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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/34221?offset=430</link>
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	<description><![CDATA[]]></description>
	
	
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/26828/bioinfolab</guid>
  <pubDate>Fri, 25 Mar 2016 11:05:35 -0500</pubDate>
  <link></link>
  <title><![CDATA[BioinfoLab]]></title>
  <description><![CDATA[
<p>Laboratory of Statistics and Computational tools for Bioinformatics</p>

<p>The Laboratory of Statistics and Computational tools for Bioinformatics (BioinfoLab) is hosted at the Istituto per le Applicazioni del Calcolo "Mauro Picone" - CNR . The laboratory has been officially opened in 2012 with the support of Programma Operativo Nazionale "Ricerca e Competitività" 2007-2013 (PON "R&amp;C"), and it incorporates several expertise and research activities started since 2007, and supported by several CNR projects. Main interest of BioinfoLab is to develop novel statistical methods and computational tools for the analysis of high dimensional data arising from "Multi-omics" applications. In particular, current activities involve the analysis of ChIP-seq and RNA-seq experiments. </p>

<p>More at http://bioinfo.na.iac.cnr.it/BioinfoLab/index.html</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27465/stand-alone-programs-for-bioinformatician</guid>
	<pubDate>Sat, 21 May 2016 22:50:15 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27465/stand-alone-programs-for-bioinformatician</link>
	<title><![CDATA[Stand-alone programs for Bioinformatician]]></title>
	<description><![CDATA[<p>This directory contains applications for stand-alone use, built specifically for a Linux 64-bit machine.</p>
<p>For help on the bigBed and bigWig applications see:<br>http://genome.ucsc.edu/goldenPath/help/bigBed.html<br>http://genome.ucsc.edu/goldenPath/help/bigWig.html</p>
<p>View the file 'FOOTER' to see the usage statement for each of the applications.</p><p>Address of the bookmark: <a href="http://hgdownload.cse.ucsc.edu/admin/exe/linux.x86_64/" rel="nofollow">http://hgdownload.cse.ucsc.edu/admin/exe/linux.x86_64/</a></p>]]></description>
	<dc:creator>Radha Agarkar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/30242/genome-assembly-tools-and-software-part1</guid>
	<pubDate>Mon, 19 Dec 2016 18:09:22 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/30242/genome-assembly-tools-and-software-part1</link>
	<title><![CDATA[Genome Assembly Tools and Software - PART1 !!]]></title>
	<description><![CDATA[<p>The genome assemblers generally take a file of short sequence reads and a file of quality-value as the input. Since the quality-value file for the high throughput short reads is usually highly memory-intensive, only a few assemblers, best suited for your assembly. For the sake of computational memory saving and convenience of data inquiry, high-throughput short reads data is always initially formatted to specific data structure. Currently, existing data structure for this usage can be predominantly classified into two categories: string-based model and graph-based model.</p><p>We therefore list many genomle assembly tools here. We mainly reported for the assembly of genomes while the others are designed aiming at handling complex genomes.</p><ul>
<li><a href="http://microbiology.se/software/trimetass/" title="TriMetAss 1.2 &ndash; The Trinity-based Iterative Metagenomics Assembler">TriMetAss 1.2 &ndash; The Trinity-based Iterative Metagenomics Assembler</a>
<ul>
<li>TriMetAss is an extension to the Trinity software [1], which can assemble select regions surrounding interesting features in metagenomic data. The software is particularly useful for very common and well-conserved genes (and &ndash; in theory &ndash; non-coding regions) that can occur in multiple contexts in the microbial community under study. It uses Vmatch [2] to extend seed reads (or contigs generated by another assembler) into longer contigs, by iteratively calling Vmatch and Trinity, until some stop criteria are met. Currently, TriMetAss lacks a thorough documentation, but you can direct questions to me if the README.txt file and the &ldquo;-h&rdquo; option is not sufficient to understand the software.<br /><br /></li>
</ul>
</li>
<li><a href="https://github.com/sharpa/OMWare" title="OMWare 1.0 &ndash; Efficient Assembly of Genome-wide Physical Maps">OMWare 1.0 &ndash; Efficient Assembly of Genome-wide Physical Maps</a>
<ul>
<li>
<p>The purpose of this Python module is help scientists use optical map data.<br />Once complete, it will encapsulate and abstractify optical maps and their most common manipulations as they exist in a variety of formats.</p>
</li>
</ul>
</li>
<li><a href="https://github.com/SaraEl-Metwally/LightAssembler" title="LightAssembler &ndash; Lightweight Resources Assembly Algorithm">LightAssembler &ndash; Lightweight Resources Assembly Algorithm</a>
<ul>
<li>
<p>Lightweight resources assembly algorithm for high-throughput sequencing reads.<br />System requirements<br />64-bit machine with g++ compiler or gcc in general, pthreads,and zlib libraries.</p>
</li>
</ul>
</li>
<li><a href="http://bioinf.spbau.ru/quast" title="QUAST 4.1 &ndash; Quality Assessment Tool for Genome Assemblies">QUAST 4.1 &ndash; Quality Assessment Tool for Genome Assemblies</a>
<ul>
<li>
<p>QUAST evaluates genome assemblies.<br />QUAST works both with and without a reference genome.&nbsp;<br />The tool accepts multiple assemblies, thus is suitable for comparison.</p>
</li>
</ul>
</li>
<li><a href="http://www.dnabaser.com/index.html" title="DNA Baser 4.36 &ndash; DNA Sequence Assembly &amp; Analysis">DNA Baser 4.36 &ndash; DNA Sequence Assembly &amp; Analysis</a>
<ul>
<li>DNA Sequence Assembler is revolutionary bioinformatics software for automatic DNA sequence assembly , DNA sequence analysis, contig editing, file format conversion and mutation detection.<br /><br /></li>
</ul>
</li>
<li><a href="https://github.com/younglululu/COCACOLA" title="COCACOLA &ndash; Binning Metagenomic Contigs using Sequence COmposition, Read CoverAge, CO-alignment, and Paired-end Read LinkAge">COCACOLA &ndash; Binning Metagenomic Contigs using Sequence COmposition, Read CoverAge, CO-alignment, and Paired-end Read LinkAge<br /></a>
<ul>
<li>COCACOLA: a general framework for binning contigs in metagenomic studies incorporating read COverage, CorrelAtion, sequence COmposition and paired-end read LinkAge<br /><br /></li>
</ul>
</li>
<li><a href="http://downloads.jbei.org/data/microbial_communities/MaxBin/MaxBin.html" title="MaxBin 2.2 &ndash; Binning Assembled Metagenomic Sequences">MaxBin 2.2 &ndash; Binning Assembled Metagenomic Sequences</a>
<ul>
<li>MaxBin is software for binning assembled metagenomic sequences based on an Expectation-Maximization algorithm. Users can understand the underlying bins (genomes) of the microbes in their metagenomes by simply providing assembled metagenomic sequences and the reads coverage information or sequencing reads.&nbsp;<br /><br /></li>
</ul>
</li>
<li><a href="http://compbio.fmph.uniba.sk/gaml/" title="GAML 0.1 &ndash; Genome Assembly by Maximum Likelihood">GAML 0.1 &ndash; Genome Assembly by Maximum Likelihood<br /></a>
<ul>
<li>GAML is a prototype genome assembly tool based on maximizing likelihood of the assembly in a model encompaasing error rate, insert length and other features of indvidual sequencing technologies. It can combine datasets produced by different technologies (currently Illumina, 454 and Pacific Biosciences).<br /><br /></li>
</ul>
</li>
<li><a href="https://github.com/kkrizanovic/NanoMark" title="NanoMark &ndash; DNA Assembly Benchmark for Nanopore long reads">NanoMark &ndash; DNA Assembly Benchmark for Nanopore long reads</a>
<ul>
<li>
<p>DNA Assembly Benchmark for Nanopore long reads<br />A system for benchmarking DNA assembly tools, based on 3rd generation sequencers.</p>
</li>
</ul>
</li>
<li><a href="http://ibest.github.io/ARC/" title="ARC 1.1.4-beta &ndash; Assembly by Reduced Complexity">ARC 1.1.4-beta &ndash; Assembly by Reduced Complexity</a>
<ul>
<li>
<p>ARC is a pipeline which facilitates iterative, reference guided de novo assemblies with the intent of:&nbsp;<br />1.Reducing time in analysis and increasing accuracy of results by only considering those reads which should assemble together.<br />2.Reducing/removing reference bias as compared to mapping based approaches.</p>
</li>
</ul>
</li>
<li><a href="https://bioinformatics.cs.vt.edu/zhanglab/software/transps/" title="TransPS 1.1.0 &ndash; Transcriptome Post Scaffolding">TransPS 1.1.0 &ndash; Transcriptome Post Scaffolding</a>
<ul>
<li>TransPS is a pipeline for post-processing of pre-assembled transcriptomes using reference based method. It applies an align-layout-consensus structure, consisting of three major stages. First, query sequences are aligned with a reference genome. Second, query sequences are ordered based on the alignment to the reference. Third, non-redundant sequences matched to the same gene of reference genome are scaffolded into one contig.&nbsp;<br /><br /></li>
</ul>
</li>
<li><a href="http://andersonlab.qb3.berkeley.edu/#/software" title="assemblyManager &ndash; Computing the Robotic Commands for 2ab Assembly">assemblyManager &ndash; Computing the Robotic Commands for 2ab Assembly</a>
<ul>
<li>Clotho provides persistence to such objects through relational databases that at least partially correspond the Clotho data model. Beyond database access and data model API support, Clotho Apps provide more specific functionality to Clotho such as viewing and editing data, running simulations, and automating various tasks. When thinking about Clotho Apps, an appropriate analogy would be Apps running on the Android operating system rather than the add-ons that extend the functionality of Firefox<br /><br /></li>
</ul>
</li>
<li><a href="https://sourceforge.net/projects/transcriptomeassembly/" title="BinPacker 1.1 &ndash; Packing-Based De Novo Transcriptome Assembly from RNA-seq Data">BinPacker 1.1 &ndash; Packing-Based De Novo Transcriptome Assembly from RNA-seq Data</a>
<ul>
<li>BinPacker is a novel de novo assembler by modeling the transcriptome assembly problem as tracking a set of trajectories of items with their sizes representing coverage of their corresponding isoforms by solving a series of bin-packing problems<br /><br /></li>
</ul>
</li>
<li><a href="https://github.com/lh3/fermikit" title="FermiKit 0.13 &ndash; De novo Assembly based Variant Calling pipeline for Illumina Short Reads">FermiKit 0.13 &ndash; De novo Assembly based Variant Calling pipeline for Illumina Short Reads</a>
<ul>
<li>FermiKit is a&nbsp;<em>de novo</em>&nbsp;assembly based variant calling pipeline for deep Illumina resequencing data. It assembles reads into unitigs, maps them to the reference genome and then calls variants from the alignment to an accuracy comparable to conventional mapping based pipelines (see evaluation in the&nbsp;<code>tex</code>&nbsp;directory). The assembly does not only encode SNPs and short INDELs, but also retains long deletions, novel sequence insertions, translocations and copy numbers<br /><br /></li>
</ul>
</li>
<li><a href="https://github.com/Reedwarbler/REPdenovo" title="REPdenovo &ndash; A tool to Construct Repeats directly from Raw Reads">REPdenovo &ndash; A tool to Construct Repeats directly from Raw Reads</a>
<ul>
<li>
<p>REPdenovo is designed for constructing repeats directly from sequence reads. It based on the idea of frequent k-mer assembly. REPdenovo provides many functionalities, and can generate much longer repeats than existing tools. The overall pipeline is shown in the mannual file. REPdenovo supports the following main functionalities.<br />1.Assembly. This step performs k-mer counting. Then we find frequent k-mers whose frequencies are over certain threshold. We then assemble these frequent k-mers into consensus repeats (in the form of contigs). Then we merge the constructed contigs to more completeness ones.<br />2.Scaffolding. We use paired-end reads to connect repeat contigs into scaffolds, also provide the average coverage (indicates the copy number) for each constructed repeats.</p>
</li>
</ul>
</li>
<li><a href="https://github.com/rdpstaff/Xander_assembler" title="Xander &ndash; Gene-targeted Metagenomic Assembler">Xander &ndash; Gene-targeted Metagenomic Assembler</a>
<ul>
