<?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/44373?offset=650</link>
	<atom:link href="https://bioinformaticsonline.com/related/44373?offset=650" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43101/luigi-a-python-package-that-helps-you-build-complex-pipelines-of-batch-jobs</guid>
	<pubDate>Thu, 24 Jun 2021 05:43:31 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43101/luigi-a-python-package-that-helps-you-build-complex-pipelines-of-batch-jobs</link>
	<title><![CDATA[Luigi: a Python package that helps you build complex pipelines of batch jobs.]]></title>
	<description><![CDATA[<p>Luigi is a Python (3.6, 3.7, 3.8, 3.9 tested) package that helps you build complex pipelines of batch jobs. It handles dependency resolution, workflow management, visualization, handling failures, command line integration, and much more.</p>
<p>Run <code>pip install luigi</code> to install the latest stable version from <a href="https://pypi.python.org/pypi/luigi">PyPI</a>. <a href="https://luigi.readthedocs.io/en/stable/">Documentation for the latest release</a> is hosted on readthedocs.</p>
<p>Run <code>pip install luigi[toml]</code> to install Luigi with <a href="https://luigi.readthedocs.io/en/stable/configuration.html">TOML-based configs</a> support.</p><p>Address of the bookmark: <a href="https://github.com/spotify/luigi" rel="nofollow">https://github.com/spotify/luigi</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/36502/creating-conda-environment-for-python27</guid>
	<pubDate>Mon, 07 May 2018 08:56:52 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/36502/creating-conda-environment-for-python27</link>
	<title><![CDATA[Creating conda environment for python2.7]]></title>
	<description><![CDATA[<p>TIP: By default, environments are installed into the&nbsp;<code><span>envs</span></code>&nbsp;directory in your conda directory. Run&nbsp;<code><span>conda</span>&nbsp;<span>create</span>&nbsp;<span>--help</span></code>&nbsp;for information on specifying a different path.</p><p>Use the Terminal or an Anaconda Prompt for the following steps.</p><ol>
<li>
<p>To create an environment:</p>
<div>
<div>
<pre><span></span><span>conda</span> <span>create</span> <span>--</span><span>name</span> <span>myenv</span>
</pre>
</div>
</div>
<p>NOTE: Replace&nbsp;<code><span>myenv</span></code>&nbsp;with the environment name.</p>
</li>
<li>
<p>When conda asks you to proceed, type&nbsp;<code><span>y</span></code>:</p>
<div>
<div>
<pre><span></span>proceed ([y]/n)?
</pre>
</div>
</div>
</li>
</ol><p>This creates the myenv environment in&nbsp;<code><span>/envs/</span></code>. This environment uses the same version of Python that you are currently using, because you did not specify a version.</p><p>To create an environment with a specific version of Python:</p><div><div><pre><span></span>conda create -n myenv <span>python</span><span>=</span><span>3</span>.4
</pre></div></div><p>To create an environment with a specific package:</p><div><div><pre><span></span>conda create -n myenv scipy
</pre></div></div><p>OR:</p><div><div><pre><span></span>conda create -n myenv python
conda install -n myenv scipy
</pre></div></div><p>To create an environment with a specific version of a package:</p><div><div><pre><span></span>conda create -n myenv <span>scipy</span><span>=</span><span>0</span>.15.0
</pre></div></div><p>OR:</p><div><div><pre><span></span>conda create -n myenv python
conda install -n myenv <span>scipy</span><span>=</span><span>0</span>.15.0
</pre></div></div><p>To create an environment with a specific version of Python and multiple packages:</p><div><div><pre><span></span>conda create -n myenv <span>python</span><span>=</span><span>3</span>.4 <span>scipy</span><span>=</span><span>0</span>.15.0 astroid babel
