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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/30440/genome-assembly-tools-and-software-part2</guid>
	<pubDate>Tue, 27 Dec 2016 16:14:35 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/30440/genome-assembly-tools-and-software-part2</link>
	<title><![CDATA[Genome Assembly Tools and Software - PART2 !!]]></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://smithlabresearch.org/software/rmap/" title="RMAP 2.1 &ndash; Short-read Mapping">RMAP 2.1 &ndash; Short-read Mapping<br /></a><a href="http://smithlabresearch.org/software/rmap/" target="_blank">RMAP</a>&nbsp;is aimed to map accurately reads from the next-generation sequencing technology. RMAP can map reads with or without error probability information (quality scores) and supports paired-end reads or bisulfite-treated reads mapping. There is no limitaions on read widths or number of mismatches. RMAP can now map more than 8 million reads in an hour at full sensitivity to 2 mismatches<br /><br /></li>
<li><a href="https://sourceforge.net/p/mira-assembler/wiki/Home/" title="MIRA 4.0.2 &ndash; Whole Genome Shotgun and EST Sequence Assembler">MIRA 4.0.2 &ndash; Whole Genome Shotgun and EST Sequence Assembler<br /></a><a href="http://sourceforge.net/p/mira-assembler/wiki/Home/" target="_blank">MIRA</a>&nbsp;(Mimicking Intelligent Read Assembly)is a whole genome shotgun and EST sequence assembler for Sanger, 454, Solexa (Illumina), IonTorrent data and PacBio (the later at the moment only CCS and error-corrected CLR reads). It can be seen as a Swiss army knife of sequence assembly developed and used in the past 12 years to get assembly jobs done efficiently &ndash; and especially accurately. That is, without actually putting too much manual work into finishing the assembly.<br /><br /></li>
<li><a href="http://www.brown.edu/Research/Istrail_Lab/hapcompass.php" title="HapCompass 0.7.7 &ndash; A Cycle-Basis Algorithm for Accurate Haplotype Assembly">HapCompass 0.7.7 &ndash; A Cycle-Basis Algorithm for Accurate Haplotype Assembly<br /></a><a href="http://www.brown.edu/Research/Istrail_Lab/hapcompass.php" target="_blank">HapCompass</a>&nbsp;for polyploid genomes can currently be used to create accurate pairwise SNP phasings.Given a set of aligned sequence reads in a SAM file and a set of variant calls in VCF format, HAPCOMPASS will assemble reads into haplotypes.<br /><br /></li>
<li><a href="http://www.csc.kth.se/~vezzi/software/" title="GAM-NGS 1.1b &ndash; Genome Assemblies Merger for Next Generation Sequencing">GAM-NGS 1.1b &ndash; Genome Assemblies Merger for Next Generation Sequencing<br /></a><a href="http://www.csc.kth.se/~vezzi/software/" target="_blank">GAM-NGS</a>&nbsp;is able to merge two or more assemblies and it rteturns an improved assembly (more contiguous and more correct). GAM-NGS shows its full potential with multi-library Illumina-based projects.<br /><br /></li>
<li><a href="http://omics.informatics.indiana.edu/GeneStitch/" title="GeneStitch 1.2.1 &ndash; Network Matching Algorithm to Gene Assembly">GeneStitch 1.2.1 &ndash; Network Matching Algorithm to Gene Assembly<br /></a><a href="http://omics.informatics.indiana.edu/GeneStitch/" target="_blank">GeneStitch</a>&nbsp;is a tool to assemble genes using network matching algorithm. Given an already-assembled dataset, it is capable of assembling contigs together to form more complete genes with the help of a reference gene set. Currently the assembly software that GeneStitch support is SOAPdenovo.<br /><br /></li>
<li><a href="http://bioen-compbio.bioen.illinois.edu/RACA/" title="RACA 0.9.1.1 &ndash; Reference-Assisted Chromosome Assembly">RACA 0.9.1.1 &ndash; Reference-Assisted Chromosome Assembly<br /></a><a href="http://bioen-compbio.bioen.illinois.edu/RACA/" target="_blank">RACA</a>&nbsp;is an algorithm to reliably order and orient sequence scaffolds generated by NGS and assemblers into longer chromosomal fragments using comparative genome information and paired-end reads.<br /><br /></li>
<li><a href="https://software.broadinstitute.org/software/discovar/blog/" title="DISCOVAR 51750 &ndash; Genome Shotgun Assembler and Variant Caller">DISCOVAR 51750 &ndash; Genome Shotgun Assembler and Variant Caller<br /></a><a href="http://www.broadinstitute.org/software/discovar/blog/" target="_blank">DISCOVAR</a>&nbsp;is a whole genome shotgun assembler and variant caller that can generate high quality assemblies and variant calls from the latest 250 base Illumina PCR-free fragment reads.<br /><br /></li>
<li><a href="http://www.seqan.de/projects/seqcons/" title="SeqCons 1.0 &ndash; de novo and reference-guided Sequence Assembly">SeqCons 1.0 &ndash; de novo and reference-guided Sequence Assembly<br /></a><a href="http://www.seqan.de/projects/seqcons/" target="_blank">&nbsp;SeqCons</a>&nbsp;(Sequence consensus) is an open source consensus computation program for Linux and Windows. The algorithm can be used for de novo and reference-guided sequence assembly.<br /><br /></li>
<li><a href="http://www.personal.psu.edu/jhm10/Vera/SoftwareC.html" title="SimAssemblyStage1/2 0.2 &ndash; Assembly Alignment of Contigs">SimAssemblyStage1/2 0.2 &ndash; Assembly Alignment of Contigs<br /></a><a href="http://www.personal.psu.edu/jhm10/Vera/SoftwareC.html" target="_blank">SimAssemblyStage1</a>: Perfectly aligns TranscriptSimulator reads to their nucleotide templates using read title inforamation, creating ideal simulated assembly of super contigs.<br /><br /></li>
<li><a href="http://www.csc.kth.se/~vezzi/software/" title="GapFiller &ndash; Closing the Gap within Paired Reads">GapFiller &ndash; Closing the Gap within Paired Reads<br /></a><a href="http://www.csc.kth.se/~vezzi/software/" target="_blank">GapFiller</a>&nbsp;is not a standard de novo assembler. It aims &ldquo;only&rdquo; at closing the gap between pairs of reads as a first step of a large number of downstream analysis<br /><br /></li>
<li><a href="http://www.sanger.ac.uk/science/tools/pagit" title="PAGIT 1.01 &ndash; Post Assembly Genome Improvement Toolkit">PAGIT 1.01 &ndash; Post Assembly Genome Improvement Toolkit<br /></a><a href="http://www.sanger.ac.uk/resources/software/pagit/" target="_blank">PAGIT</a>&nbsp;(Post Assembly Genome Improvement Toolkit) is a tools to generate automatically high quality sequence by ordering contigs, closing gaps, correcting sequence errors and transferring annotation.<br /><br /></li>
<li><a href="https://www.bsse.ethz.ch/cbg/software.html" title="ShoRAH 0.8.2 &ndash; Short Reads Assembly into Haplotypes">ShoRAH 0.8.2 &ndash; Short Reads Assembly into Haplotypes<br /></a><a href="http://www.bsse.ethz.ch/cbg/software/shorah" target="_blank">ShoRAH</a>&nbsp;is a software package that allows for inference about the structure of a population from a set of short sequence reads as obtained from ultra-deep sequencing of a mixed sample. The package contains programs that support mapping of reads to a reference genome, correcting sequencing errors by locally clustering reads in small windows of the alignment, reconstructing a minimal set of global haplotypes that explain the reads, and estimating the frequencies of the inferred haplotypes.<br /><br /></li>
<li><a href="http://www.genomics.cn/en/navigation/show_navigation?nid=2732" title="RePS 2.0 &ndash; WGS Sequence Assembler">RePS 2.0 &ndash; WGS Sequence Assembler<br /></a><a href="http://www.genomics.cn/en/navigation/show_navigation?nid=2732" target="_blank">RePS</a>&nbsp;(Repeat-masked Phrap with scaffolding), a WGS sequence assembler, that explicitly identifies exact kmer repeats from the shotgun data and removes them prior to the assembly. The established software Phrap is used to compute meaningful error probabilities for each base. Clone-end-pairing information is used to construct scaffolds that order and orient the contigs. The updated version of RePS incorporates some of the ideas introduced by Phusion on clustering<br /><br /></li>
<li><a href="http://bibiserv2.cebitec.uni-bielefeld.de/sessionTimeout.jsf" title="treecat &ndash; Phylogenetic Comparative Assembly">treecat &ndash; Phylogenetic Comparative Assembly<br /></a><a href="http://bibiserv2.cebitec.uni-bielefeld.de/cgcat?id=cgcat_treecat" target="_blank">treecat</a>&nbsp;(phylogenetic tree based contig arrangement tool) takes several genomes and their relationships in a phylogenetic tree into account to estimate a possible ordering of the contigs.<br /><br /></li>
<li><a href="http://alumni.cs.ucr.edu/~liw/isolasso.html" title="IsoLasso 2.6.1 &ndash; A LASSO Regression Approach to RNA-Seq Based Transcriptome Assembly">IsoLasso 2.6.1 &ndash; A LASSO Regression Approach to RNA-Seq Based Transcriptome Assembly<br /></a><a href="http://alumni.cs.ucr.edu/~liw/isolasso.html" target="_blank">IsoLasso</a>&nbsp;is an algorithm to assemble transcripts and estimate their expression levels from RNA-Seq reads.<br /><br /></li>
<li><a href="http://alumni.cs.ucr.edu/~liw/cem.html" title="CEM 0.9.1 &ndash; Transcriptome Assembly and Isoform Expression Level Estimation from Biased RNA-Seq Reads">CEM 0.9.1 &ndash; Transcriptome Assembly and Isoform Expression Level Estimation from Biased RNA-Seq Reads<br /></a><a href="http://alumni.cs.ucr.edu/~liw/cem.html" target="_blank">CEM</a>&nbsp;is an algorithm to assemble transcripts and estimate their expression levels from RNA-Seq reads.<br /><br /></li>
<li><a href="http://alan.cs.gsu.edu/NGS/?q=malta" title="MaLTA &ndash; Transcriptome Assembly and Quantification from Ion Torrent RNA-Seq data">MaLTA &ndash; Transcriptome Assembly and Quantification from Ion Torrent RNA-Seq data<br /></a><a href="http://alan.cs.gsu.edu/NGS/?q=malta" target="_blank">MaLTA</a>&nbsp;is a method for simultaneous transcriptome assembly and quantification from Ion Torrent RNA-Seq data.<br /><br /></li>
<li><a href="http://amos.sourceforge.net/wiki/index.php/AMOS" title="AMOS 3.1.0 &ndash; Whole Genome Shotgun Assembler">AMOS 3.1.0 &ndash; Whole Genome Shotgun Assembler<br /></a><a href="http://amos.sourceforge.net/wiki/index.php/AMOS" target="_blank">AMOS</a>&nbsp;(<strong>A</strong><strong>M</strong>odular,&nbsp;<strong>O</strong>pen-<strong>S</strong>ource)&nbsp;consortium is committed to the development of open-source whole genome assembly software. The project acronym (AMOS) represents our primary goal &mdash; to produce A Modular, Open-Source whole genome assembler.Open-source so that everyone is welcome to contribute and help build outstanding assembly tools, and modular in nature so that new contributions can be easily inserted into an existing assembly pipeline. This modular design will foster the development of new assembly algorithms and allow the AMOS project to continually grow and improve in hopes of eventually becoming a widely accepted and deployed assembly infrastructure. In this sense, AMOS is both a design philosophy and a software system.<br /><br /></li>
<li><a href="http://amos.sourceforge.net/wiki/index.php/AutoEditor" title="AutoEditor 1.20 &ndash; Automated Correction of Genome Sequence Errors">AutoEditor 1.20 &ndash; Automated Correction of Genome Sequence Errors<br /></a><a href="http://amos.sourceforge.net/wiki/index.php/AutoEditor" target="_blank">AutoEditor</a>&nbsp;is a tool for correcting sequencing and basecaller errors using sequence assembly and chromatogram data. On average AutoEditor corrects 80% of erroneous base calls, with an accuracy of 99.99%.This in turn improves the overall accuracy of genome sequences and facilitates the use of these sequences for polymorphism discovery.<br /><br /></li>
<li><a href="http://www.csd.uwo.ca/~ilie/SAGE/" title="SAGE &ndash; String Graph Assembly of GEnomes">SAGE &ndash; String Graph Assembly of GEnomes<br /></a><a href="http://www.csd.uwo.ca/~ilie/SAGE/" target="_blank">SAGE</a>&nbsp;is a new string-overlap graph-based de novo genome assembler.<br /><br /></li>