<li>Metagenomics can provide important insight into microbial communities. However, assembling metagenomic datasets has proven to be computationally challenging. We present a novel method for targeting assembly of specific protein-coding genes using a graph structure combining both de Bruijn graphs and protein HMMs. The inclusion of HMM information guides the assembly, with concomitant gene annotation.&nbsp;<br /><br /></li>
</ul>
</li>
<li><a href="https://sourceforge.net/projects/swapassembler/" title="SWAP-Assembler 2 &ndash; A scalable and fully parallelized Genome Assembler">SWAP-Assembler 2 &ndash; A scalable and fully parallelized Genome Assembler</a>
<ul>
<li>There is a growing gap between the output of new generation massively parallel sequencing machines and the ability to process and analyze the sequencing data. We present SWAP-Assembler, a scalable and fully parallelized genome assembler designed for massive sequencing data. Intend of using traditional de Bruijn Graph, SWAP-Assembler adopts multi-step bi-directed graph (MSG). With MSG, the standard genome assembly (SGA) is equivalent to the edge merging operations in a semi-group. Then a computation model, SWAP, is designed to parallelize semi-group computation. Experimental results showed that SWAP-Assembler is the fastest and most efficient assemblers ever, it can generated contigs with highest accuracy over all five selected assemblers and longest contig N50 in all selected parallel assemblers. Specially, in the scalability test, SWAP-Assembler can scales up to 1024 cores when processing Fish and Yanhuang dataset, and finishes the assembly work in only 15 and 29 minutes respecitively<br /><br /></li>
</ul>
</li>
<li><a href="https://github.com/ksanao/TGNet" title="TGNet &ndash; Visualization and Quality Assessment of de novo Genome Assemblies">TGNet &ndash; Visualization and Quality Assessment of de novo Genome Assemblies</a>
<ul>
<li>TGNet is a Cytoscape-based tool for visualization and quality assessment of de novo genome assemblies. Specifically it facilitates rapid detection of inconsistencies between a genome assembly and an independently derived transcriptome assembly.<br /><br /></li>
</ul>
</li>
<li><a href="http://sanger-pathogens.github.io/circlator/" title="Circlator 1.1.3 &ndash; A tool to Circularize Genome Assemblies">Circlator 1.1.3 &ndash; A tool to Circularize Genome Assemblies</a>
<ul>
<li>A tool to circularize genome assemblies. The algorithm and benchmarks are described in the&nbsp;<a href="http://www.genomebiology.com/2015/16/1/294">Genome Biology manuscript</a>.&nbsp;<br /><br /></li>
</ul>
</li>
<li><a href="https://github.com/hitbio/misFinder" title="misFinder v0.4.05.05 &ndash; Identify Mis-assemblies in an unbiased manner using Reference and Paired-end Reads">misFinder v0.4.05.05 &ndash; Identify Mis-assemblies in an unbiased manner using Reference and Paired-end Reads</a>
<ul>
<li>misFinder is a tool that aims to identify the assembly errors with high accuracy in an unbiased way and correct these errors at their mis-assembled positions to improve the assembly accuracy for downstream analysis. It combines the information of reference (or close related reference) genome and aligned paired-end reads to the assembled sequence. Structure variation and mis-assembly can be detected by comparing the reference genome and assembled sequence.<br /><br /></li>
</ul>
</li>
<li><a href="http://edwards.sdsu.edu/scaffold_builder/" title="Scaffold_builder v2.2 &ndash; Order Contigs generated by draft sequencing along a Reference Sequence">Scaffold_builder v2.2 &ndash; Order Contigs generated by draft sequencing along a Reference Sequence</a>
<ul>
<li>The abundance of repeat elements in genomes can impede the assembly of a single sequence. The tool Scaffold_builder was designed to generate scaffolds (super contigs of sequences joined by N-bases) using the homology provided by a closely related reference sequence. Scaffold_builder is an advanced wrapper for Nucmer, written in Python that resolves several situations that may arise when mapping contigs to the reference genome.<br /><br /></li>
</ul>
</li>
<li><a href="https://sites.google.com/a/lbl.gov/rnnotator/" title="Rnnotator 3.5.0 &ndash; de novo Transcriptome Assembly pipeline from stranded RNA-Seq reads">Rnnotator 3.5.0 &ndash; de novo Transcriptome Assembly pipeline from stranded RNA-Seq reads</a>
<ul>
<li>Comprehensive annotation and quantification of transcriptomes are outstanding problems in functional genomics. Rnnotator is an automated software pipeline that generates transcript models by de novo assembly of RNA-Seq data without the need for a reference genome. The contigs produced by Rnnotator are highly accurate and reconstruct full-length genes when transcripts are sequenced sufficiently deep, roughly 30X for a given transcript. Rnnotator was designed to assemble Illumina single or paired-end reads. Rnnotator is also able to incorporate strand-specific RNA-Seq reads into the assembly in order to further improve the assembly.<br /><br /></li>
</ul>
</li>
<li><a href="http://satrap.cribi.unipd.it/cgi-bin/satrap.pl" title="SATRAP 0.2 &ndash; SOLiD Assembler TRAnslation Program">SATRAP 0.2 &ndash; SOLiD Assembler TRAnslation Program</a>
<ul>
<li>
<p>A color space assembly must be translated into bases before applying bioinformatics analyses. SATRAP is designed to accomplish this important task adopting a very efficient strategy. The package integrates the Oases pipeline and several optimizations specifically designed for color space management. All steps of the pipeline allow to produce a SOLiD de novo transcriptome assembly and the subsequent color space translation. Alternatively, SATRAP can be used as a stand alone program to perform color space translation for either RNA-seq or DNA-seq SOLiD assemblies.</p>
</li>
</ul>
</li>
<li><a href="http://rrwick.github.io/Bandage/" title="Bandage v0.7.1 &ndash; Navigating De novo Assembly Graphs Easily">Bandage v0.7.1 &ndash; Navigating De novo Assembly Graphs Easily</a>
<ul>
<li>Bandage is a program for visualising de novo assembly graphs. By displaying connections which are not present in the contigs file, Bandage opens up new possibilities for analysing de novo assemblies.<br /><br /></li>
</ul>
</li>
<li><a href="http://hapcol.algolab.eu/" title="HapCol 1.1.1 &ndash; Haplotype Assembly from Long Gapless Reads">HapCol 1.1.1 &ndash; Haplotype Assembly from Long Gapless Reads</a>
<ul>
<li>A fast and memory-efficient method for haplotype assembly from long gapless reads, like those produced by SMRT sequencing technologies (PacBio RS II) and Oxford Nanopore flow cell technologies (MinION).<br /><br /></li>
</ul>
</li>
<li><a href="https://github.com/chengyuan/reago-1.1" title="REAGO 1.1 &ndash; REconstruct 16S ribosomal RNA Genes from MetagenOmic data">REAGO 1.1 &ndash; REconstruct 16S ribosomal RNA Genes from MetagenOmic data<br /></a>
<ul>
<li>an assembly tool for 16S ribosomal RNA recovery from metagenomic data<br /><br /></li>
</ul>
</li>
<li><a href="http://www.bioinfo.ufpr.br/" title="FGAP 1.8.1 &ndash; Automated Gap Closing tool">FGAP 1.8.1 &ndash; Automated Gap Closing tool</a>
<ul>
<li>FGAP aims to improve genome sequences by merging alternative assemblies or incorporating alternative data, analyzing the gap region and indicating the best sequence to close the gap.<br /><br /></li>
</ul>
</li>
<li><a href="http://deweylab.biostat.wisc.edu/detonate/" title="DETONATE 1.10 &ndash; DE novo TranscriptOme rNa-seq Assembly with or without the Truth Evaluation">DETONATE 1.10 &ndash; DE novo TranscriptOme rNa-seq Assembly with or without the Truth Evaluation</a>
<ul>
<li>DETONATE consists of two component packages, RSEM-EVAL and REF-EVAL. Both packages are mainly intended to be used to evaluate de novo transcriptome assemblies, although REF-EVAL can be used to compare sets of any kinds of genomic sequences.<br /><br /></li>
</ul>
</li>
<li><a href="https://github.com/trinityrnaseq/trinityrnaseq/wiki" title="Trinity 2.1.1 &ndash; RNA-Seq De novo Assembly">Trinity 2.1.1 &ndash; RNA-Seq De novo Assembly<br /></a>
<ul>
<li>Trinity represents a novel method for the efficient and robust de novo reconstruction of transcriptomes from RNA-Seq data. Trinity combines three independent software modules: Inchworm, Chrysalis, and Butterfly, applied sequentially to process large volumes of RNA-Seq reads. Trinity partitions the sequence data into many individual de Bruijn graphs, each representing the transcriptional complexity at at a given gene or locus, and then processes each graph independently to extract full-length splicing isoforms and to tease apart transcripts derived from paralogous genes.<br /><br /></li>
</ul>
</li>
<li><a href="https://github.com/shenkers/isoscm" title="IsoSCM 2.0.11 &ndash; Transcript Assembly tool using Multiple Change-point Inference to improve 3&rsquo;UTR Annotation">IsoSCM 2.0.11 &ndash; Transcript Assembly tool using Multiple Change-point Inference to improve 3&rsquo;UTR Annotation</a>
<ul>
<li>IsoSCM (Isoform Structural Change Model) is a new method for transcript assembly &nbsp;that incorporates change-point analysis to improve the 3&prime; UTR annotation process.<br /><br /></li>
</ul>
</li>
<li><a href="http://sanger-pathogens.github.io/iva/" title="IVA 1.0.3 &ndash; Iterative Virus Assembler">IVA 1.0.3 &ndash; Iterative Virus Assembler</a>
<ul>
<li>IVA is a de novo assembler designed to assemble virus genomes that have no repeat sequences, using Illumina read pairs sequenced from mixed populations at extremely high and variable depth.<br /><br /></li>
</ul>
</li>
<li><a href="https://sourceforge.net/projects/spa-assembler/" title="SFA-SPA 0.2.1 &ndash; A Suffix Array based Short Peptide Assembler for Metagenomic Data">SFA-SPA 0.2.1 &ndash; A Suffix Array based Short Peptide Assembler for Metagenomic Data</a>
<ul>
<li>SFA-SPA is a suffix array based short peptide assembler for metagenomic data<br /><br /></li>
</ul>
</li>
<li><a href="http://www.earlham.ac.uk/rampart/" title="RAMPART 0.12.2 &ndash; A Workflow Management System for de novo Genome Assembly">RAMPART 0.12.2 &ndash; A Workflow Management System for de novo Genome Assembly</a>
<ul>
<li>RAMPART is a de novo assembly pipeline that makes use of third party-tools and High Performance Computing resources. It can be used as a single interface to several popular assemblers, and can perform automated comparison and analysis of any generated assemblies<br /><br /></li>
</ul>
</li>
<li><a href="http://wgs-assembler.sourceforge.net/wiki/index.php?title=Main_Page" title="Celera Assembler 8.3 &ndash; Whole Genome Shotgun Assembler">Celera Assembler 8.3 &ndash; Whole Genome Shotgun Assembler</a>
<ul>
<li>Celera Assembler (wgs-assembler) is scientific software for DNA research. It can reconstruct long sequences of genomic DNA given the fragmentary data produced by whole-genome shotgun sequencing. The Celera Assembler has enabled discovery in microbial genomes, large eukaryotic genomes, diploid genomes, and genomes from environmental samples. Celera Assembler contributed the first diploid sequence of an individual human, and metagenomics assemblies of the Global Ocean Sampling<br /><br /></li>
</ul>
</li>
<li><a href="https://sourceforge.net/projects/ngopt/" title="A5-miseq 20150522 &ndash; de novo Assembly &amp; Analysis of Illumina Sequence data">A5-miseq 20150522 &ndash; de novo Assembly &amp; Analysis of Illumina Sequence data</a>
<ul>
<li>de novo assembly &amp; analysis of Illumina sequence data, including the A5 pipeline, A5-miseq, tools to evaluate assembly quality, and scripts to facilitate data submission to NCBI and the RAST annotation system<br /><br /></li>
</ul>
</li>
<li><a href="http://www.bcgsc.ca/platform/bioinfo/software/trans-abyss" title="Trans-ABySS 1.5.3 &ndash; Analyze ABySS multi-k-assembled Shotgun Transcriptome Data.">Trans-ABySS 1.5.3 &ndash; Analyze ABySS multi-k-assembled Shotgun Transcriptome Data.</a>
<ul>
<li>Trans-ABySS is a software pipeline for analyzing ABySS-assembled contigs from shotgun transcriptome data. The pipeline accepts assemblies that were generated across a wide range of k values in order to address variable transcript expression levels. It first filters and merges the multi-k assemblies, generating a much smaller set of nonredundant contigs. It contains scripts that map assembled contigs to known transcripts, currently supporting Blat and Exonerate contig-to-genome aligners. It identifies novel splicing events like exon-skipping, novel exons, retained introns, novel introns, and alternative splicing. Its scripts can also estimate gene expression levels, identify candidate polyadenylation sites, and identify candidate gene-fusion events.<br /><br /></li>
