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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/37198?offset=30</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37545/ncbi-magic-blast</guid>
	<pubDate>Tue, 14 Aug 2018 18:11:11 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37545/ncbi-magic-blast</link>
	<title><![CDATA[NCBI Magic-BLAST]]></title>
	<description><![CDATA[<p>Magic-BLAST is a tool for mapping large next-generation RNA or DNA sequencing runs against a whole genome or transcriptome. Each alignment optimizes a composite score, taking into account simultaneously the two reads of a pair, and in case of RNA-seq, locating the candidate introns and adding up the score of all exons. This is very different from other versions of BLAST, where each exon is scored as a separate hit and read-pairing is ignored.</p>
<p>Magic-BLAST incorporates within the NCBI BLAST code framework ideas developed in the NCBI Magic pipeline, in particular hit extensions by local walk and jump&nbsp;<a href="http://www.ncbi.nlm.nih.gov/pubmed/26109056">(http://www.ncbi.nlm.nih.gov/pubmed/26109056)</a>, and recursive clipping of mismatches near the edges of the reads, which avoids accumulating artefactual mismatches near splice sites and is needed to distinguish short indels from substitutions near the edges.</p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="https://ncbi.github.io/magicblast/" rel="nofollow">https://ncbi.github.io/magicblast/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41482/magic-blast</guid>
	<pubDate>Fri, 20 Mar 2020 15:18:36 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41482/magic-blast</link>
	<title><![CDATA[Magic-BLAST]]></title>
	<description><![CDATA[<p>Magic-BLAST is a tool for mapping large next-generation RNA or DNA sequencing runs against a whole genome or transcriptome. Each alignment optimizes a composite score, taking into account simultaneously the two reads of a pair, and in case of RNA-seq, locating the candidate introns and adding up the score of all exons. This is very different from other versions of BLAST, where each exon is scored as a separate hit and read-pairing is ignored.</p><p>Address of the bookmark: <a href="https://ncbi.github.io/magicblast/" rel="nofollow">https://ncbi.github.io/magicblast/</a></p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/44515/cleaner-blast-databases-for-more-accurate-results</guid>
	<pubDate>Tue, 23 Apr 2024 01:23:08 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/44515/cleaner-blast-databases-for-more-accurate-results</link>
	<title><![CDATA[Cleaner BLAST Databases for More Accurate Results]]></title>
	<description><![CDATA[<p>Do you use&nbsp;<a href="https://blast.ncbi.nlm.nih.gov/Blast.cgi?utm_source=ncbi_insights&amp;utm_medium=referral&amp;utm_campaign=blast-cleaner-20240422">BLAST</a><span style="font-size: 12.8px; font-weight: normal;">&nbsp;to identify a sequence or the evolutionary scope of a gene? That can be challenging if contaminated and misclassified sequences are in the BLAST databases and show up in your search results. To address</span><span style="font-size: 12.8px; font-weight: normal;">&nbsp;this problem</span><span style="font-size: 12.8px; font-weight: normal;">, we now use the NCBI quality assurance tools listed below to systematically remove these misleading sequences from the default nucleotide (nt) and protein (nr) BLAST databases.</span><span style="font-size: 12.8px; font-weight: normal;">&nbsp;</span></p><div><ul>
<li><a href="https://github.com/ncbi/fcs">Foreign Contamination Screen tool for genome cross-species screening (FCS-GX)</a>&nbsp;detects contamination from foreign organisms in genomes and other sequences using the genome cross-species aligner (GX)&nbsp;</li>
<li><a href="https://ncbiinsights.ncbi.nlm.nih.gov/2022/05/27/ani-for-assembly-validation?utm_source=ncbi_insights&amp;utm_medium=referral&amp;utm_campaign=blast-cleaner-20240422">Average Nucleotide Identity (ANI)</a>&nbsp;evaluates the taxonomic classification of prokaryotic genome assemblies. Sequences from genomes marked up as &lsquo;unverified source organism&rsquo; are considered suspect and removed.&nbsp;</li>
</ul><p>Ref&nbsp;https://ncbiinsights.ncbi.nlm.nih.gov/2024/04/22/cleaner-blast-databases-more-accurate-results/</p></div>]]></description>
	<dc:creator>LEGE</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43985/visualise-blast-results</guid>
	<pubDate>Tue, 11 Oct 2022 03:15:10 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43985/visualise-blast-results</link>
	<title><![CDATA[Visualise blast results !]]></title>
	<description><![CDATA[<p>Kablammo helps you create interactive visualizations of BLAST results from your web browser. Find your most interesting alignments, list detailed parameters for each, and export a publication-ready vector image, all without installing any software.</p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="https://kablammo.wasmuthlab.org/" rel="nofollow">https://kablammo.wasmuthlab.org/</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38449/koala-keggs-internal-annotation-tool-for-k-number-assignment-of-kegg-genes-using-ssearch-computation</guid>
	<pubDate>Wed, 12 Dec 2018 09:16:55 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38449/koala-keggs-internal-annotation-tool-for-k-number-assignment-of-kegg-genes-using-ssearch-computation</link>
	<title><![CDATA[KOALA: KEGG&#039;s internal annotation tool for K number assignment of KEGG GENES using SSEARCH computation]]></title>
	<description><![CDATA[<p>KOALA (KEGG Orthology And Links Annotation) is KEGG's internal annotation tool for&nbsp;<a href="https://www.kegg.jp/kegg/ko.html">K number</a>&nbsp;assignment of KEGG GENES using SSEARCH computation. BlastKOALA and GhostKOALA assign K numbers to the user's sequence data by&nbsp;<a href="http://www.ncbi.nlm.nih.gov/blast/">BLAST</a>&nbsp;and&nbsp;<a href="http://www.bi.cs.titech.ac.jp/ghostx/">GHOSTX</a>&nbsp;searches, respectively, against a nonredundant set of KEGG GENES. Annotate Sequence in KEGG Mapper and Pathogen Checker in KEGG Pathogen are special interfaces to the BlastKOALA server and can be executed in an interactive mode. &nbsp;&nbsp; See&nbsp;<a href="https://www.kegg.jp/blastkoala/help_blastkoala.html" target="_blastkoala">Step-by-step Instructions</a>.</p>
<div>Reference: Kanehisa, M., Sato, Y., and Morishima, K. (2016) BlastKOALA and GhostKOALA: KEGG tools for functional characterization of genome and metagenome sequences. J. Mol. Biol. 428, 726-731. [<a href="http://www.ncbi.nlm.nih.gov/pubmed/26585406">pubmed</a>] [<a href="https://doi.org/10.1016/j.jmb.2015.11.006">pdf</a>]</div><p>Address of the bookmark: <a href="https://www.kegg.jp/blastkoala/" rel="nofollow">https://www.kegg.jp/blastkoala/</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29410/entrez-direct-e-utilities-on-the-unix-command-line</guid>
	<pubDate>Wed, 19 Oct 2016 08:06:24 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29410/entrez-direct-e-utilities-on-the-unix-command-line</link>
	<title><![CDATA[Entrez Direct: E-utilities on the UNIX Command Line]]></title>
	<description><![CDATA[<p>Entrez Direct (EDirect) is an advanced method for accessing the NCBI's suite of interconnected databases (publication, sequence, structure, gene, variation, expression, etc.) from a UNIX terminal window. Functions take search terms from command-line arguments. Individual operations are combined to build multi-step queries. Record retrieval and formatting normally complete the process.</p>
<p>EDirect also provides an argument-driven function that simplifies the extraction of data from document summaries or other results that are returned in structured XML format. This can eliminate the need for writing custom software to answer ad hoc questions. Queries can move seamlessly between EDirect commands and UNIX utilities or scripts to perform actions that cannot be accomplished entirely within Entrez.</p><p>Address of the bookmark: <a href="https://www.ncbi.nlm.nih.gov/books/NBK179288/" rel="nofollow">https://www.ncbi.nlm.nih.gov/books/NBK179288/</a></p>]]></description>
	<dc:creator>Anjana</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38004/vcfr-a-package-to-manipulate-and-visualize-vcf-data-in-r</guid>
	<pubDate>Thu, 25 Oct 2018 09:05:59 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38004/vcfr-a-package-to-manipulate-and-visualize-vcf-data-in-r</link>
	<title><![CDATA[vcfR:  a package to manipulate and visualize VCF data in R]]></title>
	<description><![CDATA[<p><span>VcfR is an R package intended to allow easy manipulation and visualization of variant call format (VCF) data. Functions are provided to rapidly read from and write to VCF files. Once VCF data is read into R a parser function extracts matrices from the VCF data for use with typical R functions. This information can then be used for quality control or other purposes. Additional functions provide visualization of genomic data. Once processing is complete data may be written to a VCF file or converted into other popular R objects (e.g., genlight, DNAbin). VcfR provides a link between VCF data and the R environment connecting familiar software with genomic data.</span></p><p>Address of the bookmark: <a href="https://github.com/knausb/vcfR" rel="nofollow">https://github.com/knausb/vcfR</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34490/collinearity-scripts-to-parse-and-analyse-mcscanx-collinearity-output</guid>
	<pubDate>Wed, 29 Nov 2017 16:47:54 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34490/collinearity-scripts-to-parse-and-analyse-mcscanx-collinearity-output</link>
	<title><![CDATA[collinearity: scripts to parse and analyse MCScanX collinearity output]]></title>
	<description><![CDATA[<p><span>scripts to parse and analyse MCScanX collinearity output</span></p><p>Address of the bookmark: <a href="https://github.com/reubwn/collinearity" rel="nofollow">https://github.com/reubwn/collinearity</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/2759/dynamic-programming-alignment</guid>
	<pubDate>Thu, 22 Aug 2013 09:38:28 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/2759/dynamic-programming-alignment</link>
	<title><![CDATA[Dynamic Programming Alignment]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/EWJnDMKBEv0" frameborder="0" allowfullscreen></iframe>lecture 9, Chem. C100, Spring 2013, UCLA]]></description>
	
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27333/satsuma-highly-sensitive-whole-genome-synteny-alignments</guid>
	<pubDate>Fri, 13 May 2016 05:25:26 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27333/satsuma-highly-sensitive-whole-genome-synteny-alignments</link>
	<title><![CDATA[SATSUMA : Highly sensitive whole-genome synteny alignments.]]></title>
	<description><![CDATA[<p>Satsuma is a whole-genome synteny alignment program. It takes two genomes, computes alignments, and then keeps only the parts that are orthologous, i.e. following the conserved order and orientation of features, such as protein coding genes, non-coding genes, or neutral sequences. Satsuma does not require any pre-processing, such as repeat masking, since it will automatically detect ambiguous mappings.<br> <br> Satsuma has parallelization built-in and is designed to run on multi-core architectures. The run-time for aligning two bird-size genomes (~1.2 Gb) is around two days on 24 CPUs. <br> <br> You can find the manual <a href="http://satsuma.sourceforge.net/manual.html">here</a>.<br> Download the latest source code from <a href="https://sourceforge.net/projects/satsuma/">here.</a><br> Stable versions can also be downloaded from the <a href="https://www.broadinstitute.org/science/programs/genome-biology/spines">Broad Institute's</a> web site.<br> <br> An incomplete list of questions and answers (yes, these have really been asked by our users! Please feel free to add your own by e-mailing us) is <a href="http://satsuma.sourceforge.net/faq.html">here</a>.<br> <br> If you use Satsuma in your research, please cite:<br> <a href="http://bioinformatics.oxfordjournals.org/content/26/9/1145.long">Grabherr, M. G., Russell, P., Meyer, M., Mauceli, E., Alf&ouml;ldi, J., Di Palma, F., &amp; Lindblad-Toh, K. (2010). Genome-wide synteny through highly sensitive sequence alignment: Satsuma. Bioinformatics, 26(9), 1145-51</a>.</p>
<p><strong>Tutorial at http://evomics.org/learning/genomics/satsuma/</strong></p><p>Address of the bookmark: <a href="http://satsuma.sourceforge.net/" rel="nofollow">http://satsuma.sourceforge.net/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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