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	<title><![CDATA[BOL: Related items]]></title>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/22133/r-320-is-released</guid>
	<pubDate>Sat, 18 Apr 2015 05:06:44 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/22133/r-320-is-released</link>
	<title><![CDATA[R 3.2.0 is released]]></title>
	<description><![CDATA[<p>R 3.2.0 (codename &ldquo;Full of Ingredients&rdquo;)&nbsp;was <a href="http://r.789695.n4.nabble.com/R-3-2-0-is-released-td4705933.html" target="_blank">released yesterday</a>.&nbsp;You can get the latest binaries version <strong><a href="http://cran.rstudio.com/" target="_blank">from here</a>.</strong>&nbsp;(or the .tar.gz&nbsp;<strong>source</strong> code from <a href="http://cran.r-project.org/src/base/R-3/R-3.2.0.tar.gz" target="_blank">here</a>).&nbsp;The full list of new features and bug fixes is provided below.</p><h3>Upgrading to R 3.2.0 on Windows</h3><p>If you are using <strong>Windows&nbsp;</strong>you can easily upgrade to the latest version of R using <a href="http://cran.r-project.org/web/packages/installr/" target="_blank">the installr package</a>. Simply run the following code:</p><div><table>
<tbody>
<tr id="p612572">
<td id="p61257code2">
<pre><span style="color: #228b22;"># installing/loading the latest installr package:</span>
<span style="color: #0000ff; font-weight: bold;">install.<span>packages</span></span><span style="color: #080;">(</span><span style="color: #ff0000;">"installr"</span><span style="color: #080;">)</span><span style="color: #080;">;</span> <span style="color: #0000ff; font-weight: bold;">library</span><span style="color: #080;">(</span>installr<span style="color: #080;">)</span> <span style="color: #228b22;">#load / install+load installr</span>
&nbsp;
updateR<span style="color: #080;">(</span><span style="color: #080;">)</span> <span style="color: #228b22;"># updating R.</span></pre>
</td>
</tr>
</tbody>
</table></div><p><span>Running &ldquo;updateR()&rdquo; will detect if there is a new R version available, and if so it will download+install it (etc.).</span></p><p><span><strong>If you are an R blogger yourself</strong> you are invited to <a href="http://www.r-bloggers.com/add-your-blog/">add your own R content feed to this site</a> (<strong>Non-English</strong> R bloggers should add themselves- <a href="http://www.r-bloggers.com/lang/add-your-blog">here</a>)</span></p><h4>NEW FEATURES</h4><ul>
<li><code>anyNA()</code> gains a <code>recursive</code> argument.</li>
<li>When <code>x</code> is missing and <code>names</code> is not false (including the default value), <code>Sys.getenv(x, names)</code> returns an object of class <code>"Dlist"</code> and hence prints tidily.</li>
<li>(Windows.) <code>shell()</code> no longer consults the environment variable <span>SHELL</span>: too many systems have been encountered where it was set incorrectly (usually to a path where software was compiled, not where it was installed). <span>R_SHELL</span>, the preferred way to select a non-default shell, can be used instead.</li>
<li>Some unusual arguments to <code>embedFonts()</code> can now be specified as character vectors, and the defaults have been changed accordingly.</li>
<li>Functions in the <code>Summary</code> group duplicate less. (<a href="https://bugs.r-project.org/bugzilla3/show_bug.cgi?id=15798" target="_blank">PR#15798</a>)</li>
<li>(Unix-alikes.) <code>system(cmd, input = )</code> now uses &lsquo;shell-execution-environment&rsquo; redirection, which will be more natural if <code>cmd</code> is not a single command (but requires a POSIX-compliant shell). (Wish of <a href="https://bugs.r-project.org/bugzilla3/show_bug.cgi?id=15508" target="_blank">PR#15508</a>)</li>
<li><code>read.fwf()</code> and <code>read.DIF()</code> gain a <code>fileEncoding</code> argument, for convenience.</li>
<li>Graphics devices can add attributes to their description in <code>.Device</code> and <code>.Devices</code>. Several of those included with <strong>R</strong> use a <code>"filepath"</code> attribute.</li>
<li><code>pmatch()</code> uses hashing in more cases and so is faster at the expense of using more memory. (<a href="https://bugs.r-project.org/bugzilla3/show_bug.cgi?id=15697" target="_blank">PR#15697</a>)</li>
<li><code>pairs()</code> gains new arguments to select sets of variables to be plotted against each other.</li>
<li><code>file.info(, extra_cols = FALSE)</code> allows a minimal set of columns to be computed on Unix-alikes: on some systems without properly-configured caching this can be significantly faster with large file lists.</li>
<li>New function <code>dir.exists()</code> in package <span>base</span> to test efficiently whether one or more paths exist and are directories.</li>
<li><code>dput()</code> and friends gain new controls <span>hexNumeric</span> and <span>digits17</span> which output double and complex quantities as, respectively, binary fractions (exactly, see <code>sprintf("%a")</code>) and as decimals with up to 17 significant digits.</li>
<li><code>save()</code>, <code>saveRDS()</code> and <code>serialize()</code> now support <code>ascii = NA</code> which writes ASCII files using <code>sprintf("%a")</code> for double/complex quantities. This is read-compatible with <code>ascii = TRUE</code> but avoids binary-&gt;decimal-&gt;binary conversions with potential loss of precision. Unfortunately the Windows C runtime&rsquo;s lack of C99 compliance means that the format cannot be read correctly there in <strong>R</strong> before 3.1.2.</li>