</pre></div></div><p>TIP: Install all the programs that you want in this environment at the same time. Installing 1 program at a time can lead to dependency conflicts.</p><p>To automatically install pip or another program every time a new environment is created, add the default programs to the&nbsp;<a href="https://conda.io/docs/user-guide/configuration/use-condarc.html#config-add-default-pkgs">create_default_packages</a>&nbsp;section of your&nbsp;<code><span>.condarc</span></code>&nbsp;configuration file. The default packages are installed every time you create a new environment. If you do not want the default packages installed in a particular environment, use the&nbsp;<code><span>--no-default-packages</span></code>&nbsp;flag:</p><div><div><pre><span></span>conda create --no-default-packages -n myenv python
</pre></div></div><p>TIP: You can add much more to the&nbsp;<code><span>conda</span>&nbsp;<span>create</span></code>&nbsp;command. For details, run&nbsp;<code><span>conda</span>&nbsp;<span>create</span>&nbsp;<span>--help</span></code>.</p><p>➜ redundans git:(master) ✗ conda create --name py27 python=2.7<br />Solving environment: done</p><p><br />==&gt; WARNING: A newer version of conda exists. &lt;==<br /> current version: 4.5.0<br /> latest version: 4.5.2</p><p>Please update conda by running</p><p>$ conda update -n base conda</p><p>&nbsp;</p><p>## Package Plan ##</p><p>environment location: /home/urbe/anaconda3/envs/py27</p><p>added / updated specs: <br /> - python=2.7</p><p><br />The following packages will be downloaded:</p><p>package | build<br /> ---------------------------|-----------------<br /> wheel-0.31.0 | py27_0 61 KB<br /> python-2.7.15 | h1571d57_0 12.1 MB<br /> certifi-2018.4.16 | py27_0 142 KB<br /> sqlite-3.23.1 | he433501_0 1.5 MB<br /> setuptools-39.1.0 | py27_0 582 KB<br /> openssl-1.0.2o | h20670df_0 3.4 MB<br /> pip-10.0.1 | py27_0 1.7 MB<br /> ca-certificates-2018.03.07 | 0 124 KB<br /> ------------------------------------------------------------<br /> Total: 19.6 MB</p><p>The following NEW packages will be INSTALLED:</p><p>ca-certificates: 2018.03.07-0 <br /> certifi: 2018.4.16-py27_0 <br /> libedit: 3.1-heed3624_0 <br /> libffi: 3.2.1-hd88cf55_4 <br /> libgcc-ng: 7.2.0-hdf63c60_3 <br /> libstdcxx-ng: 7.2.0-hdf63c60_3 <br /> ncurses: 6.0-h9df7e31_2 <br /> openssl: 1.0.2o-h20670df_0<br /> pip: 10.0.1-py27_0 <br /> python: 2.7.15-h1571d57_0<br /> readline: 7.0-ha6073c6_4 <br /> setuptools: 39.1.0-py27_0 <br /> sqlite: 3.23.1-he433501_0<br /> tk: 8.6.7-hc745277_3 <br /> wheel: 0.31.0-py27_0 <br /> zlib: 1.2.11-ha838bed_2</p><p>Proceed ([y]/n)? y</p><p><br />Downloading and Extracting Packages<br />wheel 0.31.0: #################################################################################################################################################################################################### | 100% <br />python 2.7.15: ################################################################################################################################################################################################### | 100% <br />certifi 2018.4.16: ############################################################################################################################################################################################### | 100% <br />sqlite 3.23.1: ################################################################################################################################################################################################### | 100% <br />setuptools 39.1.0: ############################################################################################################################################################################################### | 100% <br />openssl 1.0.2o: ################################################################################################################################################################################################## | 100% <br />pip 10.0.1: ###################################################################################################################################################################################################### | 100% <br />ca-certificates 2018.03.07: ###################################################################################################################################################################################### | 100% <br />Preparing transaction: done<br />Verifying transaction: done<br />Executing transaction: done<br />#<br /># To activate this environment, use:<br /># &gt; source activate py27<br />#<br /># To deactivate an active environment, use:<br /># &gt; source deactivate<br />#</p><p>➜ redundans git:(master) ✗ source activate py27</p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44179/python-mini-projects</guid>
