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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/42963?offset=20</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41916/truvari-structural-variant-comparison-tool-for-vcfs</guid>
	<pubDate>Tue, 30 Jun 2020 21:30:44 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41916/truvari-structural-variant-comparison-tool-for-vcfs</link>
	<title><![CDATA[truvari: Structural variant comparison tool for VCFs]]></title>
	<description><![CDATA[<p>Structural variant comparison tool for VCFs</p>
<p>Given benchmark and comparsion sets of SVs, calculate the recall, precision, and f-measure.</p>
<p><a href="https://github.com/spiralgenetics/www.spiralgenetics.com">Spiral Genetics</a></p>
<p><a href="https://docs.google.com/presentation/d/17mvC1XOpOm7khAbZwF3SgtG2Rl4M9Mro37yF2nN7GhE/edit">Motivation</a></p><p>Address of the bookmark: <a href="https://github.com/spiralgenetics/truvari" rel="nofollow">https://github.com/spiralgenetics/truvari</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44501/minda-a-tool-for-evaluating-structural-variant-sv-callers</guid>
	<pubDate>Sun, 31 Mar 2024 02:43:50 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44501/minda-a-tool-for-evaluating-structural-variant-sv-callers</link>
	<title><![CDATA[Minda: a tool for evaluating structural variant (SV) callers]]></title>
	<description><![CDATA[<p dir="auto">Minda is a tool for evaluating structural variant (SV) callers that</p>
<ul dir="auto">
<li>standardizes VCF records for compatibility with both germline and somatic SV callers,</li>
<li>benchmarks against a single VCF input file, or</li>
<li>benchmarks against an ensemble call set created from multiple VCF input files.</li>
</ul><p>Address of the bookmark: <a href="https://github.com/KolmogorovLab/minda" rel="nofollow">https://github.com/KolmogorovLab/minda</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37666/ensembl-variation-calculated-variant-consequences</guid>
	<pubDate>Sun, 09 Sep 2018 19:17:37 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37666/ensembl-variation-calculated-variant-consequences</link>
	<title><![CDATA[Ensembl Variation - Calculated variant consequences]]></title>
	<description><![CDATA[<p><span>For each variant that is mapped to the reference genome, we identify all overlapping Ensembl transcripts. We then use a rule-based approach to predict the effects that each allele of the variant may have on each transcript. The set of consequence terms, defined by the&nbsp;</span><a href="http://www.sequenceontology.org/">Sequence Ontology</a><span>&nbsp;(SO), that can be currently assigned to each combination of an allele and a transcript is shown in the table below. Note that each allele of each variant may have a different effect in different transcripts.</span></p>
<p><span><img src="https://www.ensembl.org/info/genome/variation/prediction/consequences.jpg" width="1280" height="570" alt="image" style="border: 0px;"></span></p><p>Address of the bookmark: <a href="https://www.ensembl.org/info/genome/variation/prediction/predicted_data.html" rel="nofollow">https://www.ensembl.org/info/genome/variation/prediction/predicted_data.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/44616/basics-of-blast-programs</guid>
	<pubDate>Fri, 26 Jul 2024 06:04:26 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44616/basics-of-blast-programs</link>
	<title><![CDATA[Basics of BLAST Programs !]]></title>
	<description><![CDATA[<p>The Basic Local Alignment Search Tool (BLAST) is a powerful bioinformatics program used to compare an input sequence (such as DNA, RNA, or protein sequences) against a database of sequences to find regions of similarity. Developed by the National Center for Biotechnology Information (NCBI), BLAST is widely used for identifying species, finding functional and evolutionary relationships between sequences, and predicting the function of novel sequences.</p><p>Key Features of BLAST:<br />1. Sequence Comparison: BLAST searches for local alignments between the query sequence and sequences in a database. It identifies regions of similarity, which can help infer functional and evolutionary relationships.