<li>The default for <code>formatC(decimal.mark =)</code> has been changed to be <code>getOption("OutDec")</code>; this makes it more consistent with <code>format()</code> and suitable for use in print methods, e.g. those for classes <code>"density"</code>, <code>"ecdf"</code>, <code>"stepfun"</code> and <code>"summary.lm"</code>.
<p><code>getOption("OutDec")</code> is now consulted by the print method for class <code>"kmeans"</code>, by <code>cut()</code>, <code>dendrogram()</code>, <code>plot.ts()</code> and <code>quantile()</code> when constructing labels and for the report from<code>legend(trace = TRUE)</code>.</p>
<p>(In part, wish of <a href="https://bugs.r-project.org/bugzilla3/show_bug.cgi?id=15819" target="_blank">PR#15819</a>.)</p>
</li>
<li><code>printNum()</code> and hence <code>format()</code> and <code>formatC()</code> give a warning if <code>big.mark</code> and <code>decimal.mark</code> are set to the same value (period and comma are not uncommonly used for each, and this is a check that conventions have not got mixed).</li>
<li><code>merge()</code> can create a result which uses long vectors on 64-bit platforms.</li>
<li><code>dget()</code> gains a new argument <code>keep.source</code> which defaults to <code>FALSE</code> for speed (<code>dput()</code> and <code>dget()</code> are most often used for data objects where this can make <code>dget()</code> many times faster).</li>
<li>Packages may now use a file of common macro definitions in their help files, and may import definitions from other packages.</li>
<li>A number of macros have been added in the new &lsquo;<span>share/Rd</span>&rsquo; directory for use in package overview help pages, and <code>promptPackage()</code> now makes use of them.</li>
<li><code>tools::parse_Rd()</code> gains a new <code>permissive</code> argument which converts unrecognized macros into text. This is used by <code>utils:::format.bibentry</code> to allow LaTeX markup to be ignored.</li>
<li><code>options(OutDec =)</code> can now specify a multi-byte character, e.g., <code>options(OutDec = "u00b7")</code> in a UTF-8 locale.</li>
<li><code>is.recursive(x)</code> is no longer true when <code>x</code> is an external pointer, a weak reference or byte code; the first enables <code>all.equal(x, x)</code> when <code>x .</code></li>
<li><code>ls()</code> (aka <code>objects()</code>) and <code>as.list.environment()</code> gain a new argument <code>sorted</code>.</li>
<li>The <code>"source"</code> attribute (which has not been added to functions by <strong>R</strong> since before <strong>R</strong> version 2.14.0) is no longer treated as special.</li>
<li>Function <code>returnValue()</code> has been added to give <code>on.exit()</code> code access to a function&rsquo;s return value for debugging purposes.</li>
<li><code>crossprod(x, y)</code> allows more matrix coercions when <code>x</code> or <code>y</code> are vectors, now equalling <code>t(x) %*% y</code> in these cases (also reported by Radford Neal). Similarly, <code>tcrossprod(x,y)</code> and <code>%*%</code> work in more cases with vector arguments.</li>
<li>Utility function <code>dynGet()</code> useful for detecting cycles, aka infinite recursions.</li>
<li>The byte-code compiler and interpreter include new instructions that allow many scalar subsetting and assignment and scalar arithmetic operations to be handled more efficiently. This can result in significant performance improvements in scalar numerical code.</li>
<li><code>apply(m, 2, identity)</code> is now the same as the matrix <code>m</code> when it has <em>named</em> row names.</li>
<li>A new function <code>debuggingState()</code> has been added, allowing to temporarily turn off debugging.</li>
<li><code>example()</code> gets a new optional argument <code>run.donttest</code> and <code>tools::Rd2ex()</code> a corresponding <code>commentDonttest</code>, with a default such that <code>example(..)</code> in help examples will run <code>donttest</code> code only if used interactively (a change in behaviour).</li>
<li><code>rbind.data.frame()</code> gains an optional argument <code>make.row.names</code>, for potential speedup.</li>
<li>New function <code>extSoftVersion()</code> to report on the versions of third-party software in use in this session. Currently reports versions of <code>zlib</code>, <code>bzlib</code>, the <code>liblzma</code> from <code>xz</code>, PCRE, ICU, TRE and the <code>iconv</code> implementation.
<p>A similar function <code>grSoftVersion()</code> in package <span>grDevices</span> reports on third-party graphics software.</p>
<p>Function <code>tcltk::tclVersion()</code> reports the Tcl/Tk version.</p>
</li>
<li>Calling <code>callGeneric()</code> without arguments now works with primitive generics to some extent.</li>
<li><code>vapply(x, FUN, FUN.VALUE)</code> is more efficient notably for large <code>length(FUN.VALUE)</code>; as extension of <a href="https://bugs.r-project.org/bugzilla3/show_bug.cgi?id=16061" target="_blank">PR#16061</a>.</li>
<li><code>as.table()</code> now allows tables with one or more dimensions of length 0 (such as <code>as.table(integer())</code>).</li>
<li><code>names(x) now clears the names of call and <code>...</code> objects.</code></li>
<li><code>library()</code> will report a warning when an insufficient dependency version is masking a sufficient one later on the library search path.</li>
<li>A new <code>plot()</code> method for class <code>"raster"</code> has been added.</li>
<li>New <code>check_packages_in_dir_changes()</code> function in package <span>tools</span> for conveniently analyzing how changing sources impacts the check results of their reverse dependencies.</li>
