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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/42188?offset=60</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41559/dahak-benchmarking-and-containerization-of-tools-for-analysis-of-complex-non-clinical-metagenomes</guid>
	<pubDate>Thu, 09 Apr 2020 04:56:09 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41559/dahak-benchmarking-and-containerization-of-tools-for-analysis-of-complex-non-clinical-metagenomes</link>
	<title><![CDATA[Dahak: benchmarking and containerization of tools for analysis of complex non-clinical metagenomes.]]></title>
	<description><![CDATA[<p><span>Dahak is a software suite that integrates state-of-the-art open source tools for metagenomic analyses. Tools in the dahak software suite will perform various steps in metagenomic analysis workflows including data pre-processing, metagenome assembly, taxonomic and functional classification, genome binning, and gene assignment. We aim to deliver the analytical framework as a robust and reliable containerized workflow system, which will be free from dependency, installation, and execution problems typically associated with other open-source bioinformatics solutions. This will maximize the transparency, data provenance (i.e., the process of tracing the origins of data and its movement through the workflow), and reproducibility.</span></p>
<p><span>More at&nbsp;<a href="https://dahak-metagenomics.github.io/dahak/">https://dahak-metagenomics.github.io/dahak/</a></span></p><p>Address of the bookmark: <a href="https://github.com/dahak-metagenomics/dahak" rel="nofollow">https://github.com/dahak-metagenomics/dahak</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/42275/frequent-parameters-for-bioinformatics-tools</guid>
	<pubDate>Tue, 27 Oct 2020 19:42:32 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/42275/frequent-parameters-for-bioinformatics-tools</link>
	<title><![CDATA[Frequent parameters for bioinformatics tools !]]></title>
	<description><![CDATA[<div><div>Third party executable parameters and options.</div><div>&nbsp;</div><div>Trimmomatic</div><div>&nbsp;</div><div>&ldquo;ILLUMINACLIP:...:2:30:10&rdquo;</div><div>&ldquo;LEADING:15&rdquo;</div><div>&ldquo;TRAILING:15&rdquo;</div><div>&ldquo;SLIDINGWINDOW:4:20&rdquo;</div><div>&ldquo;MINLEN:20&rdquo;</div><div>&ldquo;TOPHRED33&rdquo;</div><div>&nbsp;</div><div>Filtlong</div><div>--min_length 500</div><div>--min_mean_q 85</div><div>--min_window_q 65</div><div>&nbsp;</div><div>FastQ Screen</div><div>--aligner bowtie2' (bwa for PacBio)</div><div>--subset 1000 (for PacBio)</div><div>&nbsp;</div><div>SPAdes</div><div>--careful</div><div>--disable-gzip-output</div><div>--cov-cutoff auto</div><div>--phred-offset 33</div><div>&nbsp;</div><div>HGAP</div><div>Pbalign.task_options.min_accuracy: 70</div><div>Pbalign.task_options.no_split_subreads: false</div><div>Genomic_consensus.task_options.min_confidence: 40</div><div>falcon_ns.task_options.HGAP_GenomeLength_str:</div><div>6000000</div><div>Pbcoretools.task_options.read_length: 0</div><div>Genomic_consensus.task_options.use_score: 0</div><div>Pbalign.task_options.min_length: 50</div><div>Pbalign.task_options.algorithm_options: --minMatch 12</div><div>--bestn 10 --minPctSimilarity 70.0</div><div>Pbalign.task_options.hit_policy: randombest</div><div>Pbcoretools.task_options.other_filters: rq &gt;= 0.7</div><div>Pbalign.task_options.concordant: false</div><div>Genomic_consensus.task_options.min_coverage: 5</div><div>falcon_ns.task_options.HGAP_SeedCoverage_str: 30</div><div>falcon_ns.task_options.HGAP_AggressiveAsm_bool: false</div><div>Genomic_consensus.task_options.algorithm: best</div><div>falcon_ns.task_options.HGAP_SeedLengthCutoff_str: -1</div><div>Genomic_consensus.task_options.diploid: false</div><div>&nbsp;</div><div>MeDuSa</div><div>-random 100</div><div>&nbsp;</div><div>Prokka</div><div>--usegenus</div><div>--force</div><div>--addgenes</div><div>--rfam</div><div>--rawproduct</div><div>&nbsp;</div><div>cmsearch (taxonomy, 16S)</div><div>--rfam</div><div>--noali</div><div>&nbsp;</div><div>blastn (taxonomy, 16S)</div><div>-evalue 1E-10</div><div>&nbsp;</div><div>blastn (MLST)</div><div>-ungapped</div></div><div><div>-dust no</div><div>-evalue 1E-20</div><div>-word_size 32</div><div>-culling_limit 2</div><div>-perc_identity 95</div><div>&nbsp;</div><div>blastp (VF)</div><div>-culling_limit 2</div><div>&nbsp;</div><div>RGI (ABR)</div><div>--input_type contig</div><div>&nbsp;</div><div>bowtie2 (mapping)</div><div>--sensitive</div><div>&nbsp;</div><div>minimap2 (mapping)</div><div>-a</div><div>-x map-ont</div><div>&nbsp;</div><div>samtools mpileup (SNP&nbsp;detection)</div><div>-uRI</div><div>&nbsp;</div><div>bcftools call (SNP detection)</div><div>--variants-only</div><div>--skip-variants indels</div><div>--output-type v</div><div>--ploidy 1</div><div>-c</div><div>&nbsp;</div><div>SNPsift filter (SNP detection)</div><div>"( QUAL &gt;= 30 ) &amp; (( na FILTER ) | (FILTER = 'PASS')) &amp;</div><div>( DP &gt;= 20 ) &amp; ( MQ &gt;= 20 )"</div><div>&nbsp;</div><div>SNPeff ann (SNP detection)</div><div>-nodownload</div><div>-no-intron</div><div>-no-downstream</div><div>-no SPLICE_SITE_REGION</div><div>-upDownStreamLen 250</div><div>&nbsp;</div><div>bcftools consensus</div><div>(phylogenetic tree)</div><div>--haplotype 1</div><div>&nbsp;</div><div>fasttreemp</div><div>-nt</div><div>-boot 100</div><div>&nbsp;</div><div>roary</div><div>-e</div><div>-n</div><div>-cd 100</div><div>-g 100000</div></div>]]></description>
	<dc:creator>BioStar</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/43260/bioinformatics-tools-for-telomere-to-telomere-assembly</guid>
	<pubDate>Tue, 17 Aug 2021 13:17:09 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/43260/bioinformatics-tools-for-telomere-to-telomere-assembly</link>
	<title><![CDATA[Bioinformatics tools for telomere to telomere assembly !]]></title>
	<description><![CDATA[<p>●&nbsp;<a href="https://github.com/arangrhie/merfin" target="_blank">Merfin</a>&nbsp;&ndash; k-mer-based assembly and variant calling evaluation for improved consensus accuracy (Arang Rhie)<br />●&nbsp;<a href="https://www.biorxiv.org/content/10.1101/2020.11.11.378133v1" target="_blank">PanGenie</a>&nbsp;&ndash; algorithm that leverages a pangenome reference built from haplotype-resolved genome assemblies in conjunction with k-mer count information from raw, short-read sequencing data to genotype a wide spectrum of genetic variation (Tobias Marschall)<br />●&nbsp;<a href="https://github.com/ConesaLab/SQANTI3" target="_blank">SQANTI3</a>&nbsp;&ndash; an automated pipeline for the classification of long-read transcripts that can assess the quality of data and the preprocessing pipeline (Roc&iacute;o Amor&iacute;n de Heged&uuml;s&nbsp;<a href="https://twitter.com/rocioadh" target="_blank">@rocioadh</a>)<br />●&nbsp;<a href="https://github.com/GenomeRIK/tama" target="_blank">tama</a>&nbsp;(Transcriptome Annotation by Modular Algorithms) &ndash; software designed for processing Iso-Seq data and other long-read transcriptome data (Richard Kuo&nbsp;<a href="https://twitter.com/GenomeRIK" target="_blank">@GenomeRIK</a>)<br />●&nbsp;<a href="https://github.com/PacificBiosciences/pbAA" target="_blank">pbaa</a>&nbsp;(PacBio Amplicon Analysis) &ndash; separates complex mixtures of amplicon targets from genomic samples to cluster and generate high-quality consensus sequences from HiFi reads (Zev Kronenberg&nbsp;<a href="https://twitter.com/zevkronenberg" target="_blank">@zevkronenberg</a>)<br />●&nbsp;<a href="https://github.com/yuanyuan929/bellerophon" target="_blank">bellerophon</a>&nbsp;&ndash; analyzes MHC typing and other low-complexity gene amplicon data; performs allele calling while detecting polymorphic sites within the sequences and removing potential chimeric sequence variants (Yuanyuan Cheng&nbsp;<a href="https://twitter.com/Yuanyuan929" target="_blank">@Yuanyuan929</a>)<br />●&nbsp;<a href="https://github.com/amwenger/svpack" target="_blank">svpack</a>&nbsp;&ndash; tools