<?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" >
<channel>
	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/21367?offset=770</link>
	<atom:link href="https://bioinformaticsonline.com/related/21367?offset=770" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<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/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/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/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/bookmarks/view/17926/orange-bioinformatics-2534</guid>
	<pubDate>Mon, 06 Oct 2014 12:51:37 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/17926/orange-bioinformatics-2534</link>
	<title><![CDATA[Orange-Bioinformatics 2.5.34]]></title>
	<description><![CDATA[<p>Orange Bioinformatics extends <a href="http://orange.biolab.si/">Orange</a>, a data mining software package, with common functionality for bioinformatics. The provided functionality can be accessed as a Python library or through a visual programming interface (Orange Canvas). The latter is also suitable for non-programmers.</p>
<p>Orange Bioinformatics provides access to publicly available data, like GEO data sets, Biomart, GO, KEGG, Atlas, ArrayExpress, and PIPAx database. As for the analytics, there is gene selection, quality control, scoring distances between experiments with multiple factors. All features can be combined with powerful visualization, network exploration and data mining techniques from the Orange data mining framework.</p><p>Address of the bookmark: <a href="https://pypi.python.org/pypi/Orange-Bioinformatics/2.5.34" rel="nofollow">https://pypi.python.org/pypi/Orange-Bioinformatics/2.5.34</a></p>]]></description>
	<dc:creator>Robert M Willioms</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/18380/jrfsrf-at-university-of-hyderabad</guid>
  <pubDate>Fri, 17 Oct 2014 01:55:44 -0500</pubDate>
  <link></link>
  <title><![CDATA[JRF/SRF at University of Hyderabad]]></title>
  <description><![CDATA[
<p>Applications are invited for the following post of Junior Research Fellow (temporary position coterminous with the project) under DBT funded research project on ““Understanding the functions of α1β1γ1/α2β1γ1 selective AMPK Modulators in dissecting the pharmacological role of these isozymes in metabolic diseases”</p>

<p>Qualified and interested candidates can send their curriculum vitae by e-mail to hr@drils.org on or before 27th October 2014 mention in the subject line of the mail the following code: AMPK-Biology.</p>

<p>Selected candidates will be called for a personal interview to Dr. Reddy’s Institute of Life Sciences, University of Hyderabad Campus, Gachibowli, Hyderabad. The selected candidate is expected to report within two weeks from the date of selection to start work on the project.</p>

<p>Junior Research Fellowship (Molecular Modeling/Biology) for two years and Senior Research fellowship for one year</p>

<p>Junior Research Fellowship: Rs. 15,600/- (consolidated) per month for first two years.<br />Senior Research Fellowship: Rs. 18,200/-(consolidated) per month for the 3rd year.</p>

<p>Duration: The duration of the fellowship is for three years. However, the performance of the candidate will be reviewed after the completion of every year and the fellowship will be renewed only upon satisfactory performance.</p>

<p>Responsibilities:</p>

<p>1) Literature search.<br />2) Design, plan and execute experiments under the supervision of the scientist.<br />3) Provide scientific support to the scientist in his/her research activities.<br />4) Book keeping and maintenance of stocks and consumables.</p>

<p>Essential Qualifications:</p>

<p>Required: M.Sc. in Microbiology/Biotechnology/Bioinformatics or any other related branch of basic Sciences from a recognized university/institute with a consistent academic record of minimum 60% aggregate in all qualifying examinations. The candidate should be NET qualified for lectureship. The candidate should be motivated to work with dedication.</p>

<p>Desirable: expertise/experience in both Molecular Modeling and Molecular Biology.</p>

<p>Experience: 0-2 years in the areas of Molecular Modeling and/or Molecular Biology and cell biology and Biochemistry.</p>

<p>Preferable: Relevant research experience as evident from thesis/dissertation/project work.</p>