<li><a href="http://omega.omicsbio.org/" title="Omega 1.0.2 &ndash; Overlap-graph de novo Assembler for Metagenomics">Omega 1.0.2 &ndash; Overlap-graph de novo Assembler for Metagenomics<br /></a><a href="http://omega.omicsbio.org/" target="_blank">Omega</a>&nbsp;is a software for assembling and scaffolding Illumina sequencing data of microbial communities.<br /><br /></li>
<li><a href="http://www.compgenome.org/TCGA-Assembler/" title="TCGA-Assembler 1.0.3 &ndash; Open-Source Software for Retrieving and Processing TCGA Data">TCGA-Assembler 1.0.3 &ndash; Open-Source Software for Retrieving and Processing TCGA Data<br /></a><a href="http://www.compgenome.org/TCGA-Assembler/" target="_blank">TCGA-Assembler</a>&nbsp;is an open-source, freely available tool that automatically downloads, assembles, and processes public The Cancer Genome Atlas (TCGA) data, to facilitate downstream data analysis by relieving investigators from the burdens of data preparation.<br /><br /></li>
<li><a href="http://sammate.sourceforge.net/" title="SAMMate 2.7.4 / assemblySAM 1.1 &ndash;  Processing Short Read Alignments in SAM/BAM format / RNA-Seq Assembly and Analysis">SAMMate 2.7.4 / assemblySAM 1.1 &ndash; Processing Short Read Alignments in SAM/BAM format / RNA-Seq Assembly and Analysis<br /></a>
<p><a href="http://sammate.sourceforge.net/" target="_blank">SAMMate</a>&nbsp;is an open source GUI software suite to process RNA-Seq data. It is composed of two modules: assemblySAM and SAMMate.</p>
<p>assemblySAM employs a novel method to localize and assemble RNA-seq reads into RNA transcript sequences.<br /><br /></p>
</li>
<li><a href="http://www.cs.tau.ac.il/~bchor/StringGraph/" title="StringGraph beta &ndash; String Graph Construction Using Incremental Hashing">StringGraph beta &ndash; String Graph Construction Using Incremental Hashing<br /></a><a href="http://www.cs.tau.ac.il/~bchor/StringGraph/" target="_blank">StringGraph</a>&nbsp;is a novel, hash based method for constructing the string graph.<br /><br /></li>
<li><a href="http://mindthegap.genouest.org/" title="MindTheGap 1.0.0 &ndash; Detection and Assembly of Insertion Variants">MindTheGap 1.0.0 &ndash; Detection and Assembly of Insertion Variants<br /></a><a href="http://mindthegap.genouest.org/" target="_blank">MindTheGap</a>&nbsp;is a software that performs detection and assembly of DNA insertion variants in NGS read datasets with respect to a reference genome.<br /><br /></li>
<li><a href="http://cbcb.umd.edu/software/metAMOS" title="MetAMOS 1.5rc3 &ndash; Metagenomic Assembly pipeline for AMOS">MetAMOS 1.5rc3 &ndash; Metagenomic Assembly pipeline for AMOS<br /></a><a href="http://cbcb.umd.edu/software/metAMOS" target="_blank">MetAMOS</a>&nbsp;is an open source and modular metagenomic assembly and analysis pipeline. MetAMOS represents an important step towards fully automated metagenomic analysis, starting with next-generation sequencing reads and producing genomic scaffolds, open-reading frames and taxonomic or functional annotations.<br /><br /></li>
<li><a href="http://impact.crhc.illinois.edu/projects.aspx#tiger" title="TIGER &ndash; DNA Sequence Assembly">TIGER &ndash; DNA Sequence Assembly<br /></a><a href="http://impact.crhc.illinois.edu/projects.aspx#tiger" target="_blank">Tiger</a>&nbsp;is a novel de novo assembly framework &nbsp;which adapts to available computing resources by iteratively decomposing the assembly problem into sub-problems.<br /><br /></li>
<li><a href="https://github.com/baoe/AlignGraph" title="AlignGraph &ndash; Secondary de novo Genome Assembly guided by closely related References">AlignGraph &ndash; Secondary de novo Genome Assembly guided by closely related References<br /></a><a href="https://github.com/baoe/AlignGraph" target="_blank">AlignGraph</a>&nbsp;is a software that extends and joins contigs or scaffolds by reassembling them with help provided by a reference genome of a closely related organism.<br /><br /></li>
<li><a href="http://compbio.cs.toronto.edu/hapsembler/scarpa.html" title="scarpa 0.241 &ndash; Scaffolding Reads with Practical Algorithms">scarpa 0.241 &ndash; Scaffolding Reads with Practical Algorithms<br /></a><a href="http://compbio.cs.toronto.edu/hapsembler/scarpa.html" target="_blank">Scarpa</a>&nbsp;is a stand-alone scaffolding tool for NGS data. It can be used together with virtually any genome assembler and any NGS read mapper that supports SAM format. Other features include support for multiple libraries and an option to estimate insert size distributions from data.<br /><br /></li>
<li><a href="http://genetics.cs.ucla.edu/vga/" title="VGA v1 &ndash; Viral Genome Assembler">VGA v1 &ndash; Viral Genome Assembler<br /></a><a href="http://genetics.cs.ucla.edu/vga/" target="_blank">VGA</a>&nbsp;is a method for accurate assembly of a heterogeneous viral population consisting of individuals viral genomes (also known as quasi-species).<br /><br /></li>
<li><a href="https://cbcl.ics.uci.edu//doku.php/software#genomix" title="Genomix 0.2.11 &ndash; Parallel Genome Assembly using Hyracks">Genomix 0.2.11 &ndash; Parallel Genome Assembly using Hyracks<br /></a><a href="https://cbcl.ics.uci.edu//doku.php/software#genomix" target="_blank">Genomix</a>&nbsp;is a parallel genome assembly system built from the ground up with scalability in mind. It can assemble large and high-coverage genomes from fastq files in a short time and produces assemblies similar to Velvet or Ray in quality.<br /><br /></li>
<li><a href="http://shendurelab.github.io/LACHESIS/" title="LACHESIS &ndash; Genome Assembly with Contact Probability Maps">LACHESIS &ndash; Genome Assembly with Contact Probability Maps<br /></a><a href="http://shendurelab.github.io/LACHESIS/" target="_blank">LACHESIS</a>&nbsp;is method that exploits contact probability map data (e.g. from Hi-C) for chromosome-scale de novo genome assembly.<br /><br /></li>
<li><a href="http://www.cmbb.arizona.edu/?page_id=312" title="KGBassembler 1.2 &ndash; Karyotype-based Genome Assembler for Brassicaceae Species">KGBassembler 1.2 &ndash; Karyotype-based Genome Assembler for Brassicaceae Species<br /></a><a href="http://www.cmbb.arizona.edu/?page_id=312" target="_blank">KGBassembler</a>&nbsp;(Brassicaceae genome assembler) is a C++ based tool for assembling contigs and/or scaffolds to full chromosomes based on the karyotype maps of Brassicaceae species and without the need of genetic and physical maps.<br /><br /></li>
<li><a href="https://sourceforge.net/projects/autoassemblyd/" title="AutoAssemblyD 0.1 &ndash; Graphical User Interface system for several Genome Assembler">AutoAssemblyD 0.1 &ndash; Graphical User Interface system for several Genome Assembler<br />The&nbsp;</a><a href="http://sourceforge.net/projects/autoassemblyd/" target="_blank">AssemblyD</a>&nbsp;is a software which performed the local and remote genome assembly by several assemblers based on an XML Template which can replace the large command lines required by most assemblers.<a href="http://www.mybiosoftware.com/autoassemblyd-0-1-graphical-user-interface-system-for-several-genome-assembler.html" title="AutoAssemblyD 0.1 &ndash; Graphical User Interface system for several Genome Assembler"><br /><br /></a></li>
<li><a href="http://bio.cs.put.poznan.pl/programs/519227629dfb89a7fa000001" title="SR-ASM &ndash; DNA Assembly of the Short Sequences coming from 454 sequencer">SR-ASM &ndash; DNA Assembly of the Short Sequences coming from 454 sequencer<br /></a><a href="http://bio.cs.put.poznan.pl/programs/519227629dfb89a7fa000001" target="_blank">SR-ASM</a>&nbsp;(Short Reads ASseMbly) algorithm is designed for DNA assembly of the short sequences coming from 454 sequencers.<a href="http://www.mybiosoftware.com/sr-asm-dna-assembly-short-sequences-coming-454-sequencer.html" title="SR-ASM &ndash; DNA Assembly of the Short Sequences coming from 454 sequencer"><br /><br /></a></li>
<li><a href="http://www.bx.psu.edu/miller_lab/" title="YASRA 2.33 &ndash; Yet Another Short Read Assembler">YASRA 2.33 &ndash; Yet Another Short Read Assembler<br /></a><a href="http://www.bx.psu.edu/miller_lab/" target="_blank">YASRA</a>&nbsp;performs comparative assembly of short reads using a reference genome, which can differ substantially from the genome being sequenced.<a href="http://www.mybiosoftware.com/yasra-2-32-short-read-assembler.html" title="YASRA 2.33 &ndash; Yet Another Short Read Assembler"><br /><br /></a></li>
<li><a href="http://derisilab.ucsf.edu/software/price/index.html" title="PRICE 1.2 &ndash; de novo Genome Assembler">PRICE 1.2 &ndash; de novo Genome Assembler<br /></a><a href="http://derisilab.ucsf.edu/software/price/index.html" target="_blank">PRICE</a>&nbsp;(Paired-Read Iterative Contig Extension) is a de novo genome assembler implemented in C++. Its name describes the strategy that it implements for genome assembly: PRICE uses paired-read information to iteratively increase the size of existing contigs. Initially, those contigs can be individual reads from a subset of the paired-read dataset, non-paired reads from sequencing technologies that provide non-paired data, or contigs that were output from a prior run of PRICE or any other&nbsp;<a href="http://www.mybiosoftware.com/price-0-18-de-novo-genome-assembler.html" title="PRICE 1.2 &ndash; de novo Genome Assembler"><br /><br /></a></li>
<li><a href="https://sc932.github.com/ALE/" title="ALE 20130717 &ndash; Assembly Likelihood Estimator">ALE 20130717 &ndash; Assembly Likelihood Estimator<br /></a><a href="http://sc932.github.com/ALE/" target="_blank">ALE</a>&nbsp;is a probabalistic framework for determining the likelihood of an assembly given the data (raw reads) used to assemble it. It allows for the rapid discovery of errors and comparisons between similar assemblies.<a href="http://www.mybiosoftware.com/ale-assembly-likelihood-estimator.html" title="ALE 20130717 &ndash; Assembly Likelihood Estimator"><br /><br /></a></li>
<li><a href="https://www.baseclear.com/genomics/bioinformatics/basetools/SSPACE" title="SSPACE 3.0 &ndash; Scaffolding pre-assembled Contigs using Paired-read data">SSPACE 3.0 &ndash; Scaffolding pre-assembled Contigs using Paired-read data<br /></a><a href="http://www.baseclear.com/lab-products/bioinformatics-tools/sspace-standard/" target="_blank">SSPACE</a>&nbsp;(SSAKE-based Scaffolding of Pre-Assembled Contigs after Extension) is a stand-alone program for scaffolding pre-assembled contigs using paired-read data. It is unique in offering the possibility to manually control the scaffolding process. By using the distance information of paired-end and/or matepair data, SSPACE is able to assess the order, distance and orientation of your contigs and combine them into scaffolds. Currently we offer this as a command-line tool in Perl. The input data is given by pre-assembled contig sequences (FASTA) and NGS paired-read data (FASTA or FASTQ). The final scaffolds are provided in FASTA format.<a href="http://www.mybiosoftware.com/sspace-1-2-scaffolding-pre-assembled-contigs-paired-read-data.html" title="SSPACE 3.0 &ndash; Scaffolding pre-assembled Contigs using Paired-read data"><br /><br /></a></li>
<li><a href="http://www.sanger.ac.uk/science/tools/image" title="IMAGE 2.4.1 &ndash; Iterative Mapping and Assembly for Gap Elimination">IMAGE 2.4.1 &ndash; Iterative Mapping and Assembly for Gap Elimination<br /></a><a href="http://www.sanger.ac.uk/resources/software/pagit/#IMAGE" target="_blank">IMAGE</a>&nbsp;( Iterative Mapping and Assembly for Gap Elimination) is a software designed to close gaps in any draft assembly using Illumina paired end reads. IMAGE is best described in several stages: aligning of Illumina reads at contig ends; local assembly of reads into new contigs; reference contigs are extended or merged; iterating the whole process to extend and merge more contigs.<a href="http://www.mybiosoftware.com/image-2-3-iterative-mapping-assembly-gap-elimination.html" title="IMAGE 2.4.1 &ndash; Iterative Mapping and Assembly for Gap Elimination"><br /><br /></a></li>
