<?xml version='1.0'?><rss version="2.0" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:georss="http://www.georss.org/georss" xmlns:atom="http://www.w3.org/2005/Atom" >
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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/1161?offset=1020</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/34463/single-cell-rnaseq-data-analysis-tutorial</guid>
	<pubDate>Mon, 27 Nov 2017 16:24:29 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/34463/single-cell-rnaseq-data-analysis-tutorial</link>
	<title><![CDATA[Single Cell RNAseq data analysis tutorial !!]]></title>
	<description><![CDATA[<ul>
<li>A major breakthrough (replaced microarrays) in the late 00&rsquo;s and has been widely used since</li>
<li>Measures the&nbsp;average expression level&nbsp;for each gene across a large population of input cells</li>
<li>Useful for comparative transcriptomics, e.g.&nbsp;samples of the same tissue from different species</li>
<li>Useful for quantifying expression signatures from ensembles, e.g.&nbsp;in disease studies</li>
<li>Insufficient&nbsp;for studying heterogeneous systems, e.g.&nbsp;early development studies, complex tissues (brain)</li>
<li>Does&nbsp;not&nbsp;provide insights into the stochastic nature of gene expression</li>
</ul><p>Following are the useful links:</p><p><a href="http://hemberg-lab.github.io/scRNA.seq.course/scRNA-seq-course.pdf" target="_blank">Single Cell RNAseq data analysis Tutorial</a></p><p><a href="https://f1000research.com/articles/5-2122/v2" target="_blank">A step-by-step workflow for low-level analysis of single-cell RNA-seq data</a></p><p><a href="https://www.bioconductor.org/help/workflows/simpleSingleCell/" target="_blank">A step-by-step workflow for low-level analysis of single-cell RNA-seq data with Bioconductor</a></p><p>SCell: single-cell RNA-seq analysis software</p><p><a href="https://github.com/diazlab/SCell">https://github.com/diazlab/SCell</a></p><p>Beta-Poisson model for single-cell RNA-seq data analyses</p><p><a href="https://github.com/nghiavtr/BPSC">https://github.com/nghiavtr/BPSC</a></p><p>Sincera: A Computational Pipeline for Single Cell RNA-Seq Profiling Analysis</p><p><a href="https://research.cchmc.org/pbge/sincera.html">https://research.cchmc.org/pbge/sincera.html</a></p><p>SC3 &ndash; consensus clustering of single-cell RNA-Seq data</p><p><a href="http://biorxiv.org/content/early/2016/09/02/036558">http://biorxiv.org/content/early/2016/09/02/036558</a></p><p>Citrus: A toolkit for single cell sequencing analysis</p><p><a href="http://biorxiv.org/content/early/2016/09/14/045070">http://biorxiv.org/content/early/2016/09/14/045070</a></p><p>Single-Cell Resolution of Temporal Gene Expression during Heart Development</p><p><a href="http://www.cell.com/developmental-cell/fulltext/S1534-5807%2816%2930682-7">http://www.cell.com/developmental-cell/fulltext/S1534-5807(16)30682-7</a></p><p>Scalable latent-factor models applied to single-cell RNA-seq data separate biological drivers from confounding effects</p><p><a href="http://biorxiv.org/content/early/2016/11/15/087775">http://biorxiv.org/content/early/2016/11/15/087775</a></p><p>Single cell transcriptomes identify human islet cell signatures and reveal cell-type-specific expression changes in type 2 diabetes</p><p><a href="http://genome.cshlp.org/content/early/2016/11/18/gr.212720.116.abstract">http://genome.cshlp.org/content/early/2016/11/18/gr.212720.116.abstract</a></p><p>SCODE: An efficient regulatory network inference algorithm from single-cell RNA-Seq during differentiation</p><p><a href="http://biorxiv.org/content/early/2016/11/21/088856">http://biorxiv.org/content/early/2016/11/21/088856</a></p><p>SCOUP is a probabilistic model to analyze single-cell expression data during differentiation</p><p><a href="https://github.com/hmatsu1226/SCOUP">https://github.com/hmatsu1226/SCOUP</a></p><p>scLVM is a modelling framework for single-cell RNA-seq data</p><p><a href="https://github.com/PMBio/scLVM">https://github.com/PMBio/scLVM</a></p><p>Selective Locally linear Inference of Cellular Expression Relationships (SLICER) algorithm for inferring cell trajectories</p><p><a href="https://github.com/jw156605/SLICER">https://github.com/jw156605/SLICER</a></p><p>SinQC: A Method and Tool to Control Single-cell RNA-seq Data Quality</p><p><a href="http://www.morgridge.net/SinQC.html">http://www.morgridge.net/SinQC.html</a></p><p>TSCAN: Pseudo-time reconstruction and evaluation in single-cell RNA-seq analysis</p><p><a href="https://github.com/zji90/TSCAN">https://github.com/zji90/TSCAN</a></p><p>Visualization and cellular hierarchy inference of single-cell data using SPADE</p><p><a href="http://www.nature.com/nprot/journal/v11/n7/full/nprot.2016.066.html">http://www.nature.com/nprot/journal/v11/n7/full/nprot.2016.066.html</a></p><p>OEFinder: Identify ordering effect genes in single cell RNA-seq data</p><p><a href="https://github.com/lengning/OEFinder">https://github.com/lengning/OEFinder</a></p>]]></description>
	<dc:creator>Robert M Willioms</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/23536/teaching-assistant-at-svims</guid>
  <pubDate>Fri, 31 Jul 2015 10:15:16 -0500</pubDate>
  <link></link>
  <title><![CDATA[Teaching Assistant at SVIMS]]></title>
  <description><![CDATA[
<p>Eligible candidates are invited for a walk-in-interview for recruitment of Teaching Assistant in the Department of Bioinformatics on 8.08.2015 at 10 A.M. in the Committee Hall, SVIMS, Tirupati. The candidates have to attend with all original certificates of qualification, experience on the date of interview. The engagement will be made purely on adhoc basis for a period of 6 months and it can be terminated at any time without notice or without assigning any reason thereof. This is purely an adhoc appointment and the candidate will not have any right to claim permanent benefits of any kind.</p>