<li>Speed-up from Peter Haverty for <code>ls()</code> and <code>methods:::.requirePackage()</code> speeding up package loading. (<a href="https://bugs.r-project.org/bugzilla3/show_bug.cgi?id=16133" target="_blank">PR#16133</a>)</li>
<li>New <code>get0()</code> function, combining <code>exists()</code> and <code>get()</code> in one call, for efficiency.</li>
<li><code>match.call()</code> gains an <code>envir</code> argument for specifying the environment from which to retrieve the <code>...</code> in the call, if any; this environment was wrong (or at least undesirable) when the<code>definition</code> argument was a function.</li>
<li><code>topenv()</code> has been made <code>.Internal()</code> for speedup, based on Peter Haverty&rsquo;s proposal in <a href="https://bugs.r-project.org/bugzilla3/show_bug.cgi?id=16140" target="_blank">PR#16140</a>.</li>
<li><code>getOption()</code> no longer calls <code>options()</code> in the main case.</li>
<li>Optional use of <code>libcurl</code> (version 7.28.0 from Oct 2012 or later) for Internet access:
<ul>
<li><code>capabilities("libcurl")</code> reports if this is available.</li>
<li><code>libcurlVersion()</code> reports the version in use, and other details of the <code>"libcurl"</code> build including which URL schemes it supports.</li>
<li><code>curlGetHeaders()</code> retrieves the headers for <code>http://</code>, <code>https://</code>, <code>ftp://</code> and <code>ftps://</code> URLs: analysis of these headers can provide insights into the &lsquo;existence&rsquo; of a URL (it might for example be permanently redirected) and is so used in <code>R CMD check --as-cran</code>.</li>
<li><code>download.file()</code> has a new optional method <code>"libcurl"</code> which will handle more URL schemes, follow redirections, and allows simultaneous downloads of multiple URLs.</li>
<li><code>url()</code> has a new method <code>"libcurl"</code> which handles more URL schemes and follows redirections. The default method is controlled by a new option <code>url.method</code>, which applies also to the opening of URLs <em>via</em> <code>file()</code> (which happens implicitly in functions such as <code>read.table</code>.)</li>
<li>When <code>file()</code> or <code>url()</code> is invoked with a <code>https://</code> or <code>ftps://</code> URL which the current method cannot handle, it switches to a suitable method if one is available.</li>
</ul>
</li>
<li>(Windows.) The DLLs &lsquo;<span>internet.dll</span>&rsquo; and &lsquo;<span>internet2.dll</span>&rsquo; have been merged. In this version it is safe to switch (repeatedly) between the internal and Windows internet functions within an <strong>R</strong>session.
<p>The Windows internet functions are still selected by flag <span>&ndash;internet2</span> or <code>setInternet2()</code>. This can be overridden for an <code>url()</code> connection <em>via</em> its new <code>method</code> argument.</p>
<p><code>download.file()</code> has new method <code>"wininet"</code>, selected as the default by <span>&ndash;internet2</span> or <code>setInternet2()</code>.</p>
</li>
<li><code>parent.env&lt;-</code> can no longer modify the parent of a locked namespace or namespace imports environment. Contributed by Karl Millar.</li>
<li>New function <code>isLoadedNamespace()</code> for readability and speed.</li>
<li><code>names(env)</code> now returns all the object names of an <code>environment</code> <code>env</code>, equivalently to <code>ls(env, all.names = TRUE, sorted = FALSE)</code> and also to the names of the corresponding list,<code>names(as.list(env, all.names = TRUE))</code>. Note that although <code>names()</code> returns a character vector, the names have no particular ordering.</li>
<li>The memory manager now grows the heap more aggressively. This reduces the number of garbage collections, in particular while data or code are loaded, at the expense of slightly increasing the memory footprint.</li>
<li>New function <code>trimws()</code> for removing leading/trailing whitespace.</li>
<li><code>cbind()</code> and <code>rbind()</code> now consider S4 inheritance during S3 dispatch and also obey <code>deparse.level</code>.</li>
<li><code>cbind()</code> and <code>rbind()</code> will delegate recursively to <code>methods::cbind2</code> (<code>methods::rbind2</code>) when at least one argument is an S4 object and S3 dispatch fails (due to ambiguity).</li>
<li>(Windows.) <code>download.file(quiet = FALSE)</code> now uses text rather than Windows progress bars in non-interactive use.</li>
<li>New function <code>hsearch_db()</code> in package <span>utils</span> for building and retrieving the help search database used by <code>help.search()</code>, along with functions for inspecting the concepts and keywords in the help search database.</li>
<li>New function <code>.getNamespaceInfo()</code>, a no-check version of <code>getNamespaceInfo()</code> mostly for internal speedups.</li>
<li>The help search system now takes <span>keyword</span> entries in Rd files which are not standard keywords (as given in &lsquo;<span>KEYWORDS</span>&rsquo; in the <strong>R</strong> documentation directory) as concepts. For standard keyword entries the corresponding descriptions are additionally taken as concepts.</li>
<li>New <code>lengths()</code> function for getting the lengths of all elements in a list.</li>
<li>New function <code>toTitleCase()</code> in package <span>tools</span>, tailored to package titles.</li>
<li>The matrix methods of <code>cbind()</code> and <code>rbind()</code> allow matrices as inputs which have <em>2^31</em> or more elements. (For <code>cbind()</code>, wish of <a href="https://bugs.r-project.org/bugzilla3/show_bug.cgi?id=16198" target="_blank">PR#16198</a>.)</li>
