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	<title><![CDATA[BOL: Related items]]></title>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/21312/r-for-microsoft-excel</guid>
	<pubDate>Wed, 18 Feb 2015 00:43:27 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/21312/r-for-microsoft-excel</link>
	<title><![CDATA[R for Microsoft Excel]]></title>
	<description><![CDATA[<div><p>If you currently use a spreadsheet like Microsoft Excel for data analysis, you might be interested in taking a look at this <a href="https://districtdatalabs.silvrback.com/intro-to-r-for-microsoft-excel-users" target="_blank">tutorial on how to transition from Excel to R</a>&nbsp;by Tony Ojeda. The tutorial explains how to use R functions in place of Excel formulas, including tools like =AVERAGE and =VLOOKUP. For the most part, it uses modern R packages to keep the R code clear and concise.</p><p>You'll likely still be using Excel as a data source, though, so you'll also want to check out this <a href="http://www.milanor.net/blog/?p=779" target="_blank">guide to importing data from Excel to R</a> from MilanoR.</p></div><p>Reference http://www.r-bloggers.com/an-r-tutorial-for-microsoft-excel-users/</p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/21444/a-guide-for-complete-r-beginners-installing-r-packages</guid>
	<pubDate>Tue, 24 Feb 2015 20:23:34 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/21444/a-guide-for-complete-r-beginners-installing-r-packages</link>
	<title><![CDATA[A guide for complete R beginners :- Installing R packages]]></title>
	<description><![CDATA[<p>Part of the reason R has become so popular is the vast array of packages available at the <a href="http://cran.r-project.org/" target="_blank">cran</a> and <a href="http://www.bioconductor.org/" target="_blank">bioconductor</a> repositories. In the last few years, the number of packages has grown <a href="http://blog.revolutionanalytics.com/2010/09/what-can-other-languages-learn-from-r.html" target="_blank">exponentially</a>!</p><p>This is a short post giving steps on how to actually install R packages. Let&rsquo;s suppose you want to install the <a href="http://had.co.nz/ggplot2/" target="_blank">ggplot2</a> package. Well nothing could be easier. We just fire up an R shell and type:<br /><code><br />&gt; install.packages("ggplot2")</code></p><p>In theory the package should just install, however:</p><ul>
<li>if you are using Linux and don&rsquo;t have root access, this command won&rsquo;t work.</li>
<li>you will be asked to select your local mirror, i.e. which server should you use to download the package.</li>
</ul><h4>Installing packages without root access</h4><p>First, you need to designate a directory where you will store the downloaded packages. On my machine, I use the directory <code>/data/Rpackages/</code> After creating a package directory, to install a package we use the command:<br /><code><br />&gt; install.packages("ggplot2"</code><code>, lib="/data/Rpackages/")<br />&gt; library(ggplot2, lib.loc="/data/Rpackages/")<br /></code></p><p>It&rsquo;s a bit of a pain having to type <code>/data/Rpackages/</code> all the time. To avoid this burden,&nbsp; we create a file <code>.Renviron</code> in our home area, and add the line <code>R_LIBS=/data/Rpackages/</code> to it. This means that whenever you start R, the directory <code>/data/Rpackages/</code> is added to the list of places to look for R packages and so:</p><p><code>&gt; install.packages("ggplot2"</code><code>)<br />&gt; library(ggplot2)</code></p><p>just works!</p><h4>Setting the repository</h4><p>Every time you install a R package, you are asked which repository R should use. To set the repository and avoid having to specify this at every package install, simply:</p><ul>
<li>create a file <code>.Rprofile</code> in your home area.</li>
<li>Add the following piece of code to it:</li>
</ul><p><code><br />cat(".Rprofile: Setting UK repositoryn")<br />r = getOption("repos") # hard code the UK repo for CRAN<br />r["CRAN"] = "http://cran.uk.r-project.org"<br />options(repos = r)<br />rm(r)<br /></code></p><p>I found this tip in a stackoverflow <a href="http://stackoverflow.com/questions/1189759/expert-r-users-whats-in-your-rprofile/1189826#1189826" target="_blank">answer </a>.</p>]]></description>
	<dc:creator>Archana Malhotra</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/23516/visual-machine-learning</guid>
	<pubDate>Wed, 29 Jul 2015 04:29:13 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/23516/visual-machine-learning</link>
	<title><![CDATA[Visual machine learning !!!]]></title>
	<description><![CDATA[<p>In machine learning, computers apply <strong>statistical learning</strong> techniques to automatically identify patterns in data. These techniques can be used to make highly accurate predictions.</p>
<p>More at http://www.r2d3.us/visual-intro-to-machine-learning-part-1/</p><p>Address of the bookmark: <a href="http://www.r2d3.us/visual-intro-to-machine-learning-part-1/" rel="nofollow">http://www.r2d3.us/visual-intro-to-machine-learning-part-1/</a></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26426/genome-browser-gbrowse</guid>
	<pubDate>Fri, 19 Feb 2016 09:22:43 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26426/genome-browser-gbrowse</link>
	<title><![CDATA[Genome Browser : GBrowse]]></title>
	<description><![CDATA[<p>Generic Genome Browser Version 2: A Tutorial for Administrators</p>
