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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/41893?offset=60</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34525/hic-pro-an-optimized-and-flexible-pipeline-for-hi-c-data-processing</guid>
	<pubDate>Wed, 06 Dec 2017 01:05:21 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34525/hic-pro-an-optimized-and-flexible-pipeline-for-hi-c-data-processing</link>
	<title><![CDATA[HiC-Pro: an optimized and flexible pipeline for Hi-C data processing]]></title>
	<description><![CDATA[<p><span>HiC-Pro was designed to process Hi-C data, from raw fastq files (paired-end Illumina data) to the normalized contact maps. Since version 2.7.0, HiC-Pro supports the main Hi-C protocols, including digestion protocols as well as protocols that do not require restriction enzyme such as DNase Hi-C. In practice, HiC-Pro can be used to process dilution Hi-C, in situ Hi-C, DNase Hi-C, Micro-C, capture-C, capture Hi-C or HiChip data.</span></p>
<p>&nbsp;</p>
<p>http://nservant.github.io/HiC-Pro/</p><p>Address of the bookmark: <a href="http://nservant.github.io/HiC-Pro/" rel="nofollow">http://nservant.github.io/HiC-Pro/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38067/metaplotr-a-perlr-pipeline-for-plotting-metagenes-of-nucleotide-modifications-and-other-transcriptomic-sites</guid>
	<pubDate>Mon, 05 Nov 2018 08:12:45 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38067/metaplotr-a-perlr-pipeline-for-plotting-metagenes-of-nucleotide-modifications-and-other-transcriptomic-sites</link>
	<title><![CDATA[MetaPlotR: a Perl/R pipeline for plotting metagenes of nucleotide modifications and other transcriptomic sites]]></title>
	<description><![CDATA[<p><span>An increasing number of studies are mapping protein binding and nucleotide modifications sites throughout the transcriptome. Often, these sites cluster in certain regions of the transcript, giving clues to their function. Hence, it is informative to summarize where in the transcript these sites occur. A metagene is a simple and effective tool for visualizing the distribution of sites along a simplified transcript model. In this work, we introduce MetaPlotR, a Perl/R pipeline for creating metagene plots.</span></p><p>Address of the bookmark: <a href="https://github.com/olarerin/metaPlotR" rel="nofollow">https://github.com/olarerin/metaPlotR</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39370/multiphate-bioinformatics-pipeline-for-functional-annotation-of-phage-isolates</guid>
	<pubDate>Thu, 16 May 2019 00:17:39 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39370/multiphate-bioinformatics-pipeline-for-functional-annotation-of-phage-isolates</link>
	<title><![CDATA[multiPhATE: bioinformatics pipeline for functional annotation of phage isolates]]></title>
	<description><![CDATA[<p><span>multiple-genome Phage Annotation Toolkit and Evaluator (multiPhATE). multiPhATE is a throughput pipeline driver that invokes an annotation pipeline (PhATE) across a user-specified set of phage genomes. This tool incorporates a&nbsp;</span><em>de novo</em><span>&nbsp;phage gene-calling algorithm and assigns putative functions to gene calls using protein-, virus-, and phage-centric databases.&nbsp;</span></p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="https://github.com/carolzhou/multiPhATE" rel="nofollow">https://github.com/carolzhou/multiPhATE</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40604/gapfinisher-a-reliable-gap-filling-pipeline-for-sspace-longread-scaffolder-output</guid>
	<pubDate>Fri, 24 Jan 2020 06:04:40 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40604/gapfinisher-a-reliable-gap-filling-pipeline-for-sspace-longread-scaffolder-output</link>
	<title><![CDATA[gapFinisher: A reliable gap filling pipeline for SSPACE-LongRead scaffolder output]]></title>
