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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/37205?offset=100</link>
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	<description><![CDATA[]]></description>
	
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43870/quip-aggressive-compression-of-fastq-sam-and-bam-files</guid>
	<pubDate>Tue, 24 May 2022 06:31:48 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43870/quip-aggressive-compression-of-fastq-sam-and-bam-files</link>
	<title><![CDATA[Quip: Aggressive compression of FASTQ, SAM and BAM files.]]></title>
	<description><![CDATA[<p>This will help us to reduce the amount of drive space we take up and decrease data transfer times</p>
<p dir="auto">Quip compresses next-generation sequencing data with extreme prejudice. It supports input and output in the&nbsp;<a href="http://en.wikipedia.org/wiki/Fastq">FASTQ</a>&nbsp;and&nbsp;<a href="http://samtools.sourceforge.net/">SAM/BAM</a>&nbsp;formats, compressing large datasets to as little as 15% of their original size.</p><p>Address of the bookmark: <a href="https://github.com/dcjones/quip" rel="nofollow">https://github.com/dcjones/quip</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/44637/tools-to-access-the-quality-of-your-assembled-genome</guid>
	<pubDate>Thu, 08 Aug 2024 23:31:18 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/44637/tools-to-access-the-quality-of-your-assembled-genome</link>
	<title><![CDATA[Tools to access the quality of your assembled genome !]]></title>
	<description><![CDATA[<ul dir="auto">
<li><a href="https://github.com/linsalrob/fasta_validator">FASTA VALIDATOR</a>&nbsp;+&nbsp;<a href="https://github.com/shenwei356/seqkit">SEQKIT RMDUP</a>: FASTA validation</li>
<li><a href="https://genometools.org/tools/gt_gff3validator.html">GENOMETOOLS GT GFF3VALIDATOR</a>: GFF3 validation</li>
<li><a href="https://github.com/PlantandFoodResearch/assemblathon2-analysis/blob/a93cba25d847434f7eadc04e63b58c567c46a56d/assemblathon_stats.pl">ASSEMBLATHON STATS</a>: Assembly statistics</li>
<li><a href="https://genometools.org/tools/gt_stat.html">GENOMETOOLS GT STAT</a>: Annotation statistics</li>
<li><a href="https://github.com/ncbi/fcs">NCBI FCS ADAPTOR</a>: Adaptor contamination pass/fail</li>
<li><a href="https://github.com/ncbi/fcs">NCBI FCS GX</a>: Foreign organism contamination pass/fail</li>
<li><a href="https://gitlab.com/ezlab/busco">BUSCO</a>: Gene-space completeness estimation</li>
<li><a href="https://github.com/tolkit/telomeric-identifier">TIDK</a>: Telomere repeat identification</li>
<li><a href="https://github.com/oushujun/LTR_retriever/blob/master/LAI">LAI</a>: Continuity of repetitive sequences</li>
<li><a href="https://github.com/DerrickWood/kraken2">KRAKEN2</a>: Taxonomy classification</li>
<li><a href="https://github.com/igvteam/juicebox.js">HIC CONTACT MAP</a>: Alignment and visualisation of HiC data</li>
<li><a href="https://github.com/mummer4/mummer">MUMMER</a>&nbsp;&rarr;&nbsp;<a href="http://circos.ca/documentation/">CIRCOS</a>&nbsp;+&nbsp;<a href="https://plotly.com/">DOTPLOT</a>&nbsp;&amp;&nbsp;<a href="https://github.com/lh3/minimap2">MINIMAP2</a>&nbsp;&rarr;&nbsp;<a href="https://github.com/schneebergerlab/plotsr">PLOTSR</a>: Synteny analysis</li>
<li><a href="https://github.com/marbl/merqury">MERQURY</a>: K-mer completeness, consensus quality and phasing assessment</li>
</ul>]]></description>
	<dc:creator>LEGE</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/44476/omark-software-for-proteome-protein-coding-gene-repertoire-quality-assessment</guid>
	<pubDate>Wed, 21 Feb 2024 15:01:20 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44476/omark-software-for-proteome-protein-coding-gene-repertoire-quality-assessment</link>
	<title><![CDATA[OMArk: software for proteome (protein-coding gene repertoire) quality assessment]]></title>
	<description><![CDATA[<p><span>OMArk is a software for proteome (protein-coding gene repertoire) quality assessment. It provides measures of proteome completeness, characterizes the consistency of all protein coding genes with regard to their homologs, and identifies the presence of contamination from other species. OMArk relies on the OMA orthology database, from which it exploits orthology relationships, and on the OMAmer software for fast placement of all proteins into gene families.</span></p><p>Address of the bookmark: <a href="https://github.com/DessimozLab/OMArk" rel="nofollow">https://github.com/DessimozLab/OMArk</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40986/cismuton-caller-that-detects-snvsindels-by-comparing-target-foreground-and-control-background-samples</guid>
