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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/44401?offset=80</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36512/hisat2-a-fast-and-sensitive-alignment-program-for-mapping-next-generation-sequencing-reads</guid>
	<pubDate>Tue, 08 May 2018 04:27:22 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36512/hisat2-a-fast-and-sensitive-alignment-program-for-mapping-next-generation-sequencing-reads</link>
	<title><![CDATA[HISAT2: a fast and sensitive alignment program for mapping next-generation sequencing reads]]></title>
	<description><![CDATA[<p><strong>HISAT2</strong><span>&nbsp;is a fast and sensitive alignment program for mapping next-generation sequencing reads (both DNA and RNA) to a population of human genomes (as well as to a single reference genome). Based on an extension of BWT for graphs&nbsp;</span><a href="http://dl.acm.org/citation.cfm?id=2674828">[Sir&eacute;n et al. 2014]</a><span>, we designed and implemented a graph FM index (GFM), an original approach and its first implementation to the best of our knowledge. In addition to using one global GFM index that represents a population of human genomes, HISAT2 uses a large set of small GFM indexes that collectively cover the whole genome (each index representing a genomic region of 56 Kbp, with 55,000 indexes needed to cover the human population). These small indexes (called local indexes), combined with several alignment strategies, enable rapid and accurate alignment of sequencing reads. This new indexing scheme is called a Hierarchical Graph FM index (HGFM).&nbsp;</span></p>
<p><span>more at&nbsp;https://ccb.jhu.edu/software/hisat2/index.shtml</span></p><p>Address of the bookmark: <a href="https://github.com/infphilo/hisat2" rel="nofollow">https://github.com/infphilo/hisat2</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/37514/list-of-non-commercial-ngs-genotype-calling-software</guid>
	<pubDate>Thu, 09 Aug 2018 04:21:32 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/37514/list-of-non-commercial-ngs-genotype-calling-software</link>
	<title><![CDATA[List of non-commercial NGS genotype-calling software]]></title>
	<description><![CDATA[<p><span>Meaningful analysis of next-generation sequencing (NGS) data, which are produced extensively by genetics and genomics studies, relies crucially on the accurate calling of SNPs and genotypes. Recently developed statistical methods both improve and quantify the considerable uncertainty associated with genotype calling, and will especially benefit the growing number of studies using low- to medium-coverage data.&nbsp;</span></p><p><span>A list of programs for genotype and SNP calling :</span></p><p><br />SOAP2&nbsp;http://soap.genomics.org.cn/index.html</p><p>Single-sample High-quality variant database (for example, dbSNP) Package for NGS data analysis, which includes a single individual genotype caller (SOAPsnp)</p><p>realSFS&nbsp;http://128.32.118.212/thorfinn/realSFS/</p><p>Single-sample Aligned reads Software for SNP and genotype calling using single individuals and allele frequencies. Site frequency spectrum (SFS) estimation</p><p>Samtools http://samtools.sourceforge.net/</p><p>Multi-sample Aligned reads Package for manipulation of NGS alignments, which includes a computation of genotype likelihoods (samtools) and SNP and genotype calling (bcftools)</p><p>GATK http://www.broadinstitute.org/gsa/wiki/index.php/The_Genome_Analysis_Toolkit Multi-sample Aligned reads Package for aligned NGS data analysis, which includes a SNP and genotype caller (Unifed Genotyper), SNP filtering (Variant Filtration) and SNP quality recalibration (Variant Recalibrator)</p><p>Beagle http://faculty.washington.edu/browning/beagle/beagle.html</p><p>Multi-sample