</ul>
</li>
<li><a href="https://sourceforge.net/projects/sat-assembler/" title="SAT-Assembler 20160120 &ndash; Scalable and Accurate Targeted Gene Assembly Tool">SAT-Assembler 20160120 &ndash; Scalable and Accurate Targeted Gene Assembly Tool</a>
<ul>
<li>SAT-Assembler can perform targeted gene assembly for both RNA-Seq and metagenomic data. It addresses the above challenges of de novo assembly of large scale NGS data by conducting family-specic gene assembly, homology-guided overlap graph construction, and careful graph traversal.<br /><br /></li>
</ul>
</li>
<li><a href="https://sourceforge.net/projects/operasf/" title="Opera 2.0.2 &ndash; Sequence Assembly Program">Opera 2.0.2 &ndash; Sequence Assembly Program</a>
<ul>
<li>Opera (Optimal Paired-End Read Assembler) is a sequence assembly program . It uses information from paired-end reads to optimally order and orient contigs assembled from shotgun-sequencing reads.<br /><br /></li>
</ul>
</li>
<li><a href="http://www.genecodes.com/" title="Sequencher 5.4.1 &ndash; DNA Sequence Assembly and Analysis">Sequencher 5.4.1 &ndash; DNA Sequence Assembly and Analysis</a>
<ul>
<li>Sequencher is the industry standard software for DNA sequence analysis. It works with all automated sequencers and is widely known for its lightning-fast contig assembly, short learning curve, user-friendly editing tools, and superb technical support. First released almost 15 years ago, Sequencher is currently used for sequence analysis tasks in every major genomic and pharmaceutical company as well as numerous academic and government labs in over 40 countries around the world. Life Science researchers use Sequencher for many diverse DNA sequence analysis applications including de novo gene sequencing, mutation detection, forensic human identification, systematics, and more.<br /><br /></li>
</ul>
</li>
<li><a href="http://minia.genouest.org/" title="Minia 2.0.3 &ndash; Short-read Assembler based on a de Bruijn graph">Minia 2.0.3 &ndash; Short-read Assembler based on a de Bruijn graph</a>
<ul>
<li>Minia is a short-read assembler based on a de Bruijn graph, capable of assembling a human genome on a desktop computer in a day<br /><br /></li>
</ul>
</li>
<li><a href="http://www.genome.umd.edu/masurca.html" title="MaSuRCA 3.1.3 &ndash; Whole Genome Short Read Assembler">MaSuRCA 3.1.3 &ndash; Whole Genome Short Read Assembler</a>
<ul>
<li>MaSuRCA is whole genome assembly software. It combines the efficiency of the de Bruijn graph and Overlap-Layout-Consensus (OLC) approaches. MaSuRCA can assemble data sets containing only short reads from Illumina sequencing or a mixture of short reads and long reads (Sanger, 454).<br /><br /></li>
</ul>
</li>
<li><a href="http://kmergenie.bx.psu.edu/" title="KmerGenie 1.6982 &ndash; K-mer size Selection for Genome Assembly">KmerGenie 1.6982 &ndash; K-mer size Selection for Genome Assembly</a>
<ul>
<li>KmerGenie estimates the best k-mer length for genome de novo assembly. Given a set of reads, KmerGenie first computes the k-mer abundance histogram for many values of k. Then, for each value of k, it predicts the number of distinct genomic k-mers in the dataset, and returns the k-mer length which maximizes this number. Experiments show that KmerGenie&rsquo;s choices lead to assemblies that are close to the best possible over all k-mer lengths.<br /><br /></li>
</ul>
</li>
<li><a href="http://software.broadinstitute.org/software/pilon/" title="pilon v1.16 &ndash; Automated Assembly Improvement">pilon v1.16 &ndash; Automated Assembly Improvement</a>
<ul>
<li>pilon uses read alignment analysis to diagnose, report, and automatically improve de novo genome assemblies.<br /><br /></li>
</ul>
</li>
<li><a href="http://www.phrap.org/phredphrapconsed.html#block_phrap" title="Phred/Phrap/Consed 29.0 &ndash; DNA Sequence Assembler &amp; Finishing Tools">Phred/Phrap/Consed 29.0 &ndash; DNA Sequence Assembler &amp; Finishing Tools<br /></a>
<ul>
<li>phrap is a program for assembling shotgun DNA sequence data. Among other features, it allows use of the entire read and not just the trimmed high quality part, it uses a combination of user-supplied and internally computed data quality information to improve assembly accuracy in the presence of repeats, it constructs the contig sequence as a mosaic of the highest quality read segments rather than a consensus, it provides extensive assembly information to assist in trouble-shooting assembly problems, and it handles large datasets.<br /><br /></li>
</ul>
</li>
<li><a href="https://www.qiagenbioinformatics.com/products/clc-genomics-workbench/" title="CLC Genomics Workbench 8.5.1 &ndash; Assembly &amp; Analysis of Sequencing Data">CLC Genomics Workbench 8.5.1 &ndash; Assembly &amp; Analysis of Sequencing Data</a>
<ul>
<li>CLC Genomics Workbench, for analyzing and visualizing Next Generation Sequencing data, incorporates cutting-edge technology and algorithms, while also supporting and integrating with the rest of your typical NGS workflow.<br /><br /></li>
</ul>
</li>
<li><a href="http://schatzlab.cshl.edu/research/metassembler/" title="Metassembler 1.5 &ndash; Combines multiple Whole Genome de novo Assemblies into a combined Consensus Assembly">Metassembler 1.5 &ndash; Combines multiple Whole Genome de novo Assemblies into a combined Consensus Assembly</a>
<ul>
<li>Metassembler is a software package for reconciling assemblies produced by de novo short-read assemblers such as SOAPdenovo and ALLPATHS-LG. The goal of assembly reconciliation, or &ldquo;metassembly,&rdquo; is to combine multiple assemblies into a single genome that is superior to all of its constituents<br /><br /></li>
</ul>
</li>
<li><a href="https://ics.hutton.ac.uk/tablet/" title="Tablet 1.15.09.01 &ndash; Next Generation Sequence Assembly Visualization">Tablet 1.15.09.01 &ndash; Next Generation Sequence Assembly Visualization</a>
<ul>
<li>Tablet is a lightweight, high-performance graphical viewer for next generation sequence assemblies and alignments.Supporting a range of input assembly formats, Tablet provides high-quality visualizations showing data in packed or stacked views, allowing instant access and navigation to any region of interest, and whole contig overviews and data summaries. Tablet is both multi-core aware and memory efficient, allowing it to handle assemblies containing millions of reads, even on a 32-bit desktop machine.<br /><br /></li>
</ul>
</li>
<li><a href="http://www.bcgsc.ca/platform/bioinfo/software/abyss" title="ABySS 1.9.0 &ndash; de novo, parallel, paired-end Sequence Assembler">ABySS 1.9.0 &ndash; de novo, parallel, paired-end Sequence Assembler</a>
<ul>
<li>ABySS (Assembly By Short Sequences) is a de novo, parallel, paired-end sequence assembler that is designed for short reads. The single-processor version is useful for assembling genomes up to 100 Mbases in size. The parallel version is implemented using MPI and is capable of assembling larger genomes.<br /><br /></li>
</ul>
</li>
<li><a href="http://www.bcgsc.ca/platform/bioinfo/software/cleat" title="CLEAT 2.0 &ndash; Identifies 3&prime; UTR Ends of Transcripts in de novo RNA-Seq Assemblies">CLEAT 2.0 &ndash; Identifies 3&prime; UTR Ends of Transcripts in de novo RNA-Seq Assemblies</a>
<ul>
<li>CLEAT is a post-processing tool for CLEavage site Analysis of Transcriptomes. CLEAT is designed to work on trans-ABySS output.<br /><br /></li>
</ul>
</li>
<li><a href="https://github.com/ythuang0522/StriDe" title="StriDe &ndash; novel Assembler">StriDe &ndash; novel Assembler</a>
<ul>
<li>The StriDe Assembler integrates string and de Bruijn graph by decomposing reads within error-prone regions, while extending paire-end read into long reads for assembly through repetitive regions.<br /><br /></li>
</ul>
</li>
<li><a href="http://www.sanger.ac.uk/science/tools/reapr" title="REAPR 1.0.18 &ndash; Genome Assembly Evaluation">REAPR 1.0.18 &ndash; Genome Assembly Evaluation</a>
<ul>
<li>REAPR (Recognising Errors in Assemblies using Paired Reads) is a tool that evaluates the accuracy of a genome assembly using mapped paired end reads, without the use of a reference genome for comparison. It can be used in any stage of an assembly pipeline to automatically break incorrect scaffolds and flag other errors in an assembly for manual inspection. It reports mis-assemblies and other warnings, and produces a new broken assembly based on the error calls.<br /><br /></li>
</ul>
</li>
<li><a href="https://www.baseclear.com/genomics/bioinformatics/basetools/gapfiller" title="GapFiller 1.10 &ndash; Close Gaps within Pre-assembled Scaffolds">GapFiller 1.10 &ndash; Close Gaps within Pre-assembled Scaffolds</a>
<ul>
<li>GapFiller is a stand-alone program for closing gaps within pre-assembled scaffolds. It is unique in offering the possibility to manually control the gapclosure process. By using the distance information of paired-read data, GapFiller seeks to close the gap from each edge in an iterative manner. From a good number of tests we see the program yields excellent results both on bacterial en eukaryotic &nbsp;datasets. The command-line Perl script and additional files van be downloaded below. The input data is given by pre-assembled scaffold sequences (FASTA) and NGS paired-read data (FASTA or FASTQ).<br /><br /></li>
</ul>
</li>
<li><a href="http://www.bcgsc.ca/platform/bioinfo/software/ssake" title="SSAKE 3.8.4 &ndash; Assembling Millions of short DNA Sequences">SSAKE 3.8.4 &ndash; Assembling Millions of short DNA Sequences</a>
<ul>
<li>SSAKE is a genomics application for assembling millions of very short DNA sequences.SSAKE is designed to help leverage the information from short sequence reads by stringently assembling them into contiguous sequences that can be used to characterize novel sequencing targets.<br /><br /></li>
</ul>
</li>
<li><a href="https://github.com/jts/sga" title="SGA 0.10.14 &ndash; String Graph Assembler">SGA 0.10.14 &ndash; String Graph Assembler</a>
<ul>
<li>SGA is a de novo assembler designed to assemble large genomes from high coverage short read data. The major goal of SGA is to be very memory efficient, which is achieved by using a compressed representation of DNA sequence reads.<br /><br /></li>
</ul>
</li>
<li><a href="https://bibiserv.cebitec.uni-bielefeld.de/cgcat" title="r2cat &ndash; Synteny Plots &amp; Comparative Assembly">r2cat &ndash; Synteny Plots &amp; Comparative Assembly<br /></a>
<ul>
<li>r2cat (related reference based contig arrangement tool) can be used to order a set of contigs with respect to a single reference genome. This is done by mapping the contigs onto the reference using a q-gram filter. The mapping is visualized in a synteny plot.<br /><br /></li>
</ul>
</li>
<li><a href="http://www.bcgsc.ca/platform/bioinfo/software/tasr" title="TASR 1.6 &ndash; Targeted Assembly of Sequence Reads">TASR 1.6 &ndash; Targeted Assembly of Sequence Reads</a>
<ul>
<li>TASR (Targeted Assembly of Sequence Reads) &nbsp;is a genomics application that allows hypothesis-based interrogation of genomic regions (sequence targets) of interest.<br /><br /></li>
</ul>
</li>
<li><a href="https://sourceforge.net/projects/bio-rainbow/" title="Rainbow v2.0.4 &ndash; Clustering and Assembling Short Reads, especially for RAD">Rainbow v2.0.4 &ndash; Clustering and Assembling Short Reads, especially for RAD</a>
<ul>
<li>Rainbow package consists of several programs used for RAD-seq related clustering and de novo assembly.<br /><br /></li>
</ul>
</li>
<li><a href="http://www.sanger.ac.uk/science/tools/caf" title="CAFTOOLS 2.0.2 &ndash; Tools for the Common Assembly Format (CAF)">CAFTOOLS 2.0.2 &ndash; Tools for the Common Assembly Format (CAF)</a>
<ul>
<li>CAFTOOLS comprises a set of libraries and programs for manipulating DNA sequence assemblies using CAF files, a comprehensive representation of a sequence assembly as a text file.</li>
</ul>
</li>
<li>Gap Resolution &ndash; Improving Newbler Genome Assemblies. Gap Resolution was developed by DOE Joint Genome Institute to improve Newbler genome assemblies by automating the closure of sequence gaps caused by repetitive regions in the DNA.<br /><br /></li>
<li><a href="http://jgi.doe.gov/data-and-tools/meraculous/" title="Meraculous 2.0.5 &ndash; De novo Genome Assembler from Short Reads">Meraculous 2.0.5 &ndash; De novo Genome Assembler from Short Reads</a>