	<description><![CDATA[<p><span>gapFinisher is based on the controlled use of a previously published gap filling tool FGAP and works on all standard Linux/UNIX command lines. They compare the performance of gapFinisher against two other published gap filling tools PBJelly and GMcloser. </span></p>
<p><span>gapFinisher can fill gaps in draft genomes quickly and reliably.</span></p><p>Address of the bookmark: <a href="https://github.com/kammoji/gapFinisher" rel="nofollow">https://github.com/kammoji/gapFinisher</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41675/gapfinisher-a-reliable-gap-filling-pipeline-for-sspace-longread-scaffolder-output</guid>
	<pubDate>Thu, 14 May 2020 15:13:30 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41675/gapfinisher-a-reliable-gap-filling-pipeline-for-sspace-longread-scaffolder-output</link>
	<title><![CDATA[gapFinisher: A reliable gap filling pipeline for SSPACE-LongRead scaffolder output]]></title>
	<description><![CDATA[<p>gapFinisher to process SSPACE-LongRead output to fill gaps after the scaffolding. gapFinisher is based on the controlled use of a previously published gap filling tool FGAP and works on all standard Linux/UNIX command lines.</p>
<p>https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6733440/</p><p>Address of the bookmark: <a href="https://github.com/kammoji/gapFinisher" rel="nofollow">https://github.com/kammoji/gapFinisher</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42941/csa-a-high-throughput-chromosome-scale-assembly-pipeline-for-vertebrate-genomes</guid>
	<pubDate>Wed, 10 Mar 2021 06:13:49 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42941/csa-a-high-throughput-chromosome-scale-assembly-pipeline-for-vertebrate-genomes</link>
	<title><![CDATA[CSA: A high-throughput chromosome-scale assembly pipeline for vertebrate genomes]]></title>
	<description><![CDATA[<p>The pipeline can use information from scaffolded assemblies (for example from HiC or 10X Genomics), or even from diverged (~65-100 Mya) reference genomes for ordering the contigs and thus support the assembly process. This typically results in improved contig N50 when compared to current state of the art methods.</p>
<p><img src="https://github.com/HMPNK/CSA2.6/raw/master/Fig1.png" alt="image" style="border: 0px;"></p>
<p>For smaller vertebrate genomes (~1 Gbp) chromosome scale assemblies can be achieved within 12h on high-end Desktop computers (Intel i7, 12 CPU threads, 128 GB RAM). Larger mammalian genomes (~3Gbp) can be processed within 15-18 h on server equipment (Xeon, 96 CPU threads, 1TB RAM).</p><p>Address of the bookmark: <a href="https://github.com/HMPNK/CSA2.6" rel="nofollow">https://github.com/HMPNK/CSA2.6</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43384/lncpipea-nextflow-based-pipeline-for-comprehensive-analyses-of-long-non-coding-rnas-from-rna-seq-datasets</guid>
	<pubDate>Fri, 17 Sep 2021 01:57:02 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43384/lncpipea-nextflow-based-pipeline-for-comprehensive-analyses-of-long-non-coding-rnas-from-rna-seq-datasets</link>
	<title><![CDATA[LncPipe:A Nextflow-based pipeline for comprehensive analyses of long non-coding RNAs from RNA-seq datasets]]></title>
	<description><![CDATA[<p><span>The pipeline was developed based on a popular workflow framework&nbsp;</span><a href="https://github.com/nextflow-io/nextflow">Nextflow</a><span>, composed of four core procedures including reads alignment, assembly, identification and quantification. It contains various unique features such as well-designed lncRNAs annotation strategy, optimized calculating efficiency, diversified classification and interactive analysis report.&nbsp;</span><a href="https://github.com/likelet/LncPipe">LncPipe</a><span>&nbsp;allows users additional control in interuppting the pipeline, resetting parameters from command line, modifying main script directly and resume analysis from previous checkpoint.</span></p>
<p>Ref&nbsp;https://www.lncrnablog.com/lncpipe-a-nextflow-based-pipeline-for-identification-and-analysis-of-long-non-coding-rnas-from-rna-seq-data/</p>