	<pubDate>Mon, 16 Jan 2023 02:14:03 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44179/python-mini-projects</link>
	<title><![CDATA[Python Mini Projects !]]></title>
	<description><![CDATA[<p><span>There is a directory for each chapter of the book. Each directory contains a&nbsp;</span><code>test.py</code><span>&nbsp;program you can use with&nbsp;</span><code>pytest</code><span>&nbsp;to check that you have written the program correctly. I have included a short README to describe each exercise. If you have problems writing code (or if you would like to support this project!), the book contains details about the skills you need.</span></p>
<p>https://github.com/kyclark/tiny_python_projects</p><p>Address of the bookmark: <a href="https://github.com/kyclark/tiny_python_projects" rel="nofollow">https://github.com/kyclark/tiny_python_projects</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34445/inc-seq-accurate-single-molecule-reads-using-nanopore-sequencing</guid>
	<pubDate>Mon, 27 Nov 2017 10:38:56 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34445/inc-seq-accurate-single-molecule-reads-using-nanopore-sequencing</link>
	<title><![CDATA[INC-Seq: accurate single molecule reads using nanopore sequencing]]></title>
	<description><![CDATA[<p><span>INC-Seq reads enabled accurate species-level classification, identification of species at 0.1&nbsp;% abundance and robust quantification of relative abundances, providing a cheap and effective approach for pathogen detection and microbiome profiling on the MinION system.</span></p><p>Address of the bookmark: <a href="https://github.com/CSB5/INC-Seq" rel="nofollow">https://github.com/CSB5/INC-Seq</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36607/tarean-a-computational-tool-for-identification-and-characterization-of-satellite-dna-from-unassembled-short-reads</guid>
	<pubDate>Tue, 15 May 2018 02:53:11 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36607/tarean-a-computational-tool-for-identification-and-characterization-of-satellite-dna-from-unassembled-short-reads</link>
	<title><![CDATA[TAREAN: A computational tool for identification and characterization of satellite DNA from unassembled short reads]]></title>
	<description><![CDATA[<p><strong>TA</strong>ndem&nbsp;<strong>RE</strong>peat&nbsp;<strong>AN</strong>alyzer -TAREAN &ndash; is a computational pipeline for&nbsp;<strong>unsupervised identification of satellite repeats</strong>&nbsp;from unassembled sequence reads. The pipeline uses low-pass whole genome sequence reads and performs their graph-based clustering. Resulting clusters, representing all types of repeats, are then examined for the presence of circular structures and putative satellite repeats are reported.</p>
<p><em><strong>How to use TAREAN</strong></em>:</p>
<ul>
<li>Install a local instance of the pipeline using its source code available from&nbsp;<a href="https://bitbucket.org/petrnovak/repex_tarean" target="_blank" title="TAREAN source code">bitbucket repository</a>.</li>
<li>Use&nbsp; public Galaxy-based server at&nbsp;<a href="https://repeatexplorer-elixir.cerit-sc.cz/" target="_blank">https://repeatexplorer-elixir.cerit-sc.cz/</a>. The server is provided in frame of the&nbsp;<a href="https://www.elixir-czech.cz/" target="_blank">Elixir CZ project</a>&nbsp;and is maintained by&nbsp;<a href="https://www.cesnet.cz/" target="_blank">CESNET</a>&nbsp;and&nbsp;<a href="https://www.cerit-sc.cz/en/index.html" target="_blank">CERIT-SC</a>. Simple registration is required to use this service.</li>
</ul>