LD Candidate SNPs, genotype likelihoods Software for imputation, phasing and association that includes a mode for genotype calling</p><p>IMPUTE2 http://mathgen.stats.ox.ac.uk/impute/impute_v2.html</p><p>Multi-sample LD Candidate SNPs, genotype likelihoods Software for imputation and phasing, including a mode for genotype calling. Requires fine-scale linkage map</p><p>QCall ftp://ftp.sanger.ac.uk/pub/rd/QCALL</p><p>Multi-sample LD &lsquo;Feasible&rsquo; genealogies at a dense set of loci, genotype likelihoods Software for SNP and genotype calling, including a method for generating candidate SNPs without LD information (NLDA) and a method for incorporating LD information (LDA). The &lsquo;feasible&rsquo; genealogies can be generated using Margarita (http://www.sanger.ac.uk/resources/software/margarita)</p><p>MaCH http://genome.sph.umich.edu/wiki/Thunder</p><p>Multi-sample LD Genotype likelihoods Software for SNP and genotype calling, including a method (GPT_Freq) for generating candidate SNPs without LD information and a method (thunder_glf_freq) for incorporating LD information</p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/38765/list-of-tools-frequently-used-while-genome-assembly</guid>
	<pubDate>Tue, 22 Jan 2019 09:39:02 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/38765/list-of-tools-frequently-used-while-genome-assembly</link>
	<title><![CDATA[List of tools frequently used while genome assembly]]></title>
	<description><![CDATA[<h4>List of tools frequently used while genome assembly:</h4><p>I have used the following assemblers</p><ul>
<li><a href="http://bioinf.spbau.ru/spades">Spades</a>&nbsp;(v. 3.10.1)</li>
<li><a href="http://canu.readthedocs.io/en/stable/index.html">CANU</a>&nbsp;(v. 1.6)</li>
<li><a href="https://github.com/rrwick/Unicycler">Unicycler&nbsp;</a>(v. v0.4.1)</li>
<li><a href="https://github.com/lh3/miniasm">Miniasm</a>&nbsp;(v. 0.2-r137-dirty)</li>
</ul><p>I have used the following mappers</p><ul>
<li><a href="https://github.com/lh3/minimap2">minimap2</a>&nbsp;(v.&nbsp;2.0rc1-r232)</li>
<li><a href="https://github.com/lh3/minimap">minimap&nbsp;</a>(v. 0.2-r124-dirty)</li>
<li><a href="https://github.com/lh3/bwa">bwa</a>&nbsp;(v.&nbsp;0.7.12-r1039)</li>
</ul><p>I have used the following polishing tools</p><ul>
<li><a href="https://github.com/isovic/racon">Racon</a>&nbsp;(v. not available)</li>
<li><a href="https://github.com/broadinstitute/pilon">Pilon</a>&nbsp;(v. 1.18)</li>
<li><a href="https://github.com/jts/nanopolish">Nanopolish</a>&nbsp;(v. 0.8.3)</li>
</ul><p>I have used the following tools to assess genome assembly characteristics</p><ul>
<li><a href="https://github.com/chjp/ANI">ANI.pl</a>&nbsp;(https://github.com/chjp/ANI)</li>
<li><a href="http://ecogenomics.github.io/CheckM/">CheckM</a>&nbsp;(v. 1.0.7)</li>
<li><a href="https://github.com/tseemann/prokka">Prokka</a>&nbsp;(v. 1.12)</li>
<li><a href="http://bioinf.spbau.ru/en/quast">QUAST</a>&nbsp;(v. 2.3)</li>
<li><a href="http://mummer.sourceforge.net/">mummer&nbsp;</a>(v. not available)</li>
</ul><p>If you have any ideas or superior tools we have missed please let us know in the comments.</p>]]></description>
	<dc:creator>BioStar</dc:creator>
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	<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/pages/view/923/phylogenetic-for-bioinformatics</guid>
	<pubDate>Tue, 16 Jul 2013 03:50:30 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/923/phylogenetic-for-bioinformatics</link>
	<title><![CDATA[Phylogenetic for Bioinformatics]]></title>
