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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/44559?offset=350</link>
	<atom:link href="https://bioinformaticsonline.com/related/44559?offset=350" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/42626/spades-team-announce-new-version-spades-v315</guid>
	<pubDate>Fri, 15 Jan 2021 10:24:27 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/42626/spades-team-announce-new-version-spades-v315</link>
	<title><![CDATA[SPADes team announce new version SPADes v3.15]]></title>
	<description><![CDATA[<p>New SPAdes 3.15.0.0. announced by the SPADes team This release includes such new features as:&nbsp;<br />- CoronaSPAdes pipeline for the assembly of transcriptomic and metatranscriptomic data of full-length coronaviridae genomes;&nbsp;<br />- Meta-Viral and RNA-Viral pipelines for metagenomic and metatranscriptomic data defining viral genomes;&nbsp;<br />-New trusted contiguous use algorithm;&nbsp;<br />-Switched to the memory allocator mimalloc;&nbsp;<br />- PlasmidSPAdes and bgcSPAdes are now provided as an input assembly graph;&nbsp;<br />- Important improvements and corrections to the metaplasmid pipeline;&nbsp;<br />- Multiple performance improvements in procedures for simplification and repeat resolving.&nbsp;<br />Please, consider updating.</p><p>Check out more at&nbsp;https://cab.spbu.ru/software/spades/</p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43315/genome-assembly-workshop-2020</guid>
	<pubDate>Wed, 25 Aug 2021 04:30:32 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43315/genome-assembly-workshop-2020</link>
	<title><![CDATA[Genome Assembly Workshop 2020]]></title>
	<description><![CDATA[<p><span>Our team offers custom bioinformatics services to academic and private organizations. We have a strong academic background with a focus on cutting edge, open source software. We replicate standard analysis pipelines (best practices) when appropriate, and/or develop novel applications and pipelines when needed, however we always emphasize biological interpretation of the data.</span></p>
<p><span>More at&nbsp;https://ucdavis-bioinformatics-training.github.io/</span></p><p>Address of the bookmark: <a href="https://ucdavis-bioinformatics-training.github.io/2020-Genome_Assembly_Workshop/snakemake/snakemake_intro" rel="nofollow">https://ucdavis-bioinformatics-training.github.io/2020-Genome_Assembly_Workshop/snakemake/snakemake_intro</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44223/ale-assembly-likelihood-estimator</guid>
	<pubDate>Wed, 08 Mar 2023 01:39:33 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44223/ale-assembly-likelihood-estimator</link>
	<title><![CDATA[ALE: Assembly Likelihood Estimator]]></title>
	<description><![CDATA[<p>Just import the assembly, bam and ALE scores. You can convert the .ale file to a set of .wig files with ale2wiggle.py and IGV can read those directly.&nbsp; Depending on your genome size you may want to convert the .wig files to the BigWig format.</p><p>Address of the bookmark: <a href="https://github.com/sc932/ALE" rel="nofollow">https://github.com/sc932/ALE</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/44722/step-by-step-guide-to-running-genome-assembly</guid>
	<pubDate>Fri, 13 Dec 2024 11:35:55 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44722/step-by-step-guide-to-running-genome-assembly</link>
	<title><![CDATA[Step-by-Step Guide to Running Genome Assembly]]></title>
	<description><![CDATA[<p>Genome assembly is a critical process in bioinformatics, enabling the reconstruction of an organism's genome from short DNA sequence reads. Whether you&rsquo;re working on a new microbial genome or a complex eukaryotic organism, this guide will walk you through the steps of genome assembly using state-of-the-art tools and best practices.</p><h4><strong>What is Genome Assembly?</strong></h4><p>Genome assembly involves piecing together short DNA sequence reads generated by sequencing platforms (e.g., Illumina, PacBio, Oxford Nanopore) into longer, contiguous sequences called contigs. This can be performed as:</p><ul>
<li><strong>De Novo Assembly</strong>: Without a reference genome.</li>
<li><strong>Reference-Guided Assembly</strong>: Using a reference genome to guide the assembly process.</li>
</ul><h4><strong>Step 1: Preparing Your Data</strong></h4><p>Before starting the assembly, ensure that your raw sequencing data is high quality.</p><ol>