<p>1. Remuneration : Rs. 12000/- per month (consolidated)</p>

<p>2. Qualification : M.Sc./M.Tech. Bioinformatics (preference will be given to the candidates with BINC / NET / GATE / Bioinformatics DBT-Traineeship / Studentship and teaching experience)</p>

<p>3. Place of work : Department of Bioinformatics, SVIMS, Tirupati</p>

<p>4. No. of Position : One</p>

<p>Terms and conditions:</p>

<p>1. Candidates are required to submit the Biodata, attested copies of relevant certificates in support of their age, educational qualification, experience etc., before the interview committee, SVIMS University, Tirupati.<br />2. No TA / DA will be paid for attending the interview.<br />3. Interim enquiries will not be entertained.<br />4. The maximum age limit for Teaching Assistant is 34 years as on 8th August, 2015.<br />5. The tenure of will be further extended subject to performance of the incumbent.</p>

<p>Advertisement: http://svimsbic.org/Teaching_Assistant_B.I._2015.pdf</p>
]]></description>
</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/view/19838</guid>
	<pubDate>Sat, 27 Dec 2014 13:30:15 -0600</pubDate>
	<link>https://bioinformaticsonline.com/view/19838</link>
	<title><![CDATA[Interview with a bioinformatician series ...]]></title>
	<description><![CDATA[<p>The aim of this series to interviews some notable bioinformaticians to get their views on various aspects of bioinformatics research. Hopefully these answers will prove useful to others in the field, especially to those who are just starting their bioinformatics careers.<br /><br />This series will be available at BOL every fortnight.<br /><br /><br /><br /></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43863/snakemake-tutorials</guid>
	<pubDate>Mon, 09 May 2022 05:20:41 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43863/snakemake-tutorials</link>
	<title><![CDATA[Snakemake Tutorials !]]></title>
	<description><![CDATA[<p>A lesson introducing the Snakemake workflow system for bioinformatics analysis.</p>
<blockquote>
<h2 id="prerequisites">Prerequisites<a href="https://carpentries-incubator.github.io/snakemake-novice-bioinformatics/index.html#prerequisites"></a></h2>
<p>This is an intermediate lesson and assumes learners have already done some bioinformatics:</p>
<ul>
<li>Familiarity with the BASH command shell, including concepts like pipes, variables and loops.</li>
<li>Knowledge of bioinformatics fundamentals like the FASTQ file format and transcriptome sequencing, in order to understand the example workflow.</li>
</ul>
<p>No previous knowledge of Snakemake or workflow systems is required.</p>
<p>https://carpentries-incubator.github.io/snakemake-novice-bioinformatics/index.html</p>
</blockquote><p>Address of the bookmark: <a href="https://carpentries-incubator.github.io/snakemake-novice-bioinformatics/aio/index.html" rel="nofollow">https://carpentries-incubator.github.io/snakemake-novice-bioinformatics/aio/index.html</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/19992/binc-examination-2015</guid>
	<pubDate>Mon, 29 Dec 2014 12:23:37 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/19992/binc-examination-2015</link>
	<title><![CDATA[BINC examination 2015 !!!]]></title>
