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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/44527?</link>
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	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38304/lordfast-sensitive-and-fast-alignment-search-tool-for-long-noisy-read-sequencing-data</guid>
	<pubDate>Tue, 27 Nov 2018 04:43:57 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38304/lordfast-sensitive-and-fast-alignment-search-tool-for-long-noisy-read-sequencing-data</link>
	<title><![CDATA[lordFAST: sensitive and Fast Alignment Search Tool for LOng noisy Read sequencing Data]]></title>
	<description><![CDATA[<p><span>lordFAST is a sensitive tool for mapping long reads with high error rates. lordFAST is specially designed for aligning reads from PacBio sequencing technology but provides the user the ability to change alignment parameters depending on the reads and application.</span></p>
<p>lordFAST, a novel long-read mapper that is specifically designed to align reads generated by PacBio and potentially other SMS technologies to a reference. lordFAST not only has higher sensitivity than the available alternatives, it is also among the fastest and has a very low memory footprint.</p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="https://github.com/vpc-ccg/lordfast" rel="nofollow">https://github.com/vpc-ccg/lordfast</a></p>]]></description>
	<dc:creator>BioJoker</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37776/rhat-a-seed-and-extension-based-noisy-long-read-alignment-tool</guid>
	<pubDate>Sun, 23 Sep 2018 05:12:22 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37776/rhat-a-seed-and-extension-based-noisy-long-read-alignment-tool</link>
	<title><![CDATA[rHAT: a seed-and-extension-based noisy long read alignment tool]]></title>
	<description><![CDATA[<p><span>rHAT is a seed-and-extension-based noisy long read alignment tool. It is suitable for aligning 3rd generation sequencing reads which are in large read length with relatively high error rate, especially Pacbio's Single Molecule Read-time (SMRT) sequencing reads.</span></p><p>Address of the bookmark: <a href="https://github.com/dfguan/rHAT" rel="nofollow">https://github.com/dfguan/rHAT</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37645/lsc-improving-pacbio-long-read-accuracy-by-short-read-alignment</guid>
	<pubDate>Thu, 06 Sep 2018 16:27:35 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37645/lsc-improving-pacbio-long-read-accuracy-by-short-read-alignment</link>
	<title><![CDATA[LSC: Improving PacBio Long Read Accuracy by Short Read Alignment]]></title>
	<description><![CDATA[<ul>
<li>Added Command line argument support.</li>
<li>Multi-stage execution modes.</li>
<li>Support for parallelization. Now execution proceeds in batches of long reads the size of which can be set by --long_read_batch_size N.</li>
<li>Better compressed intermediate files.</li>
<li>Added utilities folder.</li>
<li>Added support for multiple short read files.</li>
<li>Removed use of configuration file.</li>
</ul><p>Address of the bookmark: <a href="https://www.healthcare.uiowa.edu/labs/au/LSC/" rel="nofollow">https://www.healthcare.uiowa.edu/labs/au/LSC/</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43791/comparative-genomics-visualisation-tools</guid>
	<pubDate>Thu, 17 Feb 2022 05:37:55 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43791/comparative-genomics-visualisation-tools</link>
	<title><![CDATA[Comparative genomics visualisation tools !]]></title>
	<description><![CDATA[<p>Comparative genomics visualisation tools !</p><p>Address of the bookmark: <a href="https://cmdcolin.github.io/awesome-genome-visualization/?latest=true&amp;selected=%23BRIG&amp;tag=Comparative" rel="nofollow">https://cmdcolin.github.io/awesome-genome-visualization/?latest=true&amp;selected=%23BRIG&amp;tag=Comparative</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30375/mauve-a-system-for-constructing-multiple-genome-alignments-in-the-presence-of-large-scale-evolutionary-events-such-as-rearrangement-and-inversion</guid>
	<pubDate>Sat, 24 Dec 2016 09:20:53 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30375/mauve-a-system-for-constructing-multiple-genome-alignments-in-the-presence-of-large-scale-evolutionary-events-such-as-rearrangement-and-inversion</link>
	<title><![CDATA[Mauve: a system for constructing multiple genome alignments in the presence of large-scale evolutionary events such as rearrangement and inversion]]></title>
	<description><![CDATA[<p>Mauve is a system for constructing multiple genome alignments in the presence of large-scale evolutionary events such as rearrangement and inversion. Multiple genome alignments provide a basis for research into comparative genomics and the study of genome-wide evolutionary dynamics.</p>
<p>Mauve has been developed with the idea that a multiple genome aligner should require only modest computational resources. It employs algorithmic techniques that scale well in the lengths of sequences being aligned. For example, a pair of&nbsp;<em>Y. pestis</em>&nbsp;genomes can be aligned in under a minute, while a group of 9 divergent Enterobacterial genomes can be aligned in a few hours. However, the current algorithm&rsquo;s compute time (progressiveMauve) scales cubically in the number of genomes to align, making it unsuitable for datasets containing more than 50-100 bacterial genomes.</p><p>Address of the bookmark: <a href="http://darlinglab.org/mauve/mauve.html" rel="nofollow">http://darlinglab.org/mauve/mauve.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32855/maf2synteny</guid>
	<pubDate>Thu, 18 May 2017 05:31:30 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32855/maf2synteny</link>
	<title><![CDATA[maf2synteny]]></title>
	<description><![CDATA[<p>A tool for converting for recovering synteny blocks from multiple alignment (in MAF fromat)</p>
<p>This tool is a standalone version of Ragout module [<a href="http://fenderglass.github./Ragout">http://fenderglass.github./Ragout</a>]</p><p>Address of the bookmark: <a href="https://github.com/fenderglass/maf2synteny" rel="nofollow">https://github.com/fenderglass/maf2synteny</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42963/davi-deep-learning-based-tool-for-alignment-and-single-nucleotide-variant-identification</guid>
	<pubDate>Tue, 16 Mar 2021 05:41:33 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42963/davi-deep-learning-based-tool-for-alignment-and-single-nucleotide-variant-identification</link>
	<title><![CDATA[DAVI: Deep learning-based tool for alignment and single nucleotide variant identification]]></title>
	<description><![CDATA[<p>DAVI consists of models for both global and local alignment and for variant calling. We have evaluated the performance of DAVI against existing state-of-the-art tool sets and found that its accuracy and performance is comparable to existing tools used for bench-marking. We further demonstrate that while existing tools are based on data generated from a specific sequencing technology, the models proposed in DAVI are generic and can be used across different NGS technologies as well as across different species</p>
<p>https://iopscience.iop.org/article/10.1088/2632-2153/ab7e19/pdf</p><p>Address of the bookmark: <a href="https://github.com/gguptaiitd/NEAT" rel="nofollow">https://github.com/gguptaiitd/NEAT</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34543/acana-an-accurate-and-consistent-alignment-tool-for-dna-sequences</guid>
	<pubDate>Wed, 06 Dec 2017 09:45:29 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34543/acana-an-accurate-and-consistent-alignment-tool-for-dna-sequences</link>
	<title><![CDATA[ACANA: An accurate and consistent alignment tool for DNA sequences]]></title>
	<description><![CDATA[<p><span>ACANA is an accurate and consistent alignment tool for DNA sequences. ACANA is specifically designed for aligning sequences that share only some moderately conserved regions and/or have a high frequency of long insertions or deletions. It attempts to combine the best of local and global alignments algorithms in searching for evolutionarily related regions of sequences in order to achieve the best alignment. ACANA is also robust to the small changes of alignment parameters, particularly the gap extension score. As an accurate alignment tool, ACANA is particularly useful in comparative sequence analysis for identifying conserved functional regulatory elements.</span></p><p>Address of the bookmark: <a href="https://www.niehs.nih.gov/research/resources/software/biostatistics/acana/index.cfm" rel="nofollow">https://www.niehs.nih.gov/research/resources/software/biostatistics/acana/index.cfm</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36618/lamsa-fast-split-read-alignment-with-long-approximate-matches</guid>
	<pubDate>Tue, 15 May 2018 04:44:42 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36618/lamsa-fast-split-read-alignment-with-long-approximate-matches</link>
	<title><![CDATA[LAMSA: fast split read alignment with long approximate matches]]></title>
	<description><![CDATA[LAMSA (Long Approximate Matches-based Split Aligner) is a novel split alignment approach with faster speed and good ability of handling SV events. It is well-suited to align long reads (over thousands of base-pairs).

