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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/40701?offset=170</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29384/phymmbl</guid>
	<pubDate>Mon, 10 Oct 2016 08:56:34 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29384/phymmbl</link>
	<title><![CDATA[PHYMMBL]]></title>
	<description><![CDATA[<p><span>Metagenomics sequencing projects collect samples of DNA from uncharacterized environments that may contain hundreds or even thousands of species. One of the main challenges in analyzing a metagenome is phylogenetic classification of raw sequence reads into groups representing the same or similar species. Such classification is a useful prerequisite for genome assembly and for analysis of the biological diversity present in a sample. The newest sequencing technologies have simultaneously made metagenomics easier, by making the sequencing process faster, and more difficult, by producing shorter read lengths than previous technologies. Methods for classifying sequences as short as 100 base pairs (bp) have until now been relatively inaccurate, requiring metagenomics projects to use older, long-read technologies.&nbsp;</span><strong>Phymm</strong><span>, a new classification approach for metagenomics data which uses interpolated Markov models (IMMs) to taxonomically classify DNA sequences, can accurately classify reads as short as 100 bp. Its accuracy for short reads represents a significant leap forward over previous composition-based classification methods.&nbsp;</span><strong>PhymmBL</strong><span>&nbsp;(rhymes with "thimble"), the hybrid classifier included in this distribution which combines analysis from both Phymm and&nbsp;</span><a href="http://www.ncbi.nlm.nih.gov/BLAST">BLAST</a><span>, produces even higher accuracy.</span></p><p>Address of the bookmark: <a href="http://www.cbcb.umd.edu/software/phymm/" rel="nofollow">http://www.cbcb.umd.edu/software/phymm/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30555/yaha</guid>
	<pubDate>Fri, 20 Jan 2017 05:38:05 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30555/yaha</link>
	<title><![CDATA[YAHA]]></title>
	<description><![CDATA[<p>YAHA, a fast and flexible hash-based aligner. YAHA is as fast and accurate as BWA-SW at finding the single best alignment per query and is dramatically faster and more sensitive than both SSAHA2 and MegaBLAST at finding all possible alignments. Unlike other aligners that report all, or one, alignment per query, or that use simple heuristics to select alignments, YAHA uses a directed acyclic graph to find the optimal set of alignments that cover a query using a biologically relevant breakpoint penalty. YAHA can also report multiple mappings per defined segment of the query. We show that YAHA detects more breakpoints in less time than BWA-SW across all SV classes, and especially excels at complex SVs comprising multiple breakpoints.</p>
<p><strong>Availability:</strong> YAHA is currently supported on 64-bit Linux systems. Binaries and sample data are freely available for download from <a href="http://faculty.virginia.edu/irahall/YAHA" target="pmc_ext">http://faculty.virginia.edu/irahall/YAHA</a>.</p>
<p><strong>Contact:</strong></p>
<p>http://genome.wustl.edu/people/groups/detail/hall-lab/</p><p>Address of the bookmark: <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3463118/" rel="nofollow">https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3463118/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31302/multi-metagenome-assembly</guid>
	<pubDate>Fri, 03 Mar 2017 10:14:18 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31302/multi-metagenome-assembly</link>
	<title><![CDATA[Multi-metagenome assembly]]></title>
	<description><![CDATA[<p>This project contains scripts and tutorials on how to assemble individual microbial genomes from metagenomes, as described in:</p>