	<description><![CDATA[<p>Biologists estimate that there are about 5 to 100 million species of organisms living on Earth today. Evidence from morphological, biochemical, and gene sequence data suggests that all organisms on Earth are genetically related, and the genealogical relationships of living things can be represented by a vast evolutionary tree, the Tree of Life. The Tree of Life then represents the phylogeny of organisms, i. e., the history of organismal lineages as they change through time.<br />Every living organism contains DNA, RNA, and proteins. Closely related organisms generally have a high degree of agreement in the molecular structure of these substances, while the molecules of organisms distantly related usually show a pattern of dissimilarity. Molecular phylogeny uses such data to build a "relationship tree" that shows the probable evolution of various organisms. Not until recent decades, however, has it been possible to isolate and identify these molecular structures.&nbsp;<br />phylogenetics is the study of evolutionary relatedness among various groups of organisms (for example, species or populations), which is discovered through molecular sequencing data and morphological data matrices. In other word, Phylogenetics, the science of phylogeny, is one part of the larger field of systematics, which also includes taxonomy. Taxonomy is the science of naming and classifying the diversity of organisms Molecular phylogeny is the use of the structure of molecules to gain information on an organism's evolutionary relationships. The result of a molecular phylogenetic analysis is expressed in a so-called phylogenetic tree.</p><p>The evolutionary connections between organisms are represented graphically through phylogenetic trees. Due to the fact that evolution takes place over long periods of time that cannot be observed directly, biologists must reconstruct phylogenies by inferring the evolutionary relationships among present-day organisms.&nbsp;<br />Application of the techniques that make this possible can be seen in the very limited field of human genetics, such as the ever more popular use of genetic testing to determine a child's paternity, as well as the emergence of a new branch of criminal forensics focused on genetic evidence.<br />The effect on traditional scientific classification schemes in the biological sciences has been dramatic as well. Work that was once immensely labor- and materials-intensive can now be done quickly and easily, leading to yet another source of information becoming available for systematic and taxonomic appraisal. This particular kind of data has become so popular that taxonomical schemes based solely on molecular data may be encountered. Proponents even claim that taxonomy was previously based on morphology alone, which of course is utter fable.<br /><br /><strong>For additional information on phylogenetics, see list of Phylogenetics Resources on the Internet.</strong></p><p>Phylogeny and Reconstructing Phylogenetic Trees:&nbsp;<a href="http://aleph0.clarku.edu/~djoyce/java/Phyltree/cover.html"></a><a href="http://aleph0.clarku.edu/~djoyce/java/Phyltree/cover.html">http://aleph0.clarku.edu/~djoyce/java/Phyltree/cover.html</a><br />the CBRG and Department of Statistics Phylogeny tutorial:&nbsp;<a href="http://www.compbio.ox.ac.uk/tutorials/phylogeny/"></a><a href="http://www.compbio.ox.ac.uk/tutorials/phylogeny/">http://www.compbio.ox.ac.uk/tutorials/phylogeny/</a><br />TUTORIAL: PHYLOGENETIC ANALYSIS USING PARSIMONY:<a href="http://home.cc.umanitoba.ca/~psgendb/GDE/phylogeny/parsimony/phylip.parsimony.html"></a><a href="http://home.cc.umanitoba.ca/~psgendb/GDE/phylogeny/parsimony/phylip.parsimony.html">http://home.cc.umanitoba.ca/~psgendb/GDE/phylogeny/parsimony/phylip.parsimony.html</a></p><p>PHYLIP:&nbsp;<a href="http://www.umanitoba.ca/afs/plant_science/psgendb/doc/Phylip/main.html"></a><a