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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/34493?offset=60</link>
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	<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/36808/whatshap-fast-and-accurate-read-based-phasing</guid>
	<pubDate>Mon, 28 May 2018 09:52:16 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36808/whatshap-fast-and-accurate-read-based-phasing</link>
	<title><![CDATA[WhatsHap: fast and accurate read-based phasing]]></title>
	<description><![CDATA[<p>WhatsHap is a software for phasing genomic variants using DNA sequencing reads, also called read-based phasing or haplotype assembly. It is especially suitable for long reads, but works also well with short reads.</p>
<h1>Features<a href="https://whatshap.readthedocs.io/en/latest/#features" title="Permalink to this headline"></a></h1>
<blockquote>
<div>
<ul>
<li>Very accurate results (Martin et al.,&nbsp;<a href="https://doi.org/10.1101/085050">WhatsHap: fast and accurate read-based phasing</a>)</li>
<li>Works well with Illumina, PacBio, Oxford Nanopore and other types of reads</li>
<li>It phases SNVs, indels and even &ldquo;complex&rdquo; variants (such as&nbsp;<code><span>TCG</span></code>&nbsp;&rarr;&nbsp;<code><span>AGAA</span></code>)</li>
<li>Pedigree phasing mode uses reads from related individuals (such as trios) to improve results and to reduce coverage requirements (Garg et al.,&nbsp;<a href="https://doi.org/10.1093/bioinformatics/btw276">Read-Based Phasing of Related Individuals</a>).</li>
<li>WhatsHap is&nbsp;<a href="https://whatshap.readthedocs.io/en/latest/installation.html#installation">easy to install</a></li>
<li>It is&nbsp;<a href="https://whatshap.readthedocs.io/en/latest/guide.html#user-guide">easy to use</a>: Pass in a VCF and one or more BAM files, get out a phased VCF. Supports multi-sample VCFs.</li>
<li>It produces standard-compliant VCF output by default</li>
<li>If desired, get output that is compatible with ReadBackedPhasing</li>
<li>Open Source (MIT license)</li>
</ul>
</div>
</blockquote><p>Address of the bookmark: <a href="https://whatshap.readthedocs.io/en/latest/" rel="nofollow">https://whatshap.readthedocs.io/en/latest/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39671/flye-fast-and-accurate-de-novo-assembler-for-single-molecule-sequencing-reads</guid>
	<pubDate>Sat, 06 Jul 2019 03:48:22 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39671/flye-fast-and-accurate-de-novo-assembler-for-single-molecule-sequencing-reads</link>
	<title><![CDATA[Flye: Fast and accurate de novo assembler for single molecule sequencing reads]]></title>
	<description><![CDATA[<p><span>Flye is a de novo assembler for single molecule sequencing reads, such as those produced by PacBio and Oxford Nanopore Technologies. It is designed for a wide range of datasets, from small bacterial projects to large mammalian-scale assemblies. The package represents a complete pipeline: it takes raw PB / ONT reads as input and outputs polished contigs. Flye also includes a special mode for metagenome assembly.</span></p><p>Address of the bookmark: <a href="https://github.com/fenderglass/Flye" rel="nofollow">https://github.com/fenderglass/Flye</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42310/dada2-fast-and-accurate-sample-inference-from-amplicon-data-with-single-nucleotide-resolution</guid>
	<pubDate>Tue, 10 Nov 2020 20:26:00 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42310/dada2-fast-and-accurate-sample-inference-from-amplicon-data-with-single-nucleotide-resolution</link>
	<title><![CDATA[DADA2: Fast and accurate sample inference from amplicon data with single-nucleotide resolution]]></title>
	<description><![CDATA[<p>The&nbsp;<a href="https://benjjneb.github.io/dada2/tutorial.html">DADA2 tutorial</a>&nbsp;goes through a typical workflow for paired end Illumina Miseq data: raw amplicon sequencing data is processed into the table of exact&nbsp;<strong>amplicon sequence variants (ASVs)</strong>&nbsp;present in each sample.</p>
<p>The&nbsp;<a href="https://benjjneb.github.io/dada2/bigdata.html">DADA2 Workflow on Big Data</a>&nbsp;goes through workflow optimized to run on large datasets (10s of millions to billions of reads).</p>
<p>An&nbsp;<a href="https://benjjneb.github.io/dada2/ITS_workflow.html">ITS-specific version of the DADA2 workflow</a>&nbsp;identifies and verifiably removes primers on both ends of each ITS read, a key step due to the variable length of the ITS region.</p>
<p>Short demonstrations of&nbsp;<a href="https://benjjneb.github.io/dada2/assign.html">assigning taxonomy</a>&nbsp;and&nbsp;<a href="https://benjjneb.github.io/dada2/assign.html">assigning species</a>&nbsp;to sequences.</p><p>Address of the bookmark: <a href="https://benjjneb.github.io/dada2/index.html" rel="nofollow">https://benjjneb.github.io/dada2/index.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43856/puffaligner-a-fast-efficient-and-accurate-aligner-based-on-the-pufferfish-index</guid>
