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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/36512?offset=80</link>
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	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32855/maf2synteny</guid>
	<pubDate>Thu, 18 May 2017 05:31:30 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32855/maf2synteny</link>
	<title><![CDATA[maf2synteny]]></title>
	<description><![CDATA[<p>A tool for converting for recovering synteny blocks from multiple alignment (in MAF fromat)</p>
<p>This tool is a standalone version of Ragout module [<a href="http://fenderglass.github./Ragout">http://fenderglass.github./Ragout</a>]</p><p>Address of the bookmark: <a href="https://github.com/fenderglass/maf2synteny" rel="nofollow">https://github.com/fenderglass/maf2synteny</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43859/mumco-is-a-simple-bash-script-that-uses-whole-genome-alignment-information-provided-by-mummer-v4-to-detect-variants</guid>
	<pubDate>Wed, 27 Apr 2022 04:34:12 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43859/mumco-is-a-simple-bash-script-that-uses-whole-genome-alignment-information-provided-by-mummer-v4-to-detect-variants</link>
	<title><![CDATA[MUM&amp;Co is a simple bash script that uses Whole Genome Alignment information provided by MUMmer (v4) to detect variants.]]></title>
	<description><![CDATA[<p dir="auto">MUM&amp;Co is able to detect:<br>Deletions, insertions, tandem duplications and tandem contractions (&gt;=50bp &amp; &lt;=150kb)<br>Inversions (&gt;=1kb) and translocations (&gt;=10kb)</p><p>Address of the bookmark: <a href="https://github.com/SAMtoBAM/MUMandCo" rel="nofollow">https://github.com/SAMtoBAM/MUMandCo</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42963/davi-deep-learning-based-tool-for-alignment-and-single-nucleotide-variant-identification</guid>
	<pubDate>Tue, 16 Mar 2021 05:41:33 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42963/davi-deep-learning-based-tool-for-alignment-and-single-nucleotide-variant-identification</link>
	<title><![CDATA[DAVI: Deep learning-based tool for alignment and single nucleotide variant identification]]></title>
	<description><![CDATA[<p>DAVI consists of models for both global and local alignment and for variant calling. We have evaluated the performance of DAVI against existing state-of-the-art tool sets and found that its accuracy and performance is comparable to existing tools used for bench-marking. We further demonstrate that while existing tools are based on data generated from a specific sequencing technology, the models proposed in DAVI are generic and can be used across different NGS technologies as well as across different species</p>
<p>https://iopscience.iop.org/article/10.1088/2632-2153/ab7e19/pdf</p><p>Address of the bookmark: <a href="https://github.com/gguptaiitd/NEAT" rel="nofollow">https://github.com/gguptaiitd/NEAT</a></p>]]></description>
	<dc:creator>Jit</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/35400/zpicture-a-dynamic-blastz-alignment-visualization</guid>
	<pubDate>Tue, 30 Jan 2018 16:03:08 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35400/zpicture-a-dynamic-blastz-alignment-visualization</link>
	<title><![CDATA[zPicture: A dynamic blastz alignment visualization]]></title>
	<description><![CDATA[<p><span>zPicture is a dynamic alignment and&nbsp;</span><span>visualization</span><span>&nbsp;tool that is based on blastz alignment program utilized by PipMaker. zPicture alignments can be automatically submitted to rVista 2.0 to identify conserved transcription factor binding sites.</span></p><p>Address of the bookmark: <a href="https://zpicture.dcode.org/" rel="nofollow">https://zpicture.dcode.org/</a></p>]]></description>
	<dc:creator>Archana Malhotra</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/37198/understanding-blastn-output-format-6</guid>
	<pubDate>Wed, 27 Jun 2018 18:38:21 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/37198/understanding-blastn-output-format-6</link>
	<title><![CDATA[Understanding BLASTn output format 6 !]]></title>
	<description><![CDATA[<h3 id="sites-page-title-header" style="text-align: left;"><span>BLASTn output format 6</span></h3><div id="sites-canvas-main"><div id="sites-canvas-main-content"><div dir="ltr"><div><div><em>BLASTn</em> maps DNA against DNA, for example gene sequences against a reference genome<br /><br /><code><strong>blastn</strong>  -query <span>genes.ffn</span>  -subject <span>genome.fna</span>  -outfmt <strong>6</strong></code></div><h2>BLASTn tabular output format 6</h2>
