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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/37221?offset=130</link>
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	<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/researchlabs/view/43913/lsugenomics-lab</guid>
  <pubDate>Thu, 07 Jul 2022 05:26:37 -0500</pubDate>
  <link></link>
  <title><![CDATA[lsugenomics Lab]]></title>
  <description><![CDATA[
<p>﻿In our lab, we seek to characterize and to compare genomes in order to better understand genetic and evolutionary processes linking genotypes to phenotypes.  <br /> <br />Sequencing and decoding plant genomes have been integral in our approaches.</p>

<p>The overarching goal of our research is to understand how to interpret complex and fascinating messages embedded in genomes.</p>

<p>https://www.lsugenomics.org/</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44489/proksee</guid>
	<pubDate>Wed, 27 Mar 2024 11:11:54 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44489/proksee</link>
	<title><![CDATA[Proksee]]></title>
	<description><![CDATA[<p><span>Proksee is an expert system for genome assembly, annotation and visualization. To begin using Proksee, provide a complete genome sequence, sequencing reads or a CGView/Proksee map JSON file.</span></p>
<fieldset><legend>Please Cite the Following</legend>
<div>Grant JR, Enns E, Marinier E, Mandal A, Herman EK, Chen C, Graham M, Van Domselaar G, and Stothard P</div>
<div><a href="https://pubmed.ncbi.nlm.nih.gov/37140037/">Proksee: in-depth characterization and visualization of bacterial genomes</a></div>
<div>Nucleic Acids Research, 2023, gkad326, https://doi.org/10.1093/nar/gkad326</div>
</fieldset><p>Address of the bookmark: <a href="https://proksee.ca/" rel="nofollow">https://proksee.ca/</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34519/bandage-interactive-visualization-of-de-novo-genome-assemblies</guid>
	<pubDate>Mon, 04 Dec 2017 10:09:37 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34519/bandage-interactive-visualization-of-de-novo-genome-assemblies</link>
	<title><![CDATA[Bandage: interactive visualization of de novo genome assemblies]]></title>
	<description><![CDATA[<p>Bandage (a Bioinformatics Application for Navigating&nbsp;<em>De&nbsp;novo</em>&nbsp;Assembly Graphs Easily) is a tool for visualizing assembly graphs with connections. Users can zoom in to specific areas of the graph and interact with it by moving nodes, adding labels, changing colors and extracting sequences. BLAST searches can be performed within the Bandage graphical user interface and the hits are displayed as highlights in the graph. By displaying connections between contigs, Bandage presents new possibilities for analyzing&nbsp;<em>de novo</em>&nbsp;assemblies that are not possible through investigation of contigs alone.</p>
<p><strong>Availability and implementation:</strong>&nbsp;Source code and binaries are freely available at&nbsp;<a href="https://github.com/rrwick/Bandage" target="pmc_ext">https://github.com/rrwick/Bandage</a>. Bandage is implemented in C++ and supported on Linux, OS X and Windows. A full feature list and screenshots are available at&nbsp;<a href="http://rrwick.github.io/Bandage" target="pmc_ext">http://rrwick.github.io/Bandage</a>.</p><p>Address of the bookmark: <a href="http://rrwick.github.io/Bandage/" rel="nofollow">http://rrwick.github.io/Bandage/</a></p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37414/arc-pipeline-which-facilitates-iterative-reference-guided-de-novo-assemblies</guid>
	<pubDate>Thu, 26 Jul 2018 09:20:26 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37414/arc-pipeline-which-facilitates-iterative-reference-guided-de-novo-assemblies</link>
	<title><![CDATA[ARC: pipeline which facilitates iterative, reference guided de novo assemblies]]></title>
	<description><![CDATA[<p>ARC is a pipeline which facilitates iterative, reference guided&nbsp;<em>de novo</em>&nbsp;assemblies with the intent of:</p>
<ol>
<li>Reducing time in analysis and increasing accuracy of results by only considering those reads which should assemble together.</li>
<li>Reducing/removing reference bias as compared to mapping based approaches.</li>
</ol>
<p><span>The software is designed to work in situations where a whole-genome assembly is not the objective, but rather when the researcher wishes to assemble discreet 'targets' contained within next-generation shotgun sequence data. ARC decomplexifies the traditionally difficult problem of assembly by breaking the reads into small, manageable subsets which can then be assembled quickly and efficiently in parallel. Applications include those in which the researcher wishes to&nbsp;</span><em>de novo</em><span>&nbsp;assemble specific content and a set of semi-similar reference targets is available to initialize the assembly process.</span></p>
<p>https://ibest.github.io/ARC/</p><p>Address of the bookmark: <a href="https://ibest.github.io/ARC/" rel="nofollow">https://ibest.github.io/ARC/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38023/mitos-improved-de-novo-metazoan-mitochondrial-genome-annotation</guid>
	<pubDate>Fri, 26 Oct 2018 08:25:39 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38023/mitos-improved-de-novo-metazoan-mitochondrial-genome-annotation</link>
	<title><![CDATA[MITOS: improved de novo metazoan mitochondrial genome annotation]]></title>
