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http://www.nitrc.org/projects/xnat_extras
User software contributions for XNAT - The Extensible Neuroimaging Archive Toolkit, http://www.xnat.org
Proper citation: XNAT Extras (RRID:SCR_004759) Copy
http://www.cbcb.umd.edu/software/phymm/
Software for Phylogenetic Classification of Metagenomic Data with Interpolated Markov Models to taxonomically classify DNA sequences and accurately classify reads as short as 100 bp. PhymmBL, the hybrid classifier included in this distribution which combines analysis from both Phymm and BLAST, produces even higher accuracy.
Proper citation: Phymm and PhymmBL (RRID:SCR_004751) Copy
https://code.google.com/p/destruct/
A software tool for identifying structural variation in tumour genomes from whole genome illumina sequencing.
Proper citation: deStruct (RRID:SCR_004747) Copy
Public research university in Iowa City, Iowa. Founded in 1847, it is the oldest and the second-largest university in the state.
Proper citation: University of Iowa; Iowa; USA (RRID:SCR_005011) Copy
http://pythia.sourceforge.net/
Pythia is an open source thermodynamically oriented primer design python module. Pythia can be used in two ways. 1. Executable binaries only: under windows with cygwin and python 2.5 (built with mingw, that comes with the cygwin release). These executables allow the user to index DNA files for primer specificity search, design one primer pair per region, and tile regions with PCR amplicons. 2. A python module: under windows with cygwin, python2.5, numpy, swig, and mingw, or under linux with python2.4 or later, numpy, and swig (everything but numpy should be pre-installed on a normal linux system). The module gets you everything that the binaries get you, in a more pythonic framework. This package also includes modules for computing DNA binding and folding energies using the partition function approach with publicly available thermodynamic data. Usage documentation is in the downloads.
Proper citation: Pythia (RRID:SCR_004952) Copy
http://bioinformatics.rutgers.edu/Software/SLiQ/
Software for simple linear inequalities based Mate-Pair reads filtering and scaffolding. A set of simple linear inequalities (SLIQ) derived from the geometry of contigs on the line that can be used to predict the relative positions and orientations of contigs from individual mate pair reads and thus produce a contig digraph. The SLIQ inequalities can also filter out unreliable mate pairs and can be used as a pre-processing step for any scaffolding algorithm. This tool filters mate pairs and then produces a Directed Contig Graph (contig diGraph). Also provided is a Naive scaffolder that can then produce scaffolds out of the contig diGraph.
Proper citation: SLIQ (RRID:SCR_005003) Copy
http://cortexassembler.sourceforge.net/index_cortex_var.html
A tool for genome assembly and variation analysis from sequence data. You can use it to discover and genotype variants on single or multiple haploid or diploid samples. If you have multiple samples, you can use Cortex to look specifically for variants that distinguish one set of samples (eg phenotype=X, cases, parents, tumour) from another set of samples (eg phenotype=Y, controls, child, normal). cortex_var features * Variant discovery by de novo assembly - no reference genome required * Supports multicoloured de Bruijn graphs - have multiple samples loaded into the same graph in different colours, and find variants that distinguish them. * Capable of calling SNPs, indels, inversions, complex variants, small haplotypes * Extremely accurate variant calling - see our paper for base-pair-resolution validation of entire alleles (rather than just breakpoints) of SNPs, indels and complex variants by comparison with fully sequenced (and finished) fosmids - a level of validation beyond that demanded of any other variant caller we are aware of - currently cortex_var is the most accurate variant caller for indels and complex variants. * Capable of aligning a reference genome to a graph and using that to call variants * Support for comparing cases/controls or phenotyped strains * Typical memory use: 1 high coverage human in under 80Gb of RAM, 1000 yeasts in under 64Gb RAM, 10 humans in under 256 Gb RAM
Proper citation: cortex var (RRID:SCR_005081) Copy
http://www.appliedbiosystems.com/absite/us/en/home.html
An Antibody supplier
Proper citation: Applied Biosystems (RRID:SCR_005039) Copy
http://www.physics.rutgers.edu/~anirvans/SOPRA/
Software tool to exploit the mate pair/paired-end information for assembly of short reads from high throughput sequencing platforms, e.g. Illumina and SOLiD.