for filtering, comparing, and annotating structural variant (SV) calls in VCF format (Aaron Wenger)<br />●&nbsp;<a href="https://github.com/AntonBankevich/jumboDB" target="_blank">JumboDB</a>&nbsp;&ndash; tool for de Bruijn graph construction (Anton Bankevich&nbsp;<a href="https://twitter.com/AntonBankevich" target="_blank">@AntonBankevich</a>)<br />●&nbsp;<a href="https://github.com/ksahlin/ultra" target="_blank">uLTRA</a>&nbsp;&ndash; tool for splice alignment of long transcriptomic reads to a genome, guided by a database of exon annotations. (Kristoffer Sahlin&nbsp;<a href="https://twitter.com/krsahlin" target="_blank">@krsahlin</a>)<br />●&nbsp;<a href="https://www.biorxiv.org/content/10.1101/2021.01.25.428044v1.full.pdf" target="_blank">LeafGo</a>&nbsp;&ndash; workflow to rapidly produce high-quality de novo plant genomes (Luca Ermini&nbsp;<a href="https://twitter.com/ermini_luca" target="_blank">@ermini_luca</a>)</p><p>Reference:</p><p>https://www.pacb.com/blog/young-investigators-share-stellar-science-career-advice-and-bioinformatics-tools-at-smrt-leiden-2021/</p><p>&nbsp;</p>]]></description>
	<dc:creator>BioStar</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43791/comparative-genomics-visualisation-tools</guid>
	<pubDate>Thu, 17 Feb 2022 05:37:55 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43791/comparative-genomics-visualisation-tools</link>
	<title><![CDATA[Comparative genomics visualisation tools !]]></title>
	<description><![CDATA[<p>Comparative genomics visualisation tools !</p><p>Address of the bookmark: <a href="https://cmdcolin.github.io/awesome-genome-visualization/?latest=true&amp;selected=%23BRIG&amp;tag=Comparative" rel="nofollow">https://cmdcolin.github.io/awesome-genome-visualization/?latest=true&amp;selected=%23BRIG&amp;tag=Comparative</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/44551/bioinformatic-tools-for-pathogens-informatics-at-cvr</guid>
	<pubDate>Sat, 08 Jun 2024 15:59:46 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44551/bioinformatic-tools-for-pathogens-informatics-at-cvr</link>
	<title><![CDATA[Bioinformatic tools for pathogens informatics at CVR]]></title>
	<description><![CDATA[<div><div><div><div><div><p>Novel sequencing and analytical approaches focused on studying viruses and virus-host interactions. Below you will find summaries and links to a number of bioinformatic tools that have been developed @ CVR.</p></div><div><h3><a href="http://giffordlabcvr.github.io/DIGS-tool/" target="_blank" title="DIGS">DIGS</a></h3></div><div><p>The database-integrated genome-screening (DIGS) tool provides a framework for implementing automated in silico screening of sequence databases using BLAST in combination with a relational database (MySQL).</p></div><div><h3><a href="https://bioinformatics.cvr.ac.uk/software/discvr/" target="" title="DisCVR">DisCVR</a></h3></div><div><p>DisCVR is a Diagnostic tool for detecting known human viruses in clinical samples from Next-Generation Sequencing (NGS) data. The tool uses a simple and straightforward Graphical User Interface and is optimized on Windows OS without compromising speed and accuracy.</p></div><div><h3><a href="http://josephhughes.github.io/DiversiTools/" target="_blank" title="DiversiTools">DiversiTools</a></h3></div><div><p>DiversiTools is a computational tool that is specifically tailored towards viral HTS data sets and the analysis of the underlying viral populations that they represent. It was initially developed in collaboration with a number of virologists interested in characterising the intra-host diversity of viral populations and studying their evolution across transmission chains at the micro-evolutionary scale.</p></div><div><h3><a href="http://glue-tools.cvr.gla.ac.uk/" target="_blank" title="GLUE">GLUE</a></h3></div><div><p>GLUE is a flexible data-centric bioinformatics environment for virus sequence data, with a focus on virus evolution and genomic variation. GLUE has been applied to a range of viruses. A GLUE-based resource focused on Hepatitis C virus is HCV-GLUE.