<ul>
<li>Meraculous is a new algorithm for whole genome assembly of deep paired-end short reads, and apply it to the assembly of a dataset of paired 75-bp Illumina reads derived from the 15.4 megabase genome of the haploid yeast Pichia stipitis.<br /><br /></li>
</ul>
</li>
<li><a href="https://sourceforge.net/projects/coperead/" title="COPE 1.2.5 &ndash; Pair-end Reads Connection tool to facilitate Genome Assembly">COPE 1.2.5 &ndash; Pair-end Reads Connection tool to facilitate Genome Assembly</a>
<ul>
<li>COPE (Connecting Overlapped Pair-End reads) is a method to align and connect the illumina sequenced Pair-End reads of which the insert size is smaller than the sum of the two read length.The connected reads can be used in genome assembly, resequencing and transcriptome research.<br /><br /></li>
</ul>
</li>
<li><a href="http://sco.h-its.org/exelixis/web/software/pear/index.html" title="PEAR 0.9.6 &ndash; Pair-End reads AssembleR">PEAR 0.9.6 &ndash; Pair-End reads AssembleR</a>
<ul>
<li>PEAR is an ultrafast, memory-efficient and highly accurate pair-end reads assembler. It is fully parallelized and can run with as low as just a few kilobytes of memory.<br /><br /></li>
</ul>
</li>
<li><a href="https://sourceforge.net/projects/ebardenovo/" title="EBARDenovo 2.0.1 &ndash; Highly-accurate de novo Assembler of Paired-end RNA-Seq">EBARDenovo 2.0.1 &ndash; Highly-accurate de novo Assembler of Paired-end RNA-Seq</a>
<ul>
<li>EBARDenovo is a highly-accurate search-based de novo assembler of paired-end RNA-Seq for advance transcriptomic study.<br /><br /></li>
</ul>
</li>
<li><a href="http://marthlab.org/" title="EagleView 2.2 &ndash; Genome Assembler Viewer">EagleView 2.2 &ndash; Genome Assembler Viewer</a>
<ul>
<li>EagleView is an information-rich genome assembler viewer with data integration capability. EagleView can display a dozen different types of information including base qualities, machine specific trace signals, and genome feature annotations. It provides an easy way for inspecting visually the quality of a genome assembly and validating polymorphism candidate sites (e.g., SNPs) reported by polymorphism discovery tools. It can also facilitate data interpretation and hypothesis generation.<br /><br /></li>
</ul>
</li>
<li><a href="http://bioinformatics.tudelft.nl/" title="MAIA 0.5 &ndash; Integrating Genome Assemblies">MAIA 0.5 &ndash; Integrating Genome Assemblies</a>
<ul>
<li>
<p>MAIA (Multiple Assembly IntegrAtion) is an algorithm to integrate multiple genome assemblies. For example, assemblies originating from:<br />&ndash; Different runs of a de novo assembler<br />&ndash; Assemblies of different data types<br />&ndash; Comparative assemblies</p>
</li>
</ul>
</li>
<li><a href="http://cqb.pku.edu.cn/ZhuLab/InteMAP/index.html" title="InteMAP 1.0 &ndash; Integrated Metagenomic Assembly pipeline for NGS Short Reads">InteMAP 1.0 &ndash; Integrated Metagenomic Assembly pipeline for NGS Short Reads<br /></a>
<ul>
<li>InteMAP is a pipeline which integrates individual assemblers for assembling metagenomic short sequencing reads.<br /><br /></li>
</ul>
</li>
<li><a href="http://cqb.pku.edu.cn/ZhuLab/MAP/index.php" title="MAP 20121108 &ndash; A de novo Metagenomic Assembly program for Shotgun DNA reads">MAP 20121108 &ndash; A de novo Metagenomic Assembly program for Shotgun DNA reads</a>
<ul>
<li>MAP (Metagenomic Assembly program) is a de novo assembly approach and its implementation based on an improved Overlap/Layout/Consensus (OLC) strategy incorporated with several special algorithms.MAP uses the mate pair information, resulting in being more applicable to shotgun DNA reads (recommended as &gt; 200 bp) currently widely-used in metagenome projects. Results of extensive tests on simulated data show that MAP can be superior to both Celera and Phrap for typical longer reads by Sanger sequencing, as well as has an evident advantage over Celera, Newbler, and the newest Genovo, for typical shorter reads by 454 sequencing.<br /><br /></li>
</ul>
</li>
<li><a href="http://www.sanger.ac.uk/science/tools/phusion" title="Phusion 2.1c &ndash; Assembly Genome Sequences from Whole Genome Shotgun(WGS) Reads">Phusion 2.1c &ndash; Assembly Genome Sequences from Whole Genome Shotgun(WGS) Reads</a>
<ul>
<li>Phusion is a software package for assembling genome sequences from whole genome shotgun(WGS) reads.<br /><br /></li>
</ul>
</li>
<li><a href="http://www.codoncode.com/aligner/index.htm" title="CodonCode Aligner 6.0.2 &ndash; DNA Sequence Assembly &amp; Alignment">CodonCode Aligner 6.0.2 &ndash; DNA Sequence Assembly &amp; Alignment</a>
<ul>
<li>CodonCode Aligner is a program for sequence assembly, contig editing, and mutation detection, available for Windows and Mac OS X. Aligner is compatible with Phred-Phrap and fully supports sequence quality scores, while offering a familiar, easy-to-learn user interface.<br /><br /></li>
</ul>
</li>
<li><a href="https://sourceforge.net/projects/ceruleanassembler/" title="Cerulean 0.1.1 &ndash; Hybrid Genome Assembler">Cerulean 0.1.1 &ndash; Hybrid Genome Assembler</a>
<ul>
<li>Cerulean is a hybrid assembly using high throughput short and long reads<br /><br /></li>
</ul>
</li>
<li><a href="http://fenderglass.github.io/Ragout/" title="Ragout 1.2 &ndash; Tool for Reference-assisted Assembly">Ragout 1.2 &ndash; Tool for Reference-assisted Assembly</a>
<ul>
<li>Ragout (Reference-Assisted Genome Ordering UTility) is a tool for assisted assembly using multiple references. It takes a short read assembly (a set of contigs), a set of related references and a corresponding phylogenetic tree and then assembles the contigs into scaffolds.<br /><br /></li>
</ul>
</li>
<li><a href="https://zlab.umassmed.edu/~zhuangj/laSV/" title="laSV 1.0.2 &ndash; Local Assembly based Structural Variation Discovery tool">laSV 1.0.2 &ndash; Local Assembly based Structural Variation Discovery tool</a>
<ul>
<li>laSV is a software that employs a local de novo assembly based approach to detect genomic structural variations from whole-genome high-throughput sequencing datasets.<br /><br /></li>
</ul>
</li>
<li><a href="http://bioinf.spbau.ru/en/spades" title="SPAdes 3.6.2 &ndash; Single-cell Genome Assembler">SPAdes 3.6.2 &ndash; Single-cell Genome Assembler</a>
<ul>
<li>SPAdes (St. Petersburg genome assembler) is intended for both standard isolates and single-cell MDA bacteria assemblies.<br /><br /></li>
</ul>
</li>
<li><a href="https://github.com/hitbio/PERGA" title="PERGA 0.5.03.02 &ndash; Paired End Reads Guided Assembler">PERGA 0.5.03.02 &ndash; Paired End Reads Guided Assembler</a>
<ul>
<li>PERGA is a novel sequence reads guided de novo assembly approach which adopts greedy-like prediction strategy for assembling reads to contigs and scaffolds.<br /><br /></li>
</ul>
</li>
<li><a href="https://sourceforge.net/p/telescoper/wiki/Home/" title="Telescoper 0.2 &ndash; De novo Assembly Algorithm">Telescoper 0.2 &ndash; De novo Assembly Algorithm</a>
<ul>
<li>Telescoper is a local assembly algorithm designed for short-reads from NGS platforms such as Illumina. The reads must come from two libraries: one short insert, and one long insert.<br /><br /></li>
</ul>
</li>
<li><a href="http://metacompass.cbcb.umd.edu/" title="MetaCompass 1.0 &ndash; Comparative Assembly of Metagenomic Sequences">MetaCompass 1.0 &ndash; Comparative Assembly of Metagenomic Sequences</a>
<ul>
<li>MetaCompass is a software package for comparative assembly of metagenomic reads. MetaCompass achieves comparable assembly performance to the state of the art de novo assemblers, but these two different approaches complement each other a lot. So combining contigs between MetaCompass and other independent de novo assemblers give us the best overall metagenomic assembly.<br /><br /></li>
</ul>
</li>
<li><a href="http://evopipes.net/docs.html#scarf_section" title="SCARF &ndash; Scaffolded and Corrected Assembly of Roche 454">SCARF &ndash; Scaffolded and Corrected Assembly of Roche 454</a>
<ul>
<li>SCARF is a next-gen sequence assembly tool for evolutionary genomics. Designed especially for assembling 454 EST sequences against high quality reference sequences from related species.<br /><br /></li>
</ul>
</li>
<li><a href="http://metagenomics.atc.tcs.com/MetaCAA/" title="MetaCAA &ndash; Assembly of Metagenomic Datasets">MetaCAA &ndash; Assembly of Metagenomic Datasets</a>
<ul>
<li>MetaCAA is a sequence-assembly tool specifically intended for metagenomes.<br /><br /></li>
</ul>
</li>
<li><a href="http://mjsull.github.io/Contiguity/" title="Contiguity 1.0.4 &ndash; Contig Adjacency Graph Construction and Visualisation">Contiguity 1.0.4 &ndash; Contig Adjacency Graph Construction and Visualisation</a>
<ul>
<li>Contiguity is interactive software for the visualization and manipulation of de novo genome assemblies.<br /><br /></li>
</ul>
</li>
<li><a href="http://bioresearch.byu.edu/scaffoldscaffolder/" title="ScaffoldScaffolder 0.1 &ndash; Solving Contig Orientation via Bidirected to Directed Graph Reduction">ScaffoldScaffolder 0.1 &ndash; Solving Contig Orientation via Bidirected to Directed Graph Reduction</a>
<ul>
<li>ScaffoldScaffolder is a stand-alone scaffolding algorithm which was designed specifically for scaffolding diploid genomes.<br /><br /></li>
</ul>
</li>
<li><a href="https://github.com/cbg-ethz/haploclique" title="HaploClique 0.1 &ndash; Viral Quasispecies Assembly from Paired-end data">HaploClique 0.1 &ndash; Viral Quasispecies Assembly from Paired-end data</a>
<ul>
<li>HaploClique is a computational approach to reconstruct the structure of a viral quasispecies from next-generation sequencing data as obtained from bulk sequencing of mixed virus samples.<br /><br /></li>
</ul>
</li>
<li><a href="http://omics.informatics.indiana.edu/TAG/" title="TAG 0.91 &ndash; Transcript Assembly by Mapping Reads to Graphs">TAG 0.91 &ndash; Transcript Assembly by Mapping Reads to Graphs</a>
<ul>
<li>TAG is a tool for metatranscriptome assembly using de Bruijn graph of matched metagenome as the reference<br /><br /></li>
</ul>
</li>
<li><a href="https://github.com/bioinfomaticsCSU/EPGA2" title="EPGA2 &ndash; De Novo Assembler">EPGA2 &ndash; De Novo Assembler</a>
<ul>
<li>EPGA2 updates some modules in EPGA which can improve memory efficiency in genome asssembly.<br /><br /></li>
</ul>
</li>
<li><a href="https://sourceforge.net/projects/gmcloser/" title="GMcloser 1.5.1 / GMvalue 1.3 &ndash; Closing the Gaps in Scaffolds with Preassembled Contigs">GMcloser 1.5.1 / GMvalue 1.3 &ndash; Closing the Gaps in Scaffolds with Preassembled Contigs</a>
<ul>
<li>GMcloser fills and closes the gaps present in scaffold assemblies, especially those generated by the de novo assembly of whole genomes with next-generation sequencing (NGS) reads.<br /><br /></li>
</ul>
</li>
<li><a href="https://sites.google.com/a/ucr.edu/slicembler/" title="SLICEMBLER &ndash; Meta-assembler Designed for Ultra-deep Sequencing data">SLICEMBLER &ndash; Meta-assembler Designed for Ultra-deep Sequencing data</a>
<ul>
<li>SLICEMBLER is a meta-assembler designed for ultra-deep sequencing data<br /><br /></li>
</ul>
</li>
<li><a href="http://www.cs.colostate.edu/seq/seqlandscape/" title="SEQLandscape v1 &ndash; Generation and Visualization of Sequence Landscape">SEQLandscape v1 &ndash; Generation and Visualization of Sequence Landscape</a>
<ul>
<li>
<p>SEQLandscape is an application allowing the generation and visualization of a sequence landscape.&nbsp;HyDA-Vista: Towards Optimal Guided Selection of k-mer Size for Sequence Assembly.</p>
</li>
</ul>
</li>
<li><a href="http://www.cs.colostate.edu/seq/missequel/" title="misSEQuel v1.0beta &ndash; Misassembly Detection in Draft Genomes">misSEQuel v1.0beta &ndash; Misassembly Detection in Draft Genomes</a>
<ul>
<li>misSEQuel is a software that enhances the quality of draft genomes by identifying misassembly errors and their breakpoints using paired-end sequence reads and optical mapping data.<br /><br /></li>
</ul>
</li>
<li><a href="http://scit.us/projects/dawg/" title="Dawg 1.2 &ndash; Simulating Sequence Evolution">Dawg 1.2 &ndash; Simulating Sequence Evolution</a>
<ul>
<li>Dawg (DNA Assembly with Gaps) is an application designed to simulate the evolution of recombinant DNA sequences in continuous time based on the robust general time reversible model with gamma and invariant rate heterogeneity and a novel length-dependent model of gap formation.<br /><br /></li>
</ul>
</li>
