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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/34922?offset=330</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/43999/tools-for-differential-expression-analysis</guid>
	<pubDate>Tue, 08 Nov 2022 03:40:33 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/43999/tools-for-differential-expression-analysis</link>
	<title><![CDATA[Tools for Differential expression analysis]]></title>
	<description><![CDATA[<p><span>apeglm</span>&nbsp;-&nbsp;<a href="https://bioconductor.org/packages/release/bioc/html/apeglm.html" target="_blank">https://bioconductor.org/packages/release/bioc/html/apeglm.html</a></p><p><span>ashr</span>&nbsp;-&nbsp;<a href="https://github.com/stephens999/ashr" target="_blank">https://github.com/stephens999/ashr</a>,&nbsp;<a href="https://cran.r-project.org/web/packages/ashr/index.html" target="_blank">https://cran.r-project.org/web/packages/ashr/index.html</a></p><p><span>consensusDE</span>&nbsp;-&nbsp;<a href="https://bioconductor.org/packages/release/bioc/html/consensusDE.html" target="_blank">https://bioconductor.org/packages/release/bioc/html/consensusDE.html</a></p><p><span>DESeq2</span>&nbsp;-&nbsp;<a href="https://bioconductor.org/packages/release/bioc/html/DESeq2.html" target="_blank">https://bioconductor.org/packages/release/bioc/html/DESeq2.html</a></p><p><span>edgeR</span>&nbsp;-&nbsp;<a href="https://bioconductor.org/packages/release/bioc/html/edgeR.html" target="_blank">https://bioconductor.org/packages/release/bioc/html/edgeR.html</a></p><p><span>limma</span>&nbsp;-&nbsp;<a href="https://kasperdanielhansen.github.io/genbioconductor/html/limma.html" target="_blank">https://kasperdanielhansen.github.io/genbioconductor/html/limma.html</a>&nbsp;&nbsp;<a href="https://bioconductor.org/packages/release/bioc/html/limma.html" target="_blank">https://bioconductor.org/packages/release/bioc/html/limma.html</a></p><p><span>MetaCycle</span>&nbsp;-&nbsp;<a href="https://cran.r-project.org/web/packages/MetaCycle/index.html" target="_blank">https://cran.r-project.org/web/packages/MetaCycle/index.html</a>,&nbsp;<a href="https://github.com/gangwug/MetaCycle" target="_blank">https://github.com/gangwug/MetaCycle</a></p><p><span>RUVSeq</span>&nbsp;-&nbsp;<a href="https://bioconductor.org/packages/release/bioc/html/RUVSeq.html" target="_blank">https://bioconductor.org/packages/release/bioc/html/RUVSeq.html</a></p><p><span>SARTools</span>&nbsp;-&nbsp;<a href="https://github.com/PF2-pasteur-fr/SARTools" target="_blank">https://github.com/PF2-pasteur-fr/SARTools</a></p><p><span>tximport</span>&nbsp;-&nbsp;<a href="https://github.com/mikelove/tximport" target="_blank">https://github.com/mikelove/tximport</a></p><p>&nbsp;</p>]]></description>
	<dc:creator>Abhi</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/32946/grass-a-generic-algorithm-for-scaffolding-next-generation-sequencing-assemblies</guid>
	<pubDate>Tue, 23 May 2017 05:20:32 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32946/grass-a-generic-algorithm-for-scaffolding-next-generation-sequencing-assemblies</link>
	<title><![CDATA[GRASS: a generic algorithm for scaffolding next-generation sequencing assemblies.]]></title>
	<description><![CDATA[<p><span>GRASS (GeneRic ASsembly Scaffolder)-a novel algorithm for scaffolding second-generation sequencing assemblies capable of using diverse information sources. GRASS offers a mixed-integer programming formulation of the contig scaffolding problem, which combines contig order, distance and orientation in a single optimization objective. The resulting optimization problem is solved using an expectation-maximization procedure and an unconstrained binary quadratic programming approximation of the original problem. We compared GRASS with existing HTS scaffolders using Illumina paired reads of three bacterial genomes. Our algorithm constructs a comparable number of scaffolds, but makes fewer errors. This result is further improved when additional data, in the form of related genome sequences, are used.</span></p><p>Address of the bookmark: <a href="https://github.com/AlexeyG/GRASS" rel="nofollow">https://github.com/AlexeyG/GRASS</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</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/36897/gmcloser-closing-gaps-in-assemblies-accurately-with-a-likelihood-based-selection-of-contig-or-long-read-alignments</guid>
	<pubDate>Mon, 11 Jun 2018 05:43:44 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36897/gmcloser-closing-gaps-in-assemblies-accurately-with-a-likelihood-based-selection-of-contig-or-long-read-alignments</link>
	<title><![CDATA[GMcloser: closing gaps in assemblies accurately with a likelihood-based selection of contig or long-read alignments]]></title>
	<description><![CDATA[GMcloser uses likelihood-based classifiers calculated from the alignment statistics between scaffolds, contigs and paired-end reads to correctly assign contigs or long reads to gap regions of scaffolds, thereby achieving accurate and efficient gap closure. We demonstrate with sequencing data from various organisms that the gap-closing accuracy of GMcloser is 3–100-fold higher than those of other available tools, with similar efficiency.