</p></div><div><h3><a href="https://bioinformatics.cvr.ac.uk/tanoti/" target="_blank" title="Tanoti">Tanoti</a></h3></div><div><p>Tanoti is a BLAST guided reference based short read aligner. It is developed for maximising alignment in highly variable next generation sequence data sets (Illumina).</p></div><div><h3><a href="https://bioinformatics.cvr.ac.uk/victree/" target="_blank" title="VicTREE">ViCTree</a></h3></div><div><p>ViCTree is a bioinformatic framework that automatically selects new candidate virus sequences from GenBank, generates multiple sequence alignments, calculates a maximum likelihood phylogeny and integrates the sequences into the existing phylogenetic trees.&nbsp;<span>For more information click&nbsp;</span><a href="https://bioinformatics.cvr.ac.uk/victree_web/" target="_blank">here</a>.</p></div></div></div></div></div><div><div><div><div><div><h3><a href="https://bioinformatics.cvr.ac.uk/software/viral-host-predictor/" target="" title="Viral Host Predictor">Viral Host Predictor</a></h3></div><div><p>Viral Host Predictor provides a fast and simple way to predict the hosts and vectors of RNA viruses from viral sequences.</p></div><div><h3><a href="https://github.com/salvocamiolo/GRACy/releases/tag/v0.4.4" target="_blank" title="GRACy">GRACy</a></h3></div><div><p>GRACy is a bioinformatic tool designed for the analysis of Illumina data originated from Human cytomegalovirus samples. GRACy can be used to perform read quality filtering, genotyping, de novo assembly, variant detection, annotation and data submission to public database.</p></div><div><h3><a href="https://github.com/salvocamiolo/LoReTTA/releases/tag/v0.1" target="_blank" title="LoReTTA">LoReTTA</a></h3></div><div><p>LoReTTA (Long Read Template Targeted Assembler) is a reference assisted de novo assembler specifically designed to deal with PacBio reads generated from viral genomes.&nbsp;</p></div><div><h3><a href="https://bioinformatics.cvr.ac.uk/software/bingleseq/" target="" title="BingleSeq">BingleSeq</a></h3></div><div><p>BingleSeq is a R-package enables the user-friendly analysis of count tables obtained by both Bulk RNA-Seq and single-cell RNA-Seq protocols. The development of BingleSeq focused on providing a flexible and intuitive user experience.</p></div></div></div></div></div>]]></description>
	<dc:creator>Abhi</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36837/ranbow-a-haplotype-assembler-for-polyploid-genomes</guid>
	<pubDate>Fri, 01 Jun 2018 07:21:54 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36837/ranbow-a-haplotype-assembler-for-polyploid-genomes</link>
	<title><![CDATA[Ranbow: a haplotype assembler for polyploid genomes]]></title>
	<description><![CDATA[Ranbow is a haplotype assembler for polyploid genomes. It has been developed for the haplotype assembly of the hexaploid sweet potato genome, which is highly heterozygous. Ranbow can also be applied to other polyploid genomes. After a first phasing, Ranbow utilizes the assembled haplotypes to improve the accuracy of variant calling results and to infer the evolutionary history of the organism´s genome. Ranbow has three main modes of function:

ranbow hap: for haplotyping
ranbow eval: for evaluating of the assemble haplotypes by gold standard (long) reads 
ranbow phylo: for the phylogenetic analysis<p>Address of the bookmark: <a href="https://www.molgen.mpg.de/ranbow" rel="nofollow">https://www.molgen.mpg.de/ranbow</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/33651/darkhorse-a-method-for-genome-wide-prediction-of-horizontal-gene-transfer</guid>
	<pubDate>Thu, 22 Jun 2017 07:58:35 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/33651/darkhorse-a-method-for-genome-wide-prediction-of-horizontal-gene-transfer</link>
	<title><![CDATA[DarkHorse: a method for genome-wide prediction of horizontal gene transfer]]></title>