<li><a href="http://busco.ezlab.org/" title="BUSCO v1.1b1 &ndash; Assessing Genome Assembly and Annotation Completeness with Single-copy Orthologs">BUSCO v1.1b1 &ndash; Assessing Genome Assembly and Annotation Completeness with Single-copy Orthologs</a>
<ul>
<li>BUSCO completeness assessment employs sets of Benchmarking Universal Single-Copy Orthologs from OrthoDB to provide quantitative measures of the completeness of genome assemblies, annotated gene sets, and transcriptomes in terms of expected gene content.<br /><br /></li>
</ul>
</li>
<li><a href="http://kakitone.github.io/finishingTool/" title="FinisherSC 2.0 &ndash; A Repeat-aware tool for upgrading de-novo Assembly using Long Reads">FinisherSC 2.0 &ndash; A Repeat-aware tool for upgrading de-novo Assembly using Long Reads</a>
<ul>
<li>FinisherSC is a repeat-aware and scalable tool for upgrading de-novo assembly using long reads.<br /><br /></li>
</ul>
</li>
<li><a href="https://whatshap.readthedocs.io/en/latest/" title="WhatsHap &ndash; Haplotype Assembly for Future-Generation Sequencing Reads">WhatsHap &ndash; Haplotype Assembly for Future-Generation Sequencing Reads</a>
<ul>
<li>WhatsHap is a software for phasing genomic variants using DNA sequencing reads, also called haplotype assembly. It is especially suitable for long reads, but works also well with short reads.<br /><br /></li>
</ul>
</li>
<li><a href="http://www.mscs.mu.edu/~bozdag/compartmentalized_assembler.html" title="Compartmentalized Assembler &ndash; Assembly of Physical Maps">Compartmentalized Assembler &ndash; Assembly of Physical Maps</a>
<ul>
<li>Compartmentalized assembler is a novel method for the assemlby of high quality physical maps from fingerprinted clones.<br /><br /></li>
</ul>
</li>
<li><a href="http://genome.jgi.doe.gov/viz/" title="Elviz &ndash; Exploration of Metagenomic Assemblies">Elviz &ndash; Exploration of Metagenomic Assemblies</a>
<ul>
<li>Elviz (Environmental Laboratory Visualization) is an interactive web-based tool for the visual exploration of assembled metagenome data and their complex metadata.<br /><br /></li>
</ul>
</li>
<li><a href="http://bs.ipm.ir/softwares/ssp/" title="SSP &ndash; de novo Transcriptome Assembler">SSP &ndash; de novo Transcriptome Assembler</a>
<ul>
<li>SSP is a de novo transcriptome assembler that assembles RNA-seq reads into transcripts. SSP aims to reconstructs all the alternatively spliced isoforms and estimates the expression level of them.<br /><br /></li>
</ul>
</li>
<li><a href="http://viramp.com/" title="VirAmp &ndash; Galaxy-based Viral Genome Assembly pipeline">VirAmp &ndash; Galaxy-based Viral Genome Assembly pipeline</a>
<ul>
<li>VirAmp is a web-based semi-de novo fast virus genome assembly pipeline designed for extremely high coverage NGS data. VirAmp is a collection of existing tools, combined into a single Galaxy interface. Users without further computational knowledge can easily operate the pipeline.<br /><br /></li>
</ul>
</li>
<li><a href="https://github.com/juliema/aTRAM" title="aTRAM&nbsp;1.04 &ndash; automated Target Restricted Assembly Method">aTRAM&nbsp;1.04 &ndash; automated Target Restricted Assembly Method</a>
<ul>
<li>aTRAM performs targeted de novo assembly of loci from paired-end Illumina runs.<br /><br /></li>
</ul>
</li>
<li><a href="http://denovoassembler.sourceforge.net/" title="Ray 2.3.1 &ndash; Parallel Genome Assemblies for Parallel DNA sequencing">Ray 2.3.1 &ndash; Parallel Genome Assemblies for Parallel DNA sequencing</a>
<ul>
<li>Ray is a parallel software that computes de novo genome assemblies with next-generation sequencing data.<br /><br /></li>
</ul>
</li>
<li><a href="http://genome.cs.nthu.edu.tw/CAR/" title="CAR &ndash; Contig Assembly of Prokaryotic Draft Genomes Using Rearrangements">CAR &ndash; Contig Assembly of Prokaryotic Draft Genomes Using Rearrangements</a>
<ul>
<li>CAR is an efficient and more accurate tool for assembling contigs of a prokaryotic draft genome based on a reference genome.<br /><br /></li>
</ul>
</li>
<li><a href="http://www.lstmed.ac.uk/vtbuilder" title="VTBuilder &ndash; Assembly of Multi Isoform Transcriptomes">VTBuilder &ndash; Assembly of Multi Isoform Transcriptomes</a>
<ul>
<li>VTBuilder is a tool for the inference of non-chimeric contigs from read data that has been sequenced from complex multi-isoformic transcriptomes, such as snake venom glands, or rapidly evolving viral populations, such as HIV-1.<br /><br /></li>
</ul>
</li>
<li><a href="http://bioinfolab.uncc.edu/TruHmm_package/" title="TruHmm &ndash; TRanscription Unit Assembly by a Hidden Markov model">TruHmm &ndash; TRanscription Unit Assembly by a Hidden Markov model</a>
<ul>
<li>TruHmm is a reference based transcriptome assembler for prokaryotes, and is suitable for assembling transcripts for directional RNA-seq library.<br /><br /></li>
</ul>
</li>
<li><a href="https://sourceforge.net/projects/rnaseqassembly/?source=navbar" title="Bridger 20141201 &ndash; RNA-Seq Assembly">Bridger 20141201 &ndash; RNA-Seq Assembly</a>
<ul>
<li>Bridger is a new de novo transcriptome assembler which takes advantage of techniques employed in Cufflinks to overcome limitations of the existing de novo assemblers.<br /><br /></li>
</ul>
</li>
<li><a href="https://sourceforge.net/projects/grasp-release/" title="GRASP 0.0.4 &ndash; Guided Reference-based Assembly of Short Peptides">GRASP 0.0.4 &ndash; Guided Reference-based Assembly of Short Peptides</a>
<ul>
<li>GRASP is a gene annotation tool for metagenomic studies. GRASP assembles the fragmented short-peptides, which are called from the NGS reads, and aligns the assembled contigs to the query reference protein. GRASP achieves much higher sensitivity than BLASTP for gene annotation purpose.<br /><br /></li>
</ul>
</li>
<li><a href="http://cortexassembler.sourceforge.net/index.html" title="Cortex 1.05.21 &ndash; Genome Assembly and Variation Analysis">Cortex 1.05.21 &ndash; Genome Assembly and Variation Analysis</a>
<ul>
<li>Cortex is an efficient and low-memory software framework for analysis of genomes using sequence data. There are two main executables, being developed in parallel streams: cortex_con (primary contact Mario Caccamo) is for consensus genome assembly, and cortex_var (primary contact Zamin Iqbal) is for variation and population assembly.<br /><br /></li>
</ul>
</li>
<li><a href="https://github.com/voutcn/megahit" title="MEGAHIT v0.1.4 &ndash; Large and Complex Metagenomics Assembly via Succinct de Bruijn graph">MEGAHIT v0.1.4 &ndash; Large and Complex Metagenomics Assembly via Succinct de Bruijn graph</a>
<ul>
<li>MEGAHIT is a single node assembler for large and complex metagenomics NGS reads, such as soil. It makes use of succinct de Bruijn graph to achieve low memory usage, whereas its goal is not to make memory usage as low as possible.<br /><br /></li>
</ul>
</li>
<li><a href="http://sb.nhri.org.tw/CISA/en/CISA" title="CISA 20140304 &ndash; Contig Integrator for Sequence Assembly">CISA 20140304 &ndash; Contig Integrator for Sequence Assembly</a>
<ul>
<li>CISA has been developed to integrate the assemblies into a hybrid set of contigs, resulting in assemblies of superior contiguity and accuracy, compared with the assemblies generated by the state-of-the-art assemblers and the hybrid assemblies merged by existing tools<br /><br /></li>
</ul>
</li>
<li><a href="http://cole-trapnell-lab.github.io/cufflinks/" title="Cufflinks 2.2.1 &ndash; Transcript Assembler &amp; Abundance Estimator for RNA-Seq">Cufflinks 2.2.1 &ndash; Transcript Assembler &amp; Abundance Estimator for RNA-Seq</a>
<ul>
<li>Cufflinks assembles transcripts, estimates their abundances, and tests for differential expression and regulation in RNA-Seq samples. It accepts aligned RNA-Seq reads and assembles the alignments into a parsimonious set of transcripts. Cufflinks then estimates the relative abundances of these transcripts based on how many reads support each one.<br /><br /></li>
</ul>
</li>
<li><a href="http://colibread.inria.fr/software/mapsembler2/" title="mapsembler 2.2.4 &ndash; Targetted Assembly of Short Sequence Reads">mapsembler 2.2.4 &ndash; Targetted Assembly of Short Sequence Reads</a>
<ul>
<li>Mapsembler is a targeted assembly software. It takes as input a set of NGS raw reads and a set of input sequences (starters). It first determines if each starter is read-coherent, e.g. whether reads confirm the presence of each starter in the original sequence. Then for each read-coherent starter, Mapsembler outputs its sequence neighborhood as a linear sequence or as a graph, depending on the user choice.<br /><br /></li>
</ul>
</li>
<li><a href="https://urgi.versailles.inra.fr/Tools/Tedna" title="Tedna 1.2.2 &ndash; Transposable Element De Novo Assembler">Tedna 1.2.2 &ndash; Transposable Element De Novo Assembler</a>
<ul>
<li>Tedna is a lightweight de novo transposable element assembler. It assembles the transposable elements directly from the raw reads.<br /><br /></li>
</ul>
</li>
<li><a href="http://chitsazlab.org/software.html" title="HyDA 1.3.1 / Squeezambler 2.0.3 &ndash; Hybrid De Novo Assembler">HyDA 1.3.1 / Squeezambler 2.0.3 &ndash; Hybrid De Novo Assembler</a>
<ul>
<li>HyDA is a multipurpose assembler, particularly tested for single cell and normal multicell genome co-assembly<br /><br /></li>
</ul>
</li>
<li><a href="https://github.com/neufeld/pandaseq" title="PANDASEQ 2.8 / Pandaseq-sam 1.3 &ndash; PAired-eND Assembler for DNA sequences">PANDASEQ 2.8 / Pandaseq-sam 1.3 &ndash; PAired-eND Assembler for DNA sequences</a>
<ul>
<li>PANDASEQ is a program to align Illumina reads, optionally with PCR primers embedded in the sequence, and reconstruct an overlapping sequence.<br /><br /></li>
</ul>
</li>
<li><a href="http://lge.ibi.unicamp.br/zorro/" title="ZORRO 2.2 &ndash; Hybrid Sequencing Technology Assembler">ZORRO 2.2 &ndash; Hybrid Sequencing Technology Assembler</a>
<ul>
<li>ZORRO is a hybrid sequencing technology assembler. It merges two sets of pre-assembled contigs into a more contiguous and consistent assembly.<br /><br /></li>
</ul>
</li>
<li><a href="http://ccb.jhu.edu/software/FLASH/" title="FLASH 1.2.11 &ndash; Fast Length Adjustment of SHort reads">FLASH 1.2.11 &ndash; Fast Length Adjustment of SHort reads</a>
<ul>
<li>FLASH (Fast Length Adjustment of SHort reads) is a very accurate fast tool to merge paired-end reads from fragments that are shorter than twice the length of reads. The extended length of reads has a significant positive impact on improvement of genome assemblies.<br /><br /></li>
</ul>
</li>
<li><a href="http://software.broadinstitute.org/allpaths-lg/blog/" title="ALLPATHS-LG 51750 &ndash; Whole Genome Shotgun Assembler">ALLPATHS-LG 51750 &ndash; Whole Genome Shotgun Assembler</a>
<ul>
<li>ALLPATHS-LG (Large Genome) is a whole genome shotgun assembler that can generate high quality assemblies from short reads. It works on both small and large (mammalian size) genomes. To use it, you should first generate ~100 base Illumina reads from two libraries: one from ~180 bp fragments, and one from ~3000 bp fragments, both at about 45x coverage. Sequence from longer fragments will enable longer-range continuity.<br /><br /></li>
</ul>
</li>
<li><a href="http://bioinformaticsonline.com/pages/view/30440/genome-assembly-tools-and-software-part2">More Tools</a> at&nbsp;http://bioinformaticsonline.com/pages/view/30440/genome-assembly-tools-and-software-part2</li>
</ul>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32131/wgs-celera-assembler-version-83rc2</guid>
	<pubDate>Mon, 10 Apr 2017 04:45:40 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32131/wgs-celera-assembler-version-83rc2</link>
	<title><![CDATA[WGS Celera Assembler version 8.3rc2]]></title>
	<description><![CDATA[<p>These are release notes for Celera Assembler version 8.3rc2, which was released on May 24, 2015.<br><br>This distribution package provides a stable, tested, documented version of the software.&nbsp; The distribution is usable on most Unix-like platforms, and some platforms have pre-compiled binary distributions ready for installation.<br><br>The source code package includes full source code (revision 4627), Makefiles, and scripts.&nbsp; A subset of the kmer package (http://kmer.sourceforge.net/, version r1994), used by some modules of Celera Assembler, is included.&nbsp; This distribution includes [http://samtools.sourceforge.net/ SAMtools], [http://www.cbcb.umd.edu/software/jellyfish/ Jellyfish 2.0], [https://github.com/pbjd/pbutgcns PBUTGCNS], [https://github.com/PacificBiosciences/pbdagcon PBDAGCON], [https://github.com/PacificBiosciences/BLASR BLASR], and parts of the [https://github.com/PacificBiosciences/FALCON/tree/v0.1.3 Falcon assembler].<br><br>Full documentation can be found online at http://wgs-assembler.sourceforge.net/.</p>