<p><strong>Column headers:</strong><br /><code>qseqid sseqid pident length mismatch gapopen qstart qend sstart send evalue bitscore</code><br /></p>
<table border="1" cellspacing="0">
<tbody>
<tr>
<td> 1.</td>
<td> qseqid</td>
<td> query (e.g., gene) sequence id</td>
</tr>
<tr>
<td> 2.</td>
<td> sseqid</td>
<td> subject (e.g., reference genome) sequence id</td>
</tr>
<tr>
<td> 3.</td>
<td> pident</td>
<td> percentage of identical matches</td>
</tr>
<tr>
<td> 4.</td>
<td> length</td>
<td> alignment length</td>
</tr>
<tr>
<td> 5.</td>
<td> mismatch</td>
<td> number of mismatches</td>
</tr>
<tr>
<td> 6.</td>
<td> gapopen</td>
<td> number of gap openings</td>
</tr>
<tr>
<td> 7.</td>
<td> qstart</td>
<td> start of alignment in query</td>
</tr>
<tr>
<td> 8.</td>
<td> qend</td>
<td> end of alignment in query</td>
</tr>
<tr>
<td> 9.</td>
<td> sstart</td>
<td> start of alignment in subject</td>
</tr>
<tr>
<td> 10.</td>
<td> send</td>
<td> end of alignment in subject</td>
</tr>
<tr>
<td> 11.</td>
<td> evalue</td>
<td> <a href="http://www.metagenomics.wiki/tools/blast/evalue">expect value</a></td>
</tr>
<tr>
<td> 12.</td>
<td> bitscore</td>
<td> <a href="http://www.metagenomics.wiki/tools/blast/evalue"><strong>bit score</strong></a></td>
</tr>
</tbody>
</table>
<p><strong><br /></strong></p>
</div><h2><a name="TOC-Define-your-own-output-format" id="TOC-Define-your-own-output-format"></a>Define your own output format</h2><div><em>by adding the option -outfmt, as for example: </em><strong><br /></strong></div>
<p><code><strong>-outfmt</strong> <strong>"6</strong> <span>qseqid sseqid pident qlen length mismatch gapope evalue bitscore</span><strong>"</strong></code><br /><br /><em><strong>supported format specifiers are:</strong></em><br /><code>qseqid    </code>Query Seq-id<br /><code>qgi       </code>Query GI<br /><code>qacc      </code>Query accesion<br /><code>qaccver   </code>Query accesion.version<br /><code>qlen      </code>Query sequence length<br /><code>sseqid    </code>Subject Seq-id<br /><code>sallseqid </code>All subject Seq-id(s), separated by a ';'<br /><code>sgi       </code>Subject GI<br /><code>sallgi    </code>All subject GIs<br /><code>sacc      </code>Subject accession<br /><code>saccver   </code>Subject accession.version<br /><code>sallacc   </code>All subject accessions<br /><code>slen      </code>Subject sequence length<br /><code>qstart    </code>Start of alignment in query<br /><code>qend      </code>End of alignment in query<br /><code>sstart    </code>Start of alignment in subject<br /><code>send      </code>End of alignment in subject<br /><code>qseq      </code>Aligned part of query sequence<br /><code>sseq      </code>Aligned part of subject sequence<br /><code>evalue    </code>Expect value<br /><code>bitscore  </code>Bit score<br /><code>score     </code>Raw score<br /><code>length    </code>Alignment length<br /><code>pident    </code>Percentage of identical matches<br /><code>nident    </code>Number of identical matches<br /><code>mismatch  </code>Number of mismatches<br /><code>positive  </code>Number of positive-scoring matches<br /><code>gapopen   </code>Number of gap openings<br /><code>gaps      </code>Total number of gaps<br /><code>ppos      </code>Percentage of positive-scoring matches<br /><code>frames    </code>Query and subject frames separated by a '/'<br /><code>qframe    </code>Query frame<br /><code>sframe    </code>Subject frame<br /><code>btop      </code>Blast traceback operations (BTOP)<br /><code>staxids   </code>Subject Taxonomy ID(s), separated by a ';'<br /><code>sscinames </code>Subject Scientific Name(s), separated by a ';'<br /><code>scomnames </code>Subject Common Name(s), separated by a ';'<br /><code>sblastnames </code>Subject Blast Name(s), separated by a ';'   (in alphabetical order)<br /><code>sskingdoms  </code>Subject Super Kingdom(s), separated by a ';'     (in alphabetical order) <br /><code>stitle      </code>Subject Title<br /><code>salltitles  </code>All Subject Title(s), separated by a '&lt;&gt;'<br /><code>sstrand   </code>Subject Strand<br /><code>qcovs     </code>Query Coverage Per Subject<br /><code>qcovhsp   </code>Query Coverage Per HSP<br /><strong><br /><em>default values are:</em></strong><br /><code><code>-outfmt "</code>6 qseqid sseqid pident length mismatch gapopen qstart qend sstart send evalue bitscore"</code></p>
