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https://code.google.com/p/simrare/

A stand-alone executable software with user-friendly graphical interface implemented in Python/C++ for rare variant association studies. It is designed as a unified simulation framework to provide an unbiased and easy manner to evaluate association methods, including novel methods, under a broad range of choice of biological contexts. It consists of three modules, variant data simulator, genotype/phenotype generator and association method evaluator. SimRare generates variant data for gene regions using forward-time simulation which incorporates realistic population demographic and evolutionary scenarios. For phenotype data it is capable of generating both case-control and quantitative traits. The phenotypic effects of variants can be detrimental, protective or non-causal. SimRare has a graphical user interface which allows for easy entry of genetic and phenotypic parameters. Simulated data can be written into external files in a standard format. For novel association method implemented in R it can be imported into SimRare, which has been equipped built in functions to evaluate performance of new method and visually compare it with currently available ones in an unbiased manner.

Proper citation: SimRare (RRID:SCR_005226) Copy   

•   Source: SciCrunch Registry

http://www.broadinstitute.org/gatk/gatkdocs/org_broadinstitute_sting_gatk_walkers_indels_SomaticIndelDetector.html

Tool for calling indels in Tumor-Normal paired sample mode.

Proper citation: SomaticIndelDetector (RRID:SCR_005107) Copy   

•   Source: SciCrunch Registry

http://code.google.com/p/comrad/

A novel algorithmic framework for the integrated analysis of RNA-Seq and Whole Genome Shotgun Sequencing (WGSS) data for the purposes of discovering genomic rearrangements and aberrant transcripts. The Comrad framework leverages the advantages of both RNA-Seq and WGSS data, providing accurate classification of rearrangements as expressed or not expressed and accurate classification of the genomic or non-genomic origin of aberrant transcripts. A major benefit of Comrad is its ability to accurately identify aberrant transcripts and associated rearrangements using low coverage genome data. As a result, a Comrad analysis can be performed at a cost comparable to that of two RNA-Seq experiments, significantly lower than an analysis requiring high coverage genome data.

Proper citation: comrad (RRID:SCR_005101) Copy   

•   Source: SciCrunch Registry

http://service.iris.edu/fdsnws/dataselect/1/

Web service to access seismic time-series data for specified channels and time ranges that are selected using SEED time series identifiers (network, station, location & channel). Data are returned in miniSEED format. This service is an implementation of the International Federation of Digital Seismograph Networks (FDSN) web service specification version 1.

Proper citation: IRIS DMC FDSNWS dataselect Web Service (RRID:SCR_005103) Copy   

•   Source: SciCrunch Registry

http://biohaskell.org/Applications/FlowSim

A suite of tools for simulating the 454 pyrosequencing process. It is based on the characteristics of real 454 data, and attempts to model the known aspects of the process.

Proper citation: FlowSim (RRID:SCR_005224) Copy   

•   Source: SciCrunch Registry

http://phast.wishartlab.com/

A web server designed to rapidly and accurately identify, annotate and graphically display prophage sequences within bacterial genomes or plasmids. It accepts either raw DNA sequence data or partially annotated GenBank formatted data and rapidly performs a number of database comparisons as well as phage cornerstone feature identification steps to locate, annotate and display prophage sequences and prophage features. Relative to other prophage identification tools, PHAST is up to 40 times faster and up to 15% more sensitive. It is also able to process and annotate both raw DNA sequence data and Genbank files, provide richly annotated tables on prophage features and prophage quality and distinguish between intact and incomplete prophage. PHAST also generates downloadable, high quality, interactive graphics that display all identified prophage components in both circular and linear genomic views. Databases available for download include Virus DB, Prophage and virus DB, Bacteria DB, and PHAST result DB. Pre-calculated genomes for viewing are also available.

Proper citation: PHAge Search Tool (RRID:SCR_005184) Copy   

•   Source: SciCrunch Registry

http://code.google.com/p/snpdat/

A simple and easy to use high through-put analysis tool which can provide comprehensive annotation of both novel and known single nucleotide polymorphisms (SNPs) for any organism with a draft sequence and annotation. SNPdat makes possible analyses involving non-model organisms that are not supported by the vast majority of SNP annotation tools currently available. It is especially intended for use by researchers with limited bioinformatic experience.

