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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/34543?offset=140</link>
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	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36618/lamsa-fast-split-read-alignment-with-long-approximate-matches</guid>
	<pubDate>Tue, 15 May 2018 04:44:42 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36618/lamsa-fast-split-read-alignment-with-long-approximate-matches</link>
	<title><![CDATA[LAMSA: fast split read alignment with long approximate matches]]></title>
	<description><![CDATA[LAMSA (Long Approximate Matches-based Split Aligner) is a novel split alignment approach with faster speed and good ability of handling SV events. It is well-suited to align long reads (over thousands of base-pairs).

LAMSA takes takes the advantage of the rareness of SVs to implement a specifically designed two-step strategy. That is, LAMSA initially splits the read into relatively long fragments and co-linearly align them to solve the small variations or sequencing errors, and mitigate the effect of repeats. The alignments of the fragments are then used for implementing a sparse dynamic programming (SDP)-based split alignment approach to handle the large or non-co-linear variants.

We benchmarked LAMSA with simulated and real datasets having various read lengths and sequencing error rates, the results demonstrate that it is substantially faster than the state-of-the-art long read aligners; mean-while, it also has good ability to handle various categories of SVs.

LAMSA is open source and free for non-commercial use.

LAMSA is mainly designed by Bo Liu &amp; Yan Gao and developed by Yan Gao in Center for Bioinformatics, Harbin Institute of Technology, China.<p>Address of the bookmark: <a href="https://github.com/hitbc/LAMSA" rel="nofollow">https://github.com/hitbc/LAMSA</a></p>]]></description>
	<dc:creator>Jit</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/40217/shouji-a-fast-and-efficient-pre-alignment-filter-for-sequence-alignment</guid>
	<pubDate>Mon, 04 Nov 2019 07:09:45 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40217/shouji-a-fast-and-efficient-pre-alignment-filter-for-sequence-alignment</link>
	<title><![CDATA[Shouji: a fast and efficient pre-alignment filter for sequence alignment]]></title>
	<description><![CDATA[<p>The ability to generate massive amounts of sequencing data continues to overwhelm the processing capacity of existing algorithms and compute infrastructures. In this work, we explore the use of hardware/software co-design and hardware acceleration to significantly reduce the execution time of short sequence alignment, a crucial step in analyzing sequenced genomes.</p>
<p>&nbsp;<img src="https://github.com/BilkentCompGen/Shoji/raw/master/Figure1-GitHub.png" alt="image" style="border: 0px;"></p>
<p>We introduce Shouji, a highly parallel and accurate pre-alignment filter that remarkably reduces the need for computationally-costly dynamic programming algorithms. The first key idea of our proposed pre-alignment filter is to provide high filtering accuracy by correctly detecting all common subsequences shared between two given sequences. The second key idea is to design a hardware accelerator design that adopts modern FPGA (field-programmable gate array) architectures to further boost the performance of our algorithm.</p>
<p>More at <a href="https://github.com/CMU-SAFARI/Shouji">https://github.com/CMU-SAFARI/Shouji</a></p><p>Address of the bookmark: <a href="https://github.com/CMU-SAFARI/Shouji" rel="nofollow">https://github.com/CMU-SAFARI/Shouji</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42405/caretta-%E2%80%93-a-multiple-protein-structure-alignment-and-feature-extraction-suite</guid>
	<pubDate>Fri, 18 Dec 2020 02:09:44 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42405/caretta-%E2%80%93-a-multiple-protein-structure-alignment-and-feature-extraction-suite</link>
	<title><![CDATA[Caretta – A multiple protein structure alignment and feature extraction suite]]></title>
	<description><![CDATA[<h3>Caretta &ndash;&nbsp;a multiple protein structure alignment and feature extraction suite</h3>
<p><span>Caretta, a multiple structure alignment suite meant for homologous but sequentially divergent protein families which consistently returns accurate alignments with a higher coverage than current state-of-the-art tools. Caretta is available as a GUI and command-line application and additionally outputs an aligned structure feature matrix for a given set of input structures, which can readily be used in downstream steps for supervised or unsupervised machine learning.&nbsp;</span></p><p>Address of the bookmark: <a href="http://www.bioinformatics.nl/caretta/" rel="nofollow">http://www.bioinformatics.nl/caretta/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/file/view/989/bioinformatics-approach-to-boar-taint</guid>
	<pubDate>Wed, 17 Jul 2013 15:50:37 -0500</pubDate>
	<link>https://bioinformaticsonline.com/file/view/989/bioinformatics-approach-to-boar-taint</link>
	<title><![CDATA[Bioinformatics approach to Boar Taint]]></title>
	<description><![CDATA[<p><span>Meat products obtained from intact male pigs often produce offensive smell or odour which is recognized as a complex genetic trait called boar taint.Androstenone and Skatole&nbsp;in the fat primarily cause boar taint. Metabolism of androstenone and sex steroids share a common pathway which makes removal of boar taint a very challenging task. Castration is a traditional solution to remove boar taint but it also results in bad quality of meat due to low level of steroids which is objectionable to many consumers. Detected functional variant(s) underlying boar taint compounds can be used as genetic markers in selection of male pigs with reduced boar taint levels. Resequencing of a total of 47 samples belong to Norwegian Landrace (NL) and Duroc (D) pigs with varied boar taint levels were done in Illumina HiSeq2000 to &gt;10X average coverage. Short reads generated from these samples mapped to&nbsp;<em>Sus Scrofa</em>&nbsp;version 10.2 reference assembly using Bowtie2. Alignment file then used for calling SNPs and InDels inside previousy identified QTL regions on SSC5,13, and 7 with the aid of FreeBayes , a variant caller tool. A final list of SNPs was prepared after filtering SNPs on the basis of SNP quality, coverage of SNP allele, functional and structural annotation, and repeats, etc. Selected SNPs will be genotyped in sample population for validation and then used for constructing SNPs haplotypes in close linkage disequilibrium with QTLs and fine mapping of QTLs through association mapping of genotyped SNPs.</span><span>&nbsp;</span></p><p><span>&nbsp;</span></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
	<enclosure url="https://bioinformaticsonline.com/file/download/989" length="19688" type="image/jpeg" />
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/2518/genome-browsers</guid>
	<pubDate>Fri, 16 Aug 2013 19:04:47 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/2518/genome-browsers</link>
	<title><![CDATA[Genome Browsers]]></title>
	<description><![CDATA[<p>Genome Browser is the platform/database used for searching and retreiving sequences and annotation of genomes belong to various eukaryotes, prokaryotes, etc.</p><p>Following are the weblink for different available browsers:</p><p><a href="http://www.ensembl.org/index.html">http://www.ensembl.org/index.html</a></p><p><a href="http://ensemblgenomes.org/">http://ensemblgenomes.org/</a></p><p><a href="http://genome.ucsc.edu/">http://genome.ucsc.edu/</a></p><p><a href="http://www.ncbi.nlm.nih.gov/genome">http://www.ncbi.nlm.nih.gov/genome</a></p><p><a href="http://www.ebi.ac.uk/genomes/">http://www.ebi.ac.uk/genomes/</a></p><p><a href="http://flybase.org/">http://flybase.org/</a></p><p><a href="http://cmr.jcvi.org/tigr-scripts/CMR/CmrHomePage.cgi">http://cmr.jcvi.org/tigr-scripts/CMR/CmrHomePage.cgi</a></p><p><a href="http://www.sanger.ac.uk/resources/databases/">http://www.sanger.ac.uk/resources/databases/</a></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/4297/how-genes-are-regulated-transcription-factors</guid>
	<pubDate>Thu, 05 Sep 2013 16:54:19 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/4297/how-genes-are-regulated-transcription-factors</link>
	<title><![CDATA[How Genes are Regulated: Transcription Factors]]></title>
	<description><![CDATA[<iframe src="http://player.vimeo.com/video/30034882?byline=0" width="" height="" frameborder="0" webkitAllowFullScreen allowFullScreen></iframe>Each cell in our body inherits the same master copy of DNA, but different cell types use it differently. Transcription Factors help influence which genes are used in which cell. Understanding how these dynamic proteins physically interact with DNA allows us to better understand and model their binding to DNA and their regulation of gene expression.  Scientific Direction by the Wasserman Lab at the University of British Columbia: http://www.cmmt.ubc.ca/research/investigators/wasserman/lab  Animation and editing by Blair Lyons of Stroma Studios: http://www.stromastudios.com]]></description>
	