<p>Genome sequences of rare, uncultured bacteria obtained by differential coverage binning of multiple metagenomes<br><br>Mads Albertsen, Philip Hugenholtz, Adam Skarshewski, Gene W. Tyson, K&aring;re L. Nielsen and Per .H. Nielsen</p>
<p>Nature Biotechnology 2013, doi:&nbsp;<a href="http://www.nature.com/nbt/journal/vaop/ncurrent/abs/nbt.2579.html">10.1038/nbt.2579</a></p><p>Address of the bookmark: <a href="https://github.com/MadsAlbertsen/multi-metagenome" rel="nofollow">https://github.com/MadsAlbertsen/multi-metagenome</a></p>]]></description>
	<dc:creator>Radha Agarkar</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32129/lordec-a-hybrid-error-correction-program-for-long-pacbio-reads</guid>
	<pubDate>Mon, 10 Apr 2017 04:16:09 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32129/lordec-a-hybrid-error-correction-program-for-long-pacbio-reads</link>
	<title><![CDATA[LoRDEC: a hybrid error correction program for long, PacBio reads]]></title>
	<description><![CDATA[<p>LoRDEC is a program to correct sequencing errors in long reads from 3rd generation sequencing with high error rate, and is especially intended for PacBio reads. It uses a hybrid strategy, meaning that it uses two sets of reads: the reference read set, whose error rate is assumed to be small, and the PacBio read set, which is then corrected using the reference set. Typically, the reference set contains Illumina reads.</p>
<p><br> Usually, errors in PacBio reads include many insertions and deletions, and comparatively less substitutions. LoRDEC can correct errors of all these types.<br> After correction, a larger portion of the sequence of PacBio reads is usable for detection of region of similarity with other sequences, for aligning them to the contigs of an assembly, etc.</p>
<p>Why is LoRDEC different?</p>
<ul>
<li>It is efficient and can process large read data sets, included from eukaryotic or vertebrate species, on a usual computing server, and even works on desktop/laptop computers.</li>
<li>It adopts a novel graph based approach: it builds a succinct De Bruijn Graph (DBG) representing the short reads, and seeks a corrective sequence for each erroneous region of a long read by traversing chosen paths in the graph.</li>
</ul><p>Address of the bookmark: <a href="http://www.atgc-montpellier.fr/lordec/" rel="nofollow">http://www.atgc-montpellier.fr/lordec/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38792/nxrepair-error-correction-in-de-novo-assemblies-using-nextera-mate-pair-reads</guid>
	<pubDate>Thu, 24 Jan 2019 10:35:12 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38792/nxrepair-error-correction-in-de-novo-assemblies-using-nextera-mate-pair-reads</link>
	<title><![CDATA[NxRepair: error correction in de novo assemblies using Nextera Mate Pair Reads]]></title>
	<description><![CDATA[<p>NxRepair is a python module that automatically detects large structural errors in de novo assemblies using Nextera mate pair reads. The decector will break a contig at the site of an identified misassembly and will generate a new fasta file containing both the corrected contigs and the correct, unaffected contigs.</p>
<p>https://nxrepair.readthedocs.io/en/latest/tutorial.html</p>
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<pre>nxrepair aligned_matepairs.bam assemblyfasta.fasta error_locations.csv new_fasta.fasta</pre>
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<div>&nbsp;</div><p>Address of the bookmark: <a href="https://github.com/rebeccaroisin/nxrepair" rel="nofollow">https://github.com/rebeccaroisin/nxrepair</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43828/understanding-hifi-reads</guid>
	<pubDate>Thu, 24 Mar 2022 19:48:11 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43828/understanding-hifi-reads</link>
	<title><![CDATA[Understanding HiFi Reads !]]></title>