<p>Interesting scripts within it</p>
<p>urbe@urbo214b[bin] ls&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; []<br>-rwxrwxr-x 1 urbe urbe&nbsp; 11K Apr 10 11:41 addCNSToStore<br>-rwxrwxr-x 1 urbe urbe 575K Apr 10 11:41 addReadsToUnitigs<br>-rwxrwxr-x 1 urbe urbe 128K Apr 10 11:41 analyzeBest<br>-rwxrwxr-x 1 urbe urbe 257K Apr 10 11:41 analyzePosMap<br>-rwxrwxr-x 1 urbe urbe 1,5M Apr 10 11:41 analyzeScaffolds<br>-rwxrwxr-x 1 urbe urbe 224K Apr 10 11:41 asmOutputFasta<br>-rwxrwxr-x 1 urbe urbe 448K Apr 10 11:41 asmOutputStatistics<br>-rwxrwxr-x 1 urbe urbe 2,4K Apr 10 11:41 asmToAGP.pl<br>-rwxrwxr-x 1 urbe urbe 7,6M Apr 10 11:41 blasr<br>-rwxrwxr-x 1 urbe urbe 1,6M Apr 10 11:41 bogart<br>-rwxrwxr-x 1 urbe urbe 183K Apr 10 11:41 bogus<br>-rwxrwxr-x 1 urbe urbe 272K Apr 10 11:41 bogusness<br>-rwxrwxr-x 1 urbe urbe 247K Apr 10 11:41 buildPosMap<br>-rwxrwxr-x 1 urbe urbe 213K Apr 10 11:41 buildRefContigs<br>-rwxrwxr-x 1 urbe urbe 990K Apr 10 11:41 buildUnitigs<br>-rwxrwxr-x 1 urbe urbe&nbsp; 18K Apr 10 11:41 ca2ace.pl<br>-rwxrwxr-x 1 urbe urbe&nbsp; 12K Apr 10 11:41 caqc_help.ini<br>-rwxrwxr-x 1 urbe urbe&nbsp; 61K Apr 10 11:41 caqc.pl<br>-rwxrwxr-x 1 urbe urbe&nbsp; 23K Apr 10 11:41 cat-corrects<br>-rwxrwxr-x 1 urbe urbe&nbsp; 24K Apr 10 11:41 cat-erates<br>-rwxrwxr-x 1 urbe urbe 1,9M Apr 10 11:41 cgw<br>-rwxrwxr-x 1 urbe urbe 1,4M Apr 10 11:41 cgwDump<br>-rwxrwxr-x 1 urbe urbe 204K Apr 10 11:41 chimChe<br>-rwxrwxr-x 1 urbe urbe 201K Apr 10 11:40 chimera<br>-rwxrwxr-x 1 urbe urbe 220K Apr 10 11:41 classifyMates<br>-rwxrwxr-x 1 urbe urbe 201K Apr 10 11:41 classifyMatesApply<br>-rwxrwxr-x 1 urbe urbe 215K Apr 10 11:41 classifyMatesPairwise<br>-rwxrwxr-x 1 urbe urbe 366K Apr 10 11:41 computeCoverageStat<br>-rwxrwxr-x 1 urbe urbe 9,8K Apr 10 11:41 convert-fasta-to-v2.pl<br>-rwxrwxr-x 1 urbe urbe&nbsp; 48K Apr 10 11:41 convertOverlap<br>-rwxrwxr-x 1 urbe urbe 119K Apr 10 11:41 convertSamToCA<br>-rwxrwxr-x 1 urbe urbe&nbsp; 20K Apr 10 11:41 convertToPBCNS<br>-rwxrwxr-x 1 urbe urbe 197K Apr 10 11:41 correct-frags<br>-rwxrwxr-x 1 urbe urbe 259K Apr 10 11:41 correct-olaps<br>-rwxrwxr-x 1 urbe urbe 520K Apr 10 11:41 correctPacBio<br>-rwxrwxr-x 1 urbe urbe 540K Apr 10 11:41 ctgcns<br>-rwxrwxr-x 1 urbe urbe 162K Apr 10 11:40 deduplicate<br>-rwxrwxr-x 1 urbe urbe&nbsp; 37K Apr 10 11:41 demotePosMap<br>-rwxrwxr-x 1 urbe urbe 1,5M Apr 10 11:41 dumpCloneMiddles<br>-rwxrwxr-x 1 urbe urbe 124K Apr 10 11:41 dumpPBRLayoutStore<br>-rwxrwxr-x 1 urbe urbe 1,3M Apr 10 11:41 dumpSingletons<br>-rwxrwxr-x 1 urbe urbe 171K Apr 10 11:41 erate-estimate<br>-rwxrwxr-x 1 urbe urbe 221K Apr 10 11:40 estimate-mer-threshold<br>-rwxrwxr-x 1 urbe urbe 1,5M Apr 10 11:41 extendClearRanges<br>-rwxrwxr-x 1 urbe urbe 1,3M Apr 10 11:41 extendClearRangesPartition<br>-rwxrwxr-x 1 urbe urbe 205K Apr 10 11:40 extractmessages<br>-rwxrwxr-x 1 urbe urbe 7,2M Apr 10 11:41 falcon_sense<br>-rwxrwxr-x 1 urbe urbe 9,8K Apr 10 11:41 fastaToCA<br>-rwxrwxr-x 1 urbe urbe 124K Apr 10 11:40 fastqAnalyze<br>-rwxrwxr-x 1 urbe urbe 137K Apr 10 11:40 fastqSample<br>-rwxrwxr-x 1 urbe urbe&nbsp; 62K Apr 10 11:40 fastqSimulate<br>-rwxrwxr-x 1 urbe urbe 121K Apr 10 11:40 fastqSimulate-sort<br>-rwxrwxr-x 1 urbe urbe 246K Apr 10 11:40 fastqToCA<br>-rwxrwxr-x 1 urbe urbe 140K Apr 10 11:41 filterOverlap<br>-rwxrwxr-x 1 urbe urbe 341K Apr 10 11:40 finalTrim<br>-rwxrwxr-x 1 urbe urbe 228K Apr 10 11:41 fixUnitigs<br>-rwxrwxr-x 1 urbe urbe 147K Apr 10 11:40 fragmentDepth<br>-rwxrwxr-x 1 urbe urbe&nbsp; 29K Apr 10 11:41 fragsInVars<br>-rwxrwxr-x 1 urbe urbe 545K Apr 10 11:41 frgs2clones<br>-rwxrwxr-x 1 urbe urbe 398K Apr 10 11:40 gatekeeper<br>-rwxrwxr-x 1 urbe urbe 139K Apr 10 11:40 gatekeeperbench<br>-rwxrwxr-x 1 urbe urbe 167K Apr 10 11:40 gkpStoreCreate<br>-rwxrwxr-x 1 urbe urbe 147K Apr 10 11:40 gkpStoreDumpFASTQ<br>-rwxrwxr-x 1 urbe urbe 184K Apr 10 11:41 greedyFragmentTiling<br>-rwxrwxr-x 1 urbe urbe 1,6K Apr 10 11:41 greedy_layout_to_IUM<br>-rwxrwxr-x 1 urbe urbe 142K Apr 10 11:40 initialTrim<br>-rwxrwxr-x 1 urbe urbe 967K Apr 10 11:41 jellyfish<br>-rwxrwxr-x 1 urbe urbe 219K Apr 10 11:41 markRepeatUnique<br>-rwxrwxr-x 1 urbe urbe 273K Apr 10 11:40 markUniqueUnique<br>-rwxrwxr-x 1 urbe urbe 114K Apr 10 11:40 mercy<br>-rwxrwxr-x 1 urbe urbe 3,8K Apr 10 11:41 mergeqc.pl<br>-rwxrwxr-x 1 urbe urbe 422K Apr 10 11:40 merTrim<br>-rwxrwxr-x 1 urbe urbe 125K Apr 10 11:40 merTrimApply<br>-rwxrwxr-x 1 urbe urbe 376K Apr 10 11:40 meryl<br>-rwxrwxr-x 1 urbe urbe 176K Apr 10 11:41 metagenomics_ovl_analyses<br>-rwxrwxr-x 1 urbe urbe 297K Apr 10 11:41 olap-from-seeds<br>-rwxrwxr-x 1 urbe urbe 275K Apr 10 11:41 outputLayout<br>-rwxrwxr-x 1 urbe urbe 229K Apr 10 11:41 overlapInCore<br>-rwxrwxr-x 1 urbe urbe 144K Apr 10 11:40 overlap_partition<br>-rwxrwxr-x 1 urbe urbe 179K Apr 10 11:41 overlapStats<br>-rwxrwxr-x 1 urbe urbe 179K Apr 10 11:41 overlapStore<br>-rwxrwxr-x 1 urbe urbe 153K Apr 10 11:41 overlapStoreBucketizer<br>-rwxrwxr-x 1 urbe urbe 175K Apr 10 11:41 overlapStoreBuild<br>-rwxrwxr-x 1 urbe urbe&nbsp; 33K Apr 10 11:41 overlapStoreIndexer<br>-rwxrwxr-x 1 urbe urbe&nbsp; 48K Apr 10 11:41 overlapStoreSorter<br>-rwxrwxr-x 1 urbe urbe 604K Apr 10 11:40 overmerry<br>lrwxrwxrwx 1 urbe urbe&nbsp;&nbsp;&nbsp; 4 Apr 10 11:41 pacBioToCA -&gt; PBcR<br>-rwxrwxr-x 1 urbe urbe 131K Apr 10 11:41 PBcR<br>-rwxrwxr-x 1 urbe urbe 2,9M Apr 10 11:41 pbdagcon<br>-rwxrwxr-x 1 urbe urbe 1,9M Apr 10 11:41 pbutgcns<br>-rwxrwxr-x 1 urbe urbe 201K Apr 10 11:40 remove_fragment<br>-rwxrwxr-x 1 urbe urbe 153K Apr 10 11:40 removeMateOverlap<br>-rwxrwxr-x 1 urbe urbe 2,5K Apr 10 11:41 replaceUIDwithName-fastq<br>-rwxrwxr-x 1 urbe urbe 1,2K Apr 10 11:41 replaceUIDwithName-posmap<br>-rwxrwxr-x 1 urbe urbe 1,3M Apr 10 11:41 resolveSurrogates<br>-rwxrwxr-x 1 urbe urbe 139K Apr 10 11:41 rewriteCache<br>-rwxrwxr-x 1 urbe urbe 232K Apr 10 11:41 runCA<br>-rwxrwxr-x 1 urbe urbe&nbsp; 88K Apr 10 11:41 runCA-dedupe<br>-rwxrwxr-x 1 urbe urbe&nbsp; 14K Apr 10 11:41 runCA-overlapStoreBuild<br>-rwxrwxr-x 1 urbe urbe 3,6K Apr 10 11:41 run_greedy.csh<br>-rwxrwxr-x 1 urbe urbe 297K Apr 10 11:40 sffToCA<br>-rwxrwxr-x 1 urbe urbe&nbsp; 13K Apr 10 11:40 show-corrects<br>-rwxrwxr-x 1 urbe urbe 557K Apr 10 11:41 splitUnitigs<br>-rwxrwxr-x 1 urbe urbe 1,4M Apr 10 11:41 terminator<br>drwxrwxr-x 2 urbe urbe 4,0K Apr 10 11:41 TIGR<br>-rwxrwxr-x 1 urbe urbe 526K Apr 10 11:41 tigStore<br>-rwxrwxr-x 1 urbe urbe&nbsp; 35K Apr 10 11:41 tracearchiveToCA<br>-rwxrwxr-x 1 urbe urbe&nbsp; 35K Apr 10 11:41 tracedb-to-frg.pl<br>-rwxrwxr-x 1 urbe urbe&nbsp; 44K Apr 10 11:41 trimFastqByQVWindow<br>-rwxrwxr-x 1 urbe urbe&nbsp; 18K Apr 10 11:40 uidclient<br>-rwxrwxr-x 1 urbe urbe 589K Apr 10 11:41 unitigger<br>-rwxrwxr-x 1 urbe urbe&nbsp; 42K Apr 10 11:40 upgrade-v8-to-v9<br>-rwxrwxr-x 1 urbe urbe&nbsp; 42K Apr 10 11:40 upgrade-v9-to-v10<br>-rwxrwxr-x 1 urbe urbe&nbsp; 854 Apr 10 11:41 utg2fasta<br>-rwxrwxr-x 1 urbe urbe 731K Apr 10 11:41 utgcns<br>-rwxrwxr-x 1 urbe urbe 561K Apr 10 11:41 utgcnsfix<br><br><br></p><p>Address of the bookmark: <a href="http://wgs-assembler.sourceforge.net/wiki/index.php/Main_Page" rel="nofollow">http://wgs-assembler.sourceforge.net/wiki/index.php/Main_Page</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/36373/tools-to-predict-the-impact-of-missense-variants</guid>
	<pubDate>Mon, 23 Apr 2018 12:57:33 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/36373/tools-to-predict-the-impact-of-missense-variants</link>
	<title><![CDATA[Tools to Predict the Impact of Missense Variants !]]></title>
	<description><![CDATA[<p><span>Prioritizing missense variants for further experimental investigation is a key challenge in current sequencing studies for exploring complex and Mendelian diseases. A large number of&nbsp;</span><em>in silico</em><span>&nbsp;tools have been employed for the task of pathogenicity prediction, including PolyPhen‐2, SIFT, FatHMM, MutationTaster‐2, MutationAssessor, Combined Annotation Dependent Depletion, LRT, phyloP, and GERP++, as well as optimized methods of combining tool scores, such as Condel and Logit. Due to the wealth of these methods, an important practical question to answer is which of these tools generalize best, that is, correctly predict the pathogenic character of new variants. </span></p><p><span>Study of 10 tools on five datasets that such a comparative evaluation of these tools is hindered by two types of circularity: they arise due to (1) the same variants or (2) different variants from the same protein occurring both in the datasets used for training and for evaluation of these tools, which may lead to overly optimistic results. Comparative evaluations of predictors that do not address these types of circularity may erroneously conclude that circularity confounded tools are most accurate among all tools, and may even outperform optimized combinations of tools.</span></p><p><span>Following tools are useful for mis sense muation detection ...&nbsp;</span></p><p>PolyPhen‐2 (PP2)<br />&ldquo;Predicts possible impact of an amino acid substitution on the structure and function of a human protein using straightforward physical and comparative considerations&rdquo;</p><p>MutationTaster‐2 (MT2)<br />&ldquo;Evaluation of the disease‐causing potential of DNA sequence alterations&rdquo;</p><p>MutationAssessor (MASS)<br />&ldquo;Predicts the functional impact of amino acid substitutions in proteins, such as mutations discovered in cancer or missense polymorphisms&rdquo;</p><p>LRT<br />&ldquo;Identify a subset of deleterious mutations that disrupt highly conserved amino acids within protein‐coding sequences, which are likely to be unconditionally deleterious&rdquo;</p><p>SIFT<br />&ldquo;Predicts whether an amino acid substitution affects protein function&rdquo;</p><p>GERP++<br />&ldquo;Identifies constrained elements in multiple alignments by quantifying substitution deficits. These deficits represent substitutions that would have occurred if the element were neutral DNA, but did not occur because the element has been under functional constraint. We refer to these deficits as &ldquo;rejected substitutions.&rdquo; Rejected substitutions are a natural measure of constraint that reflects the strength of past purifying selection on the element&rdquo;</p><p>phyloP<br />&ldquo;Compute conservation or acceleration P values based on an alignment and a model of neutral evolution&rdquo;</p><p>FatHMM unweighted (FatHMM‐U)<br />Predicts &ldquo;functional consequences of both coding variants, that is, nonsynonymous single‐nucleotide variants, and noncoding variants&rdquo;</p><p>FatHMM weighted (FatHMM‐W)<br />Predicts &ldquo;functional consequences of both coding variants, that is, nonsynonymous single‐nucleotide variants, and noncoding variants&rdquo; and its weighting scheme attributes higher tolerance scores to SNVs in proteins, related proteins, or domains that already include a high fraction of pathogenic variantsh</p><p>Combined Annotation Dependent Depletion (CADD)<br />&ldquo;CADD is a tool for scoring the deleteriousness of single‐nucleotide variants as well as insertion/deletions variants in the human genome&rdquo;</p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/36398/tools-for-protein-protein-docking</guid>
	<pubDate>Wed, 25 Apr 2018 05:15:53 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/36398/tools-for-protein-protein-docking</link>
	<title><![CDATA[Tools for Protein-Protein Docking !]]></title>