<li>The default method of <code>image()</code> has an explicit check for a numeric or logical matrix (which was always required).</li>
<li><code>URLencode()</code> will not by default encode further URLs which appear to be already encoded.</li>
<li><code>BIC(mod)</code> and <code>BIC(mod, mod2)</code> now give non-NA numbers for <code>arima()</code> fitted models, as <code>nobs(mod)</code> now gives the number of &ldquo;used&rdquo; observations for such models. This fixes <a href="https://bugs.r-project.org/bugzilla3/show_bug.cgi?id=16198" target="_blank">PR#16198</a>, quite differently than proposed there.</li>
<li>The <code>print()</code> methods for <code>"htest"</code>, <code>"pairwise.htest"</code> and <code>"power.htest"</code> objects now have a <code>digits</code> argument defaulting to (a function of) <code>getOption("digits")</code>, and influencing all printed numbers coherently. Unavoidably, this changes the display of such test results in some cases.</li>
<li>Code completion for namespaces now recognizes all loaded namespaces, rather than only the ones that are also attached.</li>
<li>The code completion mechanism can now be replaced by a user-specified completer function, for (temporary) situations where the usual code completion is inappropriate.</li>
<li><code>unzip()</code> will now warn if it is able to detect truncation when unpacking a file of 4GB or more (related to <a href="https://bugs.r-project.org/bugzilla3/show_bug.cgi?id=16243" target="_blank">PR#16243</a>).</li>
<li><code>methods()</code> reports S4 in addition to S3 methods; output is simplified when the <code>class</code> argument is used. <code>.S3methods()</code> and <code>methods::.S4methods()</code> report S3 and S4 methods separately.</li>
<li>Higher order functions such as the <code>apply</code> functions and <code>Reduce()</code> now force arguments to the functions they apply in order to eliminate undesirable interactions between lazy evaluation and variable capture in closures. This resolves <a href="https://bugs.r-project.org/bugzilla3/show_bug.cgi?id=16093" target="_blank">PR#16093</a>.</li>
</ul><p>More at http://cran.rstudio.com/</p><p>Reference: http://www.r-bloggers.com/r-3-2-0-is-released-using-the-installr-package-to-upgrade-in-windows-os/</p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/45306/the-genes-that-travel-together-a-genomic-detective-story</guid>
	<pubDate>Fri, 11 Sep 2026 13:00:36 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/45306/the-genes-that-travel-together-a-genomic-detective-story</link>
	<title><![CDATA[The Genes That Travel Together: A Genomic Detective Story]]></title>
	<description><![CDATA[<p>Imagine looking through thousands of microbial genomes and discovering two genes that repeatedly appear together. The obvious conclusion is that they must somehow be connected&mdash;that perhaps they work together, participate in the same pathway, or depend on each other. But evolution has a way of leaving misleading clues. What if these two genes are found together simply because they were inherited from the same ancient ancestor? In that case, their apparent association may have little to do with their biological function; it may simply be a reflection of shared evolutionary history. This is the intriguing problem addressed by CORGIAS (https://github.com/ynishimuraLv/corgias), a computational framework developed to distinguish genuine gene associations from correlations created by common ancestry.</p><p>Instead of asking only whether two genes occur together across genomes, CORGIAS asks a deeper question: did these genes actually evolve together, repeatedly gaining or losing their presence in concert, or are they merely travelling together because of their inherited history? The framework introduces two complementary approaches, Ancestral State Adjustment (ASA) and the Simultaneous EVolution test (SEV), which incorporate evolutionary information into the search for gene associations. This distinction becomes increasingly important as genome sequencing continues to uncover enormous numbers of microbial genomes, many from organisms that have never been cultured and whose genes remain functionally mysterious. In this growing genomic landscape, simply finding a gene is no longer enough&mdash;we need clues about what that gene might be doing. CORGIAS approaches this problem almost like a genomic detective: rather than treating every association as evidence, it reconstructs the evolutionary story behind the association and asks whether the evidence survives that history. By doing so, it offers a way to separate coincidence from biological connection and potentially uncover functional relationships hidden within the vast microbial genomic landscape. The broader message is beautifully simple: genes do not evolve in isolation, and understanding what they do may require us to look beyond where they are today and reconstruct how they arrived there. Sometimes, the most important clue in a genome is not the gene itself, but the evolutionary journey it has taken.</p><p>More at&nbsp;https://academic.oup.com/nargab/article/7/4/lqaf182/8377910?</p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/22239/jrf-bioinformatics-at-national-institute-of-high-security-animal-diseases-icar</guid>
  <pubDate>Tue, 28 Apr 2015 02:21:15 -0500</pubDate>
  <link></link>
  <title><![CDATA[JRF Bioinformatics at National Institute of High Security Animal Diseases (ICAR)]]></title>
  <description><![CDATA[
<p>F.No. 4-59/2013-NIHSAD Dated: 21st April, 2015</p>