<p>This is an extensive tutorial to take you through the main features and gotchas of configuring GBrowse as a server. This tutorial assumes that you have successfully set up Perl, GD, BioPerl and the other GBrowse dependencies. If you haven't, please see the <a href="http://gmod.org/wiki/GBrowse_2.0_HOWTO">GBrowse HOWTO</a> During most of the tutorial, we will be using the "in-memory" GBrowse database (no relational database required!) Later we will show how to set up a genome size database using the berkeleydb and MySQL adaptors.</p>
<p>More at http://elp.ucdavis.edu/tutorial/tutorial.html</p><p>Address of the bookmark: <a href="http://elp.ucdavis.edu/tutorial/tutorial.html" rel="nofollow">http://elp.ucdavis.edu/tutorial/tutorial.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32184/metagenomics-assembly-workshop</guid>
	<pubDate>Tue, 18 Apr 2017 04:28:19 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32184/metagenomics-assembly-workshop</link>
	<title><![CDATA[Metagenomics assembly workshop !!]]></title>
	<description><![CDATA[<div>
<div>
<div id="welcome-to-metagenomics-workshop">
<p>Welcome to the one-day metagenomics assembly workshop. This tutorial will guide you through the typical steps of metagenome assembly and binning.</p>
<div>
<ul>
<li><a href="http://denbi-metagenomics-workshop.readthedocs.io/en/latest/data.html">The Tutorial Data Set</a></li>
<li><a href="http://denbi-metagenomics-workshop.readthedocs.io/en/latest/qc/index.html">FastQC Quality Control</a></li>
<li><a href="http://denbi-metagenomics-workshop.readthedocs.io/en/latest/assembly/index.html">Assembly</a>
<ul>
<li><a href="http://denbi-metagenomics-workshop.readthedocs.io/en/latest/assembly/velvet.html">Velvet Assembly</a></li>
<li><a href="http://denbi-metagenomics-workshop.readthedocs.io/en/latest/assembly/megahit.html">MEGAHIT Assembly</a></li>
<li><a href="http://denbi-metagenomics-workshop.readthedocs.io/en/latest/assembly/idba_ud.html">IDBA-UD Assembly</a></li>
<li><a href="http://denbi-metagenomics-workshop.readthedocs.io/en/latest/assembly/ray.html">Ray Assembly</a></li>
</ul>
</li>
<li><a href="http://denbi-metagenomics-workshop.readthedocs.io/en/latest/geneprediction/index.html">Gene Prediction</a></li>
<li><a href="http://denbi-metagenomics-workshop.readthedocs.io/en/latest/evaluation/index.html">Assembly Evaluation</a>
<ul>
<li><a href="http://denbi-metagenomics-workshop.readthedocs.io/en/latest/evaluation/mapping.html">Read Mapping</a></li>
<li><a href="http://denbi-metagenomics-workshop.readthedocs.io/en/latest/evaluation/metaquast.html">MetaQUAST</a></li>
</ul>
</li>
<li><a href="http://denbi-metagenomics-workshop.readthedocs.io/en/latest/binning/index.html">Binning</a>
<ul>
<li><a href="http://denbi-metagenomics-workshop.readthedocs.io/en/latest/binning/maxbin.html">MaxBin Binning</a></li>
<li><a href="http://denbi-metagenomics-workshop.readthedocs.io/en/latest/binning/metabat.html">MetaBAT Binning</a></li>
</ul>
</li>
<li><a href="http://denbi-metagenomics-workshop.readthedocs.io/en/latest/classification/index.html">Classification</a>
<ul>
<li><a href="http://denbi-metagenomics-workshop.readthedocs.io/en/latest/classification/kraken.html">Kraken Taxonomic Sequence Classification System</a></li>
</ul>
</li>
</ul>
</div>
</div>
</div>
</div>
<div><a href="http://denbi-metagenomics-workshop.readthedocs.io/en/latest/data.html" title="The Tutorial Data Set">Next&nbsp;<span></span></a>
<p>&nbsp;</p>
</div><p>Address of the bookmark: <a href="http://denbi-metagenomics-workshop.readthedocs.io/en/latest/index.html" rel="nofollow">http://denbi-metagenomics-workshop.readthedocs.io/en/latest/index.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44200/dashboard-designing-tutorial</guid>
	<pubDate>Thu, 02 Mar 2023 06:48:43 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44200/dashboard-designing-tutorial</link>
	<title><![CDATA[Dashboard designing tutorial !]]></title>
	<description><![CDATA[<p>Dashboard Design Tutorial</p><p>Address of the bookmark: <a href="https://github.com/dthill196/SARS-2-Dashboard-Tutorial" rel="nofollow">https://github.com/dthill196/SARS-2-Dashboard-Tutorial</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34413/coursera-genome-assembly-tutorial</guid>
	<pubDate>Sat, 25 Nov 2017 08:57:25 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34413/coursera-genome-assembly-tutorial</link>
	<title><![CDATA[coursera genome assembly tutorial]]></title>
	<description><![CDATA[<p><span>Solutions to Coursera Genome Sequencing (Bioinformatics II)</span></p><p>Address of the bookmark: <a href="https://github.com/iansealy/coursera-assembly" rel="nofollow">https://github.com/iansealy/coursera-assembly</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/39307/awk-for-beginners</guid>
	<pubDate>Fri, 26 Apr 2019 16:19:41 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/39307/awk-for-beginners</link>
	<title><![CDATA[AWK for beginners !]]></title>
	<description><![CDATA[<p>AWK is a standard tool on every POSIX-compliant UNIX system. It&rsquo;s like flex/lex, from the command-line, perfect for text-processing tasks and other scripting needs. It has a C-like syntax, but without mandatory semicolons (although, you should use them anyway, because they are required when you&rsquo;re writing one-liners, something AWK excels at), manual memory management, or static typing. It excels at text processing. You can call to it from a shell script, or you can use it as a stand-alone scripting language.</p><p>Why use AWK instead of Perl? Readability. AWK is easier to read than Perl. For simple text-processing scripts, particularly ones that read files line by line and split on delimiters, AWK is probably the right tool for the job.</p><div><pre><span>#!/usr/bin/awk -f</span>

