<?xml version='1.0'?><rss version="2.0" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:georss="http://www.georss.org/georss" xmlns:atom="http://www.w3.org/2005/Atom" >
<channel>
	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/43904?offset=50</link>
	<atom:link href="https://bioinformaticsonline.com/related/43904?offset=50" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/14191/scalpel</guid>
	<pubDate>Wed, 20 Aug 2014 02:07:58 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/14191/scalpel</link>
	<title><![CDATA[Scalpel]]></title>
	<description><![CDATA[<p>A team from Cold Spring Harbor Laboratory has released an algorithm, called Scalpel, for finding insertions and deletions in next generation sequencing data sets. Scalpel, which is open source and <a href="http://scalpel.sourceforge.net/" title="available for download">available for download</a> on SourceForge,&nbsp;<span>outperformed the popular tools GATK HaplotypeCaller and SOAPindel in test runs on both simulated and real whole human exomes.</span></p><p>Like other indel callers, Scalpel works by performing <em>de novo</em>&nbsp;assembly of regions of interest, so that misalignment to the reference genome cannot obscure the presence of an insertion or deletion. Scalpel's innovation is to repeatedly check its assembly before comparing to the reference genome, to account for simple sequence repeats that are a regular source of error in indel calling. When Scalpel assembles an exon, it collects reads that map to that exon (including partial matches), splits them into k-mers, and creates a de Bruijn graph to span the exon; however, if it detects repeats in the map, it iteratively increases the size of the k-mers by one base until the repeats are eliminated. This ensures that the final assembly of the exon is highly accurate while minimizing compute time.</p><p>The Cold Spring Harbor team's validation of Scalpel, <a href="http://www.nature.com/nmeth/journal/vaop/ncurrent/full/nmeth.3069.html" title="published over the weekend in Nature Methods">published over the weekend in <em>Nature Methods</em></a>, compares Scalpel's performance on a live whole exome against HaplotypeCaller and SOAPindel. The donor is an individual with serious neurological disorders, which may be linked to a high incidence of indels. One thousand indels from this individual's exome, called by one or more of the informatics pipelines, were selected for focused resequencing. This resequencing revealed a 77% true positive rate for Scalpel calls, dramatically better than the rates for either of the competing tools; Scalpel performed especially well with indels longer than five base pairs, a traditional weak point for indel callers.</p><p>Finally, the authors demonstrate Scalpel's use on a large set of genetic data from nearly 600 families who donated samples to the Simons Simplex Collection, a project of the Simons Foundation Autism Research Initiative. Scalpel found a very high enrichment for indels in children affected by autism, compared with their unaffected siblings, a pattern that persisted even after excluding common variants.</p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/23253/resolving-the-complexity-of-the-human-genome-using-single-molecule-sequencing</guid>
	<pubDate>Sat, 11 Jul 2015 12:47:34 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/23253/resolving-the-complexity-of-the-human-genome-using-single-molecule-sequencing</link>
	<title><![CDATA[Resolving the complexity of the human genome using single-molecule sequencing]]></title>
	<description><![CDATA[<p>The human genome is arguably the most complete mammalian reference assembly yet more than 160 euchromatic gaps remain and aspects of its structural variation remain poorly understood ten years after its completion. The results in this paper https://www.genomeweb.com/sequencing/team-uses-single-molecule-sequencing-close-gaps-chart-complexity-human-reference suggest a greater complexity of the human genome in the form of variation of longer and more complex repetitive DNA that can now be largely resolved with the application of this longer-read sequencing technology.</p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="http://www.nature.com/nature/journal/v517/n7536/full/nature13907.html" rel="nofollow">http://www.nature.com/nature/journal/v517/n7536/full/nature13907.html</a></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41144/seqmule-automated-human-exomegenome-variants-detection</guid>