href="http://www.umanitoba.ca/afs/plant_science/psgendb/doc/Phylip/main.html">http://www.umanitoba.ca/afs/plant_science/psgendb/doc/Phylip/main.html</a><br />An Introduction to Molecular Phylogeny:&nbsp;<a href="http://bibiserv.techfak.uni-bielefeld.de/gcb04/tutorials/hoef-emden/GCB04Tut.pdf"></a><a href="http://bibiserv.techfak.uni-bielefeld.de/gcb04/tutorials/hoef-emden/GCB04Tut.pdf">http://bibiserv.techfak.uni-bielefeld.de/gcb04/tutorials/hoef-emden/GCB04Tut.pdf</a></p><p>How to make a phylogenetic tree:&nbsp;<a href="http://www.hiv.lanl.gov/content/sequence/TUTORIALS/TREE_TUTORIAL/Tree"></a><a href="http://www.hiv.lanl.gov/content/sequence/TUTORIALS/TREE_TUTORIAL/Tree">http://www.hiv.lanl.gov/content/sequence/TUTORIALS/TREE_TUTORIAL/Tree</a>tutorial.html<br />Phylogenetic Trees:&nbsp;<a href="http://cnx.org/content/m11052/latest/"></a><a href="http://cnx.org/content/m11052/latest/">http://cnx.org/content/m11052/latest/</a><br />Phylogeny by Ron Shamir:&nbsp;<a href="http://www.cs.tau.ac.il/~rshamir/algmb/01/scribe08/lec08.pdf"></a><a href="http://www.cs.tau.ac.il/~rshamir/algmb/01/scribe08/lec08.pdf">http://www.cs.tau.ac.il/~rshamir/algmb/01/scribe08/lec08.pdf</a><br />Introduction to Phylogeny:&nbsp;<a href="http://www.utm.edu/departments/cens/biology/rirwin/391/391Phylog.htm"></a><a href="http://www.utm.edu/departments/cens/biology/rirwin/391/391Phylog.htm">http://www.utm.edu/departments/cens/biology/rirwin/391/391Phylog.htm</a><br />Lecturer notes on Phylogeny:&nbsp;<a href="http://www.sbc.su.se/~bens/course_material/phylocourse1/lecture2.pdf"></a><a href="http://www.sbc.su.se/~bens/course_material/phylocourse1/lecture2.pdf">http://www.sbc.su.se/~bens/course_material/phylocourse1/lecture2.pdf</a><br />Principles and Practice of Phylogenetic Systematics:<a href="http://www.faculty.biol.ttu.edu/Strauss/Phylogenetics/LectureNotes.htm"></a><a href="http://www.faculty.biol.ttu.edu/Strauss/Phylogenetics/LectureNotes.htm">http://www.faculty.biol.ttu.edu/Strauss/Phylogenetics/LectureNotes.htm</a></p><p>Inferring phylogenetic trees:&nbsp;<a href="http://www.cis.hut.fi/Opinnot/T-61.6070/slides2008/pres_6070.pdf"></a><a href="http://www.cis.hut.fi/Opinnot/T-61.6070/slides2008/pres_6070.pdf">http://www.cis.hut.fi/Opinnot/T-61.6070/slides2008/pres_6070.pdf</a></p><p><strong>Lecture Notes</strong></p><p>Chapter 1 - The Diversity, Classification, and Evolution of Vertebrates:<a href="http://academic.emporia.edu/mooredwi/nathist/chap1.htm"></a><a href="http://academic.emporia.edu/mooredwi/nathist/chap1.htm">http://academic.emporia.edu/mooredwi/nathist/chap1.htm</a></p><p>Algorithms for Phylogenetic Reconstructions:<a href="http://lectures.molgen.mpg.de/Algorithmische_Bioinformatik_WS0405/phylogeny_script.pdf"></a><a href="http://lectures.molgen.mpg.de/Algorithmische_Bioinformatik_WS0405/phylogeny_script.pdf">http://lectures.molgen.mpg.de/Algorithmische_Bioinformatik_WS0405/phylogeny_script.pdf</a></p><p>Phylogeny.fr is a free, simple to use web service dedicated to reconstructing and analysing phylogenetic relationships between molecular sequences. Phylogeny.fr runs and connects various bioinformatics programs to reconstruct a robust phylogenetic tree from a set of sequences. For more detail :&nbsp;<a href="http://www.phylogeny.fr/version2_cgi/index.cgi"></a><a href="http://www.phylogeny.fr/version2_cgi/index.cgi">http://www.phylogeny.fr/version2_cgi/index.cgi</a></p><p>A Brief Tutorial on Phylogenetics<br /><a href="http://bioss.ac.uk/~dirk/talks/tutorial_phylogenetics.pdf"></a><a href="http://bioss.ac.uk/~dirk/talks/tutorial_phylogenetics.pdf">http://bioss.ac.uk/~dirk/talks/tutorial_phylogenetics.pdf</a></p><p>A Brief Tutorial on Phylogenetics Human Rabbit Chicken<br /><a href="http://bioss.ac.uk/~dirk/talks/psnup_tutorial_phylogenetics.pdf"></a><a