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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/26426?offset=120</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31064/cgaln</guid>
	<pubDate>Wed, 22 Feb 2017 05:14:15 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31064/cgaln</link>
	<title><![CDATA[Cgaln]]></title>
	<description><![CDATA[<p>Cgaln (Coarse grained alignment) is a program designed to align a pair of whole genomic sequences of not only bacteria but also entire chromosomes of vertebrates on a nominal desktop computer. Cgaln performs an alignment job in two steps, at the block level and then at the nucleotide level. The former "coarse-grained" alignment can explore genomic rearrangements and reduce the regions to be analyzed in the next step. The latter is devoted to detailed alignment within the limited regions found in the first stage. The output of Cgaln is 'glocal' in the sense that rearrangements are taken into consideration while each alignable region is extended as long as possible. Thus, Cgaln is not only fast and memory-efficient, but also can filter noisy outputs without missing the most important homologous segment pairs.</p>
<p>http://www.iam.u-tokyo.ac.jp/chromosomeinformatics/rnakato/cgaln/</p><p>Address of the bookmark: <a href="http://www.iam.u-tokyo.ac.jp/chromosomeinformatics/rnakato/cgaln/" rel="nofollow">http://www.iam.u-tokyo.ac.jp/chromosomeinformatics/rnakato/cgaln/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30829/mercator</guid>
	<pubDate>Mon, 06 Feb 2017 04:20:36 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30829/mercator</link>
	<title><![CDATA[Mercator]]></title>
	<description><![CDATA[<p><span>Our basic strategy in building homology maps is to use exons that are orthologous in multiple genomes as map "anchors." Given K genomes, the steps in the map construction are as follows:</span></p>
<ul>
<li>For each genome, obtain a set of exon annotations. These annotations can be a combination of both exon predictions (e.g. Genscan) and annotations that have been experimentally verified (e.g. RefSeq). Ideally, we would like to have these annotations be as sensitive as possible. Specificity is not a concern, as incorrect annotations are not likely not have significant alignments with other gene annotations.</li>
<li>Compare all exons against all exons in other genomes and record significant alignments between exons. Currently, we use&nbsp;<a href="https://www.biostat.wisc.edu/~cdewey/mercator/#refBLAT">BLAT</a>&nbsp;to do this all-vs-all comparison with alignments being performed in protein space.</li>
<li>Construct a graph with each vertex corresponding to a exon and edges between vertices whose corresponding exons have significant alignments.</li>
<li>Identify cliques in this graph. These cliques are potential anchors to be used in the map.</li>
<li>Starting with the largest cliques (those that have exons in all or most of the genomes), join neighboring (adjacent in genomic coordinates, in each genome) cliques to form&nbsp;runs. Smaller cliques that are inconsistent with runs formed by larger cliques are filtered out. After the smallest cliques have been considered, cliques that are not part of a run are discarded.</li>
<li>The extents of each run in each genome are outputted as orthologous segments. The cliques from each run are used to output the exact genomic coordinates of anchors within each orthologous segment. These anchors can be used by genomic alignment programs (such as&nbsp;<a href="https://www.biostat.wisc.edu/~cdewey/mercator/#refMAVID">MAVID</a>) to do a detailed alignment of each orthologous segment.</li>
</ul>
<p>https://www.biostat.wisc.edu/~cdewey/mercator/</p><p>Address of the bookmark: <a href="https://www.biostat.wisc.edu/~cdewey/mercator/" rel="nofollow">https://www.biostat.wisc.edu/~cdewey/mercator/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31089/conpade-genome-assembly-ploidy-estimation-from-next-generation-sequencing-data</guid>
	<pubDate>Fri, 24 Feb 2017 04:55:41 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31089/conpade-genome-assembly-ploidy-estimation-from-next-generation-sequencing-data</link>
	<title><![CDATA[ConPADE: Genome Assembly Ploidy Estimation from Next-Generation Sequencing Data]]></title>
	<description><![CDATA[<p><span>ConPADE (Contig Ploidy and Allele Dosage Estimation), a probabilistic method that estimates the ploidy of any given contig/scaffold based on its allele proportions. In the process, they report findings regarding errors in sequencing. The method can be used for whole genome shotgun (WGS) sequencing data. They also show applicability of the method for variant calling and allele dosage estimation. Results for simulated and real datasets are discussed and provide evidence that ConPADE performs well as long as enough sequencing coverage is available, or the true contig ploidy is low.&nbsp;</span></p>