<p>Development of TAREAN was supported by&nbsp;<a href="https://www.elixir-czech.cz/" target="_blank" title="ELIXIR-CZ">ELIXIR CZ</a>&nbsp;research infrastructure project (MEYS Grant No: LM2015047).</p>
<p><strong><em>References</em></strong></p>
<p>Novak, P., Avila Robledillo, L., Koblizkova, A., Vrbova, I., Neumann, P., Macas, J. (2017) &ndash;&nbsp;<a href="https://academic.oup.com/nar/article/3574061/" target="_blank">TAREAN: a computational tool for identification and characterization of satellite DNA from unassembled short reads</a>.&nbsp;<em>Nucleic Acids Res.</em>, doi:10.1093/nar/gkx257</p><p>Address of the bookmark: <a href="https://bitbucket.org/petrnovak/repex_tarean" rel="nofollow">https://bitbucket.org/petrnovak/repex_tarean</a></p>]]></description>
	<dc:creator>Surabhi Chaudhary</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36812/porechop-tool-for-finding-and-removing-adapters-from-oxford-nanopore-reads</guid>
	<pubDate>Tue, 29 May 2018 07:33:44 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36812/porechop-tool-for-finding-and-removing-adapters-from-oxford-nanopore-reads</link>
	<title><![CDATA[Porechop:  tool for finding and removing adapters from Oxford Nanopore reads]]></title>
	<description><![CDATA[<p>Porechop is a tool for finding and removing adapters from <a href="https://nanoporetech.com/">Oxford Nanopore</a> reads. Adapters on the ends of reads are trimmed off, and when a read has an adapter in its middle, it is treated as chimeric and chopped into separate reads. Porechop performs thorough alignments to effectively find adapters, even at low sequence identity.</p>
<p>Porechop also supports demultiplexing of Nanopore reads that were barcoded with the <a href="https://store.nanoporetech.com/native-barcoding-kit-1d.html">Native Barcoding Kit</a>, <a href="https://store.nanoporetech.com/pcr-barcoding-kit-96.html">PCR Barcoding Kit</a> or <a href="https://store.nanoporetech.com/rapid-barcoding-sequencing-kit.html">Rapid Barcoding Kit</a>.</p><p>Address of the bookmark: <a href="https://github.com/rrwick/Porechop" rel="nofollow">https://github.com/rrwick/Porechop</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37502/alignqc-a-tool-for-assessing-an-alignment-and-generating-reports-that-are-easy-to-share</guid>
	<pubDate>Tue, 07 Aug 2018 04:41:07 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37502/alignqc-a-tool-for-assessing-an-alignment-and-generating-reports-that-are-easy-to-share</link>
	<title><![CDATA[AlignQC: A tool for assessing an alignment, and generating reports that are easy to share]]></title>
	<description><![CDATA[<p><span>Long read alignment analysis. Generate a reports on sequence alignments for mappability vs read sizes, error patterns, annotations and rarefraction curve analysis. The most basic analysis only requires a BAM file, and outputs a web browser compatible xhtml to visualize/share/store/extract analysis results.</span></p>
<p>https://f1000research.com/articles/6-100/</p>
<p>https://github.com/jason-weirather/AlignQC</p><p>Address of the bookmark: <a href="https://www.healthcare.uiowa.edu/labs/au/AlignQC/" rel="nofollow">https://www.healthcare.uiowa.edu/labs/au/AlignQC/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37957/base-a-practical-de-novo-assembler-for-large-genomes-using-long-ngs-reads</guid>
	<pubDate>Fri, 19 Oct 2018 07:25:21 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37957/base-a-practical-de-novo-assembler-for-large-genomes-using-long-ngs-reads</link>
	<title><![CDATA[BASE: a practical de novo assembler for large genomes using long NGS reads]]></title>
	<description><![CDATA[<p><span>new&nbsp;</span><em>de novo</em><span>&nbsp;assembler called BASE. It enhances the classic seed-extension approach by indexing the reads efficiently to generate adaptive seeds that have high probability to appear uniquely in the genome. Such seeds form the basis for BASE to build extension trees and then to use reverse validation to remove the branches based on read coverage and paired-end information, resulting in high-quality consensus sequences of reads sharing the seeds. Such consensus sequences are then extended to contigs.</span></p><p>Address of the bookmark: <a href="https://github.com/dhlbh/BASE" rel="nofollow">https://github.com/dhlbh/BASE</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40701/fastgt-an-alignment-free-method-for-calling-common-snvs-directly-from-raw-sequencing-reads</guid>