<li><a href="https://www.hgsc.bcm.edu/software/atlas-gapfill" title="ATLAS GapFill 2.2 &ndash; Deals with the Repetitive Gap Assembly problem">ATLAS GapFill 2.2 &ndash; Deals with the Repetitive Gap Assembly problem<br /></a><a href="https://www.hgsc.bcm.edu/software/atlas-gapfill" target="_blank">ATLAS GapFill</a>&nbsp;deals with the repetitive gap assembly problem by using the unique gap-flanking sequences to group reads and convert the problem to a local assembly task. Localizing the assembly reduces the numbers of repeats in the assembly, allows more data to be incorporated, and allows for gaps to be filled.<a href="http://www.mybiosoftware.com/atlas-gapfill-2-2-deals-repetitive-gap-assembly-problem.html" title="ATLAS GapFill 2.2 &ndash; Deals with the Repetitive Gap Assembly problem"><br /><br /></a></li>
<li><a href="https://www.hgsc.bcm.edu/software/atlas-whole-genome-assembly-suite" title="Atlas 2005 &ndash; Whole Genome Assembly Suite">Atlas 2005 &ndash; Whole Genome Assembly Suite<br /></a><a href="https://www.hgsc.bcm.edu/software/atlas-whole-genome-assembly-suite" target="_blank">Atlas</a>&nbsp;is a collection of software tools to facilitate the assembly of large genomes from whole genome shotgun reads, or a combination of whole genome shotgun reads and BAC or other localized reads.<a href="http://www.mybiosoftware.com/atlas-2005-genome-assembly-suite.html" title="Atlas 2005 &ndash; Whole Genome Assembly Suite"><br /><br /></a></li>
<li><a href="http://bio.math.berkeley.edu/cgal/" title="CGAL 0.9.6b &ndash; Computing Genome Assembly Likelihoods">CGAL 0.9.6b &ndash; Computing Genome Assembly Likelihoods<br /></a><a href="http://bio.math.berkeley.edu/cgal/" target="_blank">CGAL</a>&nbsp;is a tool for computing genome assembly likelihoods. It computes the likelihood of reads with respect to the assembly and a statistical model which can be used as a metric for evaluating assemblies.<a href="http://www.mybiosoftware.com/cgal-0-9-6-computing-genome-assembly-likelihoods.html" title="CGAL 0.9.6b &ndash; Computing Genome Assembly Likelihoods"><br /><br /></a></li>
<li><a href="https://github.com/lh3/fermi" title="Fermi 1.1 &ndash; WGS de novo Assembler based on the FMD-index for large Genomes">Fermi 1.1 &ndash; WGS de novo Assembler based on the FMD-index for large Genomes<br /></a><a href="https://github.com/lh3/fermi" target="_blank">Fermi</a>&nbsp;is a de novo assembler for Illumina reads from whole-genome short-gun sequencing. It also provides tools for error correction, sequence-to-read alignment and comparison between read sets. It uses the FMD-index, a novel compressed data structure, as the key data&nbsp;<a href="http://www.mybiosoftware.com/fermi-1-1-wgs-de-novo-assembler-based-on-the-fmd-index-for-large-genomes.html" title="Fermi 1.1 &ndash; WGS de novo Assembler based on the FMD-index for large Genomes"><br /><br /></a></li>
<li><a href="http://pasha.sourceforge.net/homepage.htm#latest" title="PASHA 1.0.10 &ndash; Parallelized Short Read Assembly">PASHA 1.0.10 &ndash; Parallelized Short Read Assembly<br /></a><a href="http://pasha.sourceforge.net/" target="_blank">PASHA</a>&nbsp;is a parallel short read assembler for large genomes using de Bruijn graphs. Taking advantage of both shared-memory multi-core CPUs and distributed-memory compute clusters, PASHA has demonstrated its potential to perform high-quality de-novo assembly of large genomes in reasonable time with modest computing resources. Our evaluation using three small real paired-end datasets shows that PASHA is able to produce better assemblies with comparable genome coverage and mis-assembly rates compared to three leading assemblers: Velvet, ABySS and SOAPdenovo. Moreover, PASHA achieves the fastest speed for all three datasets on a single CPU.<a href="http://www.mybiosoftware.com/pasha-1-0-5-parallelized-short-read-assembly.html" title="PASHA 1.0.10 &ndash; Parallelized Short Read Assembly"><br /><br /></a></li>
<li><a href="http://xgenovo.dna.bio.keio.ac.jp/" title="XGenovo &ndash; Extended Genovo Metagenomic Assembler by Incorporating Paired-End Information">XGenovo &ndash; Extended Genovo Metagenomic Assembler by Incorporating Paired-End Information<br /></a><a href="http://xgenovo.dna.bio.keio.ac.jp/" target="_blank">XGenovo</a>&nbsp;(Extended Genovo) is an extended genovo metagenomic assembler by incorporating paired-end information<a href="http://www.mybiosoftware.com/xgenovo-extended-genovo-metagenomic-assembler-by-incorporating-paired-end-information.html" title="XGenovo &ndash; Extended Genovo Metagenomic Assembler by Incorporating Paired-End Information"><br /><br /></a></li>
<li><a href="http://metavelvet.dna.bio.keio.ac.jp/" title="MetaVelvet 1.2.01 / MetaVelvet-SL &ndash; An Extension of Velvet Assembler to de novo Metagenomic Assembly / utilizing Supervised Learning">MetaVelvet 1.2.01 / MetaVelvet-SL &ndash; An Extension of Velvet Assembler to de novo Metagenomic Assembly / utilizing Supervised Learning<br /></a><a href="http://metavelvet.dna.bio.keio.ac.jp/" target="_blank">MetaVelvet</a>&nbsp;is an extension of Velvet assembler to de novo metagenome assembly from short sequence reads<a href="http://www.mybiosoftware.com/metavelvet-1-2-01-metavelvet-sl-an-extension-of-velvet-assembler-to-de-novo-metagenomic-assembly-utilizing-supervised-learning.html" title="MetaVelvet 1.2.01 / MetaVelvet-SL &ndash; An Extension of Velvet Assembler to de novo Metagenomic Assembly / utilizing Supervised Learning"><br /><br /></a></li>
<li><a href="http://www.genomic.ch/edena.php" title="Edena v3.131028 &ndash; De Novo Short Reads Assembler">Edena v3.131028 &ndash; De Novo Short Reads Assembler<br /></a><a href="http://www.genomic.ch/edena.php" target="_blank">Edena</a>&nbsp;is an assembler dedicated to process the millions of very short reads produced by the Illumina Genome Analyzer<a href="http://www.mybiosoftware.com/edena-v3-dev110920-de-novo-short-reads-assembler.html" title="Edena v3.131028 &ndash; De Novo Short Reads Assembler"><br /><br /></a></li>
<li><a href="https://github.com/gramarga/ConPADE" title="ConPADE 1.00 &ndash; Contig Ploidy and Allele Dosage Estimation">ConPADE 1.00 &ndash; Contig Ploidy and Allele Dosage Estimation<br /></a><a href="http://research.microsoft.com/en-us/downloads/62815951-4b89-47a5-9e3d-7054182dafbb/default.aspx" target="_blank">ConPADE</a>&nbsp;is a tool used to estimate contig ploidy and allele dosage in polyploid genome assemblies.<a href="http://www.mybiosoftware.com/conpade-1-00-contig-ploidy-and-allele-dosage-estimation.html" title="ConPADE 1.00 &ndash; Contig Ploidy and Allele Dosage Estimation"><br /><br /></a></li>
<li><a href="https://sourceforge.net/projects/eloper/" title="ELOPER 1.2 &ndash; Elongation of Paired-end Reads for de novo Assembly">ELOPER 1.2 &ndash; Elongation of Paired-end Reads for de novo Assembly<br /></a><a href="http://sourceforge.net/projects/eloper/" target="_blank">ELOPER</a>&nbsp;is a pre-processing tool for pair-end sequences that produces a better read library for assembly programs.<a href="http://www.mybiosoftware.com/eloper-1-2-elongation-of-paired-end-reads-for-de-novo-assembly.html" title="ELOPER 1.2 &ndash; Elongation of Paired-end Reads for de novo Assembly"><br /><br /></a></li>
<li><a href="http://www.ebi.ac.uk/~zerbino/oases/" title="Oases 0.2.08 &ndash; De novo Transcriptome Assembler for very short reads">Oases 0.2.08 &ndash; De novo Transcriptome Assembler for very short reads<br /></a><a href="http://www.ebi.ac.uk/~zerbino/oases/" target="_blank">Oases</a>&nbsp;designed to heuristically assemble RNA-seq reads in the absence of a reference genome, across a broad spectrum of expression values and in presence of alternative isoforms. It achieves this by using an array of hash lengths, a dynamic filtering of noise, a robust resolution of alternative splicing events, and the efficient merging of multiple assemblies. It was tested on human and mouse RNA-seq data and is shown to improve significantly on the transABySS and Trinity de novo&nbsp;<a href="http://www.mybiosoftware.com/oases-0-2-06-de-novo-transcriptome-assembler-short-reads.html" title="Oases 0.2.08 &ndash; De novo Transcriptome Assembler for very short reads"><br /><br /></a></li>
<li><a href="http://www.physics.rutgers.edu/~anirvans/SOPRA/" title="SOPRA 1.4.6 &ndash; Statistical Optimization of Paired Read Assembly">SOPRA 1.4.6 &ndash; Statistical Optimization of Paired Read Assembly<br /></a><a href="http://www.physics.rutgers.edu/~anirvans/SOPRA/" target="_blank">SOPRA</a>&nbsp;is an assembler for mate pair/paired-end reads from high throughput sequencing platforms, e.g. Illumina and SOLiD.<a href="http://www.mybiosoftware.com/sopra-1-4-6-statistical-optimization-paired-read-assembly.html" title="SOPRA 1.4.6 &ndash; Statistical Optimization of Paired Read Assembly"><br /><br /></a></li>
<li><a href="http://rnc.r.dendai.ac.jp/hapAssembly.html" title="hapAssembly &ndash; Haplotype Assembly from Whole-Genome Sequence Data">hapAssembly &ndash; Haplotype Assembly from Whole-Genome Sequence Data<br /></a><a href="http://rnc.r.dendai.ac.jp/hapAssembly.html" target="_blank">hapAssembly</a>&nbsp;&nbsp;beats the previous best for the important Haplotype Assembly Problem. It is&nbsp;an approach to finding optimal solutions for the haplotype assembly problem under the minimum-error-correction (MEC) model.<a href="http://www.mybiosoftware.com/hapassembly-haplotype-assembly-whole-genome-sequence-data.html" title="hapAssembly &ndash; Haplotype Assembly from Whole-Genome Sequence Data"><br /><br /></a></li>
<li><a href="https://code.google.com/archive/p/pbsim/" title="PBSIM 1.0.3 &ndash; PacBio Reads Simulator">PBSIM 1.0.3 &ndash; PacBio Reads Simulator<br /></a>PacBio sequencers produced two types of characteristic reads: CCS (short and low error rate) and CLR (long and high error rate), both of which could be useful for de novo assembly of genomes.&nbsp;<a href="https://code.google.com/p/pbsim/" target="_blank">PBSIM</a>&nbsp;simulates those PacBio reads by using either a model-based or sampling-based simulation.<a href="http://www.mybiosoftware.com/pbsim-1-0-3-pacbio-reads-simulator.html" title="PBSIM 1.0.3 &ndash; PacBio Reads Simulator"><br /><br /></a></li>
<li><a href="http://marte.ic.unicamp.br:8747/" title="SIS &ndash; Generate Draft Genome Sequence Scaffolds for Prokaryotes">SIS &ndash; Generate Draft Genome Sequence Scaffolds for Prokaryotes<br /></a><a href="http://marte.ic.unicamp.br:8747/" target="_blank">SIS</a>&nbsp;(Scaffolds from Inversion Signatures)is a new easy-to-use tool to generate contig scaffolds<a href="http://www.mybiosoftware.com/sis-generate-draft-genome-sequence-scaffolds-prokaryotes.html" title="SIS &ndash; Generate Draft Genome Sequence Scaffolds for Prokaryotes"><br /><br /></a></li>
<li><a href="https://www.cs.helsinki.fi/group/scaffold/normalizedN50/" title="NN50-calculator 0.5 &ndash; Evaluate the Correctness of Genome Assemblies">NN50-calculator 0.5 &ndash; Evaluate the Correctness of Genome Assemblies<br /></a><a href="http://www.cs.helsinki.fi/group/scaffold/normalizedN50/" target="_blank">NN50-calculator</a>&nbsp;(Normalized N50 calculator) is a tool for evaluating the correctness of genome assemblies.<a href="http://www.mybiosoftware.com/nn50-calculator-0-5-evaluate-correctness-genome-assemblies.html" title="NN50-calculator 0.5 &ndash; Evaluate the Correctness of Genome Assemblies"><br /><br /></a></li>
<li><a href="http://josephryan.github.io/baa.pl/" title="Baa.pl 0.20 &ndash; use BLAT to ASSESS an ASSEMBLY">Baa.pl 0.20 &ndash; use BLAT to ASSESS an ASSEMBLY<br /></a><a href="http://josephryan.github.io/baa.pl/" target="_blank">Baa.pl</a>&nbsp;is a simple script that parses the output of a BLAT run of a transcriptome vs. a genome assembly.<a href="http://www.mybiosoftware.com/baa-pl-0-10-blat-assess-assembly.html" title="Baa.pl 0.20 &ndash; use BLAT to ASSESS an ASSEMBLY"><br /><br /></a></li>