	<pubDate>Thu, 21 Apr 2022 05:41:39 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43856/puffaligner-a-fast-efficient-and-accurate-aligner-based-on-the-pufferfish-index</link>
	<title><![CDATA[PuffAligner: a fast, efficient and accurate aligner based on the Pufferfish index]]></title>
	<description><![CDATA[<p><span>PuffAligner, a fast, accurate and versatile aligner built on top of the Pufferfish index. PuffAligner is able to produce highly sensitive alignments, similar to those of Bowtie2, but much more quickly. While exhibiting similar speed to the ultrafast STAR aligner, PuffAligner requires considerably less memory to construct its index and align reads. PuffAligner strikes a desirable balance with respect to the time, space and accuracy tradeoffs made by different alignment tools and provides a promising foundation on which to test new alignment ideas over large collections of sequences.</span></p><p>Address of the bookmark: <a href="https://github.com/COMBINE-lab/pufferfish/tree/cigar-strings" rel="nofollow">https://github.com/COMBINE-lab/pufferfish/tree/cigar-strings</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44902/hite-a-fast-and-accurate-dynamic-boundary-adjustment-approach-for-full-length-transposable-elements-detection-and-annotation-in-genome-assemblies</guid>
	<pubDate>Sat, 20 Sep 2025 09:34:04 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44902/hite-a-fast-and-accurate-dynamic-boundary-adjustment-approach-for-full-length-transposable-elements-detection-and-annotation-in-genome-assemblies</link>
	<title><![CDATA[HiTE: a fast and accurate dynamic boundary adjustment approach for full-length Transposable Elements detection and annotation in Genome Assemblies]]></title>
	<description><![CDATA[<p dir="auto"><code>HiTE</code>&nbsp;is a Python software that uses a dynamic boundary adjustment approach to detect and annotate full-length Transposable Elements in Genome Assemblies. In comparison to other tools, HiTE demonstrates superior performance in detecting a greater number of full-length TEs.</p>
<div dir="auto">
<h2 dir="auto">panHiTE</h2>
<a href="https://github.com/CSU-KangHu/HiTE#panhite"></a></div>
<p dir="auto">We have developed panHiTE, a comprehensive and accurate pipeline for TE detection in large-scale population genomes. It has been successfully applied to hundreds of plant population genomes, demonstrating its effectiveness and scalability.</p>
<p dir="auto">For detailed instructions, please refer to the&nbsp;<a href="https://github.com/CSU-KangHu/HiTE/wiki/panHiTE-tutorial">panHiTE tutorial</a>.</p><p>Address of the bookmark: <a href="https://github.com/CSU-KangHu/HiTE" rel="nofollow">https://github.com/CSU-KangHu/HiTE</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42415/sneakysnake-a-fast-and-accurate-universal-genome-pre-alignment-filter-for-cpus-gpus-and-fpgas</guid>
	<pubDate>Sun, 20 Dec 2020 01:39:54 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42415/sneakysnake-a-fast-and-accurate-universal-genome-pre-alignment-filter-for-cpus-gpus-and-fpgas</link>
	<title><![CDATA[SneakySnake: A Fast and Accurate Universal Genome Pre-Alignment Filter for CPUs, GPUs, and FPGAs]]></title>
	<description><![CDATA[<p><span>The first and the only pre-alignment filtering algorithm that works efficiently and fast on modern CPU, FPGA, and GPU architectures. SneakySnake greatly (by more than two orders of magnitude) expedites sequence alignment calculation for both short (Illumina) and long (ONT and PacBio) reads. Described by Alser et al. (preliminary version at&nbsp;</span><a href="https://arxiv.org/abs/1910.09020">https://arxiv.org/abs/1910.09020</a><span>).</span></p><p>Address of the bookmark: <a href="https://github.com/CMU-SAFARI/SneakySnake" rel="nofollow">https://github.com/CMU-SAFARI/SneakySnake</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30831/fsa-fast-statistical-alignment</guid>
	<pubDate>Mon, 06 Feb 2017 04:26:01 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30831/fsa-fast-statistical-alignment</link>
	<title><![CDATA[FSA: Fast Statistical Alignment]]></title>
	<description><![CDATA[<p><span>FSA is a probabilistic multiple sequence alignment algorithm which uses a "distance-based" approach to aligning homologous protein, RNA or DNA sequences. Much as distance-based phylogenetic reconstruction methods like Neighbor-Joining build a phylogeny using only pairwise divergence estimates, FSA builds a multiple alignment using only pairwise estimations of homology. This is made possible by the sequence annealing technique for constructing a multiple alignment from pairwise comparisons, developed by Ariel Schwartz in&nbsp;</span><a href="http://www.eecs.berkeley.edu/Pubs/TechRpts/2007/EECS-2007-39.html">"Posterior Decoding Methods for Optimization and Control of Multiple Alignments</a><span>."</span></p>
<p>FSA brings the high accuracies previously available only for small-scale analyses of proteins or RNAs to large-scale problems such as aligning thousands of sequences or megabase-long sequences. FSA introduces several novel methods for constructing better alignments:</p>