	<pubDate>Tue, 11 Feb 2020 05:55:00 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40986/cismuton-caller-that-detects-snvsindels-by-comparing-target-foreground-and-control-background-samples</link>
	<title><![CDATA[cisMuton: caller that detects SNVs/indels by comparing target (foreground) and control (background) samples]]></title>
	<description><![CDATA[<p>cisMuton is a caller that detects SNVs/indels by comparing target (foreground) and control (background) samples.</p>
<p>cisMuton calls mutations from target capture regions, which are defined by the overlapping regions of&nbsp;<code>${GROUP}.target.bed</code>&nbsp;and&nbsp;<code>${GROUP}.gene.bed</code>.</p>
<p>Please read the&nbsp;<a href="https://static.ciscall.org/cisCall5_doc/doc/quick_start.html">Quick Start Guide for cisCall</a>&nbsp;first for an outline of how to run cisMuton.</p><p>Address of the bookmark: <a href="https://static.ciscall.org/cisCall5_doc/index.html" rel="nofollow">https://static.ciscall.org/cisCall5_doc/index.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34420/rita-rapid-identification-of-high-confidence-taxonomic-assignments-for-metagenomic-data</guid>
	<pubDate>Mon, 27 Nov 2017 08:25:33 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34420/rita-rapid-identification-of-high-confidence-taxonomic-assignments-for-metagenomic-data</link>
	<title><![CDATA[RITA: Rapid identification of high-confidence taxonomic assignments for metagenomic data]]></title>
	<description><![CDATA[<p>RITA is a standalone software package and Web server for taxonomic assignment of metagenomic sequence reads. By combining homology predictions from BLAST or UBLAST with compositional classifications from a Naive Bayes classifier, RITA is able to achieve very high accuracy on short reads. Unlike other hybrid approaches which combine these predictions for all sequences to be classified, RITA uses a pipeline to first identify cases where both types of classifier are in agreement, which constitute the highest-confidence set. Sequences not classified in this manner are subjected to a series of downstream classification steps.</p>
<p>This work has been accepted for publication:</p>
<p>MacDonald NJ, Parks DH, and Beiko RG. Rapid identification of taxonomic assignments. Accepted to&nbsp;<em>Nucleic Acids Research</em>&nbsp;April 4, 2012.</p>
<p>If you have any questions or bug reports, please let us know at &lt;beiko@cs.dal.ca&gt;.</p><p>Address of the bookmark: <a href="http://kiwi.cs.dal.ca/Software/RITA" rel="nofollow">http://kiwi.cs.dal.ca/Software/RITA</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35272/biocircosjs-is-an-open-source-interactive-javascript-library-to-interactive-display-biological-data-on-the-web</guid>
	<pubDate>Fri, 19 Jan 2018 15:03:51 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35272/biocircosjs-is-an-open-source-interactive-javascript-library-to-interactive-display-biological-data-on-the-web</link>
	<title><![CDATA[BioCircos.js is an open source interactive Javascript library to interactive display biological data on the web]]></title>
	<description><![CDATA[<p><a href="http://bioinfo.ibp.ac.cn/biocircos/index.php">BioCircos.js</a>&nbsp;is an open source interactive&nbsp;<code>Javascript</code>&nbsp;library which provides an easy way to interactive display biological data on the web. It implements a raster-based&nbsp;<code>SVG</code>&nbsp;visualization using the open source Javascript framework jquery.js. BioCircos.js is multiplatform and works in all major internet browsers (<strong>Internet Explorer</strong>,&nbsp;<strong>Mozilla Firefox</strong>,&nbsp;<strong>Google Chrome</strong>,&nbsp;<strong>Safari</strong>,&nbsp;<strong>Opera</strong>). Its speed is determined by the client&rsquo;s hardware and internet browser. For smoothest user experience, we recommend&nbsp;<strong>Google Chrome</strong>.</p>
<p>BioCircos.js provides&nbsp;<strong>SNP</strong>,&nbsp;<strong>CNV</strong>,&nbsp;<strong>HEATMAP</strong>,&nbsp;<strong>LINK</strong>,&nbsp;<strong>LINE</strong>,&nbsp;<strong>SCATTER</strong>,&nbsp;<strong>ARC</strong>,&nbsp;<strong>TEXT</strong>, and&nbsp;<strong>HISTGRAM</strong>modules to display genome-wide genetic variations (SNPs, CNVs and chromosome rearrangement), gene expression and biomolecule interactions. BioCircos.js also provides&nbsp;<strong>BACKGROUND</strong>&nbsp;module to display background and axis circles. Tooltips showing detailed information of SVG elements are also provided.</p>