	<description><![CDATA[<p>Predicting the structure of protein&ndash;protein complexes using docking approaches is a difficult problem whose major challenges include identifying correct solutions, and properly dealing with molecular flexibility and conformational changes. Following are the tools to predict&nbsp;<span>the structure of protein&ndash;protein complexes:</span></p><p><a href="http://www.sbg.bio.ic.ac.uk/docking/index.html" target="_blank">3D-Dock Suite</a></p><p>Global rigid search: FFTShape complementarity and electrostatics</p><p>Re-scoring and clustering. Refinement of interface side-chains</p><p><a href="http://www.sbg.bio.ic.ac.uk/~3dgarden/" target="_blank">3D-Garden</a></p><p>Global rigid search in ensamble</p><p>Shape complementarity and Lennard&ndash;Jones potential</p><p>Side chain and backbone dihedral refinement</p><p><a href="http://www.sdsc.edu/CCMS/DOT/" target="_blank">DOT</a></p><p>Global rigid search: FFTShape complementarity, electrostatics and VDWNone</p><p><a href="http://users.unimi.it/~ddl/escherng/index.htm" target="_blank">Escher NG</a></p><p>Global rigid searchShape complementarity, hydrogen bonds and electrostatic</p><p>Integrated in&nbsp;<a href="http://users.unimi.it/~ddl/vega/download.htm" target="_blank">VEGA</a></p><p><a href="http://vakser.bioinformatics.ku.edu/resources/gramm/gramm1" target="_blank">GRAMM</a>&nbsp;</p><p>Global rigid search: FFT. smooth protein surface representation for soft docking</p><p>Shape complementarity and Lennard-Jones potential</p><p>Clustering of conformations</p><p><a href="http://vakser.bioinformatics.ku.edu/resources/gramm/grammx/" target="_blank">GRAMM-X</a>&nbsp;</p><p>Global rigid search: FFT. smooth protein surface representation for soft docking</p><p>Shape complementarity and Lennard-Jones potentialminimization and re-scoring with multiple filters</p><p><a href="http://www.loria.fr/~ritchied/hex_server/" target="_blank">HEX</a></p><p>Global rigid search: Fourier correlation of spherical harmonics</p><p>Shape complementarity</p><p><a href="http://www.csd.abdn.ac.uk/hex/" target="_blank"></a><a href="http://haddock.chem.uu.nl/Haddock/haddock.php" target="_blank">HADDOCK</a></p><p>Global rigid searchElectrostatic ,VDW and desolvation energy termsMD simulated annealing refinement . Filtering based on external data.&nbsp;</p><p><a href="http://www.molsoft.com/docking.html">ICM</a></p><p>Global rigid search: Monte CarloEmpirical scoring function</p><p>Clustering and selection of conformations. Refinement of interface side-chains and re-scoring</p><p><a href="http://www.weizmann.ac.il/Chemical_Research_Support/molfit/" target="_blank">MolFit&nbsp;</a></p><p>Global rigid search: FFTShape complementarity</p><p>Clustering of good solutions, filtering using&nbsp;<em>a priori&nbsp;</em>information and small, local rigid rotations around selected conformations</p><p><a href="http://bioinfo3d.cs.tau.ac.il/PatchDock/" target="_blank">PatchDock</a></p><p>Global rigid searchShape complementarity and atomic desolvation energy</p><p>Clustering of conformations</p><p><a href="http://inb.bsc.es/gn6/PyDock" target="_blank">PyDock</a></p><p>Global rigid search:FFTShape complementarity</p><p>rescoring by binding electrostatics and desolvation energy</p><p><a href="http://bioinfo3d.cs.tau.ac.il/PatchDock/" target="_blank"></a><a href="http://rosettadock.graylab.jhu.edu/" target="_blank">RosettaDock</a></p><p>Local rigid search: Monte Carlo with low and high resolution structure representation levels</p><p>Different scoring parameters for the different resolutions&nbsp;</p><p><a href="http://zlab.bu.edu/zdock/" target="_blank">ZDOCK</a></p><p>Global rigid search: FFTShape complementarity, desolvation energy, and electrostatics.</p><p>Energy minimization and re-scoringFree for academics</p><p>&nbsp;</p><p>Point to note:</p><p>The proper treatment of flexibility in protein&ndash;protein docking is still an active field of research. You first should analyzed your proteins in order to define their conformational space and then choose the most suitable method for your docking problem.</p>]]></description>
	<dc:creator>Poonam Mahapatra</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36514/evidentialgene-tr2aacds-mrna-transcript-assembly-software</guid>
	<pubDate>Tue, 08 May 2018 04:39:39 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36514/evidentialgene-tr2aacds-mrna-transcript-assembly-software</link>
	<title><![CDATA[EvidentialGene: tr2aacds, mRNA Transcript Assembly Software]]></title>
	<description><![CDATA[<p><span>EvidentialGene is a genome informatics project, "Evidence Directed Gene Construction for Eukaryotes", to construct high quality, accurate gene sets for animals and plants, developed by Don Gilbert at Indiana University, see</span><br><a href="http://arthropods.eugenes.org/EvidentialGene/" target="_blank">http://arthropods.eugenes.org/EvidentialGene/<span></span></a><br><br><span>Construction refers to the combination of classical gene prediction, and more recent gene assembly (de-novo and genome-assisted) methods. The basic Evigene methods involve using available best-of-breed gene prediction and assembly software, combining all evidence for genes, from expressed sequences, genome assembly sequences, related species protein sequences, and any other, to annotate and score gene constructions. Over-produced constructions are classified by gene evidence for best qualities per "locus", including genome-aligned and gene-transcript aligned (genome-free) locus identification. All software developed for EvidentialGene is publicly available. See project wiki/blog for notes.</span></p>
<p><span>Download&nbsp;</span></p>
<p>http://arthropods.eugenes.org/EvidentialGene/trassembly.html</p>
<p>https://sourceforge.net/p/evidentialgene/blog/</p><p>Address of the bookmark: <a href="http://arthropods.eugenes.org/EvidentialGene/trassembly.html" rel="nofollow">http://arthropods.eugenes.org/EvidentialGene/trassembly.html</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38004/vcfr-a-package-to-manipulate-and-visualize-vcf-data-in-r</guid>
	<pubDate>Thu, 25 Oct 2018 09:05:59 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38004/vcfr-a-package-to-manipulate-and-visualize-vcf-data-in-r</link>
	<title><![CDATA[vcfR:  a package to manipulate and visualize VCF data in R]]></title>
	<description><![CDATA[<p><span>VcfR is an R package intended to allow easy manipulation and visualization of variant call format (VCF) data. Functions are provided to rapidly read from and write to VCF files. Once VCF data is read into R a parser function extracts matrices from the VCF data for use with typical R functions. This information can then be used for quality control or other purposes. Additional functions provide visualization of genomic data. Once processing is complete data may be written to a VCF file or converted into other popular R objects (e.g., genlight, DNAbin). VcfR provides a link between VCF data and the R environment connecting familiar software with genomic data.</span></p><p>Address of the bookmark: <a href="https://github.com/knausb/vcfR" rel="nofollow">https://github.com/knausb/vcfR</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/43896/list-of-comparative-genomics-resources</guid>
	<pubDate>Tue, 28 Jun 2022 04:08:06 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/43896/list-of-comparative-genomics-resources</link>
	<title><![CDATA[List of comparative genomics resources !]]></title>
	<description><![CDATA[<div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1096638041"><span>3D-GENOMICS -- A Database to Compare Structural and Functional Annotations of Proteins between Sequenced Genomes</span></a></div><p>Compare structural and functional annotations of proteins between sequenced genomes.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1100640374"><span>ARED Organism -- expansion of ARED reveals AU-rich element cluster variations between human and mouse</span></a></div><p>View AREs in the human transcriptome and study the comparative genomics of AREs in model organisms.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1234973128"><span>ATGC -- Alignable Tight Genomic Clusters Database</span></a></div><p>Find information about orthologous genes in prokaryotes.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1174596104"><span>AnimalQTLdb -- a livestock QTL database tool set for positional QTL information mining and beyond</span></a></div><p>Search for publicly available QTL data on livestocks and animal species.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL20110518150135"><span>BGDB -- Bovine Genome Database</span></a></div><p>Find information about bovine genomics data.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1229012662"><span>COMPARE -- a multi-organism system for cross-species data comparison and transfer of information</span></a></div><p>A multi-organism web-based resource system designed to easily retrieve, correlate and interpret data across species.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1218141952"><span>CONDOR -- COnserved Non-coDing Orthologous Regions</span></a></div><p>A database resource of developmentally associated conserved non-coding elements.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1099057221"><span>CORG -- A database for COmparative Regulatory Genomics</span></a></div><p>Delineate conserved non-coding blocks from upstream regions of putative orthologous gene pairs from man, mouse, rat, fugu, Mus musculus, Danio rerio, and zebrafish.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1203608896"><span>COXPRESdb -- a database of coexpressed gene networks in mammals</span></a></div><p>Find coexpressed gene lists and networks in human and mouse.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1097763045"><span>CVTree -- A Phylogenetic Tree Reconstruction Tool Based on Whole Genomes</span></a></div><p>Construct phylogenetic tree of microorganisms based on oligopeptide content of their complete proteomes.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1232729680"><span>CleanEST -- the cleansed EST libraries database</span></a></div><p>A novel database server that classifies GenBank's dbEST (database of expressed gene sequences) libraries and removes contaminants.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1256926144"><span>CoCoa -- COefficient of COAncestry software</span></a></div><p>Find information about the ancestral relationship between genes.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1227549154"><span>CoGemiR -- a comparative genomics microRNA database</span></a></div><p>Provides an overview of the genomic organization of microRNAs and extent of conservation during evolution in different metazoan species.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1117678221"><span>Comparative Genometrics (CG) -- a database dedicated to biometric comparisons of whole genomes</span></a></div><p>Conduct comparative biometric analysis of chromosomes of different organisms.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1151007916"><span>DoTS -- Database Of Transcribed Sequences</span></a></div><p>Search for Indices of gene and transcripts in human and mouse.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1174510065"><span>DroSpeGe -- rapid access database for new Drosophila species genomes</span></a></div><p>Search and compare 12 new and old Drosophila genomes.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1098208414"><span>ECR Browser -- A Tool for Visualizing and Accessing Data from Comparisons of Multiple Vertebrate Genomes</span></a></div><p>Access to whole genome alignments of human, mouse, rat and fish sequences.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1209738459"><span>EPGD -- Eukaryotic Paralog Group Database</span></a></div><p>Find eukaryotic paralog/paralogon information.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1232726869"><span>EVOG -- evolutionary visualizer for overlapping genes</span></a></div><p>Analyze the evolutionary process of overlapping genes when comparing different species.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1227633714"><span>GNAT -- Inter-species gene mention normalization (ISGN)</span></a></div><p>The first publicly available system reported to handle inter-species gene mention normalization.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1229438992"><span>GenColors -- annotation and comparative genomics of prokaryotes made easy</span></a></div><p>A web-based software/database system aimed at an improved and accelerated annotation of prokaryotic genomes.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1151086258"><span>GeneNest gene indices</span></a></div><p>Visualize gene indices of human, mouse, Arabidopsis, Zebrafish, Drosophila and Sheep.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1174489378"><span>GenomeTrafac -- a whole genome resource for the detection of transcription factor binding site clusters associated with conventional and microRNA encoding genes conserved between mouse and human gene orthologs</span></a></div><p>Use comparative genomics approach to characterize gene models and identify putative cis-regulatory regions of RefSeq Gene Orthologs.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL20110518150753"><span>IKMC -- International Knockout Mouse Consortium web portal</span></a></div><p>Find information about mutated mouse genes.