<li><a href="http://compbio.cs.toronto.edu/hapsembler/index.html" title="hapsembler 2.21 &ndash; Haplotype-specific Genome Assembly Toolkit">hapsembler 2.21 &ndash; Haplotype-specific Genome Assembly Toolkit<br /></a><a href="http://compbio.cs.toronto.edu/hapsembler/index.html" target="_blank">Hapsembler</a>&nbsp;is a haplotype-specific genome assembly toolkit that is designed for genomes that are rich in SNPs and other types of polymorphism. Hapsembler can be used to assemble reads from a variety of platforms including Illumina and Roche/454.<a href="http://www.mybiosoftware.com/hapsembler-2-1-haplotype-specific-genome-assembly-toolkit.html" title="hapsembler 2.21 &ndash; Haplotype-specific Genome Assembly Toolkit"><br /><br /></a></li>
<li><a href="http://alan.cs.gsu.edu/NGS/?q=content/vispa" title="ViSpA 02 &ndash; Viral Spectrum Assembler">ViSpA 02 &ndash; Viral Spectrum Assembler<br /></a><a href="http://alan.cs.gsu.edu/NGS/?q=content/vispa" target="_blank">ViSpA</a>&nbsp;(Viral Spectrum Assembling) implements a novel viral assembling and frequency estimation methods. This software uses a simple error correction, viral variants assembling based on maximum-bandwidth paths in weighted read graphs and frequency estimation via Expectation Maximization on all reads.<a href="http://www.mybiosoftware.com/vispa-01-viral-spectrum-assembler.html" title="ViSpA 02 &ndash; Viral Spectrum Assembler"><br /><br /></a></li>
<li><a href="http://www.vicbioinformatics.com/software.velvetoptimiser.shtml" title="VelvetOptimiser 2.2.5 &ndash; Automatically Optimise Velvet Assembler Parameters">VelvetOptimiser 2.2.5 &ndash; Automatically Optimise Velvet Assembler Parameters<br /></a><a href="http://www.vicbioinformatics.com/software.velvetoptimiser.shtml" target="_blank">VelvetOptimiser</a>&nbsp;is a multi-threaded Perl script for automatically optimising the three primary parameter options (K, -exp_cov, -cov_cutoff) for the Velvet de novo sequence assembler.<a href="http://www.mybiosoftware.com/velvetoptimiser-2-2-5-automatically-optimise-velvet-assembler-parameters.html" title="VelvetOptimiser 2.2.5 &ndash; Automatically Optimise Velvet Assembler Parameters"><br /><br /></a></li>
<li><a href="http://www.vicbioinformatics.com/software.assemblet.shtml" title="Assemblet 0.1 &ndash; Antigenic Variation Assembler">Assemblet 0.1 &ndash; Antigenic Variation Assembler<br /></a><a href="http://www.vicbioinformatics.com/software.assemblet.shtml" target="_blank">Assemblet</a>&nbsp;is a short read assembler for assembling antigenic variant sequences in bacteria.<a href="http://www.mybiosoftware.com/assemblet-0-1-antigenic-variation-assembler.html" title="Assemblet 0.1 &ndash; Antigenic Variation Assembler"><br /><br /></a></li>
<li><a href="http://www.vicbioinformatics.com/software.velvetk.shtml" title="VelvetK 20120606 &ndash; Find a reasonable K-mer size to Assemble Genome Reads with Velvet">VelvetK 20120606 &ndash; Find a reasonable K-mer size to Assemble Genome Reads with Velvet<br /></a><a href="http://www.vicbioinformatics.com/software.velvetk.shtml" target="_blank">VelvetK</a>&nbsp;can estimate the best k-mer size to use for your Velvet de novo assembly. It needs two inputs: the estimated genome size, and all your sequence read files. The genome size can be supplied as as a number (eg. 3.5M) or as a FASTA file of a closely related genome.<a href="http://www.mybiosoftware.com/velvetk-20120606-find-reasonable-k-mer-size-assemble-genome-reads-velvet.html" title="VelvetK 20120606 &ndash; Find a reasonable K-mer size to Assemble Genome Reads with Velvet"><br /><br /></a></li>
<li><a href="http://www.vicbioinformatics.com/software.vague.shtml" title="VAGUE 1.0.5 &ndash; Velvet Assembler Graphical User Environment">VAGUE 1.0.5 &ndash; Velvet Assembler Graphical User Environment<br /></a><a href="http://www.vicbioinformatics.com/software.vague.shtml" target="_blank">VAGUE</a>&nbsp;(Velvet Assembler Graphical Front End) is a GUI for the&nbsp;<a href="http://www.mybiosoftware.com/assembly-tools/3852">Velvet</a>&nbsp;de novo assembler.<a href="http://www.mybiosoftware.com/vague-1-0-5-velvet-assembler-graphical-user-environment.html" title="VAGUE 1.0.5 &ndash; Velvet Assembler Graphical User Environment"><br /><br /></a></li>
<li><a href="http://pritchardlab.stanford.edu/software.html" title="Transcriptome Assembler &ndash; Transcriptome Assembly used in RNA-seq of 16 Mammalian Species">Transcriptome Assembler &ndash; Transcriptome Assembly used in RNA-seq of 16 Mammalian Species<br /></a><a href="http://pritchardlab.stanford.edu/software.html" target="_blank">Transcriptome Assembler</a>&nbsp;is a software for transcriptome assembly used in RNA-seq of 16 mammalian species.<a href="http://www.mybiosoftware.com/transcriptome-assembler-transcriptome-assembly-rna-seq-16-mammalian-species.html" title="Transcriptome Assembler &ndash; Transcriptome Assembly used in RNA-seq of 16 Mammalian Species"><br /><br /></a></li>
<li><a href="http://bio.codeplex.com/wikipage?title=sequenceassembler&amp;referringTitle=sampleapps&amp;ANCHOR#sampleapps" title="BioSequenceAssembler 2.0 &ndash; Microsoft Research Sequence Assembler">BioSequenceAssembler 2.0 &ndash; Microsoft Research Sequence Assembler<br /></a><a href="http://bio.codeplex.com/wikipage?title=sequenceassembler&amp;referringTitle=sampleapps&amp;ANCHOR#sampleapps" target="_blank">BioSequenceAssembler</a>&nbsp;is intended for use by biologist and laboratory technicians who are responsible for managing next-generation genomic sequencing data for alignment, assembly, and/or BLAST identification.<a href="http://www.mybiosoftware.com/biosequenceassembler-2-0-microsoft-research-sequence-assembler.html" title="BioSequenceAssembler 2.0 &ndash; Microsoft Research Sequence Assembler"><br /><br /></a></li>
<li><a href="http://www.imperial.ac.uk/bioinformatics-data-science-group" title="BugBuilder &ndash; Microbial Genome Assembly">BugBuilder &ndash; Microbial Genome Assembly<br /></a><a href="http://www3.imperial.ac.uk/bioinfsupport/resources/software/bugbuilder" target="_blank">BugBuilder</a>&nbsp;is a pipeline for the automated assembly and annotation of microbial genomes from high-throughput sequence data. It is configurable so as not to be tied to any assembler or scaffolder, and is designed to run in a cluster environment facilitating high-throughput processing of genomes.<a href="http://www.mybiosoftware.com/bugbuilder-microbial-genome-assembly.html" title="BugBuilder &ndash; Microbial Genome Assembly"><br /></a></li>
<li><a href="http://maximuspipeline.sourceforge.net/main/">MAXIMUS 0.2 &ndash; Hybrid Reference and de novo Assembly pipeline</a><br /><a href="http://maximuspipeline.sourceforge.net/main/" target="_blank">MAXIMUS</a>&nbsp;is a genome assembly pipeline which takes the best out of multiple reference assemblies and de novo assembly. The benefits of this approach include better assembled repetitive regions, less gaps and higher accuracy for the resultant assembly.<a href="http://www.mybiosoftware.com/maximus-0-2-hybrid-reference-de-novo-assembly-pipeline.html" title="MAXIMUS 0.2 &ndash; Hybrid Reference and de novo Assembly pipeline"><br /><br /></a></li>
<li><a href="http://www.bcgsc.ca/about/pubann/the-issake-short-read-sequence-assembly-approach-for-profiling-t-cell-metagenomes" title="ISSAKE &ndash; Short Read Sequence Assembly">ISSAKE &ndash; Short Read Sequence Assembly<br /></a><a href="http://www.bcgsc.ca/about/pubann/the-issake-short-read-sequence-assembly-approach-for-profiling-t-cell-metagenomes" target="_blank">iSSAKE</a>&nbsp;(immuno-SSAKE) is a sequencing approach and assembly software for profiling T-cell metagenomes using short reads from the massively parallel sequencing platforms.<a href="http://www.mybiosoftware.com/issake-short-read-sequence-assembly.html" title="ISSAKE &ndash; Short Read Sequence Assembly"><br /><br /></a></li>
<li><a href="http://www.animalgenome.org/tools/beap/" title="IDBA / IDBA-UD 1.1.1 &ndash; De Bruijn Graph De Novo Assembler with Highly Uneven Sequencing Depth">IDBA / IDBA-UD 1.1.1 &ndash; De Bruijn Graph De Novo Assembler with Highly Uneven Sequencing Depth<br /></a><a href="http://i.cs.hku.hk/~alse/hkubrg/projects/idba/index.html" target="_blank">&nbsp;IDBA</a>&nbsp;is a practical iterative De Bruijn Graph De Novo Assembler for sequence assembly in bioinfomatics. Most assemblers based on de Bruijn graph build a de Bruijn graph with a specific k to perform the assembling task. For all of them, it is very crucial to find a specific value of k. If k is too large, there will be a lot of gap problems in the graph. If k is too small, there will a lot of branch problems. IDBA uses not only one specific k but a range of k values to build the iterative de Bruijn graph. It can keep all the information in graphs with different k values. So, it will perform better than other assemblers.<a href="http://www.mybiosoftware.com/idba-ud-1-09-de-bruijn-graph-de-novo-assembler-highly-uneven-sequencing-depth.html" title="IDBA / IDBA-UD 1.1.1 &ndash; De Bruijn Graph De Novo Assembler with Highly Uneven Sequencing Depth"><br /><br /></a></li>
<li><a href="https://code.google.com/archive/p/est2assembly/" title="est2assembly 1.13 &ndash; Assembly and Annotation of Transcriptomes for any Species">est2assembly 1.13 &ndash; Assembly and Annotation of Transcriptomes for any Species<br />The&nbsp;</a><a href="https://code.google.com/p/est2assembly/" target="_blank">est2assembly</a>&nbsp;platform is the only platform for standardising transcriptome projects: go from raw trace files to an annotated GBrowse interface driven by the Seqfeature database. It accepts both Sanger and 454 sequencing technology for a denovo assembly, annotation and data mining of EST data.<a href="http://www.mybiosoftware.com/est2assembly-1-13-assembly-annotation-transcriptomes-species.html" title="est2assembly 1.13 &ndash; Assembly and Annotation of Transcriptomes for any Species"><br /><br /></a></li>
<li><a href="https://code.google.com/archive/p/curtain/" title="Curtain 0.2.3 beta &ndash; Assembling large Genomes from Short Read Sequences">Curtain 0.2.3 beta &ndash; Assembling large Genomes from Short Read Sequences<br /></a><a href="https://code.google.com/p/curtain/" target="_blank">Curtain</a>&nbsp;is an assembler of next generation sequence. Curtain is a Java wrapper around next-generation assemblers such as Velvet, which allows the incremental introduction of read-pair information into the assembly process.<a href="http://www.mybiosoftware.com/curtain-0-2-3-beta-assembling-large-genomes-short-read-sequences.html" title="Curtain 0.2.3 beta &ndash; Assembling large Genomes from Short Read Sequences"><br /><br /></a></li>
<li><a href="http://www.comp.nus.edu.sg/~bioinfo/peasm/PE_manual.htm" title="PEAssember 1.2 &ndash; A de novo Genome Assembler">PEAssember 1.2 &ndash; A de novo Genome Assembler<br /></a><a href="http://www.comp.nus.edu.sg/~bioinfo/peasm/PE_manual.htm" target="_blank">PEAssember</a>&nbsp;is a parallel de novo genome assembler for small &ndash; mid sized genomes.<a href="http://www.mybiosoftware.com/peassember-1-2-de-novo-genome-assembler.html" title="PEAssember 1.2 &ndash; A de novo Genome Assembler"><br /><br /></a></li>
<li><a href="https://sourceforge.net/projects/contrail-bio/" title="Contrail 0.8.2 &ndash; Assembly of Large Genomes using Cloud Computing">Contrail 0.8.2 &ndash; Assembly of Large Genomes using Cloud Computing<br /></a><a href="http://contrail-bio.sourceforge.net/" target="_blank">Contrail</a>&nbsp;is a Hadoop based genome assembler for assembling large genomes in the clouds<a href="http://www.mybiosoftware.com/contrail-0-8-2-assembly-large-genomes-cloud-computing.html" title="Contrail 0.8.2 &ndash; Assembly of Large Genomes using Cloud Computing"><br /><br /></a></li>