Proper citation: SNPdat (RRID:SCR_005187) Copy   

•   Source: SciCrunch Registry

https://github.com/ruping/Breakpointer

A fast tool for locating sequence breakpoints from the alignment of single end reads (SE) produced by next generation sequencing (NGS). It adopts a heuristic method in searching for local mapping signatures created by insertion/deletions (indels) or more complex structural variants(SVs). With current NGS single-end sequencing data, the output regions by Breakpoint mainly contain the approximate breakpoints of indels and a limited number of large SVs. Notably, Breakpointer can uncover breakpoints of insertions which are longer than the read length. Breakpointer also can find breakpoints of many variants located in repetitive regions. The regions can be used not only as a extra support for SV predictions by other tools (such as by split-read method), but also can serve as a database for searching variants which might be missed by other tools. Breakpointer is a command line tool that runs under linux system. Breakpointer takes advanage of two local mapping features of single-end reads as a consequence of indel/SVs: 1) non-uniform read distribution (depth skewness) and 2) misalignments at the boundaries of indel/SVs. These features are summarized as breakpoint signature. Breakpointer proceeds in three stages in capturing this signature. It is implemented in C++ and perl. Input is the file or files containing alignments of single-end reads against a reference genome (in .BAM format). Output is the predicted regions containing potential breakpoints of SVs (in .GFF format). To be able to read in .BAM files, Breakpointer requires bamtools API, which users should install beforehand.

Proper citation: Breakpointer (RRID:SCR_005254) Copy   

•   Source: SciCrunch Registry

https://code.google.com/p/clever-sv/

A collection of tools to discover and genotype structural variations in genomes from paired-end sequencing reads. The main software is written in C++ with some auxiliary scripts in Python.

Proper citation: CLEVER Toolkit (RRID:SCR_005255) Copy   

•   Source: SciCrunch Registry

https://code.google.com/p/clippers/

A software program designed to identify long deletions of a genome as well as the RNA splicings using long Illumina reads. Currently, Clippers is implemented for long reads Illumina, ex: 75bp or 100bp, allowing mismatches and a single deletion/splicing. Clippers is a sister tool of PerM, our short reads aligner. Users are strongly suggested to use PerM to initially mapped reads and identify the deletion/splicing with the initially unmapped reads. We plan to extend it to ABI SOLiD reads in the near future. Clippers outputs gap-alignments in SAM format. You can use SAMtools or other program to interpret the deletion/splicing. The input files are a reference in fasta format and the reads is in fasta or fastq format.

Proper citation: Clippers (RRID:SCR_005256) Copy   

•   Source: SciCrunch Registry

http://sv.gersteinlab.org/age/

A tool that implements an algorithm for optimal alignment of sequences with Structural Variations (SVs).

Proper citation: AGE (RRID:SCR_005253) Copy   

•   Source: SciCrunch Registry

http://vivoweb.org/

Open source semantic web application that enables the discovery of research and scholarship across disciplines at a particular institution and across institutions by creating a semantic cloud of information that can be searched and browsed. Participants include institutions with local installations of VIVO or those with research discovery and profiling applications that can provide semantic web-compliant data. The information accessible through the national network''''s search and browse capability will therefore reside and be controlled locally within institutional VIVOs or other semantic web applications. The VIVO ontology provides a set of types (classes) and relationships (properties) to represent researchers and the full context of their experience, outputs, interests, accomplishments, and associated institutions. https://wiki.duraspace.org/display/VIVO/VIVO-ISF+Ontology VIVO is populated with detailed profiles of faculty and researchers including information such as publications, teaching, service, and professional affiliations. It also supports browsing and a search function which returns faceted results for rapid retrieval of desired information. The rich semantically structured data in VIVO support and facilitate research discovery. Examples of applications that consume these rich data include: visualizations, enhanced multi-site search through VIVO Search, and applications such as VIVO Searchlight, a browser bookmarklet which uses text content of any webpage to search for relevant VIVO profiles, and the Inter-Institutional Collaboration Explorer, an application which allows visualization of collaborative institutional partners, among others. Institutions are free to participate in the national network by installing and using the application. The application provides linked data via RDF data making users a part of the semantic web! or any other application that provides linked data can be used. Users can also get involved with developing applications that provide enhanced search, new collaboration capabilities, grouping, finding and mapping scientists and their work.

Proper citation: VIVO (RRID:SCR_005246) Copy   

•   Source: SciCrunch Registry

http://fcon_1000.projects.nitrc.org/fcpClassic/FcpTable.html

1200+ ''resting state'' functional MRI (R-fMRI) datasets independently collected at 33 sites and donated by the principal investigators for the purpose of providing the broader imaging community complete access to a large-scale functional imaging dataset. Age, sex and imaging center information are provided for each of the datasets. In accordance with HIPAA guidelines, all datasets are anonymous, with no protected health information included. We anticipate this data-sharing effort will equip researchers with a means of exploring and refining R-fMRI approaches, and facilitate the growing ethos of sharing and collaboration. Disclaimer: The ''1000 Functional Connectomes Project'' datasets are provided freely without assurance of quality or appropriateness for usage.

Proper citation: FCP Classic Data Sharing Samples (RRID:SCR_005362) Copy   

•   Source: SciCrunch Registry

http://www.ebi.ac.uk/Rebholz-srv/ebimed/

A web application that combines Information Retrieval and Extraction from Medline. EBIMed finds Medline abstracts in the same way PubMed does. Then it goes a step beyond and analyses them to offer a complete overview on associations between UniProt protein/gene names, GO annotations, Drugs and Species. The results are shown in a table that displays all the associations and links to the sentences that support them and to the original abstracts. By selecting relevant sentences and highlighting the biomedical terminology EBIMed enhances your ability to acquire knowledge, relate facts, discover implications and, overall, have a good overview economizing the effort in reading.

