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<channel>
	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/33955?offset=130</link>
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	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42359/dnasp-dna-sequence-polymorphism-is-a-software-package-for-the-analysis-of-dna-polymorphisms</guid>
	<pubDate>Wed, 25 Nov 2020 19:51:38 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42359/dnasp-dna-sequence-polymorphism-is-a-software-package-for-the-analysis-of-dna-polymorphisms</link>
	<title><![CDATA[DnaSP: DNA Sequence Polymorphism, is a software package for the analysis of DNA polymorphisms]]></title>
	<description><![CDATA[<p><span>DnaSP, DNA Sequence Polymorphism, is a software package for the analysis of DNA polymorphisms using data from a single locus (a multiple sequence aligned -MSA data), or from several loci (a Multiple-MSA data, such as formats generated by some assembler RAD-seq software). DnaSP can estimate several measures of DNA sequence variation within and between populations in noncoding, synonymous or nonsynonymous sites, or in various sorts of codon positions), as well as linkage disequilibrium, recombination, gene flow and gene conversion parameters.</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>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44555/ultra-ultra-locates-tandemly-repetitive-areas-effective-labeling-of-repetitive-genomic-sequence</guid>
	<pubDate>Sat, 08 Jun 2024 16:03:39 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44555/ultra-ultra-locates-tandemly-repetitive-areas-effective-labeling-of-repetitive-genomic-sequence</link>
	<title><![CDATA[ULTRA (ULTRA Locates Tandemly Repetitive Areas) : Effective Labeling of Repetitive Genomic Sequence]]></title>
	<description><![CDATA[<p dir="auto">ULTRA is a tool to find and annotate tandem repeats inside genomic sequence. It is able to find repeats of any length and of any period (up to a maximum period of 4000). It can find highly decayed repeats missed by other software, and it will also be able to find very large repeats in highly repetitive sequence, regardless of the size of sequence or length of repeats. ULTRA offers meaningful annotation scores and can produce annotation P-values at user request.</p>
<p dir="auto">More at&nbsp;https://www.biorxiv.org/content/10.1101/2024.06.03.597269v1</p><p>Address of the bookmark: <a href="https://github.com/TravisWheelerLab/ULTRA" rel="nofollow">https://github.com/TravisWheelerLab/ULTRA</a></p>]]></description>
	<dc:creator>Abhi</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/pages/view/36711/ancestral-sequence-reconstruction-steps</guid>
	<pubDate>Fri, 18 May 2018 08:28:26 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/36711/ancestral-sequence-reconstruction-steps</link>
	<title><![CDATA[Ancestral sequence reconstruction steps !]]></title>
	<description><![CDATA[<div><strong>Ancestral sequence reconstruction</strong>&nbsp;(<strong>ASR</strong>) &ndash; also known as&nbsp;<strong>ancestral gene</strong>/<strong>sequence reconstruction</strong>/<strong>resurrection</strong>&nbsp;&ndash; is a technique used in the study of&nbsp;molecular evolution. The method consists of the synthesis of an ancestral&nbsp;gene&nbsp;and expression of the corresponding ancestral&nbsp;protein.&nbsp;<a href="https://en.wikipedia.org/wiki/Ancestral_sequence_reconstruction#cite_note-thornton-1"></a>The idea of protein 'resurrection' was suggested in 1963 by Pauling and Zuckerkandl.<a href="https://en.wikipedia.org/wiki/Ancestral_sequence_reconstruction#cite_note-2"></a>&nbsp;Some early efforts were made in the eighties-nineties, led by the laboratory of&nbsp;Steven A. Benner, showing the potential of this technique &ndash; one that only started to be fulfilled in the post-genomic era.