<li><a href="http://www.mybiosoftware.com/beap-0-6-beta-blast-extension-assembly-program.html" title="BEAP 0.6 beta &ndash; Blast Extension and Assembly Program">BEAP 0.6 beta &ndash; Blast Extension and Assembly Program<br />The&nbsp;</a><a href="http://www.animalgenome.org/tools/beap/" target="_blank">BEAP</a>&nbsp;is a computer program that uses a short starting DNA fragment, often a EST or partial gene segment, as &ldquo;primer&rdquo;, to recursively blast nucleotide databases in an attempt to obtain all sequences that overlaps, directly or indirectly, with the &ldquo;primer&rdquo; therefore help to &ldquo;extend&rdquo; the length of the original sequence for constructing a &ldquo;full length&rdquo; sequence for functional analysis, or at least to obtain neighboring regions of the segment for SNP discovery and linkage disequilibrium&nbsp;<a href="http://www.mybiosoftware.com/beap-0-6-beta-blast-extension-assembly-program.html" title="BEAP 0.6 beta &ndash; Blast Extension and Assembly Program"><br /><br /></a></li>
<li><a href="http://manuals.bioinformatics.ucr.edu/home/branch" title="BRANCH 1.8.1 &ndash; boosting RNA-Seq Assemblies with Partial or related Genomic Sequences">BRANCH 1.8.1 &ndash; boosting RNA-Seq Assemblies with Partial or related Genomic Sequences<br /></a><a href="http://manuals.bioinformatics.ucr.edu/home/branch" target="_blank">BRANCH</a>&nbsp;is a software that extends de novo transfrags and identifies novel transfrags with DNA contigs or genes of close related species. BRANCH discovers novel exons first and then extends/joins fragmented de novo transfrags, so that the resulted transfrags are more complete.<a href="http://www.mybiosoftware.com/branch-1-8-1-boosting-rna-seq-assemblies-partial-related-genomic-sequences.html" title="BRANCH 1.8.1 &ndash; boosting RNA-Seq Assemblies with Partial or related Genomic Sequences"><br /><br /></a></li>
<li><a href="http://www.cbcb.umd.edu/software/quake/">Quake 0.3.5 &ndash; Detect &amp; Correct Substitution Sequencing Errors in WGS Data Sets</a><br />
<p><a href="http://www.cbcb.umd.edu/software/quake/" target="_blank">Quake</a>&nbsp;is a package to correct substitution sequencing errors in experiments with deep coverage (e.g. &gt;15X), specifically intended for Illumina sequencing reads. Quake adopts the k-mer error correction framework, first introduced by the EULER genome assembly package. Unlike EULER and similar progams, Quake utilizes a robust mixture model of erroneous and genuine k-mer distributions to determine where errors are located. Then Quake uses read quality values and learns the nucleotide to nucleotide error rates to determine what types of errors are most likely. This leads to more corrections and greater accuracy, especially with respect to avoiding mis-corrections,&nbsp;&nbsp;which create false sequence unsimilar to anything in the original genome sequence from which the read was taken.</p>
</li>
<li><a href="http://www.ebi.ac.uk/~zerbino/velvet/" title="Velvet 1.2.10 &ndash; Sequence Assembler for Very Short Reads">Velvet 1.2.10 &ndash; Sequence Assembler for Very Short Reads<br /></a><a href="http://www.ebi.ac.uk/~zerbino/velvet/" target="_blank">Velvet</a>&nbsp;is a de novo genomic assembler specially designed for short read sequencing technologies, such as Solexa or 454.Velvet currently takes in short read sequences, removes errors then produces high quality unique contigs. It then uses paired-end read and long read information, when available, to retrieve the repeated areas between contigs.<a href="http://www.mybiosoftware.com/velvet-1-1-07-sequence-assembler-short-reads.html" title="Velvet 1.2.10 &ndash; Sequence Assembler for Very Short Reads"><br /><br /></a></li>
<li><a href="http://www.complex.iastate.edu/download/Lucy2/index.html" title="Lucy 2.20 &ndash; DNA Sequence Quality &amp; Vector Trimming">Lucy 2.20 &ndash; DNA Sequence Quality &amp; Vector Trimming<br /></a><a href="http://www.complex.iastate.edu/download/Lucy2/index.html" target="_blank">Lucy</a>&nbsp;has been used for several years to clean sequence data from automated DNA sequencers prior to sequence assembly and other downstream uses. &nbsp;The quality trimming portion of lucy makes use of phred quality scores, such as those produced by many automated sequencers based on the Sanger sequencing method. &nbsp;As such, lucy&rsquo;s quality trimming may not be appropriate for sequence data produced by some of the new &ldquo;next-generation&rdquo; sequencers.<a href="http://www.mybiosoftware.com/lucy-2-19p-r8-dna-sequence-quality-vector-trimming.html" title="Lucy 2.20 &ndash; DNA Sequence Quality &amp; Vector Trimming"><br /><br /></a></li>
<li><a href="http://bioinfo.bti.cornell.edu/tool/iAssembler/">iAssembler 1.3.2 &ndash; de novo Assembly of Roche-454/Sanger Transcriptome Sequences</a><br /><a href="http://bioinfo.bti.cornell.edu/tool/iAssembler/" target="_blank">iAssembler</a>&nbsp;is a standalone package to assemble ESTs generated using Sanger and/or Roche-454 pyrosequencing technologies into contigs.<a href="http://www.mybiosoftware.com/iassembler-1-3-2-de-novo-assembly-roche-454sanger-transcriptome-sequences.html" title="iAssembler 1.3.2 &ndash; de novo Assembly of Roche-454/Sanger Transcriptome Sequences"><br /><br /></a></li>
<li><a href="http://www.broadinstitute.org/software/gaemr/" title="GAEMR 1.0.1 &ndash; Assembly Analysis Framework">GAEMR 1.0.1 &ndash; Assembly Analysis Framework<br /></a><a href="http://www.broadinstitute.org/software/gaemr/" target="_blank">GAEMR</a>&nbsp;(Genome Assembly Evaluation Metrics and Reportin) is a complete genome analysis package that helps you evaluate and report on a genome assembly&rsquo;s completeness, correctness, and contiguity.<a href="http://www.mybiosoftware.com/gaemr-1-0-1-assembly-analysis-framework.html" title="GAEMR 1.0.1 &ndash; Assembly Analysis Framework"><br /><br /></a></li>
<li><a href="https://mulcyber.toulouse.inra.fr/plugins/mediawiki/wiki/pyrocleaner/index.php/Main_Page" title="PyroCleaner 1.3 &ndash; Clean 454 Pyrosequencing Reads in order to ease the Assembly Process">PyroCleaner 1.3 &ndash; Clean 454 Pyrosequencing Reads in order to ease the Assembly Process<br />The&nbsp;</a><a href="https://mulcyber.toulouse.inra.fr/plugins/mediawiki/wiki/pyrocleaner/index.php/Main_Page" target="_blank">pyrocleaner</a>&nbsp;is intended to clean the reads included in the sff file in order to ease the assembly process. It enables filtering sequences on different criteria such as length, complexity, number of undetermined bases which has been proven to correlate with poor quality and multiple copy reads. It also enables to clean paired-ends sff files and generates on one side a sff with the validated paired-ends and on the other the sequences which can be used as shotgun reads.<a href="http://www.mybiosoftware.com/pyrocleaner-1-3-clean-454-pyrosequencing-reads-order-ease-assembly-process.html" title="PyroCleaner 1.3 &ndash; Clean 454 Pyrosequencing Reads in order to ease the Assembly Process"><br /><br /></a></li>
<li><a href="http://bioinformatics.rutgers.edu/Software/SLiQ/" title="SLiQ &ndash; Simple linear Inequalities based Mate-Pair reads Filtering and Scaffolding">SLiQ &ndash; Simple linear Inequalities based Mate-Pair reads Filtering and Scaffolding<br /></a><a href="http://bioinformatics.rutgers.edu/Software/SLiQ/" target="_blank">SLIQ&nbsp;</a>, a set of simple linear inequalities derived from the geometry of contigs on the line, can be used to predict the relative positions and orientations of contigs from individual mate pair reads and thus produce a contig digraph.<a href="http://www.mybiosoftware.com/sliq-simple-linear-inequalities-based-mate-pair-reads-filtering-scaffolding.html" title="SLiQ &ndash; Simple linear Inequalities based Mate-Pair reads Filtering and Scaffolding"><br /><br /></a></li>
<li><a href="http://bioinf.spbau.ru/en/rectangles" title="rectangles 2.0 &ndash; Rectangle Graph for Repeat Resolution in Genome Assembly">rectangles 2.0 &ndash; Rectangle Graph for Repeat Resolution in Genome Assembly<br /></a><a href="http://bioinf.spbau.ru/en/rectangles" target="_blank">rectangles</a>&nbsp;is an ultimate tool for resolving repeats in genome assemblies.<a href="http://www.mybiosoftware.com/rectangles-2-0-rectangle-graph-repeat-resolution-genome-assembly.html" title="rectangles 2.0 &ndash; Rectangle Graph for Repeat Resolution in Genome Assembly"><br /><br /></a></li>
<li><a href="http://archive.broadinstitute.org/crd/wiki/index.php/Arachne_Main_Page" title="Arachne 4.6233 &ndash; Whole-genome Shotgun Assembler">Arachne 4.6233 &ndash; Whole-genome Shotgun Assembler<br /></a><a href="http://www.broadinstitute.org/crd/wiki/index.php/Arachne_Main_Page" target="_blank">ARACHNE</a>&nbsp;is a program for assembling data from whole genome shotgun sequencing experiments. It was designed for long reads from Sanger sequencing technology, and has been used extensively to assemble many genomes, including many that are large and highly repetitive.<a href="http://www.mybiosoftware.com/arachne-3-2-whole-genome-shotgun-assembler.html" title="Arachne 4.6233 &ndash; Whole-genome Shotgun Assembler"><br /><br /></a></li>
<li><a href="http://terpconnect.umd.edu/~ALEKSEYZ/PhrapUMDV2/" title="Reconciliator 2.0 &ndash; The tool for Merging Assemblies">Reconciliator 2.0 &ndash; The tool for Merging Assemblies<br /></a><a href="http://terpconnect.umd.edu/~ALEKSEYZ/PhrapUMDV2/" target="_blank">Reconciliator</a>&nbsp;is the tool for merging assemblies.<a href="http://www.mybiosoftware.com/reconciliator-2-0-tool-merging-assemblies.html" title="Reconciliator 2.0 &ndash; The tool for Merging Assemblies"><br /><br /></a></li>
<li><a href="http://terpconnect.umd.edu/~ALEKSEYZ/PhrapUMDV2/" title="PhrapUMD 2 &ndash; Modified version of Phrap">PhrapUMD 2 &ndash; Modified version of Phrap<br /></a><a href="http://www.glue.umd.edu/~ALEKSEYZ/PhrapUMDV2" target="_blank">Phrap UMD</a>&nbsp;consists of the UMD Trimmer, UMD Overlapper and a modified version of Phrap.It is capable of assembling data downloaded directly from the NCBI Trace Archive. The pipeline runs in 3 stages: &nbsp;first the vector ends of the reads are examined and the vector is found. &nbsp;Then the reads are trimmed for vector and quality. &nbsp;After that the trimmed reads afe fed into the 5-pass UMD Overlapper that finds the overlaps, corrects the base caller errors and performs additional trimming if necessary. &nbsp;After the overlaps are produced, the trimmed and error-corrected reads and overlaps are input into the modified version of Phrap, whichonly puts the reads together if they overlap according to the list of overlaps produced by the UMD Overlapper.<a href="http://www.mybiosoftware.com/phrapumd-2-modified-version-phrap.html" title="PhrapUMD 2 &ndash; Modified version of Phrap"><br /><br /></a></li>
<li><a href="http://www.dna-dragon.com/" title="DNA Dragon 1.5.6 build1 &ndash; DNA Sequence Contig Assembler Software">DNA Dragon 1.5.6 build1 &ndash; DNA Sequence Contig Assembler Software<br /></a><a href="http://www.dna-dragon.com/" target="_blank">DNA Dragon</a>&nbsp;Contig Assembler assembles sequences, trace data (ABI, SCF, AB1), Illumina and Roche 454 flowgrams into contigs. It is a very fast and accurate DNA sequence assembly software. The DNA sequences are assembled into contigs and a direct comparision of trace date with nucleotide data is possible. It also allows for proofreading and base editing.<a href="http://www.mybiosoftware.com/dna-dragon-1-2-7-dna-sequence-contig-assembler-software.html" title="DNA Dragon 1.5.6 build1 &ndash; DNA Sequence Contig Assembler Software"><br /></a></li>
</ul>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/31566/software-and-tools-to-detect-structure-variation-with-long-reads</guid>