<p>Advertisement: http://www.ilsresearch.org/userfiles/Junior%20REsearch%20Fellowship%20-%20AMPK(Biology).pdf</p>
]]></description>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/18385/biinformamatics-lead-at-google-life-sciences</guid>
  <pubDate>Fri, 17 Oct 2014 02:24:55 -0500</pubDate>
  <link></link>
  <title><![CDATA[Biinformamatics Lead at Google Life Sciences]]></title>
  <description><![CDATA[
<p>Google Life Sciences is recruiting a technical lead with experience in bioinformatics and clinical bioinformatics, including for biomarker discovery projects such as the Baseline study.</p>

<p>Responsibilities</p>

<p>Lead teams of scientists in structuring, prototyping, and executing large-scale bioinformatic and other analysis.<br />Develop novel bioinformatics, statistical, data processing, pathway, data mining and other algorithms to identify biological signals and their clinical correlates in broad kinds of individual and population data.<br />Develop novel platform-level analytical tools for sequence-based assays (assembly, annotation, variant calling and interpretation, phasing, genome structure, etc.), expression assays (RNAseq and microarray), proteomics, and metabolomics.<br />Develop statistical models that robustly correlate complex laboratory-derived information with phenotypic and clinical information.<br />Create scientifically rigorous visualizations, communications, and presentations of results.</p>

<p>Reference @ https://www.google.com/about/careers/search#!t=jo&amp;jid=62095001</p>
]]></description>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/18820/jrfsrf-at-university-of-calcutta</guid>
  <pubDate>Fri, 31 Oct 2014 08:53:10 -0500</pubDate>
  <link></link>
  <title><![CDATA[JRF/SRF at University of Calcutta]]></title>
  <description><![CDATA[
<p>Applications are invited to appear at a walk-in-interview for one post of Junior Research Fellow in the DBT(DBT Twinning NER) sponsored project entitled “Protein folding kinetics is a selection force on shaping codon usage bias in the high expression genes” in the room of the HOD, Department of Biotechnology and the Coordinator, DR. B. C. Guha Centre for Genetic Engineering and Biotechnology, University College of Science, 35 Ballygunge Circular Road, Kolkata 700019 on the 12th November, 2014 at 3:00 p.m.</p>

<p>Essential qualifications: First class M. Sc. in any branch of life sciences and qualified CSIR-UGC NET/GATE Examination.</p>

<p>Desirable qualifications: Practical experience in biochemical and biophysical studies of proteins</p>

<p>Emoluments: as per DBT norms</p>

<p>The project is tenable for two years, initially for one year.</p>

<p>Age: Below 28 years (relaxable in the case of SC/ST/OBC/women candidates)</p>

<p>Candidates are requested to bring two sets of complete applications on plain paper furnishing bio-data and copies of attested certificates along with originals (for verification) on the date of interview.</p>

<p>No TA/DA is admissible for candidates appearing at the interview.</p>

<p>Dr. Rajat Banerjee<br />Assistant Professor<br />Department of Biotechnology and<br />Dr. B. C. Guha Centre for Genetic Engineering and Biotechnology<br />University College of Science<br />35, Ballygunge Circular Road<br />Kolkata 700019</p>

<p>Advertisement: www.caluniv.ac.in/news/jrf_biotech_2.pdf</p>
]]></description>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/21471/opening-for-raextended-srf-in-bioinformatics-project-by-dbt-at-bose-institute</guid>
  <pubDate>Sun, 01 Mar 2015 00:50:18 -0600</pubDate>
  <link></link>
  <title><![CDATA[Opening for RA/extended SRF in Bioinformatics project by DBT at Bose Institute]]></title>
  <description><![CDATA[
<p>The institute has evolved over the years into a multi-disciplinary research organization with stress on fundamental research in its pursuit of advancement of knowledge in Science and technology and at the same time developing highly competent and able scientific manpower for the country. The institute has on its staff highly qualified and experienced scientists working in the field of Biological, biochemical, Chemical and Physical sciences placed in long established departments of Physics, Chemistry, Botany, Microbiology, Biochemistry, and Biophysics, and the research sections on plant Molecular &amp; Cellular Genetics, Animal Physiology, Immunotechnology and Environmental science</p>

