<?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/34493?offset=500</link>
	<atom:link href="https://bioinformaticsonline.com/related/34493?offset=500" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34488/scripts-for-the-analysis-of-hgt-in-genome-sequence-data</guid>
	<pubDate>Wed, 29 Nov 2017 16:44:10 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34488/scripts-for-the-analysis-of-hgt-in-genome-sequence-data</link>
	<title><![CDATA[Scripts for the analysis of HGT in genome sequence data.]]></title>
	<description><![CDATA[<p><span>Scripts for the analysis of HGT in genome sequence data</span></p><p>Address of the bookmark: <a href="https://github.com/reubwn/hgt" rel="nofollow">https://github.com/reubwn/hgt</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/37962/wtdbg2-a-de-novo-sequence-assembler-for-long-noisy-reads-produced-by-pacbio-or-oxford-nanopore</guid>
	<pubDate>Fri, 19 Oct 2018 08:48:43 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37962/wtdbg2-a-de-novo-sequence-assembler-for-long-noisy-reads-produced-by-pacbio-or-oxford-nanopore</link>
	<title><![CDATA[Wtdbg2: a de novo sequence assembler for long noisy reads produced by PacBio or Oxford Nanopore]]></title>
	<description><![CDATA[<p><span>Wtdbg2 is a&nbsp;</span><em>de novo</em><span>&nbsp;sequence assembler for long noisy reads produced by PacBio or Oxford Nanopore Technologies (ONT). It assembles raw reads without error correction and then builds the consensus from intermediate assembly output. Wtdbg2 is able to assemble the human and even the 32Gb&nbsp;</span><a href="https://www.nature.com/articles/nature25458">Axolotl</a><span>&nbsp;genome at a speed tens of times faster than&nbsp;</span><a href="https://github.com/marbl/canu">CANU</a><span>&nbsp;and&nbsp;</span><a href="https://github.com/PacificBiosciences/FALCON">FALCON</a><span>while producing contigs of comparable base accuracy.</span></p><p>Address of the bookmark: <a href="https://github.com/ruanjue/wtdbg2" rel="nofollow">https://github.com/ruanjue/wtdbg2</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/news/view/41562/submit-your-sars-cov-2-sequence-data-to-genbank</guid>
	<pubDate>Thu, 09 Apr 2020 18:28:25 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/41562/submit-your-sars-cov-2-sequence-data-to-genbank</link>
	<title><![CDATA[Submit your SARS-CoV-2 sequence data to GenBank]]></title>
	<description><![CDATA[<div dir="auto">Submit your SARS-CoV-2 sequence data to GenBank and SRA with our new submission landing page. Submission is simple and streamlined *and* there&rsquo;s a rapid turnaround. <span><a href="https://l.facebook.com/l.php?u=https%3A%2F%2Fsubmit.ncbi.nlm.nih.gov%2Fsarscov2%2F%3Ffbclid%3DIwAR3p-OzZPe2yx4CZMoZxiWMF3kUQjXyVVduNQhBdehWmFTJ3cPBstsOLypI&amp;h=AT2d-umit7ciXRW-nrRYVL3gJSLKY4Hte8W8cXw8Wl94n6PGmoHmVqvvhgQj-mTo6A5lpMP9JDV_lRSq9RRLT5KeVVAAfcuRgJOeA6QhApIB2B9nFxUfDCD3sio4HYidpRwpmng&amp;__tn__=-UK-R&amp;c[0]=AT2zWGa1K5EvV4UcnB0b7HHvkBtX-wAyh7AF8_fZ9uI2y-02nOHQHT_Um3xgnto5KEZ26wRG0xNgUWTA1W-7HF0E25E23XtIL5XGOhloBXaDIcHw30AVjTCkQi7aFk4dN7aBCmVJeSbH37urtbM2kmMfyTCbdTvMU8FGlnX-DNVuCaZr4XfXnf_jvPNdxe9sBH84oXJ-uJz5kbqlHGAHDoqK" target="_blank">https://submit.ncbi.nlm.nih.gov/sarscov2/</a></span></div><div dir="auto">&nbsp;</div><div dir="auto"><span><span>Quickly and easily add your SARS-CoV-2 sequence data to the growing public archive with new, special features and support from NCBI. </span><a href="https://submit.ncbi.nlm.nih.gov/sarscov2/">new SARS-CoV-2 sequence submission landing page</a><span>&nbsp;will help you get started. GenBank submissions are accessioned and released in approximately 1-2 working days, and&nbsp;</span><a href="https://www.ncbi.nlm.nih.gov/sra" target="_blank">Sequence Read Archive</a><span>&nbsp;(SRA) submissions typically processed and released within hours. Submission is simple!</span></span></div><div><div dir="auto">&nbsp;</div><div dir="auto">More information is available on NCBI Insights. <span><a href="https://l.facebook.com/l.php?u=https%3A%2F%2Fncbiinsights.ncbi.nlm.nih.gov%2F2020%2F04%2F09%2Fsars-cov2-data-streamlined-submission-rapid-turnaround%2F%3Ffbclid%3DIwAR1OuLu3oDjz3VX4fDq5Jg316td9foTOUGNqnoN1eI2nFXTf4EBv28JiXD4&amp;h=AT0ah_epxwAc-nM6QiPBYvKSQ-kWmiPgHKO1w7SnxnnRiTI4etJJfNAWyzcR7snIdtxtcErAFRdHPBH2j0EY77gUPDdnBVnAsxnVbSgZnrrOPfnni331A37Xvytgnye0ArnUuWk&amp;__tn__=-UK-R&amp;c[0]=AT2zWGa1K5EvV4UcnB0b7HHvkBtX-wAyh7AF8_fZ9uI2y-02nOHQHT_Um3xgnto5KEZ26wRG0xNgUWTA1W-7HF0E25E23XtIL5XGOhloBXaDIcHw30AVjTCkQi7aFk4dN7aBCmVJeSbH37urtbM2kmMfyTCbdTvMU8FGlnX-DNVuCaZr4XfXnf_jvPNdxe9sBH84oXJ-uJz5kbqlHGAHDoqK" target="_blank">https://ncbiinsights.ncbi.nlm.nih.gov/2020/04/09/sars-cov2-data-streamlined-submission-rapid-turnaround/</a></span></div></div>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<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>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35041/seal-sequence-alignment-evaluation-suite</guid>
