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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/39307?offset=50</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32011/fools-guide</guid>
	<pubDate>Sun, 02 Apr 2017 14:31:18 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32011/fools-guide</link>
	<title><![CDATA[Fools guide]]></title>
	<description><![CDATA[<p><span>This website and accompaning documents are intended as a tool to help researchers dealing with non-model organisms acquire and process transcriptomic high-throughput sequencing data without having to learn extensive bioinformatics skills. It covers all steps from tissue collection, sample preparation and computer setup, through addressing biological questions with gene expression and SNP data.</span></p>
<p>http://sfg.stanford.edu/denovo.html</p>
<p>http://sfg.stanford.edu/sequencing.html</p>
<p>http://sfg.stanford.edu/BLAST.html</p>
<p>http://sfg.stanford.edu/denovo.html&nbsp;</p><p>Address of the bookmark: <a href="http://sfg.stanford.edu/guide.html" rel="nofollow">http://sfg.stanford.edu/guide.html</a></p>]]></description>
	<dc:creator>Poonam Mahapatra</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43943/bioinformatics-tutorial</guid>
	<pubDate>Mon, 22 Aug 2022 23:56:22 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43943/bioinformatics-tutorial</link>
	<title><![CDATA[Bioinformatics Tutorial !]]></title>
	<description><![CDATA[<p>This site aims to be a useful resource for bioinformatics beginners. Feel free to jump right in with the section most relevant to you, and if you're not sure, then the place to start is definitely Unix <p>Address of the bookmark: <a href="https://astrobiomike.github.io/" rel="nofollow">https://astrobiomike.github.io/</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31574/biostats-class-tutorial</guid>
	<pubDate>Thu, 16 Mar 2017 01:50:50 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31574/biostats-class-tutorial</link>
	<title><![CDATA[BioStats class tutorial]]></title>
	<description><![CDATA[<p>Nice biostat turorial by&nbsp;<strong>Ingo Ruczinski</strong></p><p>Address of the bookmark: <a href="http://www.biostat.jhsph.edu/~iruczins/teaching/" rel="nofollow">http://www.biostat.jhsph.edu/~iruczins/teaching/</a></p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37840/long-read-assembly-workshop</guid>
	<pubDate>Thu, 04 Oct 2018 17:23:18 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37840/long-read-assembly-workshop</link>
	<title><![CDATA[Long read assembly workshop !]]></title>
	<description><![CDATA[<p>This is a tutorial for a workshop on long-read (PacBio) genome assembly.</p>
<p>It demonstrates how to use long PacBio sequencing reads to assemble a bacterial genome, and includes additional steps for circularising, trimming, finding plasmids, and correcting the assembly with short-read Illumina data.</p>
<p>&nbsp;Please comment if you know any other long read addembly tutorial.</p><p>Address of the bookmark: <a href="http://sepsis-omics.github.io/tutorials/modules/cmdline_assembly_v2/" rel="nofollow">http://sepsis-omics.github.io/tutorials/modules/cmdline_assembly_v2/</a></p>]]></description>
	<dc:creator>Rahul Nayak</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/pages/view/2573/most-commonly-used-awk-by-bioinformatician</guid>
	<pubDate>Mon, 19 Aug 2013 01:12:38 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/2573/most-commonly-used-awk-by-bioinformatician</link>
	<title><![CDATA[Most Commonly used Awk by Bioinformatician]]></title>