	<description><![CDATA[<p>Pondicherry University,Puducherry,on behalf of Department of Biotechnology, Government of India, will conduct the BINC examination in 2015. The objective of this examination is to certify bioinformatics professionals, trained formally as well as self-trained.Registration for BINC examination 2015 will open soon.</p><p>Pondicherry University Puducherry has been identified as a nodal agency by the Department of Biotechnology, Govt. of India to coordinate this examination along with nine centres namely, Pune University, Pune; Anna University, Chennai; Calcatta University (WBUT) Kolkata; Institute of Bioinformatics &amp; Applied Biotechnology, Bangalore; North-Eastern Hill University, Shillong, University of Hyderabad, Hyderabad; University of Kerala, Thiruvananthapuram; Jawaharlal Nehru University, New Delhi and Assam Agricultural University, Guwahati.</p><p>In the BINC 2013 examination,17 candidates were certified. DBT has agreed to fund Research fellowships for all the BINC qualified Indian nationals to pursue Ph.D. in Indian Institutes/Universities. Note that the candidate must possess a postgraduate degree(or equivalent) &amp; meet the criteria of the institutes/universities in order to avail research fellowship. In addition, cash prize of Rs. 10,000/- will be awarded to the top 10 BINC qualifiers.<br /><br /></p><p>More at http://210.212.230.224:9999/BINC/</p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/20448/jrf-in-bioinformatics-nehu</guid>
  <pubDate>Tue, 20 Jan 2015 22:57:49 -0600</pubDate>
  <link></link>
  <title><![CDATA[JRF in Bioinformatics @ NEHU]]></title>
  <description><![CDATA[
<p>Department of Botany &amp; Bioinformatics Centre<br />NORTH-EASTERN HILL UNIVERSITY, SHILLONG 793022</p>

<p>Applications with complete bio-data from candidates possessing the required qualifications are invited for the posts of JRF (2) and Project Assistant (1) in</p>

<p>DBT, GOI-funded research project “Next Generation Sequencing (NGS)- based de novo assembly of expressed transcripts and genome information of Orchids in North-East India” in DBT’s Twinning programme for NE as per DBT sanction order and norms.</p>

<p>(i) JRF(2 nos.):</p>

<p>Qualifications: M.Tech/M.Sc in Life Sciences/ Botany/ Zoology/Biochemistry/ Biotechnology/ Bioinformatics; Desirable: Aptitude for Bioinformatics and Computer Programming/ Next generation sequencing data analysis</p>

<p>(ii) Project Assistant (1 no.):</p>

<p>Qualifications: Graduation in Science, Desirable: Experience of working in a Life Science/Plant Biotechnology lab. and familiarity with computers and field work viz. collection of samples.</p>

<p>The applications through email bicnehu@gmail.com or post must reach the undersigned<br />within 15 days from the date of publication of this advertisement. The advertised posts are purely temporary for the duration of the project and subject to availability of the funds from DBT. The appointment does not confer any entitlement or right over the posts for absorption in the University service.</p>

<p>Advertisement: www.nehu.ac.in/Advertisements/BICAdvtPV_200115.pdf</p>
]]></description>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/20362/20th-international-bioinformatics-workshop-on-virus-evolution-and-molecular-epidemiology-veme</guid>
  <pubDate>Mon, 12 Jan 2015 01:39:45 -0600</pubDate>
  <link></link>
  <title><![CDATA[20th International BioInformatics Workshop on Virus Evolution and Molecular Epidemiology (VEME)]]></title>
  <description><![CDATA[
<p>20th International BioInformatics Workshop on Virus Evolution and Molecular Epidemiology (VEME)<br />9 - 14 August 2015 St. Augustine, Trinidad and Tobago </p>

<p>Organiser: Christine Carrington (University of the West Indies - UWI, St. Augustine, Trinidad and Tobago)<br />Co-organisers: Anne-Mieke Vandamme, Philippe Lemey (Katholieke Universiteit Leuven, Belgium), Marco Salemi, Mattia Prosperi (University of Florida, Gainesville, USA) and Karen E. Nelson (J. Craig Venter Institute, Rockville, USA)</p>