<p><img src="https://ars.els-cdn.com/content/image/1-s2.0-S1673852718301176-gr1.jpg" alt="image" style="border: 0px;"></p><p>Address of the bookmark: <a href="https://github.com/likelet/LncPipe" rel="nofollow">https://github.com/likelet/LncPipe</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44472/pipesnake-bioinformatics-best-practice-analysis-pipeline-for-phylogenomic-reconstruction</guid>
	<pubDate>Wed, 21 Feb 2024 06:19:41 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44472/pipesnake-bioinformatics-best-practice-analysis-pipeline-for-phylogenomic-reconstruction</link>
	<title><![CDATA[pipesnake: bioinformatics best-practice analysis pipeline for phylogenomic reconstruction]]></title>
	<description><![CDATA[<p dir="auto"><span>ausarg/pipesnake</span>&nbsp;is a bioinformatics best-practice analysis pipeline for phylogenomic reconstruction starting from short-read 'second-generation' sequencing data.</p>
<p dir="auto">The pipeline is built using&nbsp;<a href="https://www.nextflow.io/">Nextflow</a>, a workflow tool to run tasks across multiple compute infrastructures in a very portable manner. It uses Docker/Singularity containers making installation trivial and results highly reproducible. The&nbsp;<a href="https://www.nextflow.io/docs/latest/dsl2.html">Nextflow DSL2</a>&nbsp;implementation of this pipeline uses one container per process which makes it much easier to maintain and update software dependencies.</p><p>Address of the bookmark: <a href="https://github.com/AusARG/pipesnake" rel="nofollow">https://github.com/AusARG/pipesnake</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43810/seqfu-a-suite-of-utilities-for-the-robust-and-reproducible-manipulation-of-sequence-files</guid>
	<pubDate>Tue, 01 Mar 2022 03:13:33 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43810/seqfu-a-suite-of-utilities-for-the-robust-and-reproducible-manipulation-of-sequence-files</link>
	<title><![CDATA[SeqFu: A Suite of Utilities for the Robust and Reproducible Manipulation of Sequence Files]]></title>
	<description><![CDATA[<p>A general-purpose program to manipulate and parse information from FASTA/FASTQ files, supporting gzipped input files. Includes functions to&nbsp;<em>interleave</em>&nbsp;and&nbsp;<em>de-interleave</em>&nbsp;FASTQ files, to&nbsp;<em>rename</em>&nbsp;sequences and to&nbsp;<em>count</em>&nbsp;and print&nbsp;<em>statistics</em>&nbsp;on sequence lengths. SeqFu is available for Linux and MacOS.</p>
<ul>
<li>A compiled program delivering high performance analyses</li>
<li>Supports FASTA/FASTQ files, also Gzip compressed</li>
<li>A growing collection of handy utilities, also for quick inspection of the datasets</li>
</ul>
<p>Can be easily&nbsp;<a href="https://telatin.github.io/seqfu2/installation">installed</a>&nbsp;via conda:</p>
<div>
<div>
<pre><code>conda <span>install</span> <span>-c</span> bioconda seqfu</code></pre>
</div>
</div><p>Address of the bookmark: <a href="https://telatin.github.io/seqfu2/" rel="nofollow">https://telatin.github.io/seqfu2/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/11368/metagenomics-role-in-antibiotic-resistance</guid>
	<pubDate>Mon, 02 Jun 2014 08:04:40 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/11368/metagenomics-role-in-antibiotic-resistance</link>
	<title><![CDATA[Metagenomics role in antibiotic resistance]]></title>
	<description><![CDATA[<p>Related latest article:</p>
<p><a href="http://www.nature.com/nature/journal/v509/n7502/pdf/nature13377.pdf">http://www.nature.com/nature/journal/v509/n7502/pdf/nature13377.pdf</a></p><p>Address of the bookmark: <a href="https://www.landesbioscience.com/journals/virulence/2013VIRULENCE0033R2.pdf" rel="nofollow">https://www.landesbioscience.com/journals/virulence/2013VIRULENCE0033R2.pdf</a></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
</item>

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