	<description><![CDATA[<p style="text-align: center;">&nbsp;</p><p>Awk is a programming language that is specifically designed for quickly manipulating space delimited data. Although you can achieve all its functionality with Perl, awk is simpler in many practical cases.</p><p>Why awk? You can replace a pipeline of 'stuff | grep | sed | cut...' with a single call to awk. For a simple script, most of the timelag is in loading these apps into memory, and it's much faster to do it all with one. This is ideal for something like an openbox pipe menu where you want to generate something on the fly. You can use awk to make a neat one-liner for some quick job in the terminal, or build an awk section into a shell script. You can find a lot of online tutorials, but here I will only show a few examples which cover most of bioinformatician daily uses of awk.</p><p>choose rows where column 3 is larger than column 5:</p><p>awk '$3&gt;$5' input.txt &gt; output.txt</p><p>extract column 2,4,5:</p><p>awk '{print $2,$4,$5}' input.txt &gt; output.txt</p><p>awk 'BEGIN{OFS="\t"}{print $2,$4,$5}' input.txt</p><p>show rows between 20th and 80th:</p><p>awk 'NR&gt;=20&amp;&amp;NR&lt;=80' input.txt &gt; output.txt</p><p>calculate the average of column 2:</p><p>awk '{x+=$2}END{print x/NR}' input.txt</p><p>regex (egrep):</p><p>awk '/^test[0-9]+/' input.txt</p><p>calculate the sum of column 2 and 3 and put it at the end of a row or replace the first column:</p><p>awk '{print $0,$2+$3}' input.txt</p><p>awk '{$1=$2+$3;print}' input.txt</p><p>join two files on column 1:</p><p>awk 'BEGIN{while((getline&lt;"file1.txt")&gt;0)l[$1]=$0}$1 in l{print $0"\t"l[$1]}' file2.txt &gt; output.txt</p><p>count number of occurrence of column 2 (uniq -c):</p><p>awk '{l[$2]++}END{for (x in l) print x,l[x]}' input.txt</p><p>apply "uniq" on column 2, only printing the first occurrence (uniq):</p><p>awk '!($2 in l){print;l[$2]=1}' input.txt</p><p>count different words (wc):</p><p>awk '{for(i=1;i!=NF;++i)c[$i]++}END{for (x in c) print x,c[x]}' input.txt</p><p>deal with simple CSV:</p><p>awk -F, '{print $1,$2}'</p><p>substitution (sed is simpler in this case):</p><p>awk '{sub(/test/, "no", $0);print}' input.txt</p><p>&nbsp;</p><p>OK now here's where to read this stuff properly explained. roll</p><p>Two thorough tutorials:</p><p>http://www.gnu.org/software/gawk/manual/gawk.html</p><p>http://www.grymoire.com/Unix/Awk.html</p><p>A famous list of useful one-liners - though they're short, many are quite tricky:</p><p>http://www.pement.org/awk/awk1line.txt</p><p>And some nice explanations of those one-liners. After reading this you'll have a pretty good grasp!</p><p>http://www.catonmat.net/blog/awk-one-li &hellip; -part-one/</p><p>http://www.catonmat.net/blog/ten-awk-ti &hellip; -pitfalls/</p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/21703/coding-ground</guid>
	<pubDate>Tue, 17 Mar 2015 00:47:20 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/21703/coding-ground</link>
	<title><![CDATA[Coding Ground]]></title>
	<description><![CDATA[<p>Online coding group for most of the programming languages.</p>
<p>Code in almost all popular languages using Coding Ground.&nbsp;Edit, compile, execute and share your projects, 100% cloud.</p>
<p>http://www.tutorialspoint.com/codingground.htm</p><p>Address of the bookmark: <a href="http://www.tutorialspoint.com/codingground.htm" rel="nofollow">http://www.tutorialspoint.com/codingground.htm</a></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42672/introduction-to-bioinformatics-and-computational-biology</guid>