<p><span>https://github.com/microsoftgenomics</span></p><p>Address of the bookmark: <a href="https://github.com/microsoftgenomics" rel="nofollow">https://github.com/microsoftgenomics</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31139/pbsuite-software-for-long-read-sequencing-data-from-pacbio</guid>
	<pubDate>Mon, 27 Feb 2017 09:54:47 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31139/pbsuite-software-for-long-read-sequencing-data-from-pacbio</link>
	<title><![CDATA[PBSuite: Software for Long-Read Sequencing Data from PacBio]]></title>
	<description><![CDATA[<p><span>PBJelly - the genome upgrading tool.&nbsp;</span><br><span>PBHoney - the structural variation discovery tool&nbsp;</span><br><br><span>Both are contained within the PBSuite code found in downloads.</span><br><br><span>----- PBJelly -----</span><br><span>Read The Paper&nbsp;</span><br><a href="http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0047768" target="_blank">http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0047768</a><br><br><span>PBJelly is a highly automated pipeline that aligns long sequencing reads (such as PacBio RS reads or long 454 reads in fasta format) to high-confidence draft assembles. PBJelly fills or reduces as many captured gaps as possible to produce upgraded draft genomes.&nbsp;</span><br><br><span>----- PBHoney -----</span><br><span>Read The Paper</span><br><a href="http://www.biomedcentral.com/1471-2105/15/180/abstract" target="_blank">http://www.biomedcentral.com/1471-2105/15/180/abstract</a><br><br><span>PBHoney is an implementation of two variant-identification approaches designed to exploit the high mappability of long reads (i.e., greater than 10,000 bp). PBHoney considers both intra-read discordance and soft-clipped tails of long reads to identify structural variants.</span></p><p>Address of the bookmark: <a href="https://sourceforge.net/projects/pb-jelly/" rel="nofollow">https://sourceforge.net/projects/pb-jelly/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31295/mycc-accurate-binning-of-metagenomic-contigs-via-automated-clustering-sequences-using-information-of-genomic-signatures-and-marker-genes</guid>
	<pubDate>Fri, 03 Mar 2017 08:34:23 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31295/mycc-accurate-binning-of-metagenomic-contigs-via-automated-clustering-sequences-using-information-of-genomic-signatures-and-marker-genes</link>
	<title><![CDATA[MyCC: Accurate binning of metagenomic contigs via automated clustering sequences using information of genomic signatures and marker genes]]></title>
	<description><![CDATA[<p><span>MyCC, an automated binning tool that combines genomic signatures, marker genes and optional contig coverages within one or multiple samples, in order to visualize the metagenomes and to identify the reconstructed genomic fragments.</span></p>
<p><span>More at&nbsp;http://www.nature.com/articles/srep24175</span></p><p>Address of the bookmark: <a href="https://sourceforge.net/projects/sb2nhri/files/MyCC/" rel="nofollow">https://sourceforge.net/projects/sb2nhri/files/MyCC/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31345/prokka-tool-for-the-rapid-annotation-of-prokaryotic-genomes</guid>
	<pubDate>Mon, 06 Mar 2017 03:49:57 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31345/prokka-tool-for-the-rapid-annotation-of-prokaryotic-genomes</link>
	<title><![CDATA[Prokka: tool for the rapid annotation of prokaryotic genomes]]></title>
	<description><![CDATA[<p>Prokka is a software tool for the rapid annotation of prokaryotic genomes. A typical 4 Mbp genome can be fully annotated in less than 10 minutes on a quad-core computer, and scales well to 32 core SMP systems. It produces GFF3, GBK and SQN files that are ready for editing in Sequin and ultimately submitted to Genbank/DDJB/ENA.</p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="http://www.vicbioinformatics.com/software.prokka.shtml" rel="nofollow">http://www.vicbioinformatics.com/software.prokka.shtml</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/42921/run-bash-script-in-perl-program</guid>
	<pubDate>Sat, 27 Feb 2021 01:42:23 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/42921/run-bash-script-in-perl-program</link>
	<title><![CDATA[Run bash script in Perl program !]]></title>