	<description><![CDATA[<p><span>Allows automatic annotation of metazoan mitochondrial genomes. MITOS is a pipeline designed to compute a consistent de novo annotation of the mitogenomic sequences. The software allows for a systematic error screening, the standardisation of gene name and gene boundary designation, anticodon labelling of tRNAs, and provides the means for the assessment of the validity of a gene assignment.</span></p><p>Address of the bookmark: <a href="http://mitos.bioinf.uni-leipzig.de/index.py" rel="nofollow">http://mitos.bioinf.uni-leipzig.de/index.py</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39903/integrative-meta-assembly-pipeline-imap-chromosome-level-genome-assembler-combining-multiple-de-novo-assemblies</guid>
	<pubDate>Sat, 31 Aug 2019 11:30:41 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39903/integrative-meta-assembly-pipeline-imap-chromosome-level-genome-assembler-combining-multiple-de-novo-assemblies</link>
	<title><![CDATA[Integrative Meta-Assembly Pipeline (IMAP): Chromosome-level genome assembler combining multiple de novo assemblies]]></title>
	<description><![CDATA[<p><span>Chromosome-level genome assembler combining multiple de novo assemblies</span></p>
<p><span><a href="https://github.com/jkimlab/IMAP">https://github.com/jkimlab/IMAP</a></span></p><p>Address of the bookmark: <a href="https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0221858" rel="nofollow">https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0221858</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37618/snakemake%E2%80%94a-scalable-bioinformatics-workflow-engine</guid>
	<pubDate>Sun, 02 Sep 2018 16:32:42 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37618/snakemake%E2%80%94a-scalable-bioinformatics-workflow-engine</link>
	<title><![CDATA[Snakemake—a scalable bioinformatics workflow engine]]></title>
	<description><![CDATA[<p><span>Snakemake is a workflow engine that provides a readable Python-based workflow definition language and a powerful execution environment that scales from single-core workstations to compute clusters without modifying the workflow.&nbsp;</span></p><p>Address of the bookmark: <a href="https://bioconda.github.io/recipes/snakemake/README.html" rel="nofollow">https://bioconda.github.io/recipes/snakemake/README.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/28809/kissplice</guid>
	<pubDate>Tue, 16 Aug 2016 08:34:19 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/28809/kissplice</link>
	<title><![CDATA[KisSplice]]></title>
	<description><![CDATA[<p>KisSplice is a software that enables to analyse RNA-seq data with or without a reference genome. It is an exact local transcriptome assembler that allows to identify SNPs, indels and alternative splicing events. It can deal with an arbitrary number of biological conditions, and will quantify each variant in each condition. It has been tested on Illumina datasets of up to 1G reads. Its memory consumption is around 5Gb for 100M reads.</p>
<p>KisSplice is not a full-length transcriptome assembler. This means that it will output the variable regions of the transcripts, not reconstruct them entirely.</p>
<p>KisSplice comes as a workflow, with several possible post-treatments meant to facilitate the analysis of the results. The choice of the post-treatment depends on the availability of a reference genome/transcriptome and on the need to perform a differential analysis, as summarised in the following table.</p><p>Address of the bookmark: <a href="http://kissplice.prabi.fr/" rel="nofollow">http://kissplice.prabi.fr/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39624/cogent-a-tool-for-reconstructing-the-coding-genome-using-high-quality-full-length-transcriptome-sequences</guid>
	<pubDate>Tue, 18 Jun 2019 05:33:04 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39624/cogent-a-tool-for-reconstructing-the-coding-genome-using-high-quality-full-length-transcriptome-sequences</link>
	<title><![CDATA[Cogent: a tool for reconstructing the coding genome using high-quality full-length transcriptome sequences.]]></title>
	<description><![CDATA[<div id="yui_3_14_1_1_1560853173251_3865">Cogent is a tool that identifies gene&nbsp;families and reconstructs the coding genome using high-quality transcriptome data without a reference genome, and can be used to check&nbsp;assemblies&nbsp;for the presence of&nbsp;these known coding sequences.</div>
<div>&nbsp;</div>
<div>
<p>Cogent is a tool for reconstructing the coding genome using high-quality full-length transcriptome sequences. It is designed to be used on&nbsp;<a href="https://github.com/PacificBiosciences/cDNA_primer/wiki">Iso-Seq data</a>&nbsp;and in cases where there is no reference genome or the ref genome is highly incomplete.</p>
<p>See a&nbsp;<a href="https://www.dropbox.com/s/mn6hwhguh0pqceu/20160106_Cogent_developers_conference_slides_Cuttlefish.pdf?dl=0">recent presentation</a>&nbsp;on Cogent being applied to the Cuttlefish Iso-Seq data.</p>
<p><a href="https://www.dropbox.com/s/kz0gi7qg0w82k9a/20161026_Cogent_manuscript_forGitHub.pdf?dl=0">Cogent preliminary draft paper (updated 2016Dec version)</a>,&nbsp;<a href="https://www.dropbox.com/s/37412o8glvnfhf9/20161026_Cogent_ManuscriptPlusSupplement_forGitHub.pdf?dl=0">Supplementary</a></p>
<p>Please see&nbsp;<a href="https://github.com/Magdoll/Cogent/wiki">wiki</a>&nbsp;for details on usage.</p>
</div><p>Address of the bookmark: <a href="https://github.com/Magdoll/Cogent" rel="nofollow">https://github.com/Magdoll/Cogent</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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