<p>SRF/ JRF job vacancies in National Institute of High Security Animal Diseases (ICAR)</p>

<p>Name of Post : JRF</p>

<p>No. of Post : 01</p>

<p>Qualification : M.V.Sc or M.Tech./M.Sc. (preferably with NET qualification) in one of following disciplines. (Biotechnology/Molecular Biology/Genetics/Microbiology/Bioinformatics or equivalent Life Sciences discipline). Desirable: Working Knowledge in the areas of Recombinant DNA Techniques, Cell Culture, Handling Laboratory Animals, Genomics.</p>

<p>Emolument : Rs.16,000/-</p>

<p>Age Limit : Up to 30 years</p>

<p>Name of Post : Project Assistant</p>

<p>No of Post : 01</p>

<p>Qualifications : First class M.Sc. /B.E/B.Tech. in one of the following disciplines Biotechnology/ Bioinformatics/ Microbiology or equivalent Life Sciences discipline). Desirable : Exposure of working in research environment, Good command over written/spoken English and computer applications.</p>

<p>Emolument : Rs.8000/-</p>

<p>Age Limit : Upto 28 years</p>

<p>Name of Post : Project Assistant</p>

<p>No of Post : 01</p>

<p>Qualification : First class M.Sc. /B.V.Sc. and A.H., B.Tech. /B.E. in Life Sciences and related areas. Desirable: Exposure of working in research environment, Good command over written/type written/spoken English and computer applications. </p>

<p>Emoluments : Rs. 8000/-</p>

<p>Age Limit : Up to 28 years<br />How to apply</p>

<p>Desirous candidates may send their applications by e-mail (techcell@hsadl.nic.in ) followed by post in the prescribed proforma latest by 11/05/2015. Walk-in-Interview will be held at NIHSAD, Kokta Road, Anand Nagar, Bhopal-462022.</p>