	<pubDate>Wed, 15 Mar 2017 14:31:09 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/31566/software-and-tools-to-detect-structure-variation-with-long-reads</link>
	<title><![CDATA[Software and Tools to detect structure variation with long reads !!]]></title>
	<description><![CDATA[<p>Uncovering the connection between genetics and heritable diseases requires an approach that looks at all the variant bases and types in a genome. While a PacBio&nbsp;<em>de novo</em>&nbsp;assembly resolves the most novel SV variants. 8-10X PacBio coverage of single genomes or trios reveals triple the SVs detectable by short-read data.</p><p>With&nbsp;<span style="text-decoration: underline;"><a href="http://www.pacb.com/smrt-science/">Single Molecule, Real-Time (SMRT) Sequencing</a></span>, you can access structural variations having a broad range of sizes, types, and GC content with the ability to:</p><ul>
<li>Uncover missing heritability linked to structural variation</li>
<li>Unambiguously identify genomic context and variant breakpoints at the sequence level to unravel the genetic etiology of disease</li>
<li>Resolve structural variation across the complete size spectrum with basepair resolution</li>
</ul><p>Following are the SV tools, which can assist you to achieve your goal.</p><p><strong>Sniffles:</strong>&nbsp;Structural variation caller using third generation sequencing</p><p>Sniffles is a structural variation caller using third generation sequencing (PacBio or Oxford Nanopore). It detects all types of SVs using evidence from split-read alignments, high-mismatch regions, and coverage analysis. Please note the current version of Sniffles requires sorted output from BWA-MEM (use -M and -x parameter) or NGM-LR with the optional SAM attributes enabled!&nbsp;</p><p>More at&nbsp;https://github.com/fritzsedlazeck/Sniffles</p><p><strong style="font-size: 12.8px;"><br />MultiBreak-SV:</strong> It identifies structural variants from next-generation paired end data, third-generation long read data, or data from a combination of sequencing platforms.</p><p>There are two pieces of software in this release: (1) a pre-processor that takes machineformat (.m5) BLASR files, and (2) MultiBreak-SV. For installation and usage instructions, see doc/MultiBreakSV-Manual.txt.</p><p>More at&nbsp;https://github.com/raphael-group/multibreak-sv</p><p><strong style="font-size: 12.8px;"><br />Parliament:</strong>&nbsp;A Structural Variation Tool. Why ask a single sv-detection approach to find every variant when you can have a parliament of tools deciding?</p><p>Publication about the algorithm and &ldquo;&hellip;the first long-read characterization of structural variation in a diploid human personal genome&hellip;&rdquo; (HS1011) -&nbsp;<a href="http://www.biomedcentral.com/1471-2164/16/286">&ldquo;Assessing structural variation in a personal genome&mdash;towards a human reference diploid genome&rdquo;</a></p><p>More at&nbsp;https://sourceforge.net/projects/parliamentsv/</p><p>https://www.dnanexus.com/papers/Parliament_Info_Sheet.pdf</p><p><br /><strong>PBHoney:</strong>&nbsp;the structural variation discovery tool&nbsp;<br /><br />PBHoney is an implementation of two variant-identification approaches designed to exploit the high mappability of long reads (i.e., greater than 10,000 bp). PBHoney considers both intra-read discordance and soft-clipped tails of long reads to identify structural variants.</p><p>Read The Paper&nbsp;<a href="http://www.biomedcentral.com/1471-2105/15/180/abstract" target="_blank">http://www.biomedcentral.com/1471-2105/15/180/abstract</a></p><p>More at&nbsp;https://sourceforge.net/projects/pb-jelly/</p><p><strong><br />SMRT-SV:</strong> Structural variant and indel caller for PacBio reads</p><p>Structural variant (SV) and indel caller for PacBio reads based on methods from&nbsp;<a href="http://www.nature.com/nature/journal/vaop/ncurrent/full/nature13907.html">Chaisson et al. 2014</a>.</p><p>SMRT-SV provides an official software package for tools described in&nbsp;<a href="http://www.nature.com/nature/journal/vaop/ncurrent/full/nature13907.html">Chaisson et al. 2014</a>&nbsp;and adds several key features including the following.</p><ul>
<li>Unified variant calling user interface with built-in cluster compute support</li>
<li>Small indel calling (2-49 bp)</li>
<li>Improved inversion calling (<code>screenInversions</code>)</li>
<li>Quality metric for SV calls based on number of local assemblies supporting each call</li>
<li>Higher sensitivity for SV calls using tiled local assemblies across the entire genome instead of "signature" regions</li>
<li>Genotyping of SVs with Illumina paired-end reads from WGS samples</li>
</ul><p>More at&nbsp;https://github.com/EichlerLab/pacbio_variant_caller</p>]]></description>
	<dc:creator>Archana Malhotra</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27696/methylkit</guid>
	<pubDate>Fri, 03 Jun 2016 10:09:29 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27696/methylkit</link>
	<title><![CDATA[methylKit]]></title>
	<description><![CDATA[<p><em>methylKit</em> is an <a href="http://en.wikipedia.org/wiki/R_%28programming_language%29">R</a> package for DNA methylation analysis and annotation from high-throughput bisulfite sequencing. The package is designed to deal with sequencing data from <a href="http://www.nature.com/nprot/journal/v6/n4/abs/nprot.2010.190.html">RRBS</a> and its variants, but also target-capture methods such as <a href="http://www.halogenomics.com/sureselect/methyl-seq">Agilent SureSelect methyl-seq</a>. In addition, methylKit can deal with base-pair resolution data for 5hmC obtained from Tab-seq or oxBS-seq. It can also handle whole-genome bisulfite sequencing data if proper input format is provided.</p><p>Address of the bookmark: <a href="https://github.com/al2na/methylKit" rel="nofollow">https://github.com/al2na/methylKit</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/32713/salzberg-lab</guid>
  <pubDate>Mon, 15 May 2017 05:14:01 -0500</pubDate>
  <link></link>
  <title><![CDATA[Salzberg lab]]></title>
  <description><![CDATA[
<p>We are a computational biology lab that develops novel methods for analysis of DNA and RNA sequences. Our research includes software for aligning and assembling RNA-seq data, whole-genome assembly, and microbiome analysis. We work closely with biomedical scientists to apply these methods to current problems arising in a broad spectrum of biological and medical research areas. We’re also part of the Center for Computational Biology, a group of 20+ faculty members and their labs at Johns Hopkins working on computational, statistical, and mathematical methods that can turn massive genomic data sets into biologically and clinically useful information.</p>

<p>https://salzberg-lab.org/</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36880/jvarkit-java-utilities-for-bioinformatics</guid>
	<pubDate>Fri, 08 Jun 2018 09:31:55 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36880/jvarkit-java-utilities-for-bioinformatics</link>
	<title><![CDATA[Jvarkit : Java utilities for Bioinformatics]]></title>
	<description><![CDATA[Collection of Java tool kits for bioinformatics works:

Jvarkit : Java utilities for Bioinformatics<p>Address of the bookmark: <a href="http://lindenb.github.io/jvarkit/" rel="nofollow">http://lindenb.github.io/jvarkit/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42359/dnasp-dna-sequence-polymorphism-is-a-software-package-for-the-analysis-of-dna-polymorphisms</guid>
	<pubDate>Wed, 25 Nov 2020 19:51:38 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42359/dnasp-dna-sequence-polymorphism-is-a-software-package-for-the-analysis-of-dna-polymorphisms</link>
	<title><![CDATA[DnaSP: DNA Sequence Polymorphism, is a software package for the analysis of DNA polymorphisms]]></title>
	<description><![CDATA[<p><span>DnaSP, DNA Sequence Polymorphism, is a software package for the analysis of DNA polymorphisms using data from a single locus (a multiple sequence aligned -MSA data), or from several loci (a Multiple-MSA data, such as formats generated by some assembler RAD-seq software). DnaSP can estimate several measures of DNA sequence variation within and between populations in noncoding, synonymous or nonsynonymous sites, or in various sorts of codon positions), as well as linkage disequilibrium, recombination, gene flow and gene conversion parameters.</span></p><p>Address of the bookmark: <a href="http://www.ub.edu/dnasp/" rel="nofollow">http://www.ub.edu/dnasp/</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/19980/seqloc-06</guid>
	<pubDate>Sun, 28 Dec 2014 12:51:29 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/19980/seqloc-06</link>
	<title><![CDATA[seqloc 0.6]]></title>
	<description><![CDATA[<p>The <code>Bio.SeqLoc</code> modules in <code>seqloc</code> are designed to represent positions and locations (ranges of positions) on sequences, particularly nucleotide sequences. My original motivation for writing these packages was handing the locations of genes in eukaryotic genomes.</p>
<p>Handle sequence locations for bioinformatics http://www.ingolia-lab.org/seqloc-tutorial.html</p><p>Address of the bookmark: <a href="http://www.stackage.org/snapshot/nightly-2014-12-28/package/seqloc-0.6" rel="nofollow">http://www.stackage.org/snapshot/nightly-2014-12-28/package/seqloc-0.6</a></p>]]></description>
	<dc:creator>Gudiya Pal</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/22807/software-packages-for-next-gen-sequence-analysis</guid>
	<pubDate>Fri, 19 Jun 2015 21:07:15 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/22807/software-packages-for-next-gen-sequence-analysis</link>
	<title><![CDATA[Software packages for next gen sequence analysis]]></title>
	<description><![CDATA[<p><strong>Integrated solutions</strong><br /> * <a href="http://www.clcbio.com/index.php?id=1240" target="_blank">CLCbio Genomics Workbench</a> - <em>de novo</em> and reference assembly of Sanger, Roche FLX, Illumina, Helicos, and SOLiD data. Commercial next-gen-seq software that extends the CLCbio Main Workbench software. Includes SNP detection, CHiP-seq, browser and other features. Commercial. Windows, Mac OS X and Linux.<br /> * <a href="http://g2.trac.bx.psu.edu/" target="_blank">Galaxy</a> - Galaxy = interactive and reproducible genomics. A job webportal.<br /> * <a href="http://www.genomatix.de/products/index.html" target="_blank">Genomatix</a> - Integrated Solutions for Next Generation Sequencing data analysis.<br /> * <a href="http://www.jmp.com/software/genomics/" target="_blank">JMP Genomics</a> - Next gen visualization and statistics tool from SAS. They are <a href="http://www.marketwatch.com/news/story/JMPR-Genomics-NCGR-Partnership-Foster/story.aspx?guid=%7B7AC9DE36-B6AA-4EDE-9CD5-633B29FE6154%7D" target="_blank">working with NCGR</a> to refine this tool and produce others.<br /> * <a href="http://softgenetics.com/NextGENe.html" target="_blank">NextGENe</a> - <em>de novo</em> and reference assembly of Illumina, SOLiD and Roche FLX data. Uses a novel Condensation Assembly Tool approach where reads are joined via "anchors" into mini-contigs before assembly. Includes SNP detection, CHiP-seq, browser and other features. Commercial. Win or MacOS.<br /> * <a href="http://www.dnastar.com/products/SMGA.php" target="_blank">SeqMan Genome Analyser</a> - Software for Next Generation sequence assembly of Illumina, Roche FLX and Sanger data integrating with Lasergene Sequence Analysis software for additional analysis and visualization capabilities. Can use a hybrid templated/de novo approach. Commercial. Win or Mac OS X.<br /> * <a href="http://1001genomes.org/downloads/shore.html" target="_blank">SHORE</a> - SHORE, for Short Read, is a mapping and analysis pipeline for short DNA sequences produced on a Illumina Genome Analyzer. A suite created by the 1001 Genomes project. Source for POSIX.<br /> * <a href="http://www.realtimegenomics.com/" target="_blank">SlimSearch</a> - Fledgling commercial product.