	<description><![CDATA[<p><span>While little public data is available for either of the new synthetic long read approaches, Illumina showed an example comparison earlier this year at the&nbsp;</span><a href="https://www.festivalofgenomics.com/rami-mehio" target="_blank">Festival of Genomics &amp; Biodata conference</a><span>&nbsp;(FoG 2022). In the IGV screenshot presented (below), synthetic Infinity reads &ndash; labeled &ldquo;Longas&rdquo; &ndash; are at the top, followed by standard Illumina short reads, and PacBio HiFi reads labeled &ldquo;CCS&rdquo; depicted at the bottom:</span></p><p>Address of the bookmark: <a href="http://pacb.com/blog/the-hifi-difference-true-long-reads-vs-synthetic-long-reads/" rel="nofollow">http://pacb.com/blog/the-hifi-difference-true-long-reads-vs-synthetic-long-reads/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/44848/trust-but-verify-sequencing-your-cell-lines-might-reveal-an-uninvited-guest</guid>
	<pubDate>Wed, 04 Jun 2025 00:07:57 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44848/trust-but-verify-sequencing-your-cell-lines-might-reveal-an-uninvited-guest</link>
	<title><![CDATA[Trust But Verify: Sequencing Your Cell Lines Might Reveal an Uninvited Guest]]></title>
	<description><![CDATA[<p>High-throughput sequencing has become indispensable in cell biology, enabling detailed insights into chromatin structure, gene expression, and regulatory dynamics. Yet, when faced with unexpectedly low mapping rates to the human genome, researchers often rush to troubleshoot technical parameters&mdash;sequencer quality, adapter trimming, or aligner settings.</p><p>Before you go down that path, consider this critical biological question:<br /> <strong>Are you sequencing human cells&mdash;or bacterial contamination?</strong></p><h2>The Silent Saboteur: Mycoplasma in Cell Cultures</h2><p><em>Mycoplasma</em> contamination remains one of the most widespread and underdiagnosed issues in tissue culture work. Studies suggest that <strong>15&ndash;35% of cell lines in use may be contaminated</strong>, often without visible signs. Unlike other microbial infections, <em>Mycoplasma</em> does not produce cloudiness, odor, or a change in pH. Many researchers won&rsquo;t detect it unless they specifically test for it.</p><p>The consequences, however, are profound. <em>Mycoplasma</em> can significantly alter:</p><ul>
<li>
<p>Host gene expression patterns</p>
</li>
<li>
<p>Cell proliferation rates</p>
</li>
<li>
<p>Epigenetic profiles and chromatin accessibility</p>
</li>
<li>
<p>Cytokine signaling and immune responses</p>
</li>
</ul><p>In short, it can skew your results, compromise your biological conclusions, and invalidate weeks or months of research.</p><h2>A Simple Diagnostic Step: Map Against <em>Mycoplasma</em> Genomes</h2><p>If you encounter poor alignment rates to the human genome, consider mapping your reads to a <em>Mycoplasma</em> reference genome&mdash;or better yet, use a <strong>combined human + <em>Mycoplasma</em></strong> reference. There have been cases where over half of all reads, initially assumed to be from human cells, were in fact bacterial in origin. This check is fast, easy, and could save your project.</p><h2>How Contamination Happens&mdash;and Persists</h2><p><em>Mycoplasma</em> is small (0.1&ndash;0.3 &mu;m), lacks a cell wall, and can pass through standard filters undetected. Common sources include:</p><ul>
<li>
<p>Contaminated reagents (e.g., FBS)</p>
</li>
<li>
<p>Infected cell lines obtained from other labs</p>
</li>
<li>
<p>Poor aseptic technique or shared equipment</p>
</li>
</ul><p>Once present, it spreads quickly between cultures and can persist for months, silently affecting results.</p><h2>Why Treatment Is Difficult</h2><p>While antibiotics such as Plasmocin or BM-Cyclin are sometimes used, they often offer only partial resolution and may themselves alter cell behavior. In many cases, the best course of action is to <strong>discard the contaminated culture</strong> and start with a fresh, verified stock.</p><h2>Practical Recommendations for Researchers</h2><ul>
<li>
<p><strong>Routinely test for <em>Mycoplasma</em></strong> using PCR, qPCR, or fluorescence-based assays</p>
</li>
<li>
<p><strong>Incorporate contamination screens into your sequencing QC pipeline</strong></p>
</li>
<li>