<li>
<p><strong>Input Data</strong></p>
<ul>
<li><strong>Short Reads</strong>: Illumina sequencing generates short, accurate reads ideal for scaffolding.</li>
<li><strong>Long Reads</strong>: PacBio and Nanopore sequencing provide long reads for resolving repetitive regions.</li>
</ul>
</li>
<li>
<p><strong>Quality Control (QC)</strong><br />Use tools like <strong>FastQC</strong> or <strong>MultiQC</strong> to assess the quality of your reads:</p>
<div>
<div dir="ltr"><code>fastqc reads.fastq multiqc . </code></div>
</div>
<p>Look for issues like low-quality bases, adapter contamination, or overrepresented sequences.</p>
</li>
<li>
<p><strong>Read Trimming and Filtering</strong><br />Trim low-quality bases and adapters using <strong>Trimmomatic</strong> or <strong>Cutadapt</strong>:</p>
<div>
<div dir="ltr"><code>trimmomatic PE reads_R1.fastq reads_R2.fastq trimmed_R1.fastq trimmed_R2.fastq \ ILLUMINACLIP:adapters.fa:2:30:10 LEADING:3 TRAILING:3 SLIDINGWINDOW:4:20 MINLEN:36 </code></div>
</div>
</li>
</ol><h4><strong>Step 2: Choosing an Assembly Strategy</strong></h4><p>Select an assembly strategy based on your data type:</p><ul>
<li>
<p><strong>Short-Read Assemblers</strong>:</p>
<ul>
<li>SPAdes: Popular for microbial genomes.</li>
<li>Velvet: Fast for smaller genomes.</li>
</ul>
</li>
<li>
<p><strong>Long-Read Assemblers</strong>:</p>
<ul>
<li>Canu: Ideal for long-read datasets.</li>
<li>Flye: Versatile for small and large genomes.</li>
</ul>
</li>
<li>
<p><strong>Hybrid Assemblers</strong>:</p>
<ul>
<li>MaSuRCA: Combines short and long reads.</li>
<li>Unicycler: Optimized for bacterial genomes.</li>
</ul>
</li>
</ul><h4><strong>Step 3: Running the Assembly</strong></h4><h5><strong>3.1. SPAdes (Short-Read Assembly)</strong></h5><p>SPAdes is an excellent choice for small genomes, such as bacteria.</p><div><div dir="ltr"><code>spades.py -1 trimmed_R1.fastq -2 trimmed_R2.fastq -o spades_output </code></div></div><p>The output includes assembled contigs (<code>contigs.fasta</code>) and scaffolds (<code>scaffolds.fasta</code>).</p><h5><strong>3.2. Canu (Long-Read Assembly)</strong></h5><p>Canu is designed for high-error long reads from PacBio or Nanopore.</p><div><div dir="ltr"><code>canu -p genome -d canu_output genomeSize=4.7m -nanopore-raw reads.fastq </code></div></div><p>The output will be in <code>canu_output/genome.contigs.fasta</code>.</p><h5><strong>3.3. Hybrid Assembly with Unicycler</strong></h5><p>Unicycler combines short and long reads for improved assemblies.</p><div><div dir="ltr"><code>unicycler -1 trimmed_R1.fastq -2 trimmed_R2.fastq -l long_reads.fastq -o unicycler_output </code></div></div><h4><strong>Step 4: Assessing Assembly Quality</strong></h4><p>After assembly, evaluate its quality using the following tools:</p><ol>
<li>
<p><strong>QUAST</strong><br />QUAST generates assembly statistics, such as N50, genome size, and GC content:</p>
<div>
<div dir="ltr"><code>quast contigs.fasta -o quast_output </code></div>
</div>
</li>
<li>
<p><strong>BUSCO</strong><br />BUSCO checks genome completeness by identifying conserved genes:</p>
<div>
<div dir="ltr"><code>busco -i contigs.fasta -o busco_output -l fungi_odb10 -m genome </code></div>
</div>
</li>
<li>
<p><strong>Assembly Graph Visualization</strong><br />Visualize assembly graphs with <strong>Bandage</strong>:</p>
<div>
<div dir="ltr"><code>Bandage load assembly_graph.gfa </code></div>
</div>
</li>
</ol><hr><h4><strong>Step 5: Post-Assembly Steps</strong></h4><ol>
<li>
<p><strong>Polishing</strong><br />Improve assembly accuracy using tools like <strong>Pilon</strong> (for short reads) or <strong>Racon</strong> (for long reads).</p>
<div>
<div dir="ltr"><code>racon long_reads.fasta mapped_reads.sam contigs.fasta &gt; polished_contigs.fasta </code></div>
</div>
</li>
<li>
<p><strong>Scaffolding</strong><br />Link contigs into scaffolds using tools like <strong>SSPACE</strong> or <strong>Opera-LG</strong> if required.</p>
</li>
<li>
<p><strong>Annotation</strong><br />Annotate the assembled genome using <strong>Prokka</strong> for prokaryotes or <strong>Maker</strong> for eukaryotes.</p>
<div>
<div dir="ltr"><code>prokka --outdir annotation_output --prefix genome contigs.fasta </code></div>
</div>
</li>
</ol><h4><strong>Step 6: Sharing and Archiving</strong></h4><ol>
<li>
<p><strong>Submit to Public Repositories</strong><br />Share your assembly in databases like <strong>NCBI GenBank</strong>, <strong>ENA</strong>, or <strong>DDBJ</strong>.</p>