<a href="https://en.wikipedia.org/wiki/Ancestral_sequence_reconstruction#cite_note-3"></a>&nbsp;Thanks to the improvement of algorithms and of better sequencing and synthesis techniques, the method was developed further in the early 2000s to allow the resurrection of a greater variety of and much more ancient genes.<a href="https://en.wikipedia.org/wiki/Ancestral_sequence_reconstruction#cite_note-4"></a>&nbsp;Over the last decade, ancestral protein resurrection has developed as a strategy to reveal the mechanisms and dynamics of protein evolution.&nbsp;</div><div>&nbsp;</div><div>BEAST is the best way to predict the ancestral structure. but, I suggest following steps?</div><div>&nbsp;</div><div>1- Alignments "Mafft -&nbsp;<a href="https://www.researchgate.net/deref/http%3A%2F%2Fmafft.cbrc.jp%2Falignment%2Fsoftware%2Fsource.html" target="_blank">http://mafft.cbrc.jp/alignment/software/source.html</a>"</div><div>mafft --maxiterate 1000 --reorder --thread 24 --genafpair Dataset.fasta &gt; Dataset_Alig.fasta</div><div>&nbsp;</div><div>2- Your dataset has a good phylogenetic signal, is possible to perform with Tree-Puzzle "<a href="https://www.researchgate.net/deref/http%3A%2F%2Fwww.tree-puzzle.de" target="_blank">http://www.tree-puzzle.de</a>";</div><div>&nbsp;</div><div id="yui_3_14_1_1_1526649596608_1443">3 - This dataset which the saturation index, I perform with "<a href="https://www.researchgate.net/deref/http%3A%2F%2Fdambe.bio.uottawa.ca%2Fdambe.asp" target="_blank">http://dambe.bio.uottawa.ca/dambe.asp</a>";</div><div>&nbsp;</div><div>4- Has evidence of possible recombination in your dataset, the evaluate if this presence or absence, because this may to influence the grouping of clades, I perform with</div><div>---recombination</div><div>&nbsp;</div><div>4.1- Phi-test, implemented in SplitTree4"<a href="https://www.researchgate.net/deref/http%3A%2F%2Fwww.splitstree.org" target="_blank">http://www.splitstree.org</a>", (.nex file)</div><div>&nbsp;</div><div>4.2- GARD deployed in webserver in the DataMonkey "<a href="https://www.researchgate.net/deref/http%3A%2F%2Fwww.datamonkey.org%2F" target="_blank">http://www.datamonkey.org/</a>" - turning to the amino acid seaview -&gt; view proteins -&gt; save as ...) Ideally do a tree-based groups.</div><div>&nbsp;</div><div>4.3- RDP4 for download and installation on Windows in "<a href="https://www.researchgate.net/deref/http%3A%2F%2Fweb.cbio.uct.ac.za%2F~darren%2Frdp.html" target="_blank">http://web.cbio.uct.ac.za/~darren/rdp.html</a>"</div><div>&nbsp;</div><div>4.4- Hyphy (Mac, Windows, Linux) in "<a href="https://www.researchgate.net/deref/http%3A%2F%2Fhyphy.org%2Fw%2Findex.php%2FDownload" target="_blank">http://hyphy.org/w/index.php/Download</a>"</div><div>&nbsp;</div><div>4.5- Path-o-Gen (temporal structure of a tree input file -&gt; arquivo.tre)</div><div>These steps above, I call of pre-processing to inferences phylogenetic...</div><div>&nbsp;</div><div>5- Perform phylogenetic tree, used Bayesian Inference with Molecular Clock, but is necessary Clock Testing:</div><div>&nbsp;</div><div>- This step is performed with program Beast (Beauti, Beast and TreeAnnotator), and Tracer_v1.5 more FigTree to inspection.</div><div>&nbsp;</div><div>- Tutorials:&nbsp;<a href="https://www.researchgate.net/deref/http%3A%2F%2Fbeast.bio.ed.ac.uk%2Ftutorials" target="_blank">http://beast.bio.ed.ac.uk/tutorials</a></div><div>- Downloads:&nbsp;<a href="https://www.researchgate.net/deref/http%3A%2F%2Fbeast.bio.ed.ac.uk%2Fdownloads" target="_blank">http://beast.bio.ed.ac.uk/downloads</a></div>]]></description>
