal of Bactopia is process your data with a broad set of tools, so that you can get to the fun part of analyses quicker!</p>
<p>Bactopia was inspired by&nbsp;<a href="https://staphopia.github.io/">Staphopia</a>, a workflow we (Tim Read and myself) released that is targeted towards&nbsp;<em>Staphylococcus aureus</em>&nbsp;genomes. Using what we learned from Staphopia and user feedback, Bactopia was developed from scratch with usability, portability, and speed in mind from the start.</p>
<p>Bactopia uses&nbsp;<a href="https://www.nextflow.io/">Nextflow</a>&nbsp;to manage the workflow, allowing for support of many types of environments (e.g. cluster or cloud). Bactopia allows for the usage of many public datasets as well as your own datasets to further enhance the analysis of your sequencing. Bactopia only uses software packages available from&nbsp;<a href="https://bioconda.github.io/">Bioconda</a>&nbsp;and&nbsp;<a href="https://conda-forge.org/">Conda-Forge</a>&nbsp;to make installation as simple as possible for&nbsp;<em>all</em>&nbsp;users.</p>
<p>To highlight the use of&nbsp;<a href="https://bactopia.github.io/latest/full-guide/">Bactopia</a>&nbsp;and&nbsp;<a href="https://bactopia.github.io/latest/bactopia-tools/">Bactopia Tools</a>, we performed an analysis of 1,664 public&nbsp;<em>Lactobacillus</em>&nbsp;genomes, focusing on&nbsp;<em>Lactobacillus crispatus</em>, a species that is a common part of the human vaginal microbiome. The results from this analysis are published in mSystems under the title:&nbsp;<em><a href="https://doi.org/10.1128/mSystems.00190-20">Bactopia: a flexible pipeline for complete analysis of bacterial genomes</a></em></p>
<p><a href="https://bactopia.github.io/latest/assets/bactopia-workflow.png"><img src="https://bactopia.github.io/latest/assets/bactopia-workflow.png" alt="Bactopia Workflow" style="border: 0px;"></a></p><p>Address of the bookmark: <a href="https://bactopia.github.io/latest/" rel="nofollow">https://bactopia.github.io/latest/</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35061/proovread-large-scale-high-accuracy-pacbio-correction-through-iterative-short-read-consensus</guid>
	<pubDate>Fri, 05 Jan 2018 04:12:20 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35061/proovread-large-scale-high-accuracy-pacbio-correction-through-iterative-short-read-consensus</link>
	<title><![CDATA[proovread : large-scale high-accuracy PacBio correction through iterative short read consensus]]></title>
	<description><![CDATA[<p>proovread : large-scale high-accuracy PacBio correction through iterative short read consensus</p>
<ul>
<li>outperforms PacBioToCA/LSC in terms of accuracy and contiguity/sensitivity (<a href="http://dx.doi.org/10.1093/bioinformatics/btu392">http://dx.doi.org/10.1093/bioinformatics/btu392</a>)</li>
<li>is easy to install/run/configure</li>
<li>supports various types of dat
<ul>
<li><strong>HiSeq/MiSeq&nbsp;</strong>(100-500bp)</li>
<li><strong>Unitigs</strong></li>
<li>454, ...</li>
</ul>
</li>
</ul>
<p>proovread maps high coverage data to pacbio reads (bwa mem, blasr, daligner) in multiple iterations.</p><p>Address of the bookmark: <a href="https://github.com/BioInf-Wuerzburg/proovread" rel="nofollow">https://github.com/BioInf-Wuerzburg/proovread</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36884/halc-high-throughput-algorithm-for-long-read-error-correction</guid>
	<pubDate>Fri, 08 Jun 2018 10:47:41 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36884/halc-high-throughput-algorithm-for-long-read-error-correction</link>
	<title><![CDATA[HALC: High throughput algorithm for long read error correction]]></title>
	<description><![CDATA[HALC, a high throughput algorithm for long read error correction. HALC aligns the long reads to short read contigs from the same species with a relatively low identity requirement so that a long read region can be aligned to at least one contig region, including its true genome region’s repeats in the contigs sufficiently similar to it (similar repeat based alignment approach)

HALC was able to obtain 6.7-41.1% higher throughput than the existing algorithms while maintaining comparable accuracy. The HALC corrected long reads can thus result in 11.4-60.7% longer assembled contigs than the existing algorithms.<p>Address of the bookmark: <a href="https://github.com/lanl001/halc" rel="nofollow">https://github.com/lanl001/halc</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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