<span># Comments are like this</span>


<span># AWK programs consist of a collection of patterns and actions.</span>
<span>pattern1</span> <span>{</span> <span>action</span><span>;</span> <span>}</span> <span># just like lex</span>
<span>pattern2</span> <span>{</span> <span>action</span><span>;</span> <span>}</span>

<span># There is an implied loop and AWK automatically reads and parses each</span>
<span># record of each file supplied. Each record is split by the FS delimiter,</span>
<span># which defaults to white-space (multiple spaces,tabs count as one)</span>
<span># You can assign FS either on the command line (-F C) or in your BEGIN</span>
<span># pattern</span>

<span># One of the special patterns is BEGIN. The BEGIN pattern is true</span>
<span># BEFORE any of the files are read. The END pattern is true after</span>
<span># an End-of-file from the last file (or standard-in if no files specified)</span>
<span># There is also an output field separator (OFS) that you can assign, which</span>
<span># defaults to a single space</span>

<span>BEGIN</span> <span>{</span>

    <span># BEGIN will run at the beginning of the program. It's where you put all</span>
    <span># the preliminary set-up code, before you process any text files. If you</span>
    <span># have no text files, then think of BEGIN as the main entry point.</span>

    <span># Variables are global. Just set them or use them, no need to declare..</span>
    <span>count</span> <span>=</span> <span>0</span><span>;</span>