<p>http://www.nihsad.nic.in/pdf/Advt.pdf</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/3868/next-generation-sequencing-ngs-tutorials</guid>
	<pubDate>Sat, 24 Aug 2013 06:01:37 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/3868/next-generation-sequencing-ngs-tutorials</link>
	<title><![CDATA[Next Generation Sequencing (NGS) Tutorials]]></title>
	<description><![CDATA[<p>Institute of computational biomedicine, Cornell University provide an NGS workshop tutorial at&nbsp;<a href="http://chagall.med.cornell.edu/NGScourse/">http://chagall.med.cornell.edu/NGScourse/</a>&nbsp;</p>
<p>You can also add your favourite NGS educational material, or workshop tutorial by commenting on this bookmarks for user benefit.&nbsp;</p>
<p>Understanding the basics of genome sequencing:</p>
<p>Tutorial by Luke Jostins.</p>
<p>http://www.genetic-inference.co.uk/blog/2009/04/basics-sequencing-dna-part-1/</p>
<p>http://www.genetic-inference.co.uk/blog/2009/08/basics-sequencing-dna-part-2/</p>
<p>A window into third-generation sequencing</p>
<p>http://hmg.oxfordjournals.org/content/19/R2/R227.full.pdf</p>
<p>==============================================</p>
<p>NGS data analysis pipelines</p>
<ul>
<li><strong>Detecting and annotating genetic variations using the HugeSeq pipeline</strong>&nbsp; DOI: <a href="http://dx.doi.org/10.1038/nbt.2134">10.1038/nbt.2134</a></li>
<li><strong> NARWHAL, a primary analysis pipeline for NGS data</strong> <a href="http://bioinformatics.oxfordjournals.org/cgi/content/abstract/28/2/284?etoc">http://bioinformatics.oxfordjournals.org/cgi/content/abstract/28/2/284?etoc</a></li>
<li><strong>RseqFlow: Workflows for RNA-Seq data analysis</strong>&nbsp; DOI: <a href="http://dx.doi.org/10.1093/bioinformatics/btr441">10.1093/bioinformatics/btr441</a></li>
<li><strong>ngs_backbone: a pipeline for read cleaning, mapping and SNP calling using Next Generation Sequence</strong>&nbsp;&nbsp;<a href="http://dx.doi.org/10.1186/1471-2164-12-285">10.1186/1471-2164-12-285</a></li>
<li><strong>A framework for variation discovery and genotyping using next-generation DNA sequencing data</strong>&nbsp; PubMed: <a href="http://www.ncbi.nlm.nih.gov/pubmed/21478889">21478889</a></li>
<li><strong>SNiPlay: a web-based tool for detection, management and analysis of SNPs. Application to grapevine diversity projects</strong>&nbsp; DOI: <a href="http://dx.doi.org/10.1186/1471-2105-12-134">10.1186/1471-2105-12-134</a> Abstract: <a href="http://www.biomedcentral.com/1471-2105/12/134/abstract">http://www.biomedcentral.com/1471-2105/12/134/abstract</a></li>
<li><strong>WEP: a high-performance analysis pipeline for whole-exome data&nbsp;</strong>http://www.biomedcentral.com/1471-2105/14/S7/S11</li>
<li><strong>DDBJ read annotation pipeline: a cloud computing-based pipeline for high-throughput analysis of next-generation sequencing data.&nbsp;</strong>http://www.ncbi.nlm.nih.gov/pubmed/23657089</li>
<li><strong>GATK: a Toolkit for Genome Analysis&nbsp;</strong>http://www.broadinstitute.org/gatk/</li>
<li><strong>Metagenomics</strong>:http://www.nbic.nl/education/nbic-phd-school/course-schedule/ngsmetagenomics/</li>
<li><strong>RNASeq</strong>:http://www.nbic.nl/education/nbic-phd-school/course-schedule/ngsrnaseq/</li>
<li><strong>Bioinformatics and Seq courses</strong>:&nbsp;http://www.isb-sib.ch/training/training-activities-schedule/archive-2013.html</li>
<li><strong>Variant Detection (Model organism) Advanced tutorial</strong> https://docs.google.com/document/pub?id=1CuKkKylVDb03tnN7RSWl5EUzleetn0ctjmvaidPKLxM</li>
<li><strong>Variant Detection Introductory tutorial</strong> https://docs.google.com/document/pub?id=1ZRzrjjOCvtAu3m-IKL-rbJ1f4On60dDL_IEwG7oejdI</li>
<li><strong>Microbial de novo Assembly for Illumina Data Introductory tutorial</strong> https://docs.google.com/document/pub?id=1N3AB9ptISUu4zULqe1kXpVF0BDyGb5f5yzxWSJd_WNM</li>
<li><strong>RNAseq Differential Gene Expression Introductory tutorial</strong> https://docs.google.com/document/pub?id=1KbTiBHtvHLfPRZ39AY3uriazrINA8TJzgjjwn1zPP7Y</li>
</ul>
<blockquote>
<p>" Please add your favourite NGS link below in comment section for the benefit of bioinformatics community ".&nbsp;</p>
</blockquote><p>Address of the bookmark: <a href="http://chagall.med.cornell.edu/NGScourse/" rel="nofollow">http://chagall.med.cornell.edu/NGScourse/</a></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/22285/project-associate-bioinformatics-iit-mandi</guid>
  <pubDate>Wed, 06 May 2015 06:18:47 -0500</pubDate>
  <link></link>
  <title><![CDATA[Project Associate Bioinformatics @ IIT Mandi]]></title>
  <description><![CDATA[
<p>Eligibility : MSc(Bio-Informatics, Bio-Tech), BSc, BE/B.Tech(Bio-Medical /Bio-Technology Engg, CSE)</p>