	<pubDate>Wed, 03 Jan 2018 05:05:46 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35041/seal-sequence-alignment-evaluation-suite</link>
	<title><![CDATA[Seal: SEquence ALignment evaluation suite]]></title>
	<description><![CDATA[<p><span>Seal</span>&nbsp;is a comprehensive sequencing simulation and alignment tool evaluation suite. This software (implemented in Java) provides several utilities that can be used to evaluate alignment algorithms, including:</p>
<ul>
<li>Reading a pre-existing reference genome from one or more FASTA files.</li>
<li>Alternatively, generating an artificial reference genome based on input parameters (length, repeat count, repeat length, repeat variability rate).</li>
<li>Simulating reads from random locations in the genome based on input parameters of read length, coverage, sequencing error rate, and indel rate.</li>
<li>Applying alignment tools to the genome and the reads through a standardized interface.</li>
<li>Parsing the output of the alignment tool and calculating the number of reads that were correctly or incorrectly mapped.</li>
<li>Computing run times and measures of accuracy.</li>
</ul>
<p><span>Seal</span>&nbsp;has interfaces to evaluate the following software packages:</p>
<ul>
<li>Bowtie</li>
<li>BWA</li>
<li>MAQ</li>
<li>mrFAST</li>
<li>mrsFAST</li>
<li>Novoalign</li>
<li>SHRiMP</li>
<li>SOAPv2</li>
</ul><p>Address of the bookmark: <a href="http://compbio.case.edu/seal/" rel="nofollow">http://compbio.case.edu/seal/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43319/k-mers-tutorial-classification-and-taxonomy</guid>
	<pubDate>Thu, 26 Aug 2021 10:28:43 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43319/k-mers-tutorial-classification-and-taxonomy</link>
	<title><![CDATA[k-mers tutorial - classification and taxonomy]]></title>
	<description><![CDATA[<p>DNA k-mers underlie much of our assembly work, and we (along with many others!) have spent a lot of time thinking about how to&nbsp;<a href="http://www.pnas.org/content/109/33/13272">store k-mer graphs efficiently</a>,&nbsp;<a href="http://ivory.idyll.org/blog/what-is-diginorm.html">discard redundant data</a>, and&nbsp;<a href="http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0101271">count them efficiently</a>.</p>
<p>More recently, we've been enthused about&nbsp;<a href="http://joss.theoj.org/papers/3d793c6e7db683bee7c03377a4a7f3c9">using k-mer based similarity measures</a>&nbsp;and&nbsp;<a href="http://ivory.idyll.org/blog/2016-sourmash-sbt.html">computing and searching k-mer-based sketch search databases for all the things</a>.</p>
<p>But I haven't spent too much talking about using k-mers for taxonomy, although that has become an&nbsp;<em>ahem</em>&nbsp;area of interest recently,&nbsp;<a href="http://www.biorxiv.org/content/early/2017/07/03/155358">if you read into our papers a bit</a>.</p>
<p>In this blog post I'm going to fix this by doing a little bit of a literature review and waxing enthusiastic about other people's work. Then in a future blog post I'll talk about how we're building off of this work in fun! and interesting? ways!</p><p>Address of the bookmark: <a href="http://ivory.idyll.org/blog/2017-something-about-kmers.html" rel="nofollow">http://ivory.idyll.org/blog/2017-something-about-kmers.html</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26252/recombination-detection-tool</guid>
	<pubDate>Tue, 02 Feb 2016 10:11:14 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26252/recombination-detection-tool</link>
	<title><![CDATA[Recombination detection tool]]></title>
	<description><![CDATA[<p>A program to detect recombination hotspots using population genetic data.</p>
<p>More at https://github.com/auton1/LDhot</p><p>Address of the bookmark: <a href="https://github.com/auton1/LDhot" rel="nofollow">https://github.com/auton1/LDhot</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

</channel>
</rss>