    <span># Operators just like in C and friends</span>
    <span>a</span> <span>=</span> <span>count</span> <span>+</span> <span>1</span><span>;</span>
    <span>b</span> <span>=</span> <span>count</span> <span>-</span> <span>1</span><span>;</span>
    <span>c</span> <span>=</span> <span>count</span> <span>*</span> <span>1</span><span>;</span>
    <span>d</span> <span>=</span> <span>count</span> <span>/</span> <span>1</span><span>;</span> <span># integer division</span>
    <span>e</span> <span>=</span> <span>count</span> <span>%</span> <span>1</span><span>;</span> <span># modulus</span>
    <span>f</span> <span>=</span> <span>count</span> <span>^</span> <span>1</span><span>;</span> <span># exponentiation</span>

    <span>a</span> <span>+=</span> <span>1</span><span>;</span>
    <span>b</span> <span>-=</span> <span>1</span><span>;</span>
    <span>c</span> <span>*=</span> <span>1</span><span>;</span>
    <span>d</span> <span>/=</span> <span>1</span><span>;</span>
    <span>e</span> <span>%=</span> <span>1</span><span>;</span>
    <span>f</span> <span>^=</span> <span>1</span><span>;</span>

    <span># Incrementing and decrementing by one</span>
    <span>a</span><span>++</span><span>;</span>
    <span>b</span><span>--</span><span>;</span>

    <span># As a prefix operator, it returns the incremented value</span>
    <span>++</span><span>a</span><span>;</span>
    <span>--</span><span>b</span><span>;</span>

    <span># Notice, also, no punctuation such as semicolons to terminate statements</span>

    <span># Control statements</span>
    <span>if</span> <span>(</span><span>count</span> <span>==</span> <span>0</span><span>)</span>
        <span>print</span> <span>"Starting with count of 0"</span><span>;</span>
    <span>else</span>
        <span>print</span> <span>"Huh?"</span><span>;</span>

    <span># Or you could use the ternary operator</span>
    <span>print</span> <span>(</span><span>count</span> <span>==</span> <span>0</span><span>)</span> <span>?</span> <span>"Starting with count of 0"</span> <span>:</span> <span>"Huh?"</span><span>;</span>

    <span># Blocks consisting of multiple lines use braces</span>
    <span>while</span> <span>(</span><span>a</span> <span>&lt;</span> <span>10</span><span>)</span> <span>{</span>
        <span>print</span> <span>"String concatenation is done"</span> <span>" with a series"</span> <span>" of"</span>
            <span>" space-separated strings"</span><span>;</span>
        <span>print</span> <span>a</span><span>;</span>

        <span>a</span><span>++</span><span>;</span>
    <span>}</span>

    <span>for</span> <span>(</span><span>i</span> <span>=</span> <span>0</span><span>;</span> <span>i</span> <span>&lt;</span> <span>10</span><span>;</span> <span>i</span><span>++</span><span>)</span>
        <span>print</span> <span>"Good ol' for loop"</span><span>;</span>

    <span># As for comparisons, they're the standards:</span>
    <span># a &lt; b   # Less than</span>
    <span># a &lt;= b  # Less than or equal</span>
    <span># a != b  # Not equal</span>
    <span># a == b  # Equal</span>
    <span># a &gt; b   # Greater than</span>
    <span># a &gt;= b  # Greater than or equal</span>

    <span># Logical operators as well</span>
    <span># a &amp;&amp; b  # AND</span>
    <span># a || b  # OR</span>

    <span># In addition, there's the super useful regular expression match</span>
    <span>if</span> <span>(</span><span>"foo"</span> <span>~</span> <span>"^fo+$"</span><span>)</span>
        <span>print</span> <span>"Fooey!"</span><span>;</span>
    <span>if</span> <span>(</span><span>"boo"</span> <span>!~</span> <span>"^fo+$"</span><span>)</span>
        <span>print</span> <span>"Boo!"</span><span>;</span>

    <span># Arrays</span>
    <span>arr</span><span>[</span><span>0</span><span>]</span> <span>=</span> <span>"foo"</span><span>;</span>
    <span>arr</span><span>[</span><span>1</span><span>]</span> <span>=</span> <span>"bar"</span><span>;</span>

    <span># You can also initialize an array with the built-in function split()</span>

    <span>n</span> <span>=</span> <span>split</span><span>(</span><span>"foo:bar:baz"</span><span>,</span> <span>arr</span><span>,</span> <span>":"</span><span>);</span>