Proper citation: SOPRA (RRID:SCR_005035) Copy
An Antibody supplier
Proper citation: Bioworld Technology (RRID:SCR_005036) Copy
http://www.baseclear.com/landingpages/basetools-a-wide-range-of-bioinformatics-solutions/sspacev12/
A stand-alone software program for scaffolding pre-assembled contigs using paired-read data. Main features are: a short runtime, multiple library input of paired-end and/or mate pair datasets and possible contig extension with unmapped sequence reads.
Proper citation: SSPACE (RRID:SCR_005056) Copy
http://meringlab.org/software/hpc-clust/
A set of tools designed to cluster large numbers (>1 million) of pre-aligned nucleotide sequences. It performs the clustering of sequences using the Hierarchical Clustering Algorithm (HCA). There are currently three different cluster metrics implemented: single-linkage, complete-linkage, and average-linkage. In addition, there are currently four sequence distance functions implemented, these are: identity (gap-gap counting as match), nogap (gap-gap being ignored), nogap-single (like nogap, but consecutive gap-nogap''s count as a single mismatch), tamura (distance is calculated with the knowledge that transitions are more likely than transversions). One advantage that HCA has over other algorithms is that instead of producing only the clustering at a given threshold, it produces the set of merges occuring at each threshold. With this approach, the clusters can afterwards very quickly be reported for every arbitrary threshold with little extra computation. This approach also allows the plotting of the variation of number of clusters with clustering threshold without requiring the clustering to be run for each threshold independently. Another feature of the way HPC-CLUST is implemented is that the single-, complete-, and average-linkage clusterings can be computed in a single run with little overhead.
Proper citation: HPC-CLUST (RRID:SCR_005052) Copy
Public research university in Manchester, England, formed in 2004 by merger of University of Manchester Institute of Science and Technology and Victoria University of Manchester. Second largest university in United Kingdom by enrollment.
Proper citation: University of Manchester; Manchester; United Kingdom (RRID:SCR_004996) Copy
Commercial supplier and developer of in vivo antibodies. Provides antibodies and antibody production services.
Proper citation: Bio X Cell (RRID:SCR_004997) Copy
http://plaza.ufl.edu/sunyijun/ES-Tree.htm
Software for hierarchical Clustering Analysis of Millions of 16S rRNA Pyrosequences in Quasi-linear Time.
Proper citation: ESPRIT-Tree (RRID:SCR_005045) Copy
http://cran.r-project.org/web/packages/MBCluster.Seq/index.html
Software to cluster genes based on Poisson or Negative-Binomial model for RNA-Seq or other digital gene expression (DGE) data.
Proper citation: MBCluster.Seq (RRID:SCR_005079) Copy
http://www.biomedcentral.com/1471-2105/13/189
An algorithm to use optical map information directly within the de Bruijn graph framework to help produce an accurate assembly of a genome that is consistent with the optical map information provided. AGORA takes as input two data structures: OpMap ? an ordered list of fragment sizes representing the optical map; and Edges ? a list of de Bruijn graph edges with their corresponding sequences.
Proper citation: AGORA (RRID:SCR_005070) Copy
https://github.com/AlexeyG/GRASS
A generic algorithm for scaffolding next-generation sequencing assemblies.
Proper citation: GRASS (RRID:SCR_005071) Copy
http://www.bioinf.boku.ac.at/pub/MapAl/
A software tool for RNA-Seq expression profiling that builds on the established programs Bowtie and Cufflinks. Allowing an incorporation of ''gene models'' already at the alignment stage almost doubles the number of transcripts that can be measured reliably.
Proper citation: MapAl (RRID:SCR_004938) Copy
Public research university and the largest university in the UK for undergraduate education. The majority of the OU's undergraduate students are based in the United Kingdom and principally study off-campus; many of its courses can also be studied anywhere in the world.
Proper citation: Open University; Milton Keynes; United Kingdom (RRID:SCR_004931) Copy
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