	<pubDate>Tue, 18 Feb 2020 03:22:54 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41144/seqmule-automated-human-exomegenome-variants-detection</link>
	<title><![CDATA[SeqMule: Automated human exome/genome variants detection]]></title>
	<description><![CDATA[<p>SeqMule takes single-end or paird-end FASTQ or BAM files, generates a script consisting of more than 10 popular alignment, analysis tools and runs the script line by line. Users can change the pipeline or fine-tune the parameters by modifying its configuration file.</p><p>Address of the bookmark: <a href="https://doc-openbio.readthedocs.io/projects/seqmule/en/latest/" rel="nofollow">https://doc-openbio.readthedocs.io/projects/seqmule/en/latest/</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34493/plast-a-fast-accurate-and-ngs-scalable-bank-to-bank-sequence-similarity-search-tool</guid>
	<pubDate>Fri, 01 Dec 2017 04:10:54 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34493/plast-a-fast-accurate-and-ngs-scalable-bank-to-bank-sequence-similarity-search-tool</link>
	<title><![CDATA[PLAST: A fast, accurate and NGS scalable bank-to-bank sequence similarity search tool]]></title>
	<description><![CDATA[<p><strong>PLAST is a fast, accurate and NGS scalable bank-to-bank sequence similarity search tool providing significant accelerations of seeds-based heuristic comparison methods, such as the Blast suite of algorithms.</strong></p>
<p><strong>Relying on unique software architecture, PLAST takes full advantage of recent multi-core personal computers without requiring any additional hardware devices.</strong></p>
<p>PLAST stands for&nbsp;<em>Parallel Local Sequence Alignment Search Tool&nbsp;</em>and is was&nbsp;<a href="http://www.biomedcentral.com/1471-2105/10/329" target="_blank">published in BMC Bioinformatics.</a></p>
<p>PLAST is a general purpose sequence comparison tool providing the following benefits:</p>
<ul>
<li>PLAST is a high-performance sequence comparison tool designed to compare two sets of sequences (query vs. reference),</li>
<li>Reduces the processing time of sequences comparisons while providing highest quality results,</li>
<li>Contains a fully integrated data filtering engine capable of selecting relevant hits with user-defined criteria (E-Value, identity, coverage, alignment length, etc.),</li>
<li>Does not require any additional hardware, since it is a software solution. It is easy to install, cost-effective, takes full advantage of multi-core processors and uses a small RAM footprint,</li>
<li>Ready to be used on desktop computer, cluster, cloud as well as within distributed system running Hadoop.</li>
</ul>
<p>https://plast.inria.fr/</p><p>Address of the bookmark: <a href="https://plast.inria.fr/" rel="nofollow">https://plast.inria.fr/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36621/hapcut2-robust-and-accurate-haplotype-assembly-for-diverse-sequencing-technologies</guid>
	<pubDate>Tue, 15 May 2018 07:35:26 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36621/hapcut2-robust-and-accurate-haplotype-assembly-for-diverse-sequencing-technologies</link>
	<title><![CDATA[HapCUT2: robust and accurate haplotype assembly for diverse sequencing technologies]]></title>
	<description><![CDATA[HapCUT2 is a maximum-likelihood-based tool for assembling haplotypes from DNA sequence reads, designed to "just work" with excellent speed and accuracy. We found that previously described haplotype assembly methods are specialized for specific read technologies or protocols, with slow or inaccurate performance on others. With this in mind, HapCUT2 is designed for speed and accuracy across diverse sequencing technologies, including but not limited to:

NGS short reads (Illumina HiSeq)
clone-based sequencing (Fosmid or BAC clones)
SMRT reads (PacBio)
Oxford Nanopore reads
10X Genomics Linked-Reads
proximity-ligation (Hi-C) reads
high-coverage sequencing (&gt;40x coverage-per-SNP) using above technologies
combinations of the above technologies (e.g. scaffold long reads with Hi-C reads)
See below for specific examples of command line options and best practices for some of these technologies.

NOTE: At this time HapCUT2 is for diploid organisms only. VCF input should contain diploid variants.

If you use HapCUT2 in your research, please cite:

Edge, P., Bafna, V. &amp; Bansal, V. HapCUT2: robust and accurate haplotype assembly for diverse sequencing technologies. Genome Res. gr.213462.116 (2016). doi:10.1101/gr.213462.116<p>Address of the bookmark: <a href="https://github.com/vibansal/HapCUT2" rel="nofollow">https://github.com/vibansal/HapCUT2</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37650/p-rna-scaffolder-a-fast-and-accurate-genome-scaffolder-using-paired-end-rna-sequencing-reads</guid>
	<pubDate>Fri, 07 Sep 2018 05:19:06 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37650/p-rna-scaffolder-a-fast-and-accurate-genome-scaffolder-using-paired-end-rna-sequencing-reads</link>
	<title><![CDATA[P_RNA_scaffolder: a fast and accurate genome scaffolder using paired-end RNA-sequencing reads]]></title>
	<description><![CDATA[<p><span>P_RNA_scaffolder is a novel scaffolding tool using Pair-end RNA-seq to scaffold genome fragments. The method is suitable for most genomes. The program could utilize Illumina Paired-end RNA-sequencing reads from target speciesies. Our method provides another practical alternative to existing mate-pair_based approaches or other Protein-based approaches (for instance,&nbsp;</span><a href="http://www.fishbrowser.org/software/PEP_scaffolder/">PEP_scaffolder&nbsp;</a><span>) for scaffolding genome sequences. The most important feature of this method is to improve the completeness of gene regions and long-coding gene regions (for instance,&nbsp;</span><a href="http://circrna.org/">circRNA</a><span>).</span></p><p>Address of the bookmark: <a href="http://www.fishbrowser.org/software/P_RNA_scaffolder/#" rel="nofollow">http://www.fishbrowser.org/software/P_RNA_scaffolder/#</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/40497/artificial-intelligence-is-more-accurate-than-doctors-in-diagnosing-breast-cancer</guid>
	<pubDate>Wed, 01 Jan 2020 22:12:34 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/40497/artificial-intelligence-is-more-accurate-than-doctors-in-diagnosing-breast-cancer</link>
	<title><![CDATA[Artificial intelligence is more accurate than doctors in diagnosing breast cancer]]></title>
	<description><![CDATA[<p>Artificial intelligence is more accurate than doctors in diagnosing breast cancer from mammograms, a study in the journal Nature suggests.</p><p>An international team, including researchers from&nbsp;<a href="https://health.google/" target="_blank">Google Health</a>&nbsp;and&nbsp;<a href="https://www.imperial.ac.uk/news/183293/research-collaboration-aims-improve-breast-cancer/" target="_blank">Imperial College London</a>, designed and trained a computer model on X-ray images from nearly 29,000 women.</p><p>The algorithm&nbsp;<a href="https://nature.com/articles/s41586-019-1799-6" target="_blank">outperformed six radiologists</a>&nbsp;in reading mammograms.</p><p>AI was still as good as two doctors working together.</p><p>Unlike humans, AI is tireless. Experts say it could improve detection. Read More:&nbsp;<a href="https://www.bbc.com/news/health-50857759" target="_blank">https://www.bbc.com/news/health-50857759</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42477/hifiasm-a-haplotype-resolved-assembler-for-accurate-hifi-reads</guid>
	<pubDate>Thu, 24 Dec 2020 10:03:36 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42477/hifiasm-a-haplotype-resolved-assembler-for-accurate-hifi-reads</link>
	<title><![CDATA[Hifiasm: a haplotype-resolved assembler for accurate Hifi reads]]></title>
	<description><![CDATA[<p><span>Hifiasm is a fast haplotype-resolved de novo assembler for PacBio Hifi reads. It can assemble a human genome in several hours and works with the California redwood genome, one of the most complex genomes sequenced so far. Hifiasm can produce primary/alternate assemblies of quality competitive with the best assemblers. It also introduces a new graph binning algorithm and achieves the best haplotype-resolved assembly given trio data.</span></p><p>Address of the bookmark: <a href="https://github.com/chhylp123/hifiasm" rel="nofollow">https://github.com/chhylp123/hifiasm</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44894/dna2bit-an-ultra-fast-and-accurate-genomic-distance-estimation-software</guid>
	<pubDate>Sun, 31 Aug 2025 06:24:58 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44894/dna2bit-an-ultra-fast-and-accurate-genomic-distance-estimation-software</link>
	<title><![CDATA[dna2bit: an ultra-fast and accurate genomic distance estimation software]]></title>
	<description><![CDATA[<p><span>dna2bit is a software tool developed in C++11, leveraging the capabilities of OpenMP for parallel computing and the popcount technique for efficient bit manipulation. It has been thoroughly tested using the g++ and clang compilers on both Linux and MacOS platforms.</span></p><p>Address of the bookmark: <a href="https://github.com/lijuzeng/dna2bit" rel="nofollow">https://github.com/lijuzeng/dna2bit</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37842/rapclust-accurate-lightweight-clustering-of-de-novo-transcriptomes-using-fragment-equivalence-classes</guid>
	<pubDate>Thu, 04 Oct 2018 17:57:10 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37842/rapclust-accurate-lightweight-clustering-of-de-novo-transcriptomes-using-fragment-equivalence-classes</link>
	<title><![CDATA[RapClust: Accurate, Lightweight Clustering of de novo Transcriptomes using Fragment Equivalence Classes]]></title>
	<description><![CDATA[<p><span>RapClust is a tool for clustering contigs from&nbsp;</span><em>de novo</em><span>&nbsp;transcriptome assemblies. RapClust is designed to be run downstream of the&nbsp;</span><a href="https://github.com/kingsfordgroup/sailfish">Sailfish</a><span>&nbsp;or&nbsp;</span><a href="https://github.com/COMBINE-lab/salmon">Salmon</a><span>&nbsp;tools for rapid transcript-level quantification. Specifically, RapClust relies on the&nbsp;</span><em>fragment equivalence classes</em><span>&nbsp;computed by these tools in order to determine how seqeunce is shared across the transcriptome, and how reads map to potentially-related contigs across different conditions.</span></p><p>Address of the bookmark: <a href="https://github.com/COMBINE-lab/RapClust" rel="nofollow">https://github.com/COMBINE-lab/RapClust</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>

</channel>
</rss>