    <span># You also have associative arrays (actually, they're all associative arrays)</span>
    <span>assoc</span><span>[</span><span>"foo"</span><span>]</span> <span>=</span> <span>"bar"</span><span>;</span>
    <span>assoc</span><span>[</span><span>"bar"</span><span>]</span> <span>=</span> <span>"baz"</span><span>;</span>

    <span># And multi-dimensional arrays, with some limitations I won't mention here</span>
    <span>multidim</span><span>[</span><span>0</span><span>,</span><span>0</span><span>]</span> <span>=</span> <span>"foo"</span><span>;</span>
    <span>multidim</span><span>[</span><span>0</span><span>,</span><span>1</span><span>]</span> <span>=</span> <span>"bar"</span><span>;</span>
    <span>multidim</span><span>[</span><span>1</span><span>,</span><span>0</span><span>]</span> <span>=</span> <span>"baz"</span><span>;</span>
    <span>multidim</span><span>[</span><span>1</span><span>,</span><span>1</span><span>]</span> <span>=</span> <span>"boo"</span><span>;</span>

    <span># You can test for array membership</span>
    <span>if</span> <span>(</span><span>"foo"</span> <span>in</span> <span>assoc</span><span>)</span>
        <span>print</span> <span>"Fooey!"</span><span>;</span>

    <span># You can also use the 'in' operator to traverse the keys of an array</span>
    <span>for</span> <span>(</span><span>key</span> <span>in</span> <span>assoc</span><span>)</span>
        <span>print</span> <span>assoc</span><span>[</span><span>key</span><span>];</span>

    <span># The command line is in a special array called ARGV</span>
    <span>for</span> <span>(</span><span>argnum</span> <span>in</span> <span>ARGV</span><span>)</span>
        <span>print</span> <span>ARGV</span><span>[</span><span>argnum</span><span>];</span>

    <span># You can remove elements of an array</span>
    <span># This is particularly useful to prevent AWK from assuming the arguments</span>
    <span># are files for it to process</span>
    <span>delete</span> <span>ARGV</span><span>[</span><span>1</span><span>];</span>

    <span># The number of command line arguments is in a variable called ARGC</span>
    <span>print</span> <span>ARGC</span><span>;</span>

    <span># AWK has several built-in functions. They fall into three categories. I'll</span>
    <span># demonstrate each of them in their own functions, defined later.</span>

    <span>return_value</span> <span>=</span> <span>arithmetic_functions</span><span>(</span><span>a</span><span>,</span> <span>b</span><span>,</span> <span>c</span><span>);</span>
    <span>string_functions</span><span>();</span>
    <span>io_functions</span><span>();</span>
<span>}</span>

<span># Here's how you define a function</span>
<span>function</span> <span>arithmetic_functions</span><span>(</span><span>a</span><span>,</span> <span>b</span><span>,</span> <span>c</span><span>,</span>     <span>d</span><span>)</span> <span>{</span>

    <span># Probably the most annoying part of AWK is that there are no local</span>
    <span># variables. Everything is global. For short scripts, this is fine, even</span>
    <span># useful, but for longer scripts, this can be a problem.</span>

    <span># There is a work-around (ahem, hack). Function arguments are local to the</span>
    <span># function, and AWK allows you to define more function arguments than it</span>
    <span># needs. So just stick local variable in the function declaration, like I</span>
    <span># did above. As a convention, stick in some extra whitespace to distinguish</span>
    <span># between actual function parameters and local variables. In this example,</span>
    <span># a, b, and c are actual parameters, while d is merely a local variable.</span>

    <span># Now, to demonstrate the arithmetic functions</span>

    <span># Most AWK implementations have some standard trig functions</span>
    <span>localvar</span> <span>=</span> <span>sin</span><span>(</span><span>a</span><span>);</span>
    <span>localvar</span> <span>=</span> <span>cos</span><span>(</span><span>a</span><span>);</span>
    <span>localvar</span> <span>=</span> <span>atan2</span><span>(</span><span>b</span><span>,</span> <span>a</span><span>);</span> <span># arc tangent of b / a</span>

    <span># And logarithmic stuff</span>
    <span>localvar</span> <span>=</span> <span>exp</span><span>(</span><span>a</span><span>);</span>
    <span>localvar</span> <span>=</span> <span>log</span><span>(</span><span>a</span><span>);</span>

    <span># Square root</span>
    <span>localvar</span> <span>=</span> <span>sqrt</span><span>(</span><span>a</span><span>);</span>