<br /> <br /> <strong>Align/Assemble to a reference</strong><br /> * <a href="https://secure.genome.ucla.edu/index.php/BFAST" target="_blank">BFAST</a> - Blat-like Fast Accurate Search Tool. Written by Nils Homer, Stanley F. Nelson and Barry Merriman at UCLA.<br /> * <a href="http://bowtie-bio.sourceforge.net/" target="_blank">Bowtie</a> - Ultrafast, memory-efficient short read aligner. It aligns short DNA sequences (reads) to the human genome at a rate of 25 million reads per hour on a typical workstation with 2 gigabytes of memory. Uses a Burrows-Wheeler-Transformed (BWT) index. <a href="http://seqanswers.com/forums/showthread.php?t=706" target="_blank">Link to discussion thread here</a>. Written by Ben Langmead and Cole Trapnell. Linux, Windows, and Mac OS X.<br /> * <a href="http://maq.sourceforge.net/" target="_blank">BWA</a> - Heng Lee's BWT Alignment program - a progression from Maq. BWA is a fast light-weighted tool that aligns short sequences to a sequence database, such as the human reference genome. By default, BWA finds an alignment within edit distance 2 to the query sequence. C++ source.<br /> * <a href="http://bioinfo.cgrb.oregonstate.edu/docs/solexa/" target="_blank">ELAND</a> - Efficient Large-Scale Alignment of Nucleotide Databases. Whole genome alignments to a reference genome. Written by Illumina author Anthony J. Cox for the Solexa 1G machine.<br /> * <a href="http://www.ebi.ac.uk/%7Eguy/exonerate/" target="_blank">Exonerate</a> - Various forms of pairwise alignment (including Smith-Waterman-Gotoh) of DNA/protein against a reference. Authors are Guy St C Slater and Ewan Birney from EMBL. C for POSIX.<br /> * <a href="http://1001genomes.org/downloads/genomemapper.html" target="_blank">GenomeMapper</a> - GenomeMapper is a short read mapping tool designed for accurate read alignments. It quickly aligns millions of reads either with ungapped or gapped alignments. A tool created by the 1001 Genomes project. Source for POSIX.<br /> * <a href="http://www.gene.com/share/gmap/" target="_blank">GMAP</a> - GMAP (Genomic Mapping and Alignment Program) for mRNA and EST Sequences. Developed by Thomas Wu and Colin Watanabe at Genentec. C/Perl for Unix.<br /> * <a href="http://dna.cs.byu.edu/gnumap/" target="_blank">gnumap</a> - The Genomic Next-generation Universal MAPper (gnumap) is a program designed to accurately map sequence data obtained from next-generation sequencing machines (specifically that of Solexa/Illumina) back to a genome of any size. It seeks to align reads from nonunique repeats using statistics. From authors at Brigham Young University. C source/Unix.<br /> * <a href="http://sourceforge.net/projects/maq/" target="_blank">MAQ</a> - Mapping and Assembly with Qualities (renamed from MAPASS2). Particularly designed for Illumina with preliminary functions to handle ABI SOLiD data. Written by Heng Li from the Sanger Centre. Features extensive supporting tools for DIP/SNP detection, etc. C++ source<br /> * <a href="http://bioinformatics.bc.edu/marthlab/Mosaik" target="_blank">MOSAIK</a> - MOSAIK produces gapped alignments using the Smith-Waterman algorithm. Features a number of support tools. Support for Roche FLX, Illumina, SOLiD, and Helicos. Written by Michael Str&ouml;mberg at Boston College. Win/Linux/MacOSX<br /> * <a href="http://mrfast.sourceforge.net/" target="_blank">MrFAST and MrsFAST</a> - mrFAST &amp; mrsFAST are designed to map short reads generated with the Illumina platform to reference genome assemblies; in a fast and memory-efficient manner. Robust to INDELs and MrsFAST has a bisulphite mode. Authors are from the University of Washington. C as source.<br /> * <a href="http://mummer.sourceforge.net/" target="_blank">MUMmer</a> - MUMmer is a modular system for the rapid whole genome alignment of finished or draft sequence. Released as a package providing an efficient suffix tree library, seed-and-extend alignment, SNP detection, repeat detection, and visualization tools. Version 3.0 was developed by Stefan Kurtz, Adam Phillippy, Arthur L Delcher, Michael Smoot, Martin Shumway, Corina Antonescu and Steven L Salzberg - most of whom are at The Institute for Genomic Research in Maryland, USA. POSIX OS required.<br /> * <a href="http://www.novocraft.com/index.html" target="_blank">Novocraft</a> - Tools for reference alignment of paired-end and single-end Illumina reads. Uses a Needleman-Wunsch algorithm. Can support Bis-Seq. Commercial. Available free for evaluation, educational use and for use on open not-for-profit projects. Requires Linux or Mac OS X.<br /> * <a href="http://pass.cribi.unipd.it/cgi-bin/pass.pl" target="_blank">PASS</a> - It supports Illumina, SOLiD and Roche-FLX data formats and allows the user to modulate very finely the sensitivity of the alignments. Spaced seed intial filter, then NW dynamic algorithm to a SW(like) local alignment. Authors are from CRIBI in Italy. Win/Linux.<br /> * <a href="http://rulai.cshl.edu/rmap/" target="_blank">RMAP</a> - Assembles 20 - 64 bp Illumina reads to a FASTA reference genome. By Andrew D. Smith and Zhenyu Xuan at CSHL. (published in BMC Bioinformatics). POSIX OS required.<br /> * <a href="http://biogibbs.stanford.edu/%7Ejiangh/SeqMap/" target="_blank">SeqMap</a> - Supports up to 5 or more bp mismatches/INDELs. Highly tunable. Written by Hui Jiang from the Wong lab at Stanford. Builds available for most OS's.<br /> * <a href="http://compbio.cs.toronto.edu/shrimp/" target="_blank">SHRiMP</a> - Assembles to a reference sequence. Developed with Applied Biosystem's colourspace genomic representation in mind. Authors are Michael Brudno and Stephen Rumble at the University of Toronto. POSIX.<br /> * <a href="http://www.bcgsc.ca/platform/bioinfo/software/slider" target="_blank"><span style="text-decoration: underline;">Slider</span></a>- An application for the Illumina Sequence Analyzer output that uses the probability files instead of the sequence files as an input for alignment to a reference sequence or a set of reference sequences. Authors are from BCGSC. Paper is <a href="http://seqanswers.com/forums/showthread.php?t=740" target="_blank">here</a>.<br /> * <a href="http://soap.genomics.org.cn/" target="_blank">SOAP</a> - SOAP (Short Oligonucleotide Alignment Program). A program for efficient gapped and ungapped alignment of short oligonucleotides onto reference sequences. The updated version uses a BWT. Can call SNPs and INDELs. Author is Ruiqiang Li at the Beijing Genomics Institute. C++, POSIX.<br /> * <a href="http://www.sanger.ac.uk/Software/analysis/SSAHA/" target="_blank">SSAHA</a> - SSAHA (Sequence Search and Alignment by Hashing Algorithm) is a tool for rapidly finding near exact matches in DNA or protein databases using a hash table. Developed at the Sanger Centre by Zemin Ning, Anthony Cox and James Mullikin. C++ for Linux/Alpha.<br /> * <a href="http://socs.biology.gatech.edu/" target="_blank">SOCS</a> - Aligns SOLiD data. SOCS is built on an iterative variation of the Rabin-Karp string search algorithm, which uses hashing to reduce the set of possible matches, drastically increasing search speed. Authors are Ondov B, Varadarajan A, Passalacqua KD and Bergman NH.<br /> * <a href="http://bibiserv.techfak.uni-bielefeld.de/swift/welcome.html" target="_blank">SWIFT</a> - The SWIFT suit is a software collection for fast index-based sequence comparison. It contains: SWIFT &mdash; fast local alignment search, guaranteeing to find epsilon-matches between two sequences. SWIFT BALSAM &mdash; a very fast program to find semiglobal non-gapped alignments based on k-mer seeds. Authors are Kim Rasmussen (SWIFT) and Wolfgang Gerlach (SWIFT BALSAM)<br /> * <a href="http://synasite.mgrc.com.my:8080/sxog/NewSXOligoSearch.php" target="_blank">SXOligoSearch</a> - SXOligoSearch is a commercial platform offered by the Malaysian based <a href="http://www.synamatix.com/" target="_blank">Synamatix</a>. Will align Illumina reads against a range of Refseq RNA or NCBI genome builds for a number of organisms. Web Portal. OS independent.<br /> * <a href="http://www.vmatch.de/" target="_blank">Vmatch</a> - A versatile software tool for efficiently solving large scale sequence matching tasks. Vmatch subsumes the software tool REPuter, but is much more general, with a very flexible user interface, and improved space and time requirements. Essentially a large string matching toolbox. POSIX.<br /> * <a href="http://www.bioinformaticssolutions.com/products/zoom/index.php" target="_blank">Zoom</a> - ZOOM (Zillions Of Oligos Mapped) is designed to map millions of short reads, emerged by next-generation sequencing technology, back to the reference genomes, and carry out post-analysis. ZOOM is developed to be highly accurate, flexible, and user-friendly with speed being a critical priority. Commercial. Supports Illumina and SOLiD data.<br /> <br /> <strong><em>De novo</em> Align/Assemble</strong><br /> * <a href="http://www.bcgsc.ca/platform/bioinfo/software/abyss" target="_blank">ABySS</a> - Assembly By Short Sequences. ABySS is a de novo sequence assembler that is designed for very short reads. The single-processor version is useful for assembling genomes up to 40-50 Mbases in size. The parallel version is implemented using MPI and is capable of assembling larger genomes. By Simpson JT and others at the Canada's Michael Smith Genome Sciences Centre. C++ as source. <br /> * <a href="http://www.broad.mit.edu/science/programs/genome-biology/computational-rd/computational-research-and-development" target="_blank">ALLPATHS</a> - ALLPATHS: De novo assembly of whole-genome shotgun microreads. ALLPATHS is a whole genome shotgun assembler that can generate high quality assemblies from short reads. Assemblies are presented in a graph form that retains ambiguities, such as those arising from polymorphism, thereby providing information that has been absent from previous genome assemblies. Broad Institute.<br /> * <a href="http://www.genomic.ch/edena.php" target="_blank">Edena</a> - Edena (Exact DE Novo Assembler) is an assembler dedicated to process the millions of very short reads produced by the Illumina Genome Analyzer. Edena is based on the traditional overlap layout paradigm. By D. Hernandez, P. Fran&ccedil;ois, L. Farinelli, M. Osteras, and J. Schrenzel. Linux/Win.<br /> * <a href="http://euler-assembler.ucsd.edu/portal/" target="_blank">EULER-SR</a> - Short read <em>de novo</em> assembly. By Mark J. Chaisson and Pavel A. Pevzner from UCSD (published in Genome Research). Uses a de Bruijn graph approach.<br /> * <a href="http://chevreux.org/projects_mira.html" target="_blank">MIRA2</a> - MIRA (Mimicking Intelligent Read Assembly) is able to perform true hybrid de-novo assemblies using reads gathered through 454 sequencing technology (GS20 or GS FLX). Compatible with 454, Solexa and Sanger data. Linux OS required.<br /> * <a href="http://www.seqan.de/projects/consensus.html" target="_blank">SEQAN</a> - A Consistency-based Consensus Algorithm for De Novo and Reference-guided Sequence Assembly of Short Reads. By Tobias Rausch and others. C++, Linux/Win.<br /> * <a href="http://sharcgs.molgen.mpg.de/" target="_blank">SHARCGS</a> - De novo assembly of short reads. Authors are Dohm JC, Lottaz C, Borodina T and Himmelbauer H. from the Max-Planck-Institute for Molecular Genetics.<br /> * <a href="http://www.bcgsc.ca/platform/bioinfo/software/ssake" target="_blank">SSAKE</a> - The Short Sequence Assembly by K-mer search and 3' read Extension (SSAKE) is a genomics application for aggressively assembling millions of short nucleotide sequences by progressively searching for perfect 3'-most k-mers using a DNA prefix tree. Authors are Ren&eacute; Warren, Granger Sutton, Steven Jones and Robert Holt from the Canada's Michael Smith Genome Sciences Centre. Perl/Linux.