	<dc:creator>Surabhi Chaudhary</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38169/amstat-display-statistics-of-large-sequence-files-from-next-generation-sequencing-projects</guid>
	<pubDate>Fri, 09 Nov 2018 13:34:56 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38169/amstat-display-statistics-of-large-sequence-files-from-next-generation-sequencing-projects</link>
	<title><![CDATA[AMStat: display statistics of large sequence files from next generation sequencing projects]]></title>
	<description><![CDATA[<p><span>SAMStat is an efficient C program to quickly display statistics of large sequence files from next generation sequencing projects. When applied to&nbsp;</span><a href="http://samstat.sourceforge.net/#about">SAM/BAM</a><span>&nbsp;files all statistics are reported for unmapped, poorly and accurately mapped reads separately. This allows for identification of a variety of problems, such as remaining linker and adaptor sequences, causing poor mapping. Apart from this SAMStat can be used to verify individual processing steps in large analysis pipelines.</span></p><p>Address of the bookmark: <a href="http://samstat.sourceforge.net/" rel="nofollow">http://samstat.sourceforge.net/</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39856/tritex-sequence-assembly-pipeline-for-triticeae-genomes</guid>
	<pubDate>Tue, 20 Aug 2019 09:47:14 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39856/tritex-sequence-assembly-pipeline-for-triticeae-genomes</link>
	<title><![CDATA[TRITEX sequence assembly pipeline for Triticeae genomes]]></title>
	<description><![CDATA[<div>
<p>The pipeline is open-source and hosted in a public Bitbucket&nbsp;<a href="https://bitbucket.org/tritexassembly/tritexassembly.bitbucket.io/src/master/">repository</a>.</p>
</div>
<div>
<p>TRITEX has been run on highly inbred genotypes of barley (<em>Hordeum vulgare</em>), tetraploid wheat (<em>Triticum turgidum</em>) and hexaploid wheat (<em>T. aestivum</em>) with reasonable results: super-scaffold N50 values in the range of dozens of Mb and pseudomolecules with better gene space representation than a BAC-by-BAC assembly. It has never been tested and is not expected to work on heterozygous or autopolyploid genomes.</p>
</div>
<div>
<p>A protocol for generating chromosome-conformation capture sequencing (Hi-C) data suitable for use with the pipeline is described in&nbsp;<a href="https://bio-protocol.org/e2955">Himmelbach et al. 2018</a>. Refer to the&nbsp;<a href="https://www.10xgenomics.com/resources/technical-notes/">technical notes</a>&nbsp;of 10X Genomics on how to generate Chromium data.</p>
</div><p>Address of the bookmark: <a href="https://tritexassembly.bitbucket.io/" rel="nofollow">https://tritexassembly.bitbucket.io/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40594/gfaviz-flexible-and-interactive-visualization-of-gfa-sequence-graphs</guid>
	<pubDate>Thu, 23 Jan 2020 07:33:46 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40594/gfaviz-flexible-and-interactive-visualization-of-gfa-sequence-graphs</link>
	<title><![CDATA[GfaViz: flexible and interactive visualization of GFA sequence graphs]]></title>
	<description><![CDATA[<p><span>GFA (Graphical Fragment Assembly) is an emerging standard format for representing sequence graphs. Although it was originally conceived as a format for sequence assembly (hence the name), and this remains its core application, it is more general, and able to represent many different types of sequence graphs, including scaffolding graphs, alignment graphs, variant graphs and splicing graphs.</span></p><p>Address of the bookmark: <a href="https://github.com/ggonnella/gfaviz" rel="nofollow">https://github.com/ggonnella/gfaviz</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41146/lofreq-a-sequence-quality-aware-ultra-sensitive-variant-caller-for-ngs-data</guid>