	<description><![CDATA[<p><span>A new approach to rapid, genome-wide identification and ranking of horizontal transfer candidate proteins is presented. The method is quantitative, reproducible, and computationally undemanding. It can be combined with genomic signature and/or phylogenetic tree-building procedures to improve accuracy and efficiency. The method is also useful for retrospective assessments of horizontal transfer prediction reliability, recognizing orthologous sequences that may have been previously overlooked or unavailable. These features are demonstrated in bacterial, archaeal, and eukaryotic examples.</span></p><p>Address of the bookmark: <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1852411/" rel="nofollow">https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1852411/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39674/simka-and-simkamin-are-comparative-metagenomics-method-dedicated-to-ngs-datasets</guid>
	<pubDate>Sat, 06 Jul 2019 13:56:10 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39674/simka-and-simkamin-are-comparative-metagenomics-method-dedicated-to-ngs-datasets</link>
	<title><![CDATA[Simka and SimkaMin are comparative metagenomics method dedicated to NGS datasets]]></title>
	<description><![CDATA[<p>Simka is a de novo comparative metagenomics tool. Simka represents each dataset as a k-mer spectrum and compute several classical ecological distances between them.</p>
<p>Developper:&nbsp;<a href="http://people.rennes.inria.fr/Gaetan.Benoit/">Ga&euml;tan Benoit</a>, PhD, former member of the&nbsp;<a href="http://team.inria.fr/genscale/">Genscale</a>&nbsp;team at Inria.</p>
<p>Contact: claire dot lemaitre at inria dot fr</p>
<p><span>Simka and SimkaMin are comparative metagenomics method dedicated to NGS datasets.&nbsp;</span><span></span><span><a href="https://gatb.inria.fr/software/simka/">https://gatb.inria.fr/software/simka/</a></span></p><p>Address of the bookmark: <a href="https://github.com/GATB/simka" rel="nofollow">https://github.com/GATB/simka</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/11175/next-generation-sequencingngs-books</guid>
	<pubDate>Fri, 30 May 2014 04:48:04 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/11175/next-generation-sequencingngs-books</link>
	<title><![CDATA[Next generation sequencing(NGS) books]]></title>
	<description><![CDATA[<p>Employing different technologies, the purpose of NGS platform is to decode the identity or modification on the nucleotides. NGS platforms evolve quickly and capture the main stream.</p>
<p>This bookmark is created to provide NGS online books links.</p><p>Address of the bookmark: <a href="http://en.wikibooks.org/wiki/Next_Generation_Sequencing_%28NGS%29/Print_version" rel="nofollow">http://en.wikibooks.org/wiki/Next_Generation_Sequencing_%28NGS%29/Print_version</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38505/allhic-phasing-and-scaffolding-polyploid-genomes-based-on-hi-c-data</guid>
	<pubDate>Thu, 20 Dec 2018 12:03:32 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38505/allhic-phasing-and-scaffolding-polyploid-genomes-based-on-hi-c-data</link>
	<title><![CDATA[ALLHiC: Phasing and scaffolding polyploid genomes based on Hi-C data]]></title>
	<description><![CDATA[<p><span>The major problem of scaffolding polyploid genome is that Hi-C signals are frequently detected between allelic haplotypes and any existing stat of art Hi-C scaffolding program links the allelic haplotypes together. To solve the problem, we developed a new Hi-C scaffolding pipeline, called ALLHIC, specifically tailored to the polyploid genomes. ALLHIC pipeline contains a total of 5 steps:&nbsp;</span><em>prune</em><span>,&nbsp;</span><em>partition</em><span>,&nbsp;</span><em>rescue</em><span>,&nbsp;</span><em>optimize</em><span>&nbsp;and&nbsp;</span><em>build</em><span>.</span></p><p>Address of the bookmark: <a href="https://github.com/tangerzhang/ALLHiC/wiki" rel="nofollow">https://github.com/tangerzhang/ALLHiC/wiki</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
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