	<description><![CDATA[<p>BioPerl is a compilation of Perl modules that can be used to build bioinformatics-related Perl scripts. It is used, for example, in the development of source codes, standalone software/tools, and algorithms in bioinformatics programmes. Different modules are easy to instal and include, making it easier to perform different functions. Despite the fact that Python is commonly favoured over Perl, some bioinformatics software, such as the standalone version of 'alienomics', is written in Perl. Often it's a major problem for beginners to execute certain Unix/shell commands in Perl script, so it's hard to determine which feature is unique to a situation.</p><div style="background-color: white;">Perl provides various features and operators for the execution of external commands (described as follows), which are unique in their own way.</div><div style="background-color: white;">&nbsp;</div><div style="background-color: white;">They vary slightly from one another, making it difficult for Perl beginners to choose between them.</div><div style="background-color: white;">&nbsp;</div><div style="background-color: white;"><strong>1. IPC::Open2</strong></div><p>More at https://bioinformaticsonline.com/snippets/view/42919/perl-ipcopen2-module</p><p><strong>2. exec&rdquo;&rdquo;</strong></p><p><em>&nbsp;syntax:&nbsp;</em><code>exec "command";</code></p><div style="background-color: #edfbff;">It's a Perl function (perlfunc) that executes a command but never returns, similar to a function's return statement.</div><div style="background-color: white;">While running the command, it keeps processing the script and does not wait until it finishes first, returns false when the command is not found, but never returns true.</div><p><strong>3. Backticks &ldquo; or qx//</strong></p><p><em>syntax:&nbsp;</em><code>`command`;</code></p><p><em>syntax:&nbsp;</em><code>qx/command/;</code></p><div style="background-color: white;">It's a Perl operator (perlop) that executes a command and then resumes the Perl script once the command has ended, but the return value is the command's STDOUT.</div><p><strong>4. IPC::Open3</strong></p><p><em>syntax:&nbsp;</em><code>$output =&nbsp;open3(\*CHLD_IN, \*CHLD_OUT, \*CHLD_ERR,&nbsp;'command arg1 arg2', 'optarg',...);</code></p><p style="text-align: justify;"><code></code>It is very similar to <code>IPC::Open2</code> with the capability to capture all three file handles of the process, i.e., STDIN, STDOUT, and STDERR. It can also be used with or without the shell. You can read about it more in the documentation: <a href="https://perldoc.perl.org/IPC/Open3.html" target="_blank">IPC::Open3</a>.</p><p><code>$output = open3(my $o ut,&nbsp;my $in, 'command arg1 arg2');</code></p><p>OR without using the shell</p><p><code>$output = open3(my $out,&nbsp;my $in, 'command', 'arg1', 'arg2');</code></p><p><strong>5.a2p</strong></p><p><em>syntax:&nbsp;</em><code>a2p [options] [awkscript]</code></p><p>There is a Perl utility known as <code>a2p</code> which translates <code>awk</code> command to Perl. It takes awk script as input and generates a comparable Perl script as the output. Suppose, you want to execute the following <code>awk</code> statement</p><p><code>awk '{$1 = ""; $2 = ""; print}' f1.txt</code></p><p>This statement gives error sometimes even after escaping the variables (\$1, \$2) but by using <code>a2p</code> it can be easily converted to Perl script:</p><p>For further information, you can read it&rsquo;s documentation: <code><a href="https://perldoc.perl.org/a2p.html" target="_blank">a2p</a></code></p><p>More help at https://bioinformaticsonline.com/snippets/view/42920/perl-script-to-run-awk-inside-perl</p><p><strong>6. system()</strong></p><p><em>syntax:&nbsp;</em><code>system( "command" );</code></p><p>It is also a Perl function (<a href="https://perldoc.perl.org/functions/system.html" target="_blank">perlfunc</a>) that executes a command and waits for it to get finished first and then resume the Perl script. The return value is the exit status of the command. It can be called in two ways:</p><p><code>system( "command arg1 arg2" );</code></p><p>OR</p><p><code>system( "command", "arg1", "arg2" );</code></p><p>HELP</p><p>Here are some useful Perl cheat sheets that can be used as a quick reference guide.--&nbsp;<a href="https://www.pcwdld.com/perl-cheat-sheet" target="_blank">https://www.pcwdld.com/perl-cheat-sheet</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31377/groopm-metagenomic-binning-toolset</guid>
	<pubDate>Tue, 07 Mar 2017 08:59:45 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31377/groopm-metagenomic-binning-toolset</link>
	<title><![CDATA[GroopM: Metagenomic binning toolset]]></title>