<p>Location : Kulu</p>

<p>Job Category : Govt Jobs, Research</p>

<p>Last Date : 20 May 2015</p>

<p>Job Type : Full Time</p>

<p>Hiring Process : Walk - In<br />IIT Mandi - Job Details<br />IIT Mandi</p>

<p>Project Associate Bioinformatics Job vacancies in IIT Mandi on purely temporary</p>

<p>Project: “Exploring the Human Microbiome: A hunt for the candidates for Pre- and Pro-biotics.”</p>

<p>Minimum Qualification and Experience: M.Sc. in Bioinformatics OR B.Tech / BE in Bioinformatics OR M. Sc. in Biotechnology / Life sciences or related areas with Diploma or relevant experience in Bioinformatics OR B.Tech in Biotechnology / Computer Science or MCA or B. Sc. in Life Sciences or related areas with PG diploma in Bioinformatics. Candidates with experience in NGS data handling and analysis will be preferred. Tenure: Initially for one year, extendable based upon performance.</p>

<p>No of Posts: 01</p>

<p>Salary: Rs. 12000- 18000/- per month.</p>

<p>How to apply</p>

<p>Interested candidates can come for a Walk-in-Interview on 20th May 2015 starting at 8:30 AM at the Academic Block, Indian Institute of Technology (IIT), Mandi, Vallabh College Campus, Near Bus Stand, Mandi, HP. The candidates should bring along their curriculum vitae (CV) and copies of educational and experience certificates. In case of any queries please contact: Dr. Tulika Prakash Srivastava (Principal Investigator), Indian Institute of Technology Mandi, Near Bus Stand Mandi - 175 001, Himachal Pradesh.</p>

<p>More at</p>

<p>http://www.iitmandi.ac.in/administration/advrt/Walk-in-interview_Ad.pdf</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/23174/scaffolding-of-a-bacterial-genome-using-minion-nanopore-sequencing</guid>
	<pubDate>Tue, 07 Jul 2015 16:59:25 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/23174/scaffolding-of-a-bacterial-genome-using-minion-nanopore-sequencing</link>
	<title><![CDATA[Scaffolding of a bacterial genome using MinION nanopore sequencing]]></title>
	<description><![CDATA[<p><span>Second generation sequencing has revolutionized genomic studies. However, most genomes contain repeated DNA elements that are longer than the read lengths achievable with typical sequencers, so the genomic order of several generated contigs cannot be easily resolved. A new generation of sequencers offering substantially longer reads is emerging, notably the Pacific Biosciences (PacBio) RS II system and the MinION system, released in early 2014 by Oxford Nanopore Technologies through an early access program.</span></p><p>Address of the bookmark: <a href="http://www.nature.com/srep/2015/150707/srep11996/full/srep11996.html" rel="nofollow">http://www.nature.com/srep/2015/150707/srep11996/full/srep11996.html</a></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/22317/project-associate-bioinformatics-central-food-technological-research-institute-cftri</guid>
  <pubDate>Tue, 19 May 2015 07:01:12 -0500</pubDate>
  <link></link>
  <title><![CDATA[Project Associate Bioinformatics @ Central Food Technological Research Institute (CFTRI)]]></title>
  <description><![CDATA[
<p>Central Food Technological Research Institute (CFTRI)</p>

<p>Project Assistant (Level-II) job position in Central Food Technological Research Institute (CFTRI) on a temporary contractual basis in the research project (GAP 0469) funded by Science &amp; Engineering Research Board (SERB), Government of India, New Delhi tenable at the Lipidomics Centre, CSIR-CFTRI, Mysore, Karnataka</p>