<p>Requests for information directly to:<br />Christine Carrington<br />Department of Preclinical Sciences<br />Faculty of Medical Sciences<br />University of the West Indies (UWI)<br />St. Augustine<br />Trinidad and Tobago<br />Telephone: +1-868-6452640 ext. 5009, +1-868-6848803<br />Fax: +1-868-6621873<br />E-mail: veme2015@sta.uwi.edu</p>

<p>Deadline for receipt of applications by local organiser: 15 March 2015<br />CALL FOR APPLICATIONS NOW OPEN<br />http://www.icgeb.org/course-application-trinidad-and-tobago-2015.html</p>

<p>http://rega.kuleuven.be/cev/veme-workshop/2015</p>
]]></description>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/21200/ra-bioinformatics-at-ciba</guid>
  <pubDate>Fri, 13 Feb 2015 11:23:18 -0600</pubDate>
  <link></link>
  <title><![CDATA[RA Bioinformatics at CIBA]]></title>
  <description><![CDATA[
<p>Recruitment The following posts are to be filled purely on temporary basis under CIBA Component of “Centre for Agricultural Bioinformatics (CABin)” project at this Institute.</p>

<p>Posts Research Associate</p>

<p>Date &amp; Time of Interview 18th Feb 2015 at 10.00 a.m.</p>

<p>Project Name “Centre for Agricultural Bioinformatics (CABin)”</p>

<p>Duration 12th Plan (2012-2017) / co-terminus with the project 12th Plan (2012-2017) / co-terminus with the project</p>

<p>Essential Qualification Ph.d / M.Sc./ M.Phil (Bioinformatics) With 1st division or 60% marks or equivalent overall grade point average with at least two years of research experience in the relevant subject.</p>

<p>Technician</p>

<p>B.Tech. or Master degree in computer science/Computer Engineering /MCA or equivalent. Desirable qualification: Experience in Java/ C++/ PHP/ PERL/ Python etc. based application development using Linux, Apache and MySQL/Oracle.</p>

<p>Emoluments Rs.24000/- p.m. + 30% HRA for Ph.D holders / Rs.23000/- p.m. + 30% HRA for Master Degree holders A consolidated pay Rs.25000/- per month.</p>

<p>Age Limit Maximum 40 years for men and 45 years for women as on date of interview.</p>

<p>Age limits are relaxable for SC / ST / OBC candidates as per rules.</p>

<p>Maximum 40 years for men and 45 years for women as on date of interview.</p>

<p>Age limits are relaxable for SC / ST / OBC candidates as per rules.</p>

<p>Eligible Candidates may send their Curriculum Vitae along with the contact numbers to ashok@ciba.res.in on or before 13-02-2015.</p>

<p>Candidates selected after initial screening will be called for interview.</p>

<p>Advertisement: www.ciba.res.in/attachments/jobs/CABin-3006.pdf</p>
]]></description>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/20677/postdoctoral-researcher-at-department-of-biotechnology-catholic-university-of-daegu-kyungsan-kyungbuk-south-korea</guid>
  <pubDate>Thu, 29 Jan 2015 12:11:16 -0600</pubDate>
  <link></link>
  <title><![CDATA[Postdoctoral Researcher at Department of Biotechnology, Catholic University of Daegu, Kyungsan, Kyungbuk, South Korea.]]></title>
  <description><![CDATA[
<p>Applications are invited from Indian nationals for a Post Doctoral position at Molecular Medical Laboratory, Department of Biotechnology, Catholic University of Daegu, Kyungsan, Kyungbuk, South Korea.</p>

<p>Qualification required: PhD in Life Sciences/ Molecular Biology/ Bioinformatics or related discipline.</p>

<p>Desirable Qualification:</p>

<p>1. Candidates having experience in molecular biology techniques and must be well versed with bioinformatics tool or expert in relevant fields will be preferred.<br />2. The candidate should have good communication skill, knowledge about designing experiments and analyzing data.<br />3. Sense of initiative, autonomy, organization and thoroughness, good relation qualities.<br />Remuneration: 2000USD per month.</p>

<p>Last date of submitting the complete applications furnishing Bio-data is 10th February, 2015.</p>

<p>Interested candidates should send their resume including all personal as well as academic details to the principal investigator Prof Seung-Won Park (email:microsw@cu.ac.kr)</p>

<p>The shortlisted candidates will be intimated within February 2015.</p>
]]></description>
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