Proper citation: EBIMed (RRID:SCR_005314) Copy   

•   Source: SciCrunch Registry

http://www.axa-research.org/

The core mission of the AXA Research Fund is to finance basic research contributing to understand and prevent risks. We support innovative and cutting-edge projects within three areas: environmental, life, and socio-economic risks. Only research institutions may submit applications. * Funding for research projects, postdoc and graduate fellowships, and long and short term projects * Encourages international applicants and research around the world Research projects funded by the Fund must fall within the scope of one of the themes identified by the AXA Scientific Board. The themes for 2011 are identified below: * Life risks ** Aging & Long-term care ** Biomedical risks ** Addictions and risky behaviors * Socio-economic risks ** Geopolitical risks ** Macroeconomic and financial systemic risks ** Individual and collective behaviors when facing uncertainties ** Large corporate risks * Environmental risks ** Climate change ** Natural hazards ** Human driven environmental changes

Proper citation: AXA Research Fund (RRID:SCR_005276) Copy   

•   Source: SciCrunch Registry

http://www.neuron.yale.edu

NEURON is a simulation environment for modeling individual neurons and networks of neurons. It provides tools for conveniently building, managing, and using models in a way that is numerically sound and computationally efficient. It is particularly well-suited to problems that are closely linked to experimental data, especially those that involve cells with complex anatomical and biophysical properties. NEURON has benefited from judicious revision and selective enhancement, guided by feedback from the growing number of neuroscientists who have used it to incorporate empirically-based modeling into their research strategies. NEURON's computational engine employs special algorithms that achieve high efficiency by exploiting the structure of the equations that describe neuronal properties. It has functions that are tailored for conveniently controlling simulations, and presenting the results of real neurophysiological problems graphically in ways that are quickly and intuitively grasped. Instead of forcing users to reformulate their conceptual models to fit the requirements of a general purpose simulator, NEURON is designed to let them deal directly with familiar neuroscience concepts. Consequently, users can think in terms of the biophysical properties of membrane and cytoplasm, the branched architecture of neurons, and the effects of synaptic communication between cells. * helps users focus on important biological issues rather than purely computational concerns * has a convenient user interface * has a user-extendable library of biophysical mechanisms * has many enhancements for efficient network modeling * offers customizable initialization and simulation flow control * is widely used in neuroscience research by experimentalists and theoreticians * is well-documented and actively supported * is free, open source, and runs on (almost) everything

Proper citation: NEURON (RRID:SCR_005393) Copy   

•   Source: SciCrunch Registry

http://www.genoscope.cns.fr/externe/gmorse/

Software 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 : the testing of junctions is directed by the information available in the RNA-Seq dataset rather than a priori knowledge about the genome. Exons can thus be chained into stranded gene models.

Proper citation: G-Mo.R-Se (RRID:SCR_005273) Copy   

•   Source: SciCrunch Registry

http://cistrome.org/BETA/

A software package that integrates ChIP-seq of transcription factors or chromatin regulators with differential gene expression data to infer direct target genes. BETA has three functions: (1) to predict whether the factor has activating or repressive function; (2) to infer the factor''''s target genes; and (3) to identify the motif of the factor and its collaborators which might modulate the factor''''s activating or repressive function. BETA requires ~2GB RAM and 1h for the whole procedure. BETA may run on the web server at Cistrome or may be downloaded.

Proper citation: Binding and Expression Target Analysis (RRID:SCR_005396) Copy   

•   Source: SciCrunch Registry

http://www.icn.ucl.ac.uk/motorcontrol/

Using robotic devices to investigate human motor behavior, this group develops computational models to understand the underlying control and learning processes. By simulating novel objects or dynamic environments they study how the brain recalibrates well-learned motor skills or acquires new ones. These insights are used to design fMRI studies to investigate how these processes map onto the brain. They have developed a number of novel techniques of how to study motor control in the MRI environment, and how to analyze MRI data of the human cerebellum. They also study patients with stroke or neurological disease to further determine how the brain manages to control the body.

Proper citation: UCL Motor Control Group (RRID:SCR_005271) Copy   

•   Source: SciCrunch Registry

http://bio.math.berkeley.edu/SysCall/

A logistic regression based classifier distinguishing heterozygous sites from systematic errors. Given a list of candidate heterozygous genomic locations and a sam file of sequenced reads SysCall classifies each genomic location as either a heterozygous site or a systematic error and outputs according lists, along with the assigned posterior probabilities.

Proper citation: SysCall (RRID:SCR_005307) Copy   

•   Source: SciCrunch Registry