<p>Name of the Position : </p>

<p>Qualification : First class M. Sc. in Biochemistry/Microbiology/Genetics/ Bioinformatics with good academic record and preferably with experience in molecular biology techniques and basic knowledge of molecular biology and biological chemistry</p>

<p>Emoluments : Rs. 12,000/- per month (Consolidated)</p>

<p>Age Limit : The upper age limit for applying shall be 28 years (as on 22-5-2015), which is relaxed for candidates belonging to Scheduled Castes/Schedule Tribes, Women, Persons with Disabilities (PWD) and OBCs as per GoI norms. <br /> <br />How to apply</p>

<p>Eligible candidates may send their complete Bio-data with e-mail address/contact phone number along with attested copies of the necessary certificates through post to Prof. Ram Rajasekharan, Lipidomics Centre, Department of Lipid Science, CSIR-CFTRI, Mysore-570 020, Karnataka (email: ram@cftri.res.in) on or before 22.05.2015</p>

<p>More at http://www.cftri.com/pa_gap0469.html</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32862/gam-ngs-genomic-assemblies-merger-for-next-generation-sequencing</guid>
	<pubDate>Fri, 19 May 2017 07:44:14 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32862/gam-ngs-genomic-assemblies-merger-for-next-generation-sequencing</link>
	<title><![CDATA[GAM-NGS: genomic assemblies merger for next generation sequencing]]></title>
	<description><![CDATA[<p><span>GAM-NGS is a tool able to merge two or more assemblies in order to improve contiguity and correctness. It can be used on all NGS-based assembly projects and it shows its full potential with multi-library Illumina-based projects. With more than 20 available assemblers it is hard to select the best tool. In this context we propose a tool that improves assemblies (and, as a by-product, perhaps even assemblers) by merging them and selecting the generating that is most likely to be correct.</span></p><p>Address of the bookmark: <a href="https://github.com/vice87/gam-ngs" rel="nofollow">https://github.com/vice87/gam-ngs</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/22430/nrco-vacancies-for-junior-research-fellow-%E2%80%93-pakyong-sikkim</guid>
  <pubDate>Thu, 28 May 2015 19:10:07 -0500</pubDate>
  <link></link>
  <title><![CDATA[NRCO Vacancies For Junior Research Fellow – Pakyong, Sikkim]]></title>
  <description><![CDATA[
<p>Junior Research Fellow<br />Pay Scale:Rs 25,000/-<br />Educational Requirements:MSc (with NET qualification) / M.Tech degree (with or without NET) with minimum 55% marks in Biotechnology/ Bioinformatics/ Molecular Biology or any other related field.<br />Other Qualification:Computer Skills (Linux, Perl, Java, MySQL) with experience in advanced molecular Biology techniques.<br />No of Post: 01<br />How To Apply: Walk-in-Interviews will be held at ICAR-National Research Centre for Orchids,Pakyong 737106, Sikkim for the post of 01 (One) Junior Research Fellow and 01 (One) Project Attendant under Project ‘DBT’s Twinning programme for the NE’ titled “Assessment of chemical and genetic divergence of some fragrant orchids of north-east India for sustainable improvement of community livelihood” as indicated below. The appointment will be on contractual basis and the incumbents shall not have any claim for regular appointment in ICAR.</p>

<p>Details will be available at: http://nrcorchids.nic.in/Employments/Vacancy%20-%20JRF.pdf</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/33506/bedops-v2426-high-performance-genomic-feature-operations</guid>
	<pubDate>Mon, 12 Jun 2017 10:11:01 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/33506/bedops-v2426-high-performance-genomic-feature-operations</link>
	<title><![CDATA[BEDOPS v2.4.26: high-performance genomic feature operations]]></title>
	<description><![CDATA[<p><strong>BEDOPS v2.4.26</strong> is a suite of tools to address common questions raised in genomic studies &mdash; mostly with regard to overlap and proximity relationships between data sets. It aims to be scalable and flexible, facilitating the efficient and accurate analysis and management of large-scale genomic data.</p>
<p>The <a href="https://bedops.readthedocs.io/en/latest/content/overview.html#overview">overview</a> section of the <strong>BEDOPS v2.4.26</strong> documentation summarizes the toolkit, functionality and performance enhancements. The <a href="https://bedops.readthedocs.io/en/latest/index.html#reference">reference</a> table offers documentation for all applications and scripts.</p><p>Address of the bookmark: <a href="https://github.com/bedops/bedops" rel="nofollow">https://github.com/bedops/bedops</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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