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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/28121?offset=210</link>
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	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30236/pyscaf</guid>
	<pubDate>Mon, 19 Dec 2016 14:20:33 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30236/pyscaf</link>
	<title><![CDATA[pyScaf]]></title>
	<description><![CDATA[<p>pyScaf orders contigs from genome assemblies utilising several types of information:</p>
<ul>
<li>paired-end (PE) and/or mate-pair libraries (<a href="https://github.com/lpryszcz/pyScaf#ngs-based-scaffolding">NGS-based mode</a>)</li>
<li>long reads (<a href="https://github.com/lpryszcz/pyScaf#scaffolding-based-on-long-reads">NGS-based mode</a>)</li>
<li>synteny to the genome of some related species (<a href="https://github.com/lpryszcz/pyScaf#reference-based-scaffolding">reference-based mode</a>)</li>
</ul>
<p>Scaffolding&nbsp;</p>
<p>In reference-based mode, pyScaf uses synteny to the genome of closely related species in order to order contigs and estimate distances between adjacent contigs.</p>
<p>Contigs are aligned globally (end-to-end) onto reference chromosomes, ignoring:</p>
<ul>
<li>matches not satisfying cut-offs (<code>--identity</code>&nbsp;and&nbsp;<code>--overlap</code>)</li>
<li>suboptimal matches (only best match of each query to reference is kept)</li>
<li>and removing overlapping matches on reference.</li>
</ul>
<p>In preliminary tests, pyScaf performed superbly on simulated heterozygous genomes based on&nbsp;<em>C. parapsilosis</em>&nbsp;(13 Mb; CANPA) and&nbsp;<em>A. thaliana</em>&nbsp;(119 Mb; ARATH) chromosomes, reconstructing correctly all chromosomes always for CANPA and nearly always for ARATH (<a href="https://www.dropbox.com/sh/bb7lwggo40xrwtc/AAAZ7pByVQQQ-WhUXZVeJaZVa/pyScaf?dl=0">Figures in dropbox</a>,&nbsp;<a href="https://docs.google.com/spreadsheets/d/1InBExy-qKDLj-upd8tlPItVSKc4mLepZjZxB31ii9OY/edit#gid=2036953672">CANPA table</a>,&nbsp;<a href="https://docs.google.com/spreadsheets/d/1InBExy-qKDLj-upd8tlPItVSKc4mLepZjZxB31ii9OY/edit#gid=1920757821">ARATH table</a>).<br>Runs took ~0.5 min for CANPA on&nbsp;<code>4 CPUs</code>&nbsp;and ~2 min for ARATH on&nbsp;<code>16 CPUs</code>.</p>
<p><span>Important remarks:</span></p>
<ul>
<li>Reduce your assembly before (fasta2homozygous.py) as any redundancy will likely break the synteny.</li>
<li>pyScaf works better with contigs than scaffolds, as scaffolds are often affected by mis-assemblies (no&nbsp;<em>de novo assembler</em>&nbsp;/ scaffolder is perfect...), which breaks synteny.</li>
<li>pyScaf works very well if divergence between reference genome and assembled contigs is below 20% at nucleotide level.</li>
<li>pyScaf deals with large rearrangements ie. deletions, insertion, inversions, translocations.&nbsp;<span>Note however, this is experimental implementation!</span></li>
<li>Consider closing gaps after scaffolding.</li>
</ul><p>Address of the bookmark: <a href="https://github.com/lpryszcz/pyScaf" rel="nofollow">https://github.com/lpryszcz/pyScaf</a></p>]]></description>
	<dc:creator>Bulbul</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30304/mcscan</guid>
	<pubDate>Thu, 22 Dec 2016 03:53:58 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30304/mcscan</link>
	<title><![CDATA[MCscan]]></title>
	<description><![CDATA[<p><span>MCscan is a computer program that can simultaneously scan multiple genomes to identify homologous chromosomal regions and subsequently align these regions using genes as anchors. This is the toolset for generating the synteny correspondences in&nbsp;</span><a href="http://chibba.agtec.uga.edu/duplication">Plant Genome Duplication Database</a><span>. It is intended as an easy-to-use and quick way to identify conserved gene arrays both within the same genome and across different genomes.</span></p>
<p><span>More at&nbsp;http://chibba.agtec.uga.edu/duplication/mcscan/</span></p><p>Address of the bookmark: <a href="http://chibba.agtec.uga.edu/duplication/mcscan/" rel="nofollow">http://chibba.agtec.uga.edu/duplication/mcscan/</a></p>]]></description>
	<dc:creator>Bulbul</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30555/yaha</guid>
	<pubDate>Fri, 20 Jan 2017 05:38:05 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30555/yaha</link>
	<title><![CDATA[YAHA]]></title>
	<description><![CDATA[<p>YAHA, a fast and flexible hash-based aligner. YAHA is as fast and accurate as BWA-SW at finding the single best alignment per query and is dramatically faster and more sensitive than both SSAHA2 and MegaBLAST at finding all possible alignments. Unlike other aligners that report all, or one, alignment per query, or that use simple heuristics to select alignments, YAHA uses a directed acyclic graph to find the optimal set of alignments that cover a query using a biologically relevant breakpoint penalty. YAHA can also report multiple mappings per defined segment of the query. We show that YAHA detects more breakpoints in less time than BWA-SW across all SV classes, and especially excels at complex SVs comprising multiple breakpoints.</p>