    <span># Truncate floating point to integer</span>
    <span>localvar</span> <span>=</span> <span>int</span><span>(</span><span>5.34</span><span>);</span> <span># localvar =&gt; 5</span>

    <span># Random numbers</span>
    <span>srand</span><span>();</span> <span># Supply a seed as an argument. By default, it uses the time of day</span>
    <span>localvar</span> <span>=</span> <span>rand</span><span>();</span> <span># Random number between 0 and 1.</span>

    <span># Here's how to return a value</span>
    <span>return</span> <span>localvar</span><span>;</span>
<span>}</span>

<span>function</span> <span>string_functions</span><span>(</span>    <span>localvar</span><span>,</span> <span>arr</span><span>)</span> <span>{</span>

    <span># AWK, being a string-processing language, has several string-related</span>
    <span># functions, many of which rely heavily on regular expressions.</span>

    <span># Search and replace, first instance (sub) or all instances (gsub)</span>
    <span># Both return number of matches replaced</span>
    <span>localvar</span> <span>=</span> <span>"fooooobar"</span><span>;</span>
    <span>sub</span><span>(</span><span>"fo+"</span><span>,</span> <span>"Meet me at the "</span><span>,</span> <span>localvar</span><span>);</span> <span># localvar =&gt; "Meet me at the bar"</span>
    <span>gsub</span><span>(</span><span>"e+"</span><span>,</span> <span>"."</span><span>,</span> <span>localvar</span><span>);</span> <span># localvar =&gt; "m..t m. at th. bar"</span>

    <span># Search for a string that matches a regular expression</span>
    <span># index() does the same thing, but doesn't allow a regular expression</span>
    <span>match</span><span>(</span><span>localvar</span><span>,</span> <span>"t"</span><span>);</span> <span># =&gt; 4, since the 't' is the fourth character</span>

    <span># Split on a delimiter</span>
    <span>n</span> <span>=</span> <span>split</span><span>(</span><span>"foo-bar-baz"</span><span>,</span> <span>arr</span><span>,</span> <span>"-"</span><span>);</span> <span># a[1] = "foo"; a[2] = "bar"; a[3] = "baz"; n = 3</span>

    <span># Other useful stuff</span>
    <span>sprintf</span><span>(</span><span>"%s %d %d %d"</span><span>,</span> <span>"Testing"</span><span>,</span> <span>1</span><span>,</span> <span>2</span><span>,</span> <span>3</span><span>);</span> <span># =&gt; "Testing 1 2 3"</span>
    <span>substr</span><span>(</span><span>"foobar"</span><span>,</span> <span>2</span><span>,</span> <span>3</span><span>);</span> <span># =&gt; "oob"</span>
    <span>substr</span><span>(</span><span>"foobar"</span><span>,</span> <span>4</span><span>);</span> <span># =&gt; "bar"</span>
    <span>length</span><span>(</span><span>"foo"</span><span>);</span> <span># =&gt; 3</span>
    <span>tolower</span><span>(</span><span>"FOO"</span><span>);</span> <span># =&gt; "foo"</span>
    <span>toupper</span><span>(</span><span>"foo"</span><span>);</span> <span># =&gt; "FOO"</span>
<span>}</span>

<span>function</span> <span>io_functions</span><span>(</span>    <span>localvar</span><span>)</span> <span>{</span>

    <span># You've already seen print</span>
    <span>print</span> <span>"Hello world"</span><span>;</span>

    <span># There's also printf</span>
    <span>printf</span><span>(</span><span>"%s %d %d %d\n"</span><span>,</span> <span>"Testing"</span><span>,</span> <span>1</span><span>,</span> <span>2</span><span>,</span> <span>3</span><span>);</span>

    <span># AWK doesn't have file handles, per se. It will automatically open a file</span>
    <span># handle for you when you use something that needs one. The string you used</span>
    <span># for this can be treated as a file handle, for purposes of I/O. This makes</span>
    <span># it feel sort of like shell scripting, but to get the same output, the string</span>
    <span># must match exactly, so use a variable:</span>

    <span>outfile</span> <span>=</span> <span>"/tmp/foobar.txt"</span><span>;</span>

    <span>print</span> <span>"foobar"</span> <span>&gt;</span> <span>outfile</span><span>;</span>

    <span># Now the string outfile is a file handle. You can close it:</span>
    <span>close</span><span>(</span><span>outfile</span><span>);</span>

