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http://www.sanger.ac.uk/science/tools/olorin

An interactive filtering tool for next generation sequencing data coming from the study of large complex disease pedigrees. It integrates gene flow output from Merlin and next generation sequencing data. Users can interactively filter and prioritize variants based on haplotype sharing across different sets of selected individuals and allele frequency in reference datasets. (entry from Genetic Analysis Software)

Proper citation: OLORIN (RRID:SCR_002015) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/nirx2nirs/

A matlab script which takes near-infrared spectroscopy data recorded by NIRx system(s) and converts it to a .nirs file format for use with the HOMER2 NIRS processing pacakge.

Proper citation: NIRx2nirs: A NIRx to .nirs data converter (RRID:SCR_002492) Copy   

•   Source: SciCrunch Registry

https://sites.pitt.edu/~weeks/docs/SimIBD.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23,2022. Software application (entry from Genetic Analysis Software)

Proper citation: SIMIBD (RRID:SCR_002094) Copy   

•   Source: SciCrunch Registry

http://gmt.genome.wustl.edu/packages/breakdancer/

A Perl/C++ software package that provides genome-wide detection of structural variants from next generation paired-end sequencing reads. BreakDancerMax predicts five types of structural variants: insertions, deletions, inversions, inter- and intra-chromosomal translocations from next-generation short paired-end sequencing reads using read pairs that are mapped with unexpected separation distances or orientation. (entry from Genetic Analysis Software)

Proper citation: BREAKDANCER (RRID:SCR_001799) Copy   

•   Source: SciCrunch Registry

http://haplopainter.sourceforge.net/

A pedigree drawing program, suitable in processing haplotype outputs from GENEHUNTER, ALLEGRO, MERLIN, and SIMWALK (entry from Genetic Analysis Software)

Proper citation: HAPLOPAINTER (RRID:SCR_001710) Copy   

•   Source: SciCrunch Registry

http://www.rightfield.org.uk/

An open-source tool for adding ontology term selection to Excel spreadsheets. It is used by a "Template Creator" to create semantically aware Excel spreadsheet templates. The Excel templates are then reused by Scientists to collect and annotate their data; without any need to understand, or even be aware of, RightField or the ontologies used. For each annotation field, RightField can specify a range of allowed terms from a chosen ontology (subclasses, individuals or combinations). The resulting spreadsheet presents these terms to the users as a simple drop-down list. This reduces the adoption barrier for using community ontologies as the annotation is made by the scientist that generated the data rather than a third party, and the annotation is collected at the time of data collection. RightField is a standalone Java application which uses Apache-POI for interacting with Microsoft documents. It enables users to import Excel spreadsheets, or generate new ones from scratch. Ontologies can either be imported from their local file systems, or from the BioPortal ontology repository. Individual cells, or whole columns or rows can be marked with the required ranges of ontology terms and an individual spreadsheet can be annotated with terms from multiple ontologies.

Proper citation: RightField (RRID:SCR_002649) Copy   

•   Source: SciCrunch Registry

https://code.google.com/p/genome-smasher/

Software repository for tools used to create diploid FASTA files with containing snps, indels, duplications, deletions, and translocations. They can be used to create artificial genomes for next-gen sequencing simulations.

Proper citation: GenomeSmasher (RRID:SCR_002406) Copy   

•   Source: SciCrunch Registry

http://sig.biostr.washington.edu/projects/wirm/

WIRM is an innovative software toolkit that allows the creation of web applications that facilitate the acquisition, integration, and dissemination of multimedia biomedical data over the web, thereby reducing the cost of knowledge sharing. WIRM reduces the complexity of building custom biomedical web applications and it's visual modeling tools enable domain experts to describe the structure of their knowledge, from which WIRM automatically generates full-featured, customizable content management systems. WIRM is a Perl-based application server that provides a high-level programming environment for developing web information systems. WIRM consists of an object-relational database and a suite of Perl interfaces for visualizing, integrating and analyzing heterogeneous multimedia data. WIRM provides facilities for creating context-sensitive views over a multimedia database, allowing developers to rapidly build dynamic web sites that adapt their content and presentation to multiple classes of end-users. WIRM was developed by Rex Jakobovits as part of his PhD dissertation at the University of Washington Computer Science department, under the guidance of Dr. James F. Brinkley of the Department of Biological Structure. The system was generalized from work funded by NIH SBIR grant R43-MH61277-01 and Human Brain Project grant DC/LM02310.

Proper citation: WIRM - Web Interfacing Repository Manager (RRID:SCR_002039) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/multimpute/

A software toolkit that performs multiple imputation for group level, single sample t-tests. Whole brain group level statistic maps from fMRI rarely cover the entire brain as a result of missing data. Missingness between subjects in fMRI datasets can result from susceptibility artifacts, bounding box (acquisition parameters), and small differences in post-normalized morphology. The toolkit consists of several interactive command line scripts that guide the user to map the spatial distribution of missing data across contrast images, calculate spatial neighborhood averages that help impute values, perform conventional and multiple imputed t-statistics, save the results to brain maps, and create result tables. The toolkit contains an instruction manual (pdf), two Matlab scripts and one R-Statistics script, which depend on functions defined in the popular SPM toolbox and functions defined in the MICE package for (R).

Proper citation: Group