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1209411604"><span>IMG/M -- Integrated Microbial Genomes/Metagenomes</span></a></div><p>A data management and analysis system for metagenomes</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1234976694"><span>ISED -- Influenza sequence and epitope database.</span></a></div><p>Search for influenza sequence, vaccine, and drug resistance information.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL20140710115515"><span>LAMDHI: The Search for Animal Models Starts Here</span></a></div><p>LAMHDI, the initiative to Link Animal Models to Human DIsease, is designed to accelerate the research process by providing biomedical researchers with a simple, comprehensive Web-based resource to find the best animal models for their research.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1228843803"><span>MANTIS -- a phylogenetic framework for multi-species genome comparisons</span></a></div><p>The missing link between multi-species full genome comparisons and functional analysis.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1099578148"><span>MBGD -- Microbial genome database for comparative analysis</span></a></div><p>Conduct comparative analysis of completely sequenced microbial genomes.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1221077729"><span>MEGA -- Molecular Evolutionary Genetics Analysis</span></a></div><p>A biologist-centric software for evolutionary analysis of DNA and protein sequences.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1174596756"><span>MamPol -- a database of nucleotide polymorphism in the Mammalia class</span></a></div><p>Conduct single nucleotide polymorphisms diversity measurements among homologous sequences from the Mammalia class.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1266437314"><span>MicrobesOnline -- Prokaryotic Genome Database</span></a></div><p>Find information about 1000s of microbial genomes.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1208461006"><span>Narcisse -- a mirror view of conserved syntenies</span></a></div><p>A database dedicated to the study of genome conservation.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1219772764"><span>OMA -- the Orthologous MAtrix project</span></a></div><p>Explore orthologous relations across 352 complete genomes.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1209738741"><span>OPTIC -- orthologous and paralogous transcripts in clades</span></a></div><p>Browse complete genomes in several clades.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1209573208"><span>OrthoDB -- the hierarchical catalog of eukaryotic orthologs</span></a></div><p>Find groups of orthologous genes.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1221231200"><span>OrthoMaM -- orthologous mammalian markers</span></a></div><p>A database of orthologous genomic markers for placental mammal phylogenetics.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1100009979"><span>PEDANT -- Protein Extraction, Description and ANalysis Tool</span></a></div><p>Conduct genome wide functional and structural analysis.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1174489475"><span>PReMod -- a database of genome-wide mammalian cis-regulatory module predictions</span></a></div><p>Conduct genome-wide cis-regulatory module (CRM) predictions for both the human and the mouse genomes.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1151083092"><span>PhenomicDB -- Comparison of phenotypes of orthologous genes in human and model organisms</span></a></div><p>Compare phenotypes of a given gene or gene set in different model organisms.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1190899370"><span>Phylemon -- A suite of web tools for molecular evolution, phylogenetics and phylogenomics</span></a></div><p>Phylemon is a web server that integrates a selected suite of more than 20 different tools from the most popular stand-alone programs of phylogenetic and evolutionary analysis.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1232555615"><span>PhyloPat -- the phylogenetic pattern database</span></a></div><p>Use this database to see where in the evolution some phylogenetic lineages were started, and over which species they were contained.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1174510223"><span>Pristionchus.org -- a genome-centric database of the nematode satellite species Pristionchus pacificus</span></a></div><p>Search for genomic information on nematode satellite species Pristionchus pacificus.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1236367352"><span>ProtClustDB -- NCBI Protein Clusters Database</span></a></div><p>Find information about related protein sequences.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1209410278"><span>ProtozoaDB -- database of protozoan genomes</span></a></div><p>Database hosting genomics and post-genomics data from multiple protozoans.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1232554690"><span>Pseudofam -- the pseudogene families database</span></a></div><p>A database of pseudogene families based on the protein families from the Pfam database.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL20110518151439"><span>RIDM - RIKEN Integrated Database of Mammals</span></a></div><p>Find genomic information about mammals.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1272562567"><span>RegPrecise -- Regulon Prediction Database</span></a></div><p>Find information about predicted regulons in prokaryotic transcription regulation.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1272477473"><span>SALAD -- Surveyed contained motif ALignment diagram and the Associating Dendrogram</span></a></div><p>Perform systematic comparison of proteome data among species.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1229010765"><span>SGN -- SOL Genomics Network</span></a></div><p>A comparative map viewer dedicated to the biology of the Solanaceae family.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1256669040"><span>ShotgunFunctionalizeR -- R-package for functional comparison of metagenomes</span></a></div><p>Analyze data from functional analysis on fragmented microbial genetic material.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1256238439"><span>SnoopCGH -- Comparative Genomic Hybridization software</span></a></div><p>Visualize and explore comparative genomic hybridization data sets.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1174489598"><span>SwissRegulon -- a database of genome-wide annotations of regulatory sites</span></a></div><p>Search for genome-wide annotations of regulatory sites in yeast and prokaryotes genomes.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1229013521"><span>TaxonGap -- a visualization tool for intra- and inter-species variation among individual biomarkers</span></a></div><p>Compare and select individual biomarkers.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1106063477"><span>The Adaptive Evolution Database (TAED) -- a phylogeny based tool for comparative genomics</span></a></div><p>Search for information on adaptive evolution in gene families of higher plants and chordate.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1216742716"><span>The CGView Server -- a comparative genomics tool for circular genomes</span></a></div><p>Generate graphical maps of circular genomes that show sequence features, base composition plots, analysis results and sequence similarity plots.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1099663588"><span>The ERGO -- Genome analysis and discovery system</span></a></div><p>Conduct a comprehensive analysis of genes and genomes.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1177611772"><span>The Macaque Genome: Interactive Poster and Teaching Resource</span></a></div><p>An interactive online poster presentation on the Macaque genome, including high-quality images, video clips, and Web resources</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1103816940"><span>The TIGR Gene Indices -- clustering and assembling EST and known genes and integration with eukaryotic genomes</span></a></div><p>Search for annotated genetic information of expressed sequence tags (ESTs) in different eukaryotic organisms.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1043767169"><span>UniGene</span></a></div><p>Find mapping and expression information for a unigene cluster (ESTs and full-length mRNA sequences organized into clusters that each represent a unique known or putative gene)</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1216738072"><span>Uprobe -- universal overgo hybridization-based probe retrieval and design</span></a></div><p>A public online resource for identifying or designing 'universal' overgo-hybridization probes from conserved sequences that can be used to efficiently screen one or more genomic libraries from a designated group of species.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1098205291"><span>VISTA -- Computational Tools for Comparative Genomics</span></a></div><p>Comprehensive suite of programs and databases for comparative analysis of genomic sequences.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL20110518144404"><span>cBARBEL -- Catfish Breeder and Researcher Bioinformatics Entry Location</span></a></div><p>Find information about ictalurid catfish.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1209738040"><span>eggNOG -- evolutionary genealogy of genes: Non-supervised Orthologous Groups</span></a></div><p>Discover orthologous groups of genes.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1234370319"><span>metaTIGER -- a metabolic gene evolution resource</span></a></div><p>Find metabolic networks and phylogenomic information on a taxonomically diverse range of eukaryotes.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1138901833"><span>xBASE -- a collection of online databases for bacterial comparative genomics</span></a></div><p>Conduct bacterial comparative genomics.</p></div>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/44401/bioinformatics-tools-for-phylogeny</guid>
	<pubDate>Mon, 06 Nov 2023 03:09:59 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44401/bioinformatics-tools-for-phylogeny</link>
	<title><![CDATA[Bioinformatics Tools for Phylogeny !]]></title>
	<description><![CDATA[<p><span>Direct access to the individual tools available on this server.</span></p><table summary="list of individual tools">
<thead>
<tr><th>Multiple Alignment:</th><th>Phylogeny:</th><th>Tree viewers:</th><th>Utilities:</th></tr>
</thead>
<tbody>
<tr>
<td><a href="http://phylogeny.lirmm.fr/phylo_cgi/one_task.cgi?task_type=muscle">MUSCLE</a></td>
<td><a href="http://phylogeny.lirmm.fr/phylo_cgi/one_task.cgi?task_type=phyml">PhyML</a></td>
<td><a href="http://phylogeny.lirmm.fr/phylo_cgi/one_task.cgi?task_type=treedyn">TreeDyn</a></td>
<td><a href="http://phylogeny.lirmm.fr/phylo_cgi/one_task.cgi?task_type=gblocks">Gblocks</a></td>
</tr>
<tr>
<td><a href="http://phylogeny.lirmm.fr/phylo_cgi/one_task.cgi?task_type=tcoffee">T-Coffee</a>&nbsp;/&nbsp;<a href="http://phylogeny.lirmm.fr/phylo_cgi/one_task.cgi?task_type=expresso">3DCoffee</a></td>
<td><a href="http://phylogeny.lirmm.fr/phylo_cgi/one_task.cgi?task_type=tnt">TNT</a></td>
<td><a href="http://phylogeny.lirmm.fr/phylo_cgi/one_task.cgi?task_type=drawgram">Drawgram</a></td>
<td><a href="http://phylogeny.lirmm.fr/phylo_cgi/one_task.cgi?task_type=jalview">Jalview</a></td>
</tr>
<tr>
<td><a href="http://phylogeny.lirmm.fr/phylo_cgi/one_task.cgi?task_type=clustalw">ClustalW</a></td>
<td><a href="http://phylogeny.lirmm.fr/phylo_cgi/one_task.cgi?task_type=bionj">BioNJ</a></td>
<td><a href="http://phylogeny.lirmm.fr/phylo_cgi/one_task.cgi?task_type=drawtree">Drawtree</a></td>
<td><a href="http://phylogeny.lirmm.fr/phylo_cgi/one_task.cgi?task_type=readseq">Readseq</a></td>
</tr>
<tr>
<td><a href="http://phylogeny.lirmm.fr/phylo_cgi/one_task.cgi?task_type=probcons">ProbCons</a></td>
<td><a href="http://phylogeny.lirmm.fr/phylo_cgi/one_task.cgi?task_type=mrbayes">MrBayes</a></td>
<td><a href="http://phylogeny.lirmm.fr/phylo_cgi/one_task.cgi?task_type=atv">ATV (A Tree Viewer)</a></td>
<td><a href="http://phylogeny.lirmm.fr/phylo_cgi/data_converter.cgi">Built-in converter</a></td>
</tr>
</tbody>
</table>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>

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