<p><strong>Use combined reference genomes</strong> when mapping ambiguous reads</p>
</li>
<li>
<p><strong>Practice strict aseptic technique</strong> and monitor all incoming cell lines</p>
</li>
<li>
<p><strong>Don&rsquo;t ignore unexplained data anomalies</strong>&mdash;they might point to contamination</p>
</li>
</ul><h2>Closing Thought: Contamination Is a Biological Variable</h2><p>It&rsquo;s easy to view poor mapping as a technical issue, but sometimes the problem lies deeper&mdash;in the biology itself. <em>Mycoplasma</em> contamination doesn&rsquo;t just interfere with sequencing; it interferes with science. As a research community, we must treat contamination not as an afterthought, but as a key variable to control.</p><p>So next time your reads won&rsquo;t align, don&rsquo;t just tune the aligner. Ask if your cells are telling the truth&mdash;or if they're hiding something.</p>]]></description>
	<dc:creator>LEGE</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/4099/sequencing-solutions-to-world-health</guid>
	<pubDate>Thu, 29 Aug 2013 15:05:35 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/4099/sequencing-solutions-to-world-health</link>
	<title><![CDATA[Sequencing Solutions to World Health]]></title>
	<description><![CDATA[<p>"<em>New technology that quickly, easily and economically reveals the genomes of viruses and pathogens transforms public health and medicine."</em></p>
<p><strong>Source</strong>: Life technologies</p><p>Address of the bookmark: <a href="http://www.lifetechnologies.com/global/en/home/communities-social/blog/blogs/sequencing-solutions-to-world-health.html?cid=social_blogseries_20130829_11098264" rel="nofollow">http://www.lifetechnologies.com/global/en/home/communities-social/blog/blogs/sequencing-solutions-to-world-health.html?cid=social_blogseries_20130829_11098264</a></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/2518/genome-browsers</guid>
	<pubDate>Fri, 16 Aug 2013 19:04:47 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/2518/genome-browsers</link>
	<title><![CDATA[Genome Browsers]]></title>
	<description><![CDATA[<p>Genome Browser is the platform/database used for searching and retreiving sequences and annotation of genomes belong to various eukaryotes, prokaryotes, etc.</p><p>Following are the weblink for different available browsers:</p><p><a href="http://www.ensembl.org/index.html">http://www.ensembl.org/index.html</a></p><p><a href="http://ensemblgenomes.org/">http://ensemblgenomes.org/</a></p><p><a href="http://genome.ucsc.edu/">http://genome.ucsc.edu/</a></p><p><a href="http://www.ncbi.nlm.nih.gov/genome">http://www.ncbi.nlm.nih.gov/genome</a></p><p><a href="http://www.ebi.ac.uk/genomes/">http://www.ebi.ac.uk/genomes/</a></p><p><a href="http://flybase.org/">http://flybase.org/</a></p><p><a href="http://cmr.jcvi.org/tigr-scripts/CMR/CmrHomePage.cgi">http://cmr.jcvi.org/tigr-scripts/CMR/CmrHomePage.cgi</a></p><p><a href="http://www.sanger.ac.uk/resources/databases/">http://www.sanger.ac.uk/resources/databases/</a></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/4164/two-major-breakthrough</guid>
	<pubDate>Mon, 02 Sep 2013 10:18:11 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/4164/two-major-breakthrough</link>
	<title><![CDATA[Two major breakthrough!!]]></title>
	<description><![CDATA[<p>"Scientists in Uruguay in colloboration with European partners sequenced the genome of the high-value Tannat grape, from which "the most healthy of red wines" are fermented.</p><p>A quick, $1 syphilis&nbsp;test in development by researchers from UNU-BIOLAC."</p><p><strong>Source</strong>:</p><p><a href="http://www.sciencedaily.com/releases/2013/09/130902101846.htm">http://www.sciencedaily.com/releases/2013/09/130902101846.htm</a></p><p><a href="http://www.eurekalert.org/pub_releases/2013-09/tca-ssg082613.php">http://www.eurekalert.org/pub_releases/2013-09/tca-ssg082613.php</a></p><p>&nbsp;</p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
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