<p>Walk-in-Interview will be held on 04th March 2015 at 11.30 A.M. in the Bio- Informatics Centre of Bose Institute, P-1/12, C.I.T. Scheme VII-M, Kolkata- 700054 for two (02) positions of Research Associate/ Extended Senior Research Fellow in the DBT sponsored following two projects running under the CoE- Bioinformatics under the guidance of Prof. Pinakpani Chakrabarti, Bioinformatics Centre.</p>

<p>Position : RA/SRF<br />Project title : 1. "Centre of Excellence (CoE) in Bioinformatics at Bose Institute”,2. Project entitled “Setting up of National Facility on Interactive Graphysics Computer System (IGCS) for Biomolecular Modeling, Molecular Dynamics &amp; Structures”</p>

<p>Desired Profile : Ph.D degree in Biological or Chemical Sciences with in-depth understanding of protein structure and dynamics for R.A. position.Those who have submitted thesis can be considered for Extended SRF position<br />Preferred : Knowledge of computer programming and bioinformatics softwares.<br />Stipend : For R.A- Rs. 22,000/- p.m., plus admissible H.R.A. and Medical benefit. For Extended SRF - Rs. 20,000/- p.m., plus admissible H.R.A.and Medical benefit.<br />Age : For R.A- Below 35 years; For Extended SRF - Below 33 years<br />Interested and eligible candidates should appear before the Selection Committee with atyped application addressed to the Sr.Prof. &amp; In-Charge, Registrar's Office, Bose Institute, P- 1/12, CIT Scheme VII-M, Kankurgachi, Kolkata-700054 along with Bio-data giving details of qualification i.e. examination passed, year, division, percentage of marks from Secondary onwards with attested copies of Certificates, Mark-Sheet and testimonials. The candidates should also bring the original mark-sheets, certificates etc. at the time of Interview.</p>

<p>Walk in Interview : 04.03.15</p>

<p>More at http://www.boseinst.ernet.in/ADVT/14/p_34.pdf</p>
]]></description>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/21619/research-associate-biotechnologyjrflab-assistant-indian-institute-of-vegetable-research-iivr-varanasi-uttar-pradesh</guid>
  <pubDate>Wed, 11 Mar 2015 08:59:27 -0500</pubDate>
  <link></link>
  <title><![CDATA[Research Associate Biotechnology/JRF/Lab. Assistant  Indian Institute of Vegetable Research (IIVR) - Varanasi, Uttar Pradesh]]></title>
  <description><![CDATA[
<p>F. No.: 2-19/2011-Adm.I </p>

<p>Research Associate Biotechnology /JRF / Lab. Assistant recruitment in Indian Institute of Vegetable Research </p>

<p>Project:<br />Genomics assisted selection of Solanum chilense introgression lines for enhancing drought tolerance in tomato <br />Post Name : Research Associate <br />Qualification : Ph.D in Biotechnology/ Bioinformatics/Genetics &amp; Plant Breeding. M. Tech in Computer Science with at least one research paper in science citation indexed journal. Desirable: Experience in bioinformatics and next generation sequence data handling. Familiarity in Linux, R, Perl/Phython or other programming languages. Willingness to travel to European partner centers. </p>

<p>Pay Scale : Rs. 36000 for 1st and 2nd year as per rules for Research Associate. Rs. 25000/- for 1st and 2nd year and Rs. 28000 as per rules for Junior Research Fellow. Rs. 7000/- for Lab. Assistant. </p>

<p>Age : Not more than 35 years for Men and 40 years for Women (Relaxable for SC/ST/OBC/PH candidates as per rules) for Research Associate/ Junior Research Fellow. Minimum age will be 21 years and maximum age will be 45 years (Relaxable for SC/ST/OBC/PH candidates as per rules) for Lab.Assistant.</p>

<p>More at http://iivr.org.in/Job%20Oppurtunities/RA20.03.2015.pdf</p>
]]></description>
</item>

</channel>
</rss>