	<pubDate>Tue, 28 Jan 2020 03:27:33 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40701/fastgt-an-alignment-free-method-for-calling-common-snvs-directly-from-raw-sequencing-reads</link>
	<title><![CDATA[FastGT: an alignment-free method for calling common SNVs directly from raw sequencing reads]]></title>
	<description><![CDATA[<p>FastGT is a program package for whole-genome genotyping of genome variants directly from raw sequencing reads. It is written in C and runs in Linux. FastGT uses a list of variant-specific k-mer pairs that are unique in human genome, counts the frequency of k-mers in sequencing data and predicts the genotype. All this takes less than 1 hour on average low-cost Linux server.</p>
<p><a href="http://bioinfo.ut.ee/FastGT/">http://bioinfo.ut.ee/FastGT/</a></p>
<p><strong><a href="https://github.com/bioinfo-ut/GenomeTester4/">https://github.com/bioinfo-ut/GenomeTester4/</a></strong></p><p>Address of the bookmark: <a href="http://bioinfo.ut.ee/FastGT/" rel="nofollow">http://bioinfo.ut.ee/FastGT/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42130/shaman-a-user-friendly-website-for-metataxonomic-analysis-from-raw-reads-to-statistical-analysis</guid>
	<pubDate>Mon, 17 Aug 2020 05:21:09 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42130/shaman-a-user-friendly-website-for-metataxonomic-analysis-from-raw-reads-to-statistical-analysis</link>
	<title><![CDATA[SHAMAN: a user-friendly website for metataxonomic analysis from raw reads to statistical analysis]]></title>
	<description><![CDATA[<p><span>SHAMAN is a shiny application for differential analysis of metagenomic data (16S, 18S, 23S, 28S, ITS and WGS) including bioinformatics treatment of raw reads for targeted metagenomics, statistical analysis and results visualization with a large variety of plots (barplot, boxplot, heatmap, &hellip;).</span><br><span>The bioinformatics treatment is based on Vsearch [</span><a href="http://www.ncbi.nlm.nih.gov/pubmed/27781170">Rognes 2016</a><span>] which showed to be both accurate and fast [</span><a href="http://www.ncbi.nlm.nih.gov/pubmed/26664811">Wescott 2015</a><span>].The statistical analysis is based on DESeq2 R package [</span><a href="http://www.ncbi.nlm.nih.gov/pubmed/20979621">Anders and Huber 2010</a><span>] which robustly identifies the differential abundant features as suggested in [</span><a href="http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3974642/">McMurdie and Holmes 2014</a><span>] and [</span><a href="http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4727335/">Jonsson2016</a><span>]. SHAMAN robustly identifies the differential abundant genera with the Generalized Linear Model implemented in DESeq2 [</span><a href="http://www.ncbi.nlm.nih.gov/pubmed/25516281">Love 2014</a><span>].</span><br><span>SHAMAN is compatible with standard formats for metagenomic analysis (.csv, .tsv, .biom) and figures can be downloaded in several formats. A presentation about SHAMAN is available&nbsp;</span><a href="https://github.com/aghozlane/shaman/blob/master/www/shaman_presentation.pdf">here</a><span>&nbsp;and a poster&nbsp;</span><a href="https://github.com/aghozlane/shaman/blob/master/www/shaman_poster.pdf">here</a><span>.&nbsp;</span></p>
<p><span>More at&nbsp;<a href="https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-020-03666-4">https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-020-03666-4</a></span></p><p>Address of the bookmark: <a href="https://github.com/aghozlane/shaman" rel="nofollow">https://github.com/aghozlane/shaman</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>

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