<br /> * <a href="http://soap.genomics.org.cn/" target="_blank">SOAPdenovo</a> - Part of the SOAP suite. See above. <br /> * <a href="https://sourceforge.net/projects/vcake" target="_blank">VCAKE</a> - De novo assembly of short reads with robust error correction. An improvement on early versions of SSAKE.<br /> * <a href="http://www.ebi.ac.uk/%7Ezerbino/velvet/" target="_blank">Velvet</a> - Velvet is a de novo genomic assembler specially designed for short read sequencing technologies, such as Solexa or 454. Need about 20-25X coverage and paired reads. Developed by Daniel Zerbino and Ewan Birney at the European Bioinformatics Institute (EMBL-EBI). <br /> <br /> <strong>SNP/Indel Discovery</strong><br /> * <a href="http://www.sanger.ac.uk/Software/analysis/ssahaSNP/" target="_blank">ssahaSNP</a> - ssahaSNP is a polymorphism detection tool. It detects homozygous SNPs and indels by aligning shotgun reads to the finished genome sequence. Highly repetitive elements are filtered out by ignoring those kmer words with high occurrence numbers. More tuned for ABI Sanger reads. Developers are Adam Spargo and Zemin Ning from the Sanger Centre. Compaq Alpha, Linux-64, Linux-32, Solaris and Mac<br /> * <a href="http://bioinformatics.bc.edu/marthlab/PbShort" target="_blank">PolyBayesShort</a> - A re-incarnation of the PolyBayes SNP discovery tool developed by Gabor Marth at Washington University. This version is specifically optimized for the analysis of large numbers (millions) of high-throughput next-generation sequencer reads, aligned to whole chromosomes of model organism or mammalian genomes. Developers at Boston College. Linux-64 and Linux-32.<br /> * <a href="http://bioinformatics.bc.edu/marthlab/PyroBayes" target="_blank">PyroBayes</a> - PyroBayes is a novel base caller for pyrosequences from the 454 Life Sciences sequencing machines. It was designed to assign more accurate base quality estimates to the 454 pyrosequences. Developers at Boston College. <br /> <br /> <strong>Genome Annotation/Genome Browser/Alignment Viewer/Assembly Database</strong><br /> * <a href="http://bioinformatics.bc.edu/marthlab/EagleView" target="_blank">EagleView</a> - An information-rich genome assembler viewer. EagleView can display a dozen different types of information including base quality and flowgram signal. Developers at Boston College.<br /> * <a href="http://www.sanger.ac.uk/Software/analysis/lookseq/" target="_blank">LookSeq</a> - LookSeq is a web-based application for alignment visualization, browsing and analysis of genome sequence data. LookSeq supports multiple sequencing technologies, alignment sources, and viewing modes; low or high-depth read pileups; and easy visualization of putative single nucleotide and structural variation. From the Sanger Centre.<br /> * <a href="http://evolution.sysu.edu.cn/mapview/" target="_blank">MapView</a> - MapView: visualization of short reads alignment on desktop computer. From the Evolutionary Genomics Lab at Sun-Yat Sen University, China. Linux.<br /> * <a href="http://www.bcgsc.ca/platform/bioinfo/software/sam" target="_blank">SAM</a> - Sequence Assembly Manager. Whole Genome Assembly (WGA) Management and Visualization Tool. It provides a generic platform for manipulating, analyzing and viewing WGA data, regardless of input type. Developers are Rene Warren, Yaron Butterfield, Asim Siddiqui and Steven Jones at Canada's Michael Smith Genome Sciences Centre. MySQL backend and Perl-CGI web-based frontend/Linux. <br /> * <a href="http://staden.sourceforge.net/" target="_blank">STADEN</a> - Includes GAP4. GAP5 once completed will handle next-gen sequencing data. A partially implemented test version is available <a href="https://sourceforge.net/project/show...kage_id=256957" target="_blank">here</a><br /> * <a href="http://www.bcgsc.ca/platform/bioinfo/software/xmatchview" target="_blank">XMatchView</a> - A visual tool for analyzing cross_match alignments. Developed by Rene Warren and Steven Jones at Canada's Michael Smith Genome Sciences Centre. Python/Win or Linux.<br /> <br /> <strong>Counting e.g. CHiP-Seq, Bis-Seq, CNV-Seq</strong><br /> * <a href="http://epigenomics.mcdb.ucla.edu/BS-Seq/download.html" target="_blank">BS-Seq</a> - The source code and data for the "Shotgun Bisulphite Sequencing of the Arabidopsis Genome Reveals DNA Methylation Patterning" Nature paper by <a href="http://www.ncbi.nlm.nih.gov/sites/entrez?holding=&amp;db=pubmed&amp;cmd=search&amp;term=Shotgun%20Bisulphite%20Sequencing" target="_blank">Cokus et al.</a> (Steve Jacobsen's lab at UCLA). POSIX.<br /> * <a href="http://woldlab.caltech.edu/chipseq/" target="_blank">CHiPSeq</a> - Program used by Johnson et al. (2007) in their Science publication<br /> * <a href="http://tiger.dbs.nus.edu.sg/cnv-seq/" target="_blank">CNV-Seq</a> - CNV-seq, a new method to detect copy number variation using high-throughput sequencing. Chao Xie and Martti T Tammi at the National University of Singapore. Perl/R.<br /> * <a href="http://www.bcgsc.ca/platform/bioinfo/software/findpeaks" target="_blank">FindPeaks</a> - perform analysis of ChIP-Seq experiments. It uses a naive algorithm for identifying regions of high coverage, which represent Chromatin Immunoprecipitation enrichment of sequence fragments, indicating the location of a bound protein of interest. Original algorithm by Matthew Bainbridge, in collaboration with Gordon Robertson. Current code and implementation by Anthony Fejes. Authors are from the Canada's Michael Smith Genome Sciences Centre. JAVA/OS independent. Latest versions available as part of the <a href="http://vancouvershortr.sourceforge.net/" target="_blank">Vancouver Short Read Analysis Package</a><br /> * <a href="http://liulab.dfci.harvard.edu/MACS/" target="_blank">MACS</a> - Model-based Analysis for ChIP-Seq. MACS empirically models the length of the sequenced ChIP fragments, which tends to be shorter than sonication or library construction size estimates, and uses it to improve the spatial resolution of predicted binding sites. MACS also uses a dynamic Poisson distribution to effectively capture local biases in the genome sequence, allowing for more sensitive and robust prediction. Written by Yong Zhang and Tao Liu from Xiaole Shirley Liu's Lab. <br /> * <a href="http://www.gersteinlab.org/proj/PeakSeq/" target="_blank">PeakSeq</a> - PeakSeq: Systematic Scoring of ChIP-Seq Experiments Relative to Controls. a two-pass approach for scoring ChIP-Seq data relative to controls. The first pass identifies putative binding sites and compensates for variation in the mappability of sequences across the genome. The second pass filters out sites that are not significantly enriched compared to the normalized input DNA and computes a precise enrichment and significance. By Rozowsky J et al. C/Perl.<br /> * <a href="http://mendel.stanford.edu/sidowlab/downloads/quest/" target="_blank">QuEST</a> - Quantitative Enrichment of Sequence Tags. Sidow and Myers Labs at Stanford. From the 2008 publication <a href="http://www.ncbi.nlm.nih.gov/pubmed/18711362" target="_blank">Genome-wide analysis of transcription factor binding sites based on ChIP-Seq data</a>. (C++)<br /> * <a href="http://dir.nhlbi.nih.gov/papers/lmi/epigenomes/sissrs/" target="_blank">SISSRs</a> - Site Identification from Short Sequence Reads. BED file input. Raja Jothi @ NIH. Perl.<br /> **See also <a href="http://seqanswers.com/forums/showthread.php?t=742" target="_blank">this thread</a> for ChIP-Seq, until I get time to update this list.<br /> <br /> <strong>Alternate Base Calling</strong><br /> * <a href="http://svitsrv25.epfl.ch/R-doc/library/Rolexa/html/00Index.html" target="_blank">Rolexa</a> - R-based framework for base calling of Solexa data. Project <a href="http://www.biomedcentral.com/1471-2105/9/431" target="_blank">publication</a><br /> * <a href="http://hannonlab.cshl.edu/Alta-Cyclic/main.html" target="_blank">Alta-cyclic</a> - "a novel Illumina Genome-Analyzer (Solexa) base caller"<br /> <br /> <strong>Transcriptomics</strong><br /> * <a href="http://woldlab.caltech.edu/rnaseq/" target="_blank">ERANGE</a> - Mapping and Quantifying Mammalian Transcriptomes by RNA-Seq. Supports Bowtie, BLAT and ELAND. From the Wold lab.<br /> * <a href="http://www.genoscope.cns.fr/externe/gmorse/" target="_blank">G-Mo.R-Se</a> - G-Mo.R-Se is a method aimed at using RNA-Seq short reads to build de novo gene models. First, candidate exons are built directly from the positions of the reads mapped on the genome (without any ab initio assembly of the reads), and all the possible splice junctions between those exons are tested against unmapped reads. From CNS in France.<br /> * <a href="http://evolution.sysu.edu.cn/english/software/mapnext.htm" target="_blank">MapNext</a> - MapNext: A software tool for spliced and unspliced alignments and SNP detection of short sequence reads. From the Evolutionary Genomics Lab at Sun-Yat Sen University, China.<br /> * <a href="http://www.fml.tuebingen.mpg.de/raetsch/suppl/qpalma" target="_blank">QPalma</a> - Optimal Spliced Alignments of Short Sequence Reads. Authors are Fabio De Bona, Stephan Ossowski, Korbinian Schneeberger, and Gunnar R&auml;tsch. A paper is <a href="http://www.fml.tuebingen.mpg.de/raetsch/suppl/qpalma/qpalma-final.pdf" target="_blank">available</a>.<br /> * <a href="http://biogibbs.stanford.edu/%7Ejiangh/rsat/" target="_blank">RSAT</a> - RSAT: RNA-Seq Analysis Tools. RNASAT is developed and maintained by Hui Jiang at Stanford University.<br /> * <a href="http://tophat.cbcb.umd.edu/" target="_blank">TopHat</a> - TopHat is a fast splice junction mapper for RNA-Seq reads. It aligns RNA-Seq reads to mammalian-sized genomes using the ultra high-throughput short read aligner Bowtie, and then analyzes the mapping results to identify splice junctions between exons. TopHat is a collaborative effort between the University of Maryland and the University of California, Berkeley</p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26303/maker</guid>
	<pubDate>Sun, 07 Feb 2016 15:59:24 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26303/maker</link>
	<title><![CDATA[MAKER]]></title>
	<description><![CDATA[<p>MAKER is a portable and easily configurable genome annotation pipeline.Its purpose is to allow smaller eukaryotic and prokaryotic genome projects to independently annotate their genomes and to create genome databases. MAKER identifies repeats, aligns ESTs and proteins to a genome, produces ab-initio gene predictions and automatically synthesizes these data into gene annotations having evidence-based quality values.</p>
<p>More at http://www.yandell-lab.org/software/maker.html</p><p>Address of the bookmark: <a href="http://www.yandell-lab.org/software/maker.html" rel="nofollow">http://www.yandell-lab.org/software/maker.html</a></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27331/andi</guid>
	<pubDate>Fri, 13 May 2016 05:16:35 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27331/andi</link>
	<title><![CDATA[Andi]]></title>
	<description><![CDATA[<p>This is the <code>andi</code> program for estimating the evolutionary distance between closely related genomes. These distances can be used to rapidly infer phylogenies for big sets of genomes. Because <code>andi</code> does not compute full alignments, it is so efficient that it scales even up to thousands of bacterial genomes.</p>
<p>This readme covers all necessary instructions for the impatient to get <code>andi</code> up and running. For extensive instructions please consult the <a href="https://github.com/EvolBioInf/andi/blob/master/andi-manual.pdf">manual</a>.</p>
<p>More at https://github.com/evolbioinf/andi/</p><p>Address of the bookmark: <a href="http://bioinformatics.oxfordjournals.org/content/early/2015/01/13/bioinformatics.btu815.full" rel="nofollow">http://bioinformatics.oxfordjournals.org/content/early/2015/01/13/bioinformatics.btu815.full</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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