	<pubDate>Tue, 18 Feb 2020 03:24:22 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41146/lofreq-a-sequence-quality-aware-ultra-sensitive-variant-caller-for-ngs-data</link>
	<title><![CDATA[LoFreq*: A sequence-quality aware, ultra-sensitive variant caller for NGS data]]></title>
	<description><![CDATA[<p>LoFreq* (i.e. LoFreq version 2) is a fast and sensitive variant-caller for inferring SNVs and indels from next-generation sequencing data. It makes full use of base-call qualities and other sources of errors inherent in sequencing (e.g. mapping or base/indel alignment uncertainty), which are usually ignored by other methods or only used for filtering.</p>
<p>https://github.com/CSB5/lofreq</p>
<p>http://csb5.github.io/lofreq/installation/</p>
<p>https://github.com/CSB5/lofreq/tree/master/dist</p><p>Address of the bookmark: <a href="http://csb5.github.io/lofreq/" rel="nofollow">http://csb5.github.io/lofreq/</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41959/rna-bloom-a-fast-and-memory-efficient-de-novo-transcript-sequence-assembler</guid>
	<pubDate>Thu, 09 Jul 2020 03:13:06 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41959/rna-bloom-a-fast-and-memory-efficient-de-novo-transcript-sequence-assembler</link>
	<title><![CDATA[RNA-Bloom: a fast and memory-efficient de novo transcript sequence assembler]]></title>
	<description><![CDATA[<p><strong>RNA-Bloom</strong><span>&nbsp;</span>is a fast and memory-efficient<span>&nbsp;</span><em>de novo</em><span>&nbsp;</span>transcript sequence assembler. It is designed for the following sequencing data types:</p>
<ul>
<li>single-end/paired-end bulk RNA-seq (strand-specific/agnostic)</li>
<li>paired-end single-cell RNA-seq (strand-specific/agnostic)</li>
<li>nanopore RNA-seq (PCR cDNA/direct cDNA/direct RNA)</li>
</ul>
<p>Written by<span>&nbsp;</span><a>Ka Ming Nip</a><span>&nbsp;</span>✉️</p><p>Address of the bookmark: <a href="https://github.com/bcgsc/RNA-Bloom" rel="nofollow">https://github.com/bcgsc/RNA-Bloom</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43268/kmer-a-suite-of-tools-for-dna-sequence-analysis</guid>
	<pubDate>Wed, 18 Aug 2021 00:02:54 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43268/kmer-a-suite-of-tools-for-dna-sequence-analysis</link>
	<title><![CDATA[Kmer: a suite of tools for DNA sequence analysis]]></title>
	<description><![CDATA[<p>More at&nbsp;https://help.rc.ufl.edu/doc/Kmer</p>
<p>This also includes:</p>
<ul>
<li>A2Amapper: ATAC, Assembly to Assembly Comparision tool:
<ul>
<li>Comparative mapping between two genome assemblies (same species), or between two different genomes (cross species).</li>
</ul>
</li>
</ul>
<ul>
<li>Sim4db:
<ul>
<li>Spliced alignment of cDNA and genomic sequences, from the same (sim4) or related (sim4cc) species. Optimized for high-throughput batched alignment.</li>
</ul>
</li>
</ul>
<ul>
<li>LEAFF:
<ul>
<li>LEAFF (ahem, Let's Extract Anything From Fasta) is a utility program for working with multi-fasta files. In addition to providing random access to the base level, it includes several analysis functions.</li>
</ul>
</li>
</ul>
<ul>
<li>Meryl:
<ul>
<li>An out-of-core k-mer counter. The amount of sequence that can be processed for any size k depends only on the amount of free disk space.</li>
</ul>
</li>
</ul><p>Address of the bookmark: <a href="https://help.rc.ufl.edu/doc/Kmer" rel="nofollow">https://help.rc.ufl.edu/doc/Kmer</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>

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