<p><strong>Availability:</strong> YAHA is currently supported on 64-bit Linux systems. Binaries and sample data are freely available for download from <a href="http://faculty.virginia.edu/irahall/YAHA" target="pmc_ext">http://faculty.virginia.edu/irahall/YAHA</a>.</p>
<p><strong>Contact:</strong></p>
<p>http://genome.wustl.edu/people/groups/detail/hall-lab/</p><p>Address of the bookmark: <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3463118/" rel="nofollow">https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3463118/</a></p>]]></description>
	<dc:creator>Jit</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/31012/genomecomp</guid>
	<pubDate>Fri, 17 Feb 2017 08:38:32 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31012/genomecomp</link>
	<title><![CDATA[GenomeComp]]></title>
	<description><![CDATA[<p>GenomeComp is a tool for summarizing, parsing and visualizing the genome wide sequence comparison results derived from voluminous BLAST textual output, so as to locate the rearrangements, insertions or deletions of genome segments between species or strains.<br><br>It can be easily used to compare, parsing and visualize large genomic sequences, especially closely related genomes such as inter-species or inter-strains. In addition, it can also show other sequence features like repeat sequence distributions in one whole-genome DNA sequence by comparing the genome to itself.<br><br>It is a stand-alone graphical user interface (GUI) program which runs on Linux, Unix, Mac OS X (tested on version 10.2.4 only) and Microsoft Windows platforms and is written in Perl/Tk.</p><p>Address of the bookmark: <a href="http://www.mgc.ac.cn/GenomeComp/" rel="nofollow">http://www.mgc.ac.cn/GenomeComp/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36974/many-to-many-pairwise-alignments-of-two-sequence-sets</guid>
	<pubDate>Tue, 19 Jun 2018 08:34:15 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36974/many-to-many-pairwise-alignments-of-two-sequence-sets</link>
	<title><![CDATA[Many-to-many pairwise alignments of two sequence sets]]></title>
	<description><![CDATA[needleall reads a set of input sequences and compares them all to one or more sequences, writing their optimal global sequence alignments to file. It uses the Needleman-Wunsch alignment algorithm to find the optimum alignment (including gaps) of two sequences along their entire length. The algorithm uses a dynamic programming method to ensure the alignment is optimum, by exploring all possible alignments and choosing the best. A scoring matrix is read that contains values for every possible residue or nucleotide match. Needleall finds the alignment with the maximum possible score where the score of an alignment is equal to the sum of the matches taken from the scoring matrix, minus penalties arising from opening and extending gaps in the aligned sequences. The substitution matrix and gap opening and extension penalties are user-specified.<p>Address of the bookmark: <a href="http://emboss.sourceforge.net/apps/release/6.6/emboss/apps/needleall.html" rel="nofollow">http://emboss.sourceforge.net/apps/release/6.6/emboss/apps/needleall.html</a></p>]]></description>
	<dc:creator>Poonam Mahapatra</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31714/krona</guid>
	<pubDate>Wed, 22 Mar 2017 04:47:35 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31714/krona</link>
	<title><![CDATA[Krona]]></title>
	<description><![CDATA[<p>Krona allows hierarchical data to be explored with zooming, multi-layered pie charts. Krona charts can be created using an <a href="https://github.com/marbl/Krona/wiki/ExcelTemplate">Excel template</a> or <a href="https://github.com/marbl/Krona/wiki/KronaTools">KronaTools</a>, which includes support for several bioinformatics tools and raw data formats. The interactive charts are self-contained and can be viewed with any modern web browser (see <a href="https://github.com/marbl/Krona/wiki/Browser%20support">Browser support</a>).</p>
<p><a href="http://marbl.github.io/Krona/img/screen_mgrast.png"><img src="https://camo.githubusercontent.com/27b71b1f1832523723c3d14dec764e7ad098438c/687474703a2f2f6d6172626c2e6769746875622e696f2f4b726f6e612f696d672f7468756d625f6d67726173742e706e67" width="210" height="167" alt="image" style="border: 0px;"></a></p><p>Address of the bookmark: <a href="https://github.com/marbl/Krona/wiki" rel="nofollow">https://github.com/marbl/Krona/wiki</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/843/structural-polymorphism-analysis-from-ngs-data</guid>
  <pubDate>Sat, 13 Jul 2013 17:12:47 -0500</pubDate>
  <link></link>
  <title><![CDATA[Structural polymorphism analysis from NGS data]]></title>
  <description><![CDATA[
<p>The LabEx BASC (Biodiversity, Agroecosystems, Society, Climate), a network of 13 laboratories of the Paris-Saclay Scientific Cluster, is seeking a bioinformatician to analyze Next Generation Sequencing (NGS) data analysis. In the context of a flagship project aiming at understanding and improving the adaptive capacity of agroecosystems it will be critical to establish a link between sequence variation, functional variation, gene/protein expression and phenotypic adaptation.</p>