LAMSA takes takes the advantage of the rareness of SVs to implement a specifically designed two-step strategy. That is, LAMSA initially splits the read into relatively long fragments and co-linearly align them to solve the small variations or sequencing errors, and mitigate the effect of repeats. The alignments of the fragments are then used for implementing a sparse dynamic programming (SDP)-based split alignment approach to handle the large or non-co-linear variants.

We benchmarked LAMSA with simulated and real datasets having various read lengths and sequencing error rates, the results demonstrate that it is substantially faster than the state-of-the-art long read aligners; mean-while, it also has good ability to handle various categories of SVs.

LAMSA is open source and free for non-commercial use.

LAMSA is mainly designed by Bo Liu &amp; Yan Gao and developed by Yan Gao in Center for Bioinformatics, Harbin Institute of Technology, China.<p>Address of the bookmark: <a href="https://github.com/hitbc/LAMSA" rel="nofollow">https://github.com/hitbc/LAMSA</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44508/a-web-based-tool-for-sequence-alignment-statistics-and-innovative-visualization</guid>
	<pubDate>Thu, 04 Apr 2024 01:44:50 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44508/a-web-based-tool-for-sequence-alignment-statistics-and-innovative-visualization</link>
	<title><![CDATA[A web-based tool for sequence alignment statistics and innovative visualization]]></title>
	<description><![CDATA[<p>AlignStatPlot, a new R package and online tool that is well-documented and easy-to usefor MSA and post-MSA analysis. This tool performs both traditional and cutting-edge analy-ses on sequencing data and generates new visualisation methods for MSA results. Whencompared to currently available tools, AlignStatPlot provides a robust ability to handle andvisualise diversity data, while the online version will save time and encourage researchersto focus on explaining their findings. It is a simple tool that can be used in conjunction withpopulation genetics software (PDF) AlignStatPlot: An R package and online tool for robust sequence alignment statistics and innovative visualization of big data.</p><p>Address of the bookmark: <a href="https://bioinformatics.um6p.ma/AlignStatPlot/" rel="nofollow">https://bioinformatics.um6p.ma/AlignStatPlot/</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>

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