<p><a href="http://bioinfo.ibp.ac.cn/biocircos/document/demo/pages/paper01.html">Demo</a></p><p>Address of the bookmark: <a href="http://bioinfo.ibp.ac.cn/biocircos/document/index.html" rel="nofollow">http://bioinfo.ibp.ac.cn/biocircos/document/index.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37259/epiviz-an-interactive-visualization-tool-for-functional-genomics-data</guid>
	<pubDate>Mon, 09 Jul 2018 05:27:39 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37259/epiviz-an-interactive-visualization-tool-for-functional-genomics-data</link>
	<title><![CDATA[Epiviz: an interactive visualization tool for functional genomics data.]]></title>
	<description><![CDATA[<p><span>Epiviz is an interactive visualization tool for functional genomics data. It supports genome navigation like other genome browsers, but allows multiple visualizations of data within genomic regions using scatterplots, heatmaps and other user-supplied visualizations. It also includes data from the&nbsp;</span><a href="http://barcode.luhs.org/" target="_blank">Gene Expression Barcode project</a><span>&nbsp;for transcriptome visualization. It has a flexible plugin framework so users can add</span><a href="http://d3js.org/" target="_blank">d3</a><span>&nbsp;visualizations. You can see a video tour&nbsp;</span><a href="http://youtu.be/099c4wUxozA" target="_blank">here</a><span>.</span></p>
<p><span>https://bioconductor.org/packages/release/bioc/html/epivizr.html</span></p>
<p><span>https://github.com/epiviz</span></p>
<p><span>https://github.com/epiviz/epiviz</span></p><p>Address of the bookmark: <a href="https://epiviz.github.io/" rel="nofollow">https://epiviz.github.io/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38593/excavator-detecting-copy-number-variants-from-whole-exome-sequencing-data</guid>
	<pubDate>Fri, 04 Jan 2019 10:10:48 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38593/excavator-detecting-copy-number-variants-from-whole-exome-sequencing-data</link>
	<title><![CDATA[EXCAVATOR: detecting copy number variants from whole-exome sequencing data]]></title>
	<description><![CDATA[<p><span>EXCAVATOR, for the detection of copy number variants (CNVs) from whole-exome sequencing data. EXCAVATOR combines a three-step normalization procedure with a novel heterogeneous hidden Markov model algorithm and a calling method that classifies genomic regions into five copy number states. We validate EXCAVATOR on three datasets and compare the results with three other methods. These analyses show that EXCAVATOR outperforms the other methods and is therefore a valuable tool for the investigation of CNVs in largescale projects, as well as in clinical research and diagnostics. EXCAVATOR is freely available at&nbsp;</span><span><a href="http://sourceforge.net/projects/excavatortool/" target="_blank"><span>http://sourceforge.net/projects/excavatortool/</span></a></span><span>.</span><br><br><br><span>EXCAVATOR is a novel software package for the detection of copy number variants (CNVs) from whole-exome sequencing data.</span><br><span>EXCAVATOR has been published on Genome Biology (</span><a href="http://genomebiology.com/2013/14/10/R120/abstract" target="_blank">http://genomebiology.com/2013/14/10/R120/abstract<span></span></a><span>).</span></p><p>Address of the bookmark: <a href="https://sourceforge.net/projects/excavatortool/" rel="nofollow">https://sourceforge.net/projects/excavatortool/</a></p>]]></description>
	<dc:creator>Radha Agarkar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38829/nquire-a-statistical-framework-for-ploidy-estimation-using-ngs-short-read-data</guid>
	<pubDate>Thu, 31 Jan 2019 05:12:19 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38829/nquire-a-statistical-framework-for-ploidy-estimation-using-ngs-short-read-data</link>
	<title><![CDATA[nQuire: A statistical framework for ploidy estimation using NGS short-read data]]></title>
	<description><![CDATA[<p>nQuire implements a set of commands to estimate ploidy level of individuals from species, where recent polyploidization occurred and intraspecific ploidy variation is observed. Specifically, nQuire uses next-generation sequencing data to distinguish between diploids, triploids and tetraploids, on the basis of frequency distributions at variant sites where only two bases are segregating.</p>
<p>For more background see also the publication at&nbsp;<a href="https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-018-2128-z">BMC Bioinformatics</a>.</p>
<p>https://github.com/clwgg/nQuire</p><p>Address of the bookmark: <a href="https://github.com/clwgg/nQuire" rel="nofollow">https://github.com/clwgg/nQuire</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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