</li>
<li>
<p><strong>Metadata Preparation</strong><br />Include detailed metadata for your submission, such as organism name, sequencing platform, and coverage.</p>
</li>
</ol><h4><strong>Best Practices</strong></h4><ul>
<li>Always perform quality checks at each stage to ensure data integrity.</li>
<li>Use multiple tools to cross-validate results when working with complex genomes.</li>
<li>Document parameters and software versions for reproducibility.</li>
</ul><h4><strong>Conclusion</strong></h4><p>Genome assembly is a powerful process that transforms raw sequencing data into a coherent representation of an organism&rsquo;s genome. By following this step-by-step guide, you can successfully assemble genomes and uncover valuable biological insights. Whether you&rsquo;re assembling a microbial genome or tackling the complexities of a eukaryotic genome, these tools and strategies will set you on the path to success.</p>]]></description>
	<dc:creator>Abhi</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/view/1926</guid>
	<pubDate>Sun, 11 Aug 2013 11:42:32 -0500</pubDate>
	<link>https://bioinformaticsonline.com/view/1926</link>
	<title><![CDATA[Want to Know which genome assembler rule the world ?]]></title>
	<description><![CDATA[<p><span><strong>Assemblathon 2</strong>: evaluating de novo methods of genome assembly&nbsp;</span></p><p><span><a href="http://www.gigasciencejournal.com/content/2/1/10/abstract">http://www.gigasciencejournal.com/content/2/1/10/abstract</a></span></p><p><span><a href="http://blogs.nature.com/news/2013/07/genome-assembly-contest-prompts-soul-searching.html">http://blogs.nature.com/news/2013/07/genome-assembly-contest-prompts-soul-searching.html</a></span></p><p><a href="http://assemblathon.org/post/44431915644/feedback-and-analysis-of-the-assemblathon-2-p">http://assemblathon.org/post/44431915644/feedback-and-analysis-of-the-assemblathon-2-p</a></p><p>&nbsp;</p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/3917/the-story-of-you-encode-and-the-human-genome</guid>
	<pubDate>Sat, 24 Aug 2013 18:49:03 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/3917/the-story-of-you-encode-and-the-human-genome</link>
	<title><![CDATA[The Story of You: ENCODE and the human genome]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/TwXXgEz9o4w" frameborder="0" allowfullscreen></iframe><p>Ever since a monk called Mendel started breeding pea plants we've been learning about our genomes. In 1953, Watson, Crick and Franklin described the structure of the molecule that makes up our genomes: the DNA double helix. Then, in 2001, scientists wrote down the entire 3-billion letter code contained in the average human genome. Now they're trying to interpret that code; to work out how it's used to make different types of cells and different people. The ENCODE project, as it's called, is the latest chapter in the story of you. To read the ENCODE research papers and more, visit http://www.nature.com/ENCODE</p>]]></description>
	
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	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/4761/dna-is-packaged-in-a-chromosome-experiment</guid>
	<pubDate>Mon, 23 Sep 2013 18:01:12 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/4761/dna-is-packaged-in-a-chromosome-experiment</link>
	<title><![CDATA[DNA is packaged in a chromosome experiment]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/fecfROFrp_c" frameborder="0" allowfullscreen></iframe>For more information, log on to-
http://shomusbiology.weebly.com/
Download the study materials here-
http://shomusbiology.weebly.com/bio-materials.html
A nucleosome is the basic unit of DNA packaging in eukaryotes, consisting of a segment of DNA wound in sequence around four histone protein cores.[1] This structure is often compared to thread wrapped around a spool.[2]

Nucleosomes form the fundamental repeating units of eukaryotic chromatin,[3] which is used to pack the large eukaryotic genomes into the nucleus while still ensuring appropriate access to it (in mammalian cells approximately 2 m of linear DNA have to be packed into a nucleus of roughly 10 µm diameter). Nucleosomes are folded through a series of successively higher order structures to eventually form a chromosome; this both compacts DNA and creates an added layer of regulatory control, which ensures correct gene expression. Nucleosomes are thought to carry epigenetically inherited information in the form of covalent modifications of their core histones. Nucleosomes were observed as particles in the electron microscope by Don and Ada Olins [4] and their existence and structure (as histone octamers surrounded by approximately 200 base pairs of DNA) were proposed by Roger Kornberg.[5][6] The role of the nucleosome as a general gene repressor was demonstrated by Lorch et al. in vitro [7] and by Han and Grunstein in vivo.]]></description>
	