href="http://bioss.ac.uk/~dirk/talks/psnup_tutorial_phylogenetics.pdf">http://bioss.ac.uk/~dirk/talks/psnup_tutorial_phylogenetics.pdf</a></p><p>Phylogenetic Tree Computation Tutorial Overview<br /><a href="http://pga.lbl.gov/Workshop/April2002/lectures/Olken.pdf"></a><a href="http://pga.lbl.gov/Workshop/April2002/lectures/Olken.pdf">http://pga.lbl.gov/Workshop/April2002/lectures/Olken.pdf</a></p><p>MrBayes: A program for the Bayesian inference of phylogeny<br /><a href="http://golab.unl.edu/teaching/SBseminar/manual.pdf"></a><a href="http://golab.unl.edu/teaching/SBseminar/manual.pdf">http://golab.unl.edu/teaching/SBseminar/manual.pdf</a></p><p><strong>Web sites providing software for the construction of phylogenetic trees</strong></p><ul>
<li><a href="http://www.mbio.ncsu.edu/BioEdit/bioedit.html">BioEdit</a></li>
</ul><ul>
<li><a href="http://www.dinofish.com/">Coelocanth-Fish Out of Time</a></li>
</ul><ul>
<li><a href="http://cbrg.inf.ethz.ch/">Computational Biochemistry Research Group</a></li>
</ul><ul>
<li><a href="http://www.geocities.com/RainForest/Vines/8695/software.html">Digital Taxonomy</a></li>
</ul><ul>
<li><a href="http://www.cladistics.org/education/hennig86.html">Hennig 86</a></li>
</ul><ul>
<li><a href="http://www.bioinformaticssolutions.com/">Hyperclean</a>&nbsp;from Bioinformatics Solutions, Inc.</li>
</ul><ul>
<li><a href="http://www.mun.ca/biology/scarr/Directory.html">Memorial University of Newfoundland</a></li>
</ul><ul>
<li><a href="http://morphbank.ebc.uu.se/mrbayes/">Mr. Bayes</a></li>
</ul><ul>
<li><a href="http://www.cladistics.com/about_nona.htm">NONA</a></li>
</ul><ul>
<li><a href="http://evolve.zoo.ox.ac.uk/">Oxford University Evolutionary Biology Group</a></li>
</ul><ul>
<li><a href="http://flatpebble.nceas.ucsb.edu/public/">Paleobiology Database</a></li>
</ul><ul>
<li><a href="http://paup.csit.fsu.edu/index.html">PAUP</a></li>
</ul><ul>
<li><a href="http://evolution.genetics.washington.edu/phylip.html">Phylip Homepage</a></li>
</ul><ul>
<li><a href="http://research.amnh.org/scicomp/projects/poy.php">Poy</a></li>
</ul><ul>
<li><a href="http://www.sinauer.com/">Sinauer Associates</a></li>
</ul><ul>
<li><a href="http://www.cladistics.org/downloads/webtnt.html">TNT</a>-Tree Analysis Using New Technology</li>
</ul><ul>
<li><a href="http://www.treebase.org/treebase/index.html">Tree Base</a></li>
</ul><ul>
<li><a href="http://www.treefinder.de/">Treefinder</a></li>
</ul><ul>
<li><a href="http://www.tree-puzzle.de/">Tree-Puzzle</a></li>
</ul><ul>
<li><a href="http://taxonomy.zoology.gla.ac.uk/rod/treeview.html">Tree View</a>-Taxonomy and Systematics Group at Glasgow</li>
</ul><ul>
<li><a href="http://evolution.genetics.washington.edu/phylip/software.html">Washington University</a>-List of Phylogeny Software</li>
</ul>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43548/upgma-worked-example</guid>
	<pubDate>Wed, 13 Oct 2021 06:13:34 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43548/upgma-worked-example</link>
	<title><![CDATA[UPGMA Worked Example]]></title>
	<description><![CDATA[<p><span>The tabs below include a walkthrough of clustering 7 biological sequences (A-G) using the Unweighted Pair-Group Method with Arithmetic mean (UPGMA) method. Note that UPGMA is actually a generic method and thus the walkthrough could apply to any objects A-G for which pairwise distances can be calculated. A small CGI site for generating a UPGMA tree from a distance matrix can be found&nbsp;</span><a href="http://bioware.soton.ac.uk/upgma.html">here</a><span>.</span></p><p>Address of the bookmark: <a href="http://www.slimsuite.unsw.edu.au/teaching/upgma/" rel="nofollow">http://www.slimsuite.unsw.edu.au/teaching/upgma/</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
</item>

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