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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/43663?</link>
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	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43661/maftools</guid>
	<pubDate>Fri, 17 Dec 2021 03:18:28 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43661/maftools</link>
	<title><![CDATA[maftools]]></title>
	<description><![CDATA[<p>With advances in Cancer Genomics, <a href="https://docs.gdc.cancer.gov/Data/File_Formats/MAF_Format/">Mutation Annotation Format</a> (MAF) is being widely accepted and used to store somatic variants detected. <a href="http://cancergenome.nih.gov">The Cancer Genome Atlas</a> Project has sequenced over 30 different cancers with sample size of each cancer type being over 200. <a href="https://wiki.nci.nih.gov/display/TCGA/TCGA+MAF+Files">Resulting data</a> consisting of somatic variants are stored in the form of <a href="https://docs.gdc.cancer.gov/Data/File_Formats/MAF_Format/">Mutation Annotation Format</a>. This package attempts to summarize, analyze, annotate and visualize MAF files in an efficient manner from either TCGA sources or any in-house studies as long as the data is in MAF format.</p>
<p>https://www.bioconductor.org/packages/devel/bioc/vignettes/maftools/inst/doc/maftools.html</p><p>Address of the bookmark: <a href="https://github.com/PoisonAlien/maftools" rel="nofollow">https://github.com/PoisonAlien/maftools</a></p>]]></description>
	<dc:creator>Surabhi Chaudhary</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43094/pandoc-a-universal-document-converter</guid>
	<pubDate>Thu, 24 Jun 2021 01:33:47 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43094/pandoc-a-universal-document-converter</link>
	<title><![CDATA[Pandoc: a universal document converter]]></title>
	<description><![CDATA[<p>If you need to convert files from one markup format into another, pandoc is your swiss-army knife. Pandoc can convert almost all formats</p>
<p>https://pandoc.org/index.html</p><p>Address of the bookmark: <a href="https://pandoc.org/" rel="nofollow">https://pandoc.org/</a></p>]]></description>
	<dc:creator>Surabhi Chaudhary</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42472/maftools-summarize-analyze-and-visualize-maf-files</guid>
	<pubDate>Wed, 23 Dec 2020 05:29:33 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42472/maftools-summarize-analyze-and-visualize-maf-files</link>
	<title><![CDATA[maftools : Summarize, Analyze and Visualize MAF Files]]></title>
	<description><![CDATA[<p><span>With advances in Cancer Genomics,&nbsp;</span><a href="https://docs.gdc.cancer.gov/Data/File_Formats/MAF_Format/">Mutation Annotation Format</a><span>&nbsp;(MAF) is being widely accepted and used to store somatic variants detected.&nbsp;</span><a href="http://cancergenome.nih.gov/">The Cancer Genome Atlas</a><span>&nbsp;Project has sequenced over 30 different cancers with sample size of each cancer type being over 200.&nbsp;</span><a href="https://wiki.nci.nih.gov/display/TCGA/TCGA+MAF+Files">Resulting data</a><span>&nbsp;consisting of somatic variants are stored in the form of&nbsp;</span><a href="https://docs.gdc.cancer.gov/Data/File_Formats/MAF_Format/">Mutation Annotation Format</a><span>. This package attempts to summarize, analyze, annotate and visualize MAF files in an efficient manner from either TCGA sources or any in-house studies as long as the data is in MAF format.</span></p><p>Address of the bookmark: <a href="https://www.bioconductor.org/packages/release/bioc/vignettes/maftools/inst/doc/maftools.html" rel="nofollow">https://www.bioconductor.org/packages/release/bioc/vignettes/maftools/inst/doc/maftools.html</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30966/maftools</guid>
	<pubDate>Thu, 16 Feb 2017 11:16:01 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30966/maftools</link>
	<title><![CDATA[MafTools]]></title>
	<description><![CDATA[<p>maftools - An R package to summarize, analyze and visualize MAF files. <a href="https://github.com/PoisonAlien/maftools#introduction"></a>Introduction.</p>
<p>With advances in Cancer Genomics, Mutation Annotation Format (MAF) is being widley accepted and used to store variants detected. <a href="http://cancergenome.nih.gov">The Cancer Genome Atlas</a> Project has seqenced over 30 different cancers with sample size of each cancer type being over 200. The <a href="https://wiki.nci.nih.gov/display/TCGA/TCGA+MAF+Files">resulting data</a> consisting of genetic variants is stored in the form of <a href="https://wiki.nci.nih.gov/display/TCGA/Mutation+Annotation+Format+%28MAF%29+Specification">Mutation Annotation Format</a>. This package attempts to summarize, analyze, annotate and visualize MAF files in an efficient manner either from TCGA sources or any in-house studies as long as the data is in MAF format. Maftools can also handle ICGC Simple Somatic Mutation format.</p>
<p>maftools is on <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f449.png" alt=":point_right:" width="20" height="20" style="border: 0px;"> <a href="http://biorxiv.org/content/early/2016/05/11/052662">bioRxiv</a> <img src="https://assets-cdn.github.com/images/icons/emoji/bowtie.png" alt=":bowtie:" title=":bowtie:" width="20" height="20" style="border: 0px; text-align: absmiddle;"></p>
<p>Please cite the below if you find this tool useful for you.</p>