<ul>
<li>FSA uses machine-learning techniques to estimate gap and substitution parameters on the fly for each set of input sequences. This "query-specific learning" alignment method makes FSA very robust: it can produce superior alignments of sets of homologous sequences which are subject to very different evolutionary constraints.</li>
<li>FSA is capable of aligning hundreds or even thousands of sequences using a randomized inference algorithm to reduce the computational cost of multiple alignment. This randomized inference can be over ten times faster than a direct approach with little loss of accuracy.</li>
<li>FSA can quickly align very long sequences using the "anchor annealing" technique for resolving anchors and projecting them with transitive anchoring. It then stitches together the alignment between the anchors using the methods described above.</li>
<li>The included GUI, MAD (Multiple Alignment Display), can display the intermediate alignments produced by FSA, where each character is colored according to the probability that it is correctly aligned (see the picture and&nbsp;<a href="http://fsa.sourceforge.net/images/Suchard_SIV.fsa.mov">movie</a>&nbsp;at the top of the page).</li>
</ul>
<p><span>You can see more information on the&nbsp;</span><a href="http://fsa.sourceforge.net/FAQ.html">FAQ</a><span>.&nbsp;</span></p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="http://fsa.sourceforge.net/" rel="nofollow">http://fsa.sourceforge.net/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40208/ragoo-fast-reference-guided-scaffolding-of-genome-assembly-contigs</guid>
	<pubDate>Sun, 27 Oct 2019 00:57:23 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40208/ragoo-fast-reference-guided-scaffolding-of-genome-assembly-contigs</link>
	<title><![CDATA[RaGOO: Fast Reference-Guided Scaffolding of Genome Assembly Contigs]]></title>
	<description><![CDATA[<p>Alonge M, Soyk S, Ramakrishnan S, Wang X, Goodwin S, Sedlazeck FJ, Lippman ZB, Schatz MC:&nbsp;<a href="https://www.biorxiv.org/content/early/2019/01/13/519637">Fast and accurate reference-guided scaffolding of draft genomes</a>.&nbsp;<em>bioRxiv</em>&nbsp;2019.</p>
<p>RaGOO is a tool for coalescing genome assembly contigs into pseudochromosomes via minimap2 alignments to a closely related reference genome. The focus of this tool is on practicality and therefore has the following features:</p>
<ol>
<li>Good performance. On a MacBook Pro using Arabidopsis data, pseudochromosome construction takes less than a minute and the whole pipeline with SV calling takes ~2 minutes.</li>
<li>Intact ordering and orienting of contigs.</li>
<li><a href="https://github.com/malonge/RaGOO/wiki/Misassembly-Correction">Misassembly correction</a></li>
<li><a href="https://github.com/malonge/RaGOO/wiki/GFF-File-Lift-Over">GFF lift-over</a></li>
<li><a href="https://github.com/malonge/RaGOO/wiki/Calling-Structural-Variants">Structural variant calling with and integrated version of Assemblytics</a></li>
<li>Confidence scores associated with the grouping, localization, and orientation for each contig.</li>
</ol><p>Address of the bookmark: <a href="https://github.com/malonge/RaGOO" rel="nofollow">https://github.com/malonge/RaGOO</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36026/mmseqs20-ultra-fast-and-sensitive-protein-search-and-clustering-suite</guid>
	<pubDate>Thu, 22 Mar 2018 10:40:51 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36026/mmseqs20-ultra-fast-and-sensitive-protein-search-and-clustering-suite</link>
	<title><![CDATA[MMseqs2.0: ultra fast and sensitive protein search and clustering suite]]></title>
	<description><![CDATA[<p>MMseqs2 (Many-against-Many sequence searching) is a software suite to search and cluster huge protein sequence sets. MMseqs2 is open source GPL-licensed software implemented in C++ for Linux, MacOS, and (as beta version, via cygwin) Windows. The software is designed to run on multiple cores and servers and exhibits very good scalability. MMseqs2 can run 10000 times faster than BLAST. At 100 times its speed it achieves almost the same sensitivity. It can perform profile searches with the same sensitivity as PSI-BLAST at over 400 times its speed.</p>
<p>The MMseqs2 user guide is available as&nbsp;<a href="https://github.com/soedinglab/mmseqs2/wiki">Github Wiki</a>&nbsp;or as&nbsp;<a href="https://mmseqs.com/latest/userguide.pdf">PDF file</a>&nbsp;(Thanks to&nbsp;<a href="https://github.com/jgm/pandoc">pandoc</a>!)</p>
<p>Please cite:&nbsp;<a href="https://www.nature.com/nbt/journal/vaop/ncurrent/full/nbt.3988.html">Steinegger M and Soeding J. MMseqs2 enables sensitive protein sequence searching for the analysis of massive data sets. Nature Biotechnology, doi: 10.1038/nbt.3988 (2017)</a>.</p><p>Address of the bookmark: <a href="https://github.com/soedinglab/MMseqs2" rel="nofollow">https://github.com/soedinglab/MMseqs2</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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