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/4943/molecular-genetics-lecture</guid>
	<pubDate>Fri, 27 Sep 2013 04:24:45 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/4943/molecular-genetics-lecture</link>
	<title><![CDATA[Molecular Genetics Lecture]]></title>
	<description><![CDATA[<p><span>"Robert Sapolsky makes interdisciplinary connections between behavioral biology and molecular genetic influences. He relates protein synthesis and point mutations to microevolutionary change, and discusses conflicting theories of gradualism and punctuated equilibrium and the influence of epigenetics on development theories."&nbsp;</span></p>
<p><span>"<span><strong>Robert Sapolsky</strong> is an American neuroendocrinologist, professor of biology, neuroscience, and neurosurgery at Stanford University, researcher and author" ----Wikipedia</span></span></p><p>Address of the bookmark: <a href="http://www.youtube.com/watch?v=_dRXA1_e30o" rel="nofollow">http://www.youtube.com/watch?v=_dRXA1_e30o</a></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/10664/dna-replication-process-3d-animation</guid>
	<pubDate>Sat, 10 May 2014 04:41:22 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/10664/dna-replication-process-3d-animation</link>
	<title><![CDATA[DNA Replication Process [3D Animation]]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/27TxKoFU2Nw" frameborder="0" allowfullscreen></iframe>See an organised list of all the animations: http://doctorprodigious.wordpress.com/hd-animations/]]></description>
	
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