<p>Mayakonda, A. and H.P. Koeffler, Maftools: Efficient analysis, visualization and summarization of MAF files from large-scale cohort based cancer studies. bioRxiv, 2016. doi: <a href="http://dx.doi.org/10.1101/052662">http://dx.doi.org/10.1101/052662</a></p><p>Address of the bookmark: <a href="https://github.com/PoisonAlien/maftools" rel="nofollow">https://github.com/PoisonAlien/maftools</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<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/27461/maftools</guid>
	<pubDate>Sat, 21 May 2016 22:40:21 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27461/maftools</link>
	<title><![CDATA[mafTools]]></title>
	<description><![CDATA[<p><span>Bioinformatics tools for dealing with Multiple Alignment Format (MAF) files.</span></p><p>Address of the bookmark: <a href="https://github.com/dentearl/mafTools" rel="nofollow">https://github.com/dentearl/mafTools</a></p>]]></description>
	<dc:creator>Radha Agarkar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/34600/converting-blast-output-into-csv</guid>
	<pubDate>Mon, 11 Dec 2017 04:17:58 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/34600/converting-blast-output-into-csv</link>
	<title><![CDATA[Converting BLAST output into CSV]]></title>
	<description><![CDATA[<p>Suppose we wanted to do something with all this BLAST output. Generally, that&rsquo;s the case - you want to retrieve all matches, or do a reciprocal BLAST, or something.</p><p>As with most programs that run on UNIX, the text output is in some specific format. If the program is popular enough, there will be one or more parsers written for that format &ndash; these are just utilities written to help you retrieve whatever information you are interested in from the output.</p><p>Let&rsquo;s conclude this tutorial by converting the BLAST output in out.txt into a spreadsheet format, using a Python script.&nbsp;</p><p>First, we need to get the script. We&rsquo;ll do that using the &lsquo;git&rsquo; program:</p><div><div><pre>git clone <a href="https://github.com/ngs-docs/ngs-scripts.git">https://github.com/ngs-docs/ngs-scripts.git</a> /root/ngs-scripts
</pre></div></div><p>We&rsquo;ll discuss &lsquo;git&rsquo; more later; for now, just think of it as a way to get ahold of a particular set of files. In this case, we&rsquo;ve placed the files in /root/ngs-scripts/, and you&rsquo;re looking to run the script blast/blast-to-csv.py using Python:</p><div><div><pre>python /root/ngs-scripts/blast/blast-to-csv.py out.txt
</pre></div></div><p>This outputs a spread-sheet like list of names and e-values. To save this to a file, do:</p><div><div><pre>python /root/ngs-scripts/blast/blast-to-csv.py out.txt &gt; ~out.csv
</pre></div></div><p>If you have Excel installed, try double clicking on it.</p>]]></description>
	<dc:creator>Poonam Mahapatra</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32048/json</guid>
	<pubDate>Tue, 04 Apr 2017 08:02:39 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32048/json</link>
	<title><![CDATA[JSON]]></title>
	<description><![CDATA[<p><strong>JSON</strong>&nbsp;(JavaScript Object Notation) is a lightweight data-interchange format. It is easy for humans to read and write. It is easy for machines to parse and generate. It is based on a subset of the&nbsp;<a href="http://javascript.crockford.com/">JavaScript Programming Language</a>,&nbsp;<a href="http://www.ecma-international.org/publications/files/ecma-st/ECMA-262.pdf">Standard ECMA-262 3rd Edition - December 1999</a>. JSON is a text format that is completely language independent but uses conventions that are familiar to programmers of the C-family of languages, including C, C++, C#, Java, JavaScript, Perl, Python, and many others. These properties make JSON an ideal data-interchange language.</p>
<p>JSON is built on two structures:</p>
<ul>
<li>A collection of name/value pairs. In various languages, this is realized as an&nbsp;<em>object</em>, record, struct, dictionary, hash table, keyed list, or associative array.</li>
<li>An ordered list of values. In most languages, this is realized as an&nbsp;<em>array</em>, vector, list, or sequence.</li>
</ul>
<p>These are universal data structures. Virtually all modern programming languages support them in one form or another. It makes sense that a data format that is interchangeable with programming languages also be based on these structures.</p><p>Address of the bookmark: <a href="http://json.org/" rel="nofollow">http://json.org/</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</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/36624/convert-vcf-to-tab-deilimited-table</guid>
	<pubDate>Tue, 15 May 2018 07:39:08 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/36624/convert-vcf-to-tab-deilimited-table</link>
	<title><![CDATA[Convert VCF to tab-deilimited table]]></title>
	<description><![CDATA[
<p>Performed with GATK :</p>

<p>java -Xmx8g -jar GenomeAnalysisTK.jar \<br /> -T VariantsToTable \<br /> -R reference.fa \<br /> -V reference_genomes_GT.vcf \<br /> -F CHROM -F POS -F REF -F ALT -GF GT \<br /> -o reference_genomes_GT.table<br />multiple_sample.vcf should also be converted to multiple_sample_GT.table using this approach.</p>
]]></description>
	<dc:creator>Seema Singh</dc:creator>
</item>

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