	<pubDate>Mon, 25 Jan 2021 01:32:30 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42672/introduction-to-bioinformatics-and-computational-biology</link>
	<title><![CDATA[Introduction to Bioinformatics and Computational Biology]]></title>
	<description><![CDATA[<p><span>This is the course material for STAT115/215 BIO/BST282 at Harvard University.</span></p>
<p>Xiaole Shirley Liu (lead instructor)<br>Joshua Starmer<br>Martin Hemberg<br>Ting Wang<br>Feng Yue</p>
<p>Ming Tang<br>Yang Liu<br>Jack Kang<br>Scarlett Ge<br>Jiazhen Rong<br>Phillip Nicol<br>Maartin De Vries</p>
<p>We thank many colleagues in the community, who helped Dr.&nbsp;Liu in prepare the STAT115/215 BIO/BST282 course over the years.&nbsp;</p><p>Address of the bookmark: <a href="https://liulab-dfci.github.io/bioinfo-combio/" rel="nofollow">https://liulab-dfci.github.io/bioinfo-combio/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/42814/bioinformatics-in-africa-part6-sudan</guid>
	<pubDate>Sat, 06 Feb 2021 21:20:59 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/42814/bioinformatics-in-africa-part6-sudan</link>
	<title><![CDATA[Bioinformatics in Africa: Part6 - Sudan]]></title>
	<description><![CDATA[<p>Commission&nbsp;for&nbsp;Biotechnology&nbsp;&amp;&nbsp;Genetic&nbsp;Engineering&nbsp;&shy;&nbsp;Khartoum: The&nbsp;Commission&nbsp;for&nbsp;Biotechnology&nbsp;and&nbsp;Genetic&nbsp;Engineering&nbsp;was&nbsp;established&nbsp;in&nbsp;9/2/1993&nbsp;as&nbsp; research&nbsp;unit.&nbsp;In&nbsp;addition&nbsp;to&nbsp;research&nbsp;activities&nbsp;it&nbsp;acts&nbsp;as&nbsp;focal&nbsp;point&nbsp;for&nbsp;the&nbsp;International&nbsp;Center&nbsp;for&nbsp; Biotechnology&nbsp;and&nbsp;Genetic&nbsp;Engineering. The&nbsp;commission&nbsp;conducts&nbsp;researches&nbsp;in&nbsp;order&nbsp;to&nbsp;play&nbsp;a&nbsp;part&nbsp;in&nbsp;solving&nbsp;economical,&nbsp;environmental,&nbsp; health&nbsp;and&nbsp;nutritional&nbsp;problems&nbsp;using&nbsp;modern&nbsp;research&nbsp;techniques&nbsp;with&nbsp;an&nbsp;emphasis&nbsp;on&nbsp;the&nbsp;applied&nbsp; researches&nbsp;in&nbsp;these&nbsp;areas. The&nbsp;laboratories&nbsp;were&nbsp;well&nbsp;furnished&nbsp;with&nbsp;the&nbsp;essential&nbsp;equipments&nbsp;and&nbsp;the&nbsp;catalyst&nbsp;infrastructure&nbsp;to&nbsp; facilitate&nbsp;emergence&nbsp;of&nbsp;a&nbsp;successful&nbsp;for&nbsp;research.&nbsp;The&nbsp;Commission&nbsp;equipped&nbsp;with&nbsp;a&nbsp;computer&nbsp;center&nbsp; and&nbsp;information&nbsp;to&nbsp;serve&nbsp;as&nbsp;informatics&nbsp;and&nbsp;Digital&nbsp;library.</p><p>Research&nbsp;Interest&nbsp;and&nbsp;Activities: 1. Plant&nbsp;Genetic&nbsp;Transformations<br />2. Molecular&nbsp;Population&nbsp;Genetics 3. Detection&nbsp;of&nbsp;human&nbsp;and&nbsp;Animals&nbsp;diseases 4. Breast&nbsp;Cancer&shy;specific&nbsp;protein&nbsp;marker 5. Phytochemical 6. Genomic&nbsp;map 7. Bioremediation 8. Tissue&nbsp;Culture.</p><p>Web&nbsp;site&nbsp;and&nbsp;links: www.geocity.cbge.com</p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43431/code-golf</guid>
	<pubDate>Wed, 06 Oct 2021 04:17:29 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43431/code-golf</link>
	<title><![CDATA[Code Golf]]></title>
	<description><![CDATA[<p>Code Golf is a game designed to let you show off your code-fu by solving problems in the least number of characters.</p>
<p>Since this is your first time here, I suggest starting with something simple like&nbsp;<a href="https://code.golf/fizz-buzz">Fizz Buzz</a>.</p><p>Address of the bookmark: <a href="https://code.golf/" rel="nofollow">https://code.golf/</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
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