</div></div></div>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/37677/installing-blat-on-linux</guid>
	<pubDate>Tue, 11 Sep 2018 08:17:35 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/37677/installing-blat-on-linux</link>
	<title><![CDATA[Installing BLAT on Linux !]]></title>
	<description><![CDATA[<p><span>It's been a while since I last installed BLAT and when I went to the download directory at UCSC:&nbsp;</span><a href="http://users.soe.ucsc.edu/~kent/src/">http://users.soe.ucsc.edu/~kent/src/</a><span>&nbsp;I found that the latest blast is now version 35 and that the code to download was:&nbsp;</span><a href="http://users.soe.ucsc.edu/~kent/src/blatSrc35.zip">blatSrc35.zip</a><span>. However, you can also get pre-compiled binaries at:&nbsp;</span><a href="http://hgdownload.cse.ucsc.edu/admin/exe/">http://hgdownload.cse.ucsc.edu/admin/exe/</a><span>&nbsp;and that there was a linux x86_64 executable for my architecture available at:&nbsp;</span><a href="http://hgdownload.cse.ucsc.edu/admin/exe/linux.x86_64/blat/">http://hgdownload.cse.ucsc.edu/admin/exe/linux.x86_64/blat/</a><span>. Though YYMV, BLAT can be a little bit of a tricky beast to get going, so I decided to download the source code and compile that.</span><br /><br /><span>I will be compiling this code as 'root' as a system tool in&nbsp;</span><code>/usr/local/src</code><span>, so do not scream at me for that.</span><br /><br /><span>First I created an /usr/local/src/blat directory and I copied the blatSrc35.zip file into that.</span><br /><br /><span>Next I used</span></p><pre><code>unzip blatSrc35.zip</code></pre><p><span>to unpack the archive. This gives a directory blatSrc now move into that directory.</span></p><pre><code>#cd blatSrc</code></pre><p><span>before you begin read the README file that comes with the source code.</span><br /><br /><span>One thing about building blat is that you need to set the MACHTYPE variable so that the BLAT sources know what type of machine you are compiling the software on.</span><br /><br /><span>on most *nix machines, typing</span></p><pre><code>echo $MACHTYPE</code></pre><p><span>will return the machine architecture type.</span><br /><br /><span>On my CentOS 6 based system this gave:</span></p><pre><code>x86_64-redhat-linux-gnu</code></pre><p><span>However, what BLAT requires is the 'short value' (ie the first part of the MACHTYPE). To correct this, in the bash shell type (change this to the correct MACHTYPE for your system)</span></p><pre><code>MACHTYPE=x86_64
export MACHTYPE</code></pre><p><span>now running the command:</span></p><pre><code>echo $MACHTYPE</code></pre><p><span>should give the correct short form of the MACHTYPE:</span></p><pre><code>x86_64</code></pre><p><span>now create the directory lib/$MACHTYPE in the source tree. ie:</span></p><pre><code>mkdir lib/$MACHTYPE</code></pre><p><span>For my machine, lib/x86_64 already existed, so I did not have to do this, but this is not the case for all architectures.</span><br /><br /><span>The BLAT code assumes that you are compiling BLAT as a non-privileged (ie non-root) user. As a result, you must create the directory for the executables to go into:</span><br /><br /><span>mkdir ~/bin/$MACHTYPE</span><br /><br /><span>If you are installing as a normal user, edit your .bashrc to add the following (change the x86_64 to be your MACHTYPE):</span><br /><br /><span>export PATH=~/bin/x86_64::$PATH</span><br /><br /><span>For me, though, this was not good enough. I wanted the executables in /usr/local/bin where all my other code goes. As a result I did some hackery...</span><br /><br /><span>There is a master make template in the&nbsp;</span><code>inc</code><span>&nbsp;directory called&nbsp;</span><code>common.mk</code><span>&nbsp;and I edited this file with the command:</span><br /><br /><span>vi inc/common.mk</span><br /><br /><span>I replaced the line</span></p><pre><code>    BINDIR=${HOME}/bin/${MACHTYPE}</code></pre><p><span>with</span></p><pre><code>    BINDIR=/usr/local/bin</code></pre><p><span>saved and quit (as this is in my path, I do not need to do anything else)</span><br /><br /><span>All the preparation is now done and you can create the blat executables by going into the toplevel of the blat source tree (for me it was&nbsp;</span><code>/usr/local/src/blat/blatSrc</code><span>, but change to wherever you unpacked blat into).