<p>The successful candidate will be in charge of the detection of polymorphisms including structural variants, of the comparison of multiple and diverse genomes of a same species and of the construction of pan- and core-genomes. These challenging tasks will require bioinformatics developments and implementation of methods for accommodating the high level of repetitiveness of complex genomes. The tools will be integrated into pipelines and made available to end-users through the Galaxy platform. The bioinformatician will therefore also have to provide researchers with advices on their experimental designs in order to ensure compliance of produced datasets with pipelines requirements. He/she will be hosted by a bioinformatics/informatics team (7 people) (http://moulon.inra.fr/index.php/fr/equipestransversales/atelier-de-bioinformatique) which has computational facilities and expertise in NGS data analysis, and will benefit as well from national and international collaborative networks (Aplibio http://www.renabi.fr/platforms/aplibio/, Transplant http://transplantdb.eu, AMAIZING http://www.amaizing.fr/).</p>

<p>The position requires a doctoral degree (PhD) in bioinformatics with strong expertise in script writing (Python/Perl) and pipeline development. </p>

<p>Applicants should send a CV and the names of 2 referees willing to provide a letter of recommendation to joets@moulon.inra.fr.</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32420/fastq-format</guid>
	<pubDate>Wed, 03 May 2017 04:23:32 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32420/fastq-format</link>
	<title><![CDATA[Fastq format]]></title>
	<description><![CDATA[<p><strong>FASTQ format</strong>&nbsp;is a text-based&nbsp;<a href="https://en.wikipedia.org/wiki/File_format" title="File format">format</a>&nbsp;for storing both a biological sequence (usually&nbsp;<a href="https://en.wikipedia.org/wiki/Nucleotide_sequence" title="Nucleotide sequence">nucleotide sequence</a>) and its corresponding quality scores. Both the sequence letter and quality score are each encoded with a single&nbsp;<a href="https://en.wikipedia.org/wiki/ASCII" title="ASCII">ASCII</a>&nbsp;character for brevity.</p>
<p>It was originally developed at the&nbsp;<a href="https://en.wikipedia.org/wiki/Wellcome_Trust_Sanger_Institute" title="Wellcome Trust Sanger Institute">Wellcome Trust Sanger Institute</a>&nbsp;to bundle a&nbsp;<a href="https://en.wikipedia.org/wiki/FASTA_format" title="FASTA format">FASTA</a>&nbsp;sequence and its quality data, but has recently become the&nbsp;<em>de facto</em>&nbsp;standard for storing the output of high-throughput sequencing instruments such as the&nbsp;<a href="https://en.wikipedia.org/wiki/Illumina_(company)" title="Illumina (company)">Illumina</a>&nbsp;Genome Analyzer.<sup id="cite_ref-Cock2009_1-0"><a href="https://en.wikipedia.org/wiki/FASTQ_format#cite_note-Cock2009-1">[1]</a></sup></p><p>Address of the bookmark: <a href="https://en.wikipedia.org/wiki/FASTQ_format" rel="nofollow">https://en.wikipedia.org/wiki/FASTQ_format</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/2336/3rd-annual-next-generation-sequencing-asia-congress-2013-at-singapore-singapore</guid>
  <pubDate>Wed, 14 Aug 2013 09:55:04 -0500</pubDate>
  <link></link>
  <title><![CDATA[3rd Annual Next Generation Sequencing Asia Congress 2013 at Singapore, Singapore]]></title>
  <description><![CDATA[
<p>The 3rd Annual Next Generation Sequencing Asia Congress is to be held on the 22nd and 23rd of October 2013 in Singapore. Over the 2 days, the conference will provide an overview of the current options of next-generation sequencing platforms, technologies, applications and the newest computational tools for the analysis of next-generation sequencing data and analytical genomics as well as overcoming data management problems. The event will attract over 200 senior-level decision makers working in areas such as next generation sequencing, analytical genomics, computational biology, oncology, RNA profiling, molecular genomics, biomarkers, bioinformatics &amp; data management and clinical &amp; diagnostics development.</p>

<p>Dated : 22 Nov 2013 -23 Nov 2013</p>

<p>http://www.ngsasia-congress.com/</p>
]]></description>
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