    <span># Here's how you run something in the shell</span>
    <span>system</span><span>(</span><span>"echo foobar"</span><span>);</span> <span># =&gt; prints foobar</span>

    <span># Reads a line from standard input and stores in localvar</span>
    <span>getline</span> <span>localvar</span><span>;</span>

    <span># Reads a line from a pipe (again, use a string so you close it properly)</span>
    <span>cmd</span> <span>=</span> <span>"echo foobar"</span><span>;</span>
    <span>cmd</span> <span>|</span> <span>getline</span> <span>localvar</span><span>;</span> <span># localvar =&gt; "foobar"</span>
    <span>close</span><span>(</span><span>cmd</span><span>);</span>

    <span># Reads a line from a file and stores in localvar</span>
    <span>infile</span> <span>=</span> <span>"/tmp/foobar.txt"</span><span>;</span>
    <span>getline</span> <span>localvar</span> <span>&lt;</span> <span>infile</span><span>;</span> 
    <span>close</span><span>(</span><span>infile</span><span>);</span>
<span>}</span>

<span># As I said at the beginning, AWK programs consist of a collection of patterns</span>
<span># and actions. You've already seen the BEGIN pattern. Other</span>
<span># patterns are used only if you're processing lines from files or standard</span>
<span># input.</span>
<span>#</span>
<span># When you pass arguments to AWK, they are treated as file names to process.</span>
<span># It will process them all, in order. Think of it like an implicit for loop,</span>
<span># iterating over the lines in these files. these patterns and actions are like</span>
<span># switch statements inside the loop. </span>

<span>/^fo+bar$/</span> <span>{</span>

    <span># This action will execute for every line that matches the regular</span>
    <span># expression, /^fo+bar$/, and will be skipped for any line that fails to</span>
    <span># match it. Let's just print the line:</span>

    <span>print</span><span>;</span>

    <span># Whoa, no argument! That's because print has a default argument: $0.</span>
    <span># $0 is the name of the current line being processed. It is created</span>
    <span># automatically for you.</span>

    <span># You can probably guess there are other $ variables. Every line is</span>
    <span># implicitly split before every action is called, much like the shell</span>
    <span># does. And, like the shell, each field can be access with a dollar sign</span>

    <span># This will print the second and fourth fields in the line</span>
    <span>print</span> <span>$</span><span>2</span><span>,</span> <span>$</span><span>4</span><span>;</span>

    <span># AWK automatically defines many other variables to help you inspect and</span>
    <span># process each line. The most important one is NF</span>

    <span># Prints the number of fields on this line</span>
    <span>print</span> <span>NF</span><span>;</span>

    <span># Print the last field on this line</span>
    <span>print</span> <span>$</span><span>NF</span><span>;</span>
<span>}</span>

<span># Every pattern is actually a true/false test. The regular expression in the</span>
<span># last pattern is also a true/false test, but part of it was hidden. If you</span>
<span># don't give it a string to test, it will assume $0, the line that it's</span>
<span># currently processing. Thus, the complete version of it is this:</span>

<span>$</span><span>0</span> <span>~</span> <span>/^fo+bar$/</span> <span>{</span>
    <span>print</span> <span>"Equivalent to the last pattern"</span><span>;</span>
<span>}</span>

<span>a</span> <span>&gt;</span> <span>0</span> <span>{</span>
    <span># This will execute once for each line, as long as a is positive</span>
<span>}</span>

<span># You get the idea. Processing text files, reading in a line at a time, and</span>
<span># doing something with it, particularly splitting on a delimiter, is so common</span>
<span># in UNIX that AWK is a scripting language that does all of it for you, without</span>
<span># you needing to ask. All you have to do is write the patterns and actions</span>
<span># based on what you expect of the input, and what you want to do with it.</span>

<span># Here's a quick example of a simple script, the sort of thing AWK is perfect</span>
<span># for. It will read a name from standard input and then will print the average</span>
<span># age of everyone with that first name. Let's say you supply as an argument the</span>
<span># name of a this data file:</span>
<span>#</span>
<span># Bob Jones 32</span>
<span># Jane Doe 22</span>
<span># Steve Stevens 83</span>
<span># Bob Smith 29</span>
<span># Bob Barker 72</span>
<span>#</span>
<span># Here's the script:</span>