	<description><![CDATA[<p>GroopM is a metagenomic binning toolset. It leverages spatio-temoral<br>dynamics (differential coverage) to accurately (and almost automatically)<br>extract population genomes from multi-sample metagenomic datasets.</p>
<p>GroopM is largely parameter-free. Use: groopm -h for more info.</p>
<p>For installation and usage instructions see : http://ecogenomics.github.io/GroopM/</p><p>Address of the bookmark: <a href="https://github.com/ecogenomics/GroopM" rel="nofollow">https://github.com/ecogenomics/GroopM</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31552/multigenome-assembly</guid>
	<pubDate>Tue, 14 Mar 2017 04:41:23 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31552/multigenome-assembly</link>
	<title><![CDATA[Multigenome assembly]]></title>
	<description><![CDATA[<p>This project contains scripts and tutorials on how to assemble individual microbial genomes from metagenomes, as described in:</p>
<p>Genome sequences of rare, uncultured bacteria obtained by differential coverage binning of multiple metagenomes</p>
<p>Mads Albertsen, Philip Hugenholtz, Adam Skarshewski, Gene W. Tyson, K&aring;re L. Nielsen and Per .H. Nielsen</p>
<p>Nature Biotechnology 2013, doi:&nbsp;<a href="http://www.nature.com/nbt/journal/vaop/ncurrent/abs/nbt.2579.html">10.1038/nbt.2579</a></p>
<p>See the associated&nbsp;<a href="http://madsalbertsen.github.io/multi-metagenome/">online guide</a>&nbsp;for detailed information.</p>
<p>https://github.com/MadsAlbertsen/multi-metagenome</p><p>Address of the bookmark: <a href="https://github.com/MadsAlbertsen/multi-metagenome" rel="nofollow">https://github.com/MadsAlbertsen/multi-metagenome</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32184/metagenomics-assembly-workshop</guid>
	<pubDate>Tue, 18 Apr 2017 04:28:19 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32184/metagenomics-assembly-workshop</link>
	<title><![CDATA[Metagenomics assembly workshop !!]]></title>
	<description><![CDATA[<div>
<div>
<div id="welcome-to-metagenomics-workshop">
<p>Welcome to the one-day metagenomics assembly workshop. This tutorial will guide you through the typical steps of metagenome assembly and binning.</p>
<div>
<ul>
<li><a href="http://denbi-metagenomics-workshop.readthedocs.io/en/latest/data.html">The Tutorial Data Set</a></li>
<li><a href="http://denbi-metagenomics-workshop.readthedocs.io/en/latest/qc/index.html">FastQC Quality Control</a></li>
<li><a href="http://denbi-metagenomics-workshop.readthedocs.io/en/latest/assembly/index.html">Assembly</a>
<ul>
<li><a href="http://denbi-metagenomics-workshop.readthedocs.io/en/latest/assembly/velvet.html">Velvet Assembly</a></li>
<li><a href="http://denbi-metagenomics-workshop.readthedocs.io/en/latest/assembly/megahit.html">MEGAHIT Assembly</a></li>
<li><a href="http://denbi-metagenomics-workshop.readthedocs.io/en/latest/assembly/idba_ud.html">IDBA-UD Assembly</a></li>
<li><a href="http://denbi-metagenomics-workshop.readthedocs.io/en/latest/assembly/ray.html">Ray Assembly</a></li>
</ul>
</li>
<li><a href="http://denbi-metagenomics-workshop.readthedocs.io/en/latest/geneprediction/index.html">Gene Prediction</a></li>
<li><a href="http://denbi-metagenomics-workshop.readthedocs.io/en/latest/evaluation/index.html">Assembly Evaluation</a>
<ul>
<li><a href="http://denbi-metagenomics-workshop.readthedocs.io/en/latest/evaluation/mapping.html">Read Mapping</a></li>
<li><a href="http://denbi-metagenomics-workshop.readthedocs.io/en/latest/evaluation/metaquast.html">MetaQUAST</a></li>
</ul>
</li>
<li><a href="http://denbi-metagenomics-workshop.readthedocs.io/en/latest/binning/index.html">Binning</a>
<ul>
<li><a href="http://denbi-metagenomics-workshop.readthedocs.io/en/latest/binning/maxbin.html">MaxBin Binning</a></li>
<li><a href="http://denbi-metagenomics-workshop.readthedocs.io/en/latest/binning/metabat.html">MetaBAT Binning</a></li>
</ul>
</li>
<li><a href="http://denbi-metagenomics-workshop.readthedocs.io/en/latest/classification/index.html">Classification</a>
<ul>
<li><a href="http://denbi-metagenomics-workshop.readthedocs.io/en/latest/classification/kraken.html">Kraken Taxonomic Sequence Classification System</a></li>
</ul>
</li>
</ul>
</div>
</div>
</div>
</div>
<div><a href="http://denbi-metagenomics-workshop.readthedocs.io/en/latest/data.html" title="The Tutorial Data Set">Next&nbsp;<span></span></a>
<p>&nbsp;</p>
</div><p>Address of the bookmark: <a href="http://denbi-metagenomics-workshop.readthedocs.io/en/latest/index.html" rel="nofollow">http://denbi-metagenomics-workshop.readthedocs.io/en/latest/index.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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