https://academic.oup.com/bioinformatics/article/31/23/3733/209212<p>Address of the bookmark: <a href="https://academic.oup.com/bioinformatics/article/31/23/3733/209212" rel="nofollow">https://academic.oup.com/bioinformatics/article/31/23/3733/209212</a></p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37737/rebaler-program-for-conducting-reference-based-assemblies-using-long-reads</guid>
	<pubDate>Tue, 18 Sep 2018 07:52:41 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37737/rebaler-program-for-conducting-reference-based-assemblies-using-long-reads</link>
	<title><![CDATA[Rebaler: program for conducting reference-based assemblies using long reads.]]></title>
	<description><![CDATA[<p>Rebaler is a program for conducting reference-based assemblies using long reads. It relies mainly on&nbsp;<a href="https://github.com/lh3/minimap2">minimap2</a>&nbsp;for alignment and&nbsp;<a href="https://github.com/isovic/racon">Racon</a>&nbsp;for making consensus sequences.</p>
<p>I made Rebaler for bacterial genomes (specifically for the task of&nbsp;<a href="https://github.com/rrwick/Basecalling-comparison">testing basecallers</a>). It should in principle work for non-bacterial genomes as well, but I haven't tested it.</p><p>Address of the bookmark: <a href="https://github.com/rrwick/Rebaler" rel="nofollow">https://github.com/rrwick/Rebaler</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41831/merqury-reference-free-quality-and-phasing-assessment-for-genome-assemblies</guid>
	<pubDate>Sat, 06 Jun 2020 05:38:34 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41831/merqury-reference-free-quality-and-phasing-assessment-for-genome-assemblies</link>
	<title><![CDATA[Merqury: reference-free quality and phasing assessment for genome assemblies]]></title>
	<description><![CDATA[<p><span>Often, genome assembly projects have illumina whole genome sequencing reads available for the assembled individual. The k-mer spectrum of this read set can be used for independently evaluating assembly quality without the need of a high quality reference. Merqury provides a set of tools for this purpose.</span></p>
<p><span><a href="https://github.com/marbl/meryl">https://github.com/marbl/meryl</a></span></p><p>Address of the bookmark: <a href="https://github.com/marbl/merqury" rel="nofollow">https://github.com/marbl/merqury</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41937/merqury-evaluate-genome-assemblies-with-k-mers</guid>
	<pubDate>Fri, 03 Jul 2020 19:29:34 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41937/merqury-evaluate-genome-assemblies-with-k-mers</link>
	<title><![CDATA[merqury: Evaluate genome assemblies with k-mers]]></title>
	<description><![CDATA[<p><span>Often, genome assembly projects have illumina whole genome sequencing reads available for the assembled individual. The k-mer spectrum of this read set can be used for independently evaluating assembly quality without the need of a high quality reference. Merqury provides a set of tools for this purpose.</span></p>
<p><span>More at&nbsp;<a href="https://www.biorxiv.org/content/10.1101/2020.03.15.992941v1.full">https://www.biorxiv.org/content/10.1101/2020.03.15.992941v1.full</a></span></p><p>Address of the bookmark: <a href="https://github.com/marbl/merqury" rel="nofollow">https://github.com/marbl/merqury</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43888/syri-compares-alignments-between-two-chromosome-level-assemblies-and-identifies-synteny-and-structural-rearrangements</guid>
	<pubDate>Wed, 01 Jun 2022 02:01:13 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43888/syri-compares-alignments-between-two-chromosome-level-assemblies-and-identifies-synteny-and-structural-rearrangements</link>
	<title><![CDATA[Syri compares alignments between two chromosome-level assemblies and identifies synteny and structural rearrangements.]]></title>
	<description><![CDATA[<p><span>Syri compares alignments between two chromosome-level assemblies and identifies synteny and structural rearrangements.</span></p>
<p><span><img src="https://github.com/schneebergerlab/syri/raw/master/example/ampril_col0_chr3_6600000_10000000.png" alt="image" style="border: 0px;"></span></p><p>Address of the bookmark: <a href="https://github.com/schneebergerlab/syri" rel="nofollow">https://github.com/schneebergerlab/syri</a></p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34546/comparative-genomics-scripts</guid>
	<pubDate>Wed, 06 Dec 2017 15:20:45 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34546/comparative-genomics-scripts</link>
	<title><![CDATA[Comparative genomics scripts]]></title>
	<description><![CDATA[<p>Comparative genomics educational material and papers bookmarks</p>
<p>https://github.com/iansealy/coursera-comparinggenomes</p><p>Address of the bookmark: <a href="https://github.com/iansealy/coursera-comparinggenomes" rel="nofollow">https://github.com/iansealy/coursera-comparinggenomes</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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