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	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/5761/how-i-discovered-dna-james-watson</guid>
	<pubDate>Fri, 18 Oct 2013 11:30:26 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/5761/how-i-discovered-dna-james-watson</link>
	<title><![CDATA[How I discovered DNA - James Watson]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/RvdxGDJogtA" frameborder="0" allowfullscreen></iframe><p>View full lesson: http://ed.ted.com/lessons/james-watson-on-how-he-discovered-dna Nobel laureate James Watson opens TED2005 with the frank and funny story of how he and his research partner, Francis Crick, discovered the structure of DNA. Talk by James Watson.</p>]]></description>
	
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	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/20585/dna-transcription-advanced</guid>
	<pubDate>Thu, 29 Jan 2015 05:31:42 -0600</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/20585/dna-transcription-advanced</link>
	<title><![CDATA[DNA Transcription (Advanced)]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/SMtWvDbfHLo" frameborder="0" allowfullscreen></iframe><p>Transcription is the process by which the information in DNA is copied into messenger RNA (mRNA) for protein production. Originally created for DNA Interactive ( http://www.dnai.org ). TRANSCRIPT: The Central Dogma of Molecular Biology: "DNA makes RNA makes protein" Here the process begins. Transcription factors assemble at a specific promoter region along the DNA. The length of DNA following the promoter is a gene and it contains the recipe for a protein. A mediator protein complex arrives carrying the enzyme RNA polymerase. It manoeuvres the RNA polymerase into place... inserting it with the help of other factors between the strands of the DNA double helix. The assembled collection of all these factors is referred to as the transcription initiation complex... and now it is ready to be activated. The initiation complex requires contact with activator proteins, which bind to specific sequences of DNA known as enhancer regions. These regions may be thousands of base pairs distant from the start of the gene. Contact between the activator proteins and the initiation-complex releases the copying mechanism. The RNA polymerase unzips a small portion of the DNA helix exposing the bases on each strand. Only one of the strands is copied. It acts as a template for the synthesis of an RNA molecule which is assembled one sub-unit at a time by matching the DNA letter code on the template strand. The sub-units can be seen here entering the enzyme through its intake hole and they are joined together to form the long messenger RNA chain snaking out of the top.</p>]]></description>
	
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30833/dnasp-v5-a-software-for-comprehensive-analysis-of-dna-polymorphism-data</guid>
	<pubDate>Mon, 06 Feb 2017 04:45:37 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30833/dnasp-v5-a-software-for-comprehensive-analysis-of-dna-polymorphism-data</link>
	<title><![CDATA[DnaSP v5: a software for comprehensive analysis of DNA polymorphism data]]></title>
	<description><![CDATA[<p><span>DnaSP is a software package for a comprehensive analysis of DNA polymorphism data. Version 5 implements a number of new features and analytical methods allowing extensive DNA polymorphism analyses on large datasets. Among other features, the newly implemented methods allow for: (i) analyses on multiple data files; (ii) haplotype phasing; (iii) analyses on insertion/deletion polymorphism data; (iv) visualizing sliding window results integrated with available genome annotations in the UCSC browser.</span></p><p>Address of the bookmark: <a href="http://www.ub.edu/dnasp/" rel="nofollow">http://www.ub.edu/dnasp/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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