</span><br /><br /><span>Now simply run the command:</span></p><pre><code>make</code></pre><p><span>to compile the code.</span><br /><br /><span>Blat installed cleanly and the executables were all neatly placed in /usr/local/bin/x86_64, just like I wanted.</span><br /><br /><span>now simply running the command:</span></p><pre><code>blat</code></pre><p><span>on the command line gives me information on blat and sample usage.</span><br /><br /><span>Blat is installed and it's installed properly in my system code tree!!!</span></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42150/parallellastz-lastz-with-multi-threads-support</guid>
	<pubDate>Sat, 22 Aug 2020 05:58:40 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42150/parallellastz-lastz-with-multi-threads-support</link>
	<title><![CDATA[parallelLastz: Lastz with multi-threads support.]]></title>
	<description><![CDATA[<p>Running Lastz (<a href="https://github.com/lastz/lastz">https://github.com/lastz/lastz</a>) in parallel mode. This program is for single computer with multiple core processors.</p>
<p>When the query file format is fasta, you can specify many threads to process it. It can reduce run time linearly, and use almost equal memory as the original lastz program. This is useful when you lastz a big query file to a huge reference like human whole genome sequence.</p>
<p>The program is an extension on the original lastz program which was written by Bob Harris (the LASTZ guy).</p><p>Address of the bookmark: <a href="https://github.com/jnarayan81/parallelLastz" rel="nofollow">https://github.com/jnarayan81/parallelLastz</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44887/alfapang-alignment-free-algorithm-for-pangenome-graph-construction</guid>
	<pubDate>Thu, 28 Aug 2025 02:56:35 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44887/alfapang-alignment-free-algorithm-for-pangenome-graph-construction</link>
	<title><![CDATA[AlfaPang: alignment free algorithm for pangenome graph construction]]></title>
	<description><![CDATA[<p><span>AlfaPang constructs variation graphs, leveraging its alignment-free and reference-free approach, based solely on intrinsic sequence properties. This design allows AlfaPang's runtime and memory usage to scale linearly with the size of input sequences, enabling it to handle significantly larger genome sets compared to other methods.</span></p><p>Address of the bookmark: <a href="https://github.com/AdamCicherski/AlfaPang" rel="nofollow">https://github.com/AdamCicherski/AlfaPang</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27845/cnidaria-fast-reference-free-phylogenomic-clustering</guid>
	<pubDate>Thu, 16 Jun 2016 17:55:17 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27845/cnidaria-fast-reference-free-phylogenomic-clustering</link>
	<title><![CDATA[CNIDARIA: fast, reference-free phylogenomic clustering]]></title>
	<description><![CDATA[<p>Motivation: Identification of biological specimens is a major requirement for a range of applications. Reference-free methods analyse unprocessed sequencing data without relying on prior knowledge, but these do not scale to arbitrarily large genomes and arbitrarily large phylogenetic distances.</p>
<p>Results: We present Cnidaria, a practical tool for clustering genomic and transcriptomic data with no limitation on ge-nome size or phylogenetic distances. We successfully simultaneously clustered 169 genomic and transcriptomic datasets from 4 kingdoms, achieving 100% accuracy at supra-species level and 78% accuracy for species level.</p>
<p>Availability and Implementation: Cnidaria is written in C++ and Python and is available at http://www.ab.wur.nl/cnidaria.</p>
<p>Contact: Saulo Aflitos - sauloal@gmail.com</p>
<p>Supplementary information: Supplementary data are available at Bioinformatics online.</p><p>Address of the bookmark: <a href="https://github.com/sauloal/cnidaria/wiki" rel="nofollow">https://github.com/sauloal/cnidaria/wiki</a></p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
</item>

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