<span>BEGIN</span> <span>{</span>

    <span># First, ask the user for the name</span>
    <span>print</span> <span>"What name would you like the average age for?"</span><span>;</span>

    <span># Get a line from standard input, not from files on the command line</span>
    <span>getline</span> <span>name</span> <span>&lt;</span> <span>"/dev/stdin"</span><span>;</span>
<span>}</span>

<span># Now, match every line whose first field is the given name</span>
<span>$</span><span>1</span> <span>==</span> <span>name</span> <span>{</span>

    <span># Inside here, we have access to a number of useful variables, already</span>
    <span># pre-loaded for us:</span>
    <span># $0 is the entire line</span>
    <span># $3 is the third field, the age, which is what we're interested in here</span>
    <span># NF is the number of fields, which should be 3</span>
    <span># NR is the number of records (lines) seen so far</span>
    <span># FILENAME is the name of the file being processed</span>
    <span># FS is the field separator being used, which is " " here</span>
    <span># ...etc. There are plenty more, documented in the man page.</span>

    <span># Keep track of a running total and how many lines matched</span>
    <span>sum</span> <span>+=</span> <span>$</span><span>3</span><span>;</span>
    <span>nlines</span><span>++</span><span>;</span>
<span>}</span>

<span># Another special pattern is called END. It will run after processing all the</span>
<span># text files. Unlike BEGIN, it will only run if you've given it input to</span>
<span># process. It will run after all the files have been read and processed</span>
<span># according to the rules and actions you've provided. The purpose of it is</span>
<span># usually to output some kind of final report, or do something with the</span>
<span># aggregate of the data you've accumulated over the course of the script.</span>

<span>END</span> <span>{</span>
    <span>if</span> <span>(</span><span>nlines</span><span>)</span>
        <span>print</span> <span>"The average age for "</span> <span>name</span> <span>" is "</span> <span>sum</span> <span>/</span> <span>nlines</span><span>;</span>
<span>}</span>
</pre><p><span>&nbsp;</span></p></div>]]></description>
	<dc:creator>BioJoker</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/blog/view/44871/10-books-to-kickstart-and-level-up-your-bioinformatics-journey</guid>
	<pubDate>Tue, 12 Aug 2025 03:50:11 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44871/10-books-to-kickstart-and-level-up-your-bioinformatics-journey</link>
	<title><![CDATA[10 Books to Kickstart (and Level Up) Your Bioinformatics Journey]]></title>
	<description><![CDATA[<p>If you&rsquo;re starting out in bioinformatics or looking to sharpen your computational biology skills, having the right learning resources makes all the difference.<br />Here&rsquo;s my curated list of 10 must-read books &mdash; from beginner-friendly introductions to advanced computational genomics.</p><p>1️⃣ Data Analysis for the Life Sciences<br />A fantastic starting point to learn statistics, R programming, and exploratory data analysis in the context of biology. The best part? It&rsquo;s available free online from HarvardX.</p><p>2️⃣ Practical Computing for Biologists<br />The very first book I picked up when I started learning computational biology. It&rsquo;s beginner-friendly and focuses on essential computing skills every biologist needs.</p><p>3️⃣ A Primer for Computational Biology<br />An open-access, hands-on introduction to computational biology concepts and coding techniques. Perfect if you want to learn through real examples.</p><p>4️⃣ Computational Genomics with R<br />For those who already know R and want to dive deeper into genome-scale data analysis, from sequence alignment to gene expression.</p><p>5️⃣ The Biologist&rsquo;s Guide to Computing<br />Bridges the gap between biological problems and computational thinking, making it easier for life scientists to approach programming and data analysis.</p><p>6️⃣ Bioinformatics Data Skills<br />A must-read to sharpen your bioinformatics toolkit &mdash; from command-line skills to reproducible research workflows. Ideal once you&rsquo;ve covered the basics.</p><p>7️⃣ Bioinformatics Workbook<br />A practical tutorial series to help scientists design bioinformatics projects, analyze data, and understand best practices.</p><p>8️⃣ Modern Statistics for Modern Biology<br />An essential guide to modern statistical methods applied to biology, blending theory with hands-on examples in R.</p><p>9️⃣ Algorithms on Strings, Trees, and Sequences by Dan Gusfield<br />A classic reference for anyone wanting to understand the algorithms behind sequence alignment, genome assembly, and biological data structures.</p><p></p>]]></description>
	<dc:creator>Neel</dc:creator>
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