</p><p>2. Speed and Efficiency: BLAST uses heuristic algorithms, making it faster than exhaustive search methods, suitable for large-scale database searches.</p><p>3. Versatility: There are several versions of BLAST for different types of sequence comparisons:<br /> - blastn: Compares a nucleotide query sequence against a nucleotide sequence database.<br /> - blastp: Compares a protein query sequence against a protein sequence database.<br /> - blastx: Compares a nucleotide query sequence translated in all reading frames against a protein sequence database.<br /> - tblastn: Compares a protein query sequence against a nucleotide sequence database translated in all reading frames.<br /> - tblastx: Compares the six-frame translations of a nucleotide query sequence against the six-frame translations of a nucleotide sequence database.</p><p>4. Scoring and E-value: BLAST results are scored based on the quality and length of the alignments. The E-value (expect value) indicates the number of alignments one can expect to find by chance, with lower E-values representing more significant matches.</p><p>5. Output Formats: BLAST provides results in various formats, including plain text, HTML, XML, and JSON, making it adaptable for different types of analyses and integrations with other tools.</p><p>Applications of BLAST:<br />- Genomic Research: Identifying genes, understanding genetic diversity, and mapping genome sequences.<br />- Protein Function Prediction: Inferring the function of unknown proteins by comparing them to known protein sequences.<br />- Evolutionary Studies: Exploring evolutionary relationships between organisms by comparing their genetic material.<br />- Medical Research: Identifying pathogens, understanding disease mechanisms, and developing treatments by comparing sequences of interest.</p><p>Overall, BLAST is an essential tool in bioinformatics, offering a reliable and efficient way to analyze and interpret biological sequence data.</p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<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/44508/a-web-based-tool-for-sequence-alignment-statistics-and-innovative-visualization</guid>
	<pubDate>Thu, 04 Apr 2024 01:44:50 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44508/a-web-based-tool-for-sequence-alignment-statistics-and-innovative-visualization</link>
	<title><![CDATA[A web-based tool for sequence alignment statistics and innovative visualization]]></title>
	<description><![CDATA[<p>AlignStatPlot, a new R package and online tool that is well-documented and easy-to usefor MSA and post-MSA analysis. This tool performs both traditional and cutting-edge analy-ses on sequencing data and generates new visualisation methods for MSA results. Whencompared to currently available tools, AlignStatPlot provides a robust ability to handle andvisualise diversity data, while the online version will save time and encourage researchersto focus on explaining their findings. It is a simple tool that can be used in conjunction withpopulation genetics software (PDF) AlignStatPlot: An R package and online tool for robust sequence alignment statistics and innovative visualization of big data.</p><p>Address of the bookmark: <a href="https://bioinformatics.um6p.ma/AlignStatPlot/" rel="nofollow">https://bioinformatics.um6p.ma/AlignStatPlot/</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44527/alvis-a-tool-for-contig-and-read-alignment-visualisation-and-chimera-detection</guid>
	<pubDate>Wed, 08 May 2024 07:02:55 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44527/alvis-a-tool-for-contig-and-read-alignment-visualisation-and-chimera-detection</link>
	<title><![CDATA[Alvis: a tool for contig and read ALignment VISualisation and chimera detection]]></title>
	<description><![CDATA[<p><span>Alvis, a simple command line tool that can generate visualisations for a number of common alignment analysis tasks. Alvis is a fast and portable tool that accepts input in a variety of alignment formats and will output production ready vector images. Additionally, Alvis will highlight potentially chimeric reads or contigs, a common source of misassemblies.</span></p>
<p>More at&nbsp;https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-021-04056-0</p><p>Address of the bookmark: <a href="https://github.com/SR-Martin/alvis" rel="nofollow">https://github.com/SR-Martin/alvis</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43112/calling-variants-in-non-diploid-systems</guid>
	<pubDate>Sat, 26 Jun 2021 15:37:49 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43112/calling-variants-in-non-diploid-systems</link>
	<title><![CDATA[Calling variants in non-diploid systems]]></title>
	<description><![CDATA[<p><span>The main challenge associated with non-diploid variant calling is the difficulty in distinguishing between the sequencing noise (abundant in all NGS platforms) and true low frequency variants. Some of the early attempts to do this well have been accomplished on human mitochondrial&nbsp;</span><span>DNA</span><span>&nbsp;although the same approaches will work equally good on viral and bacterial genomes (</span><a href="https://training.galaxyproject.org/training-material/topics/variant-analysis/tutorials/non-dip/tutorial.html#Rebolledo-Jaramillo2014">Rebolledo-Jaramillo&nbsp;<em>et al.</em>&nbsp;2014</a><span>,&nbsp;</span><a href="https://training.galaxyproject.org/training-material/topics/variant-analysis/tutorials/non-dip/tutorial.html#Li2015">Li&nbsp;<em>et al.</em>&nbsp;2015</a><span>).</span></p><p>Address of the bookmark: <a href="https://training.galaxyproject.org/training-material/topics/variant-analysis/tutorials/non-dip/tutorial.html" rel="nofollow">https://training.galaxyproject.org/training-material/topics/variant-analysis/tutorials/non-dip/tutorial.html</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/2791/ncbi-psi-blast-tutorial</guid>
	<pubDate>Fri, 23 Aug 2013 02:25:02 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/2791/ncbi-psi-blast-tutorial</link>
	<title><![CDATA[NCBI PSI-BLAST Tutorial]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/T3kHEieyylk" frameborder="0" allowfullscreen></iframe>http:--www.biotechnology.jhu.edu-
Tutorial for PSI-BLAST, an extension of BLAST that uses matrix algebra. BLAST is a cornerstone bioinformatics tool at NCBI. BLAST is the
Basic Local Alignment Search tool and will protein and DNA sequences that
are related to a sequence that the user provides.]]></description>
	
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27216/yass-genomic-similarity-search-tool</guid>
	<pubDate>Mon, 02 May 2016 09:26:00 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27216/yass-genomic-similarity-search-tool</link>
	<title><![CDATA[YASS :: genomic similarity search tool]]></title>
	<description><![CDATA[<p>YASS is a genomic similarity search tool, for nucleic (DNA/RNA) sequences in fasta or plain text format (<em>it produces local pairwise alignments</em>). Like most of the heuristic pairwise local alignment tools for DNA sequences (FASTA, BLAST, PATTERNHUNTER, BLASTZ/LASTZ, LAST ...), YASS uses <em>seeds</em> to detect potential similarity regions, and then tries to extend them to local alignments. This genomic search tool uses <em>multiple transition constrained spaced seeds</em> that enable to search more fuzzy repeats, as non-coding DNA/RNA. Another simple, but interesting feature is that you can specify the seed pattern used in the search step (as provided for example by <a href="http://bioinfo.lifl.fr/yass/iedera.php">iedera</a>).</p>
<p>Main features of YASS are:</p>
<ul>
<li>multiple, possibly overlapping seeds and a new hit criterion to ensure a good sensitivity/selectivity trade-off</li>
<li>transition-constrained spaced seeds to improve sensitivity (transition mutations are purine to purine [<code>A&lt;-&gt;G</code>] or pyrimidine to pyrimidine [<code>C&lt;-&gt;T</code>])</li>
<li>using different scoring schemes with bit-score and E-value evaluated according to the sequence background frequencies</li>
<li>parameterizable <em>output</em> filter for low complexity repeats</li>
<li>reporting of various alignment statistical parameters (mutation bias along triplets, transition/transversion)</li>
<li>post-processing step to group gapped alignments</li>
</ul><p>Address of the bookmark: <a href="http://bioinfo.lifl.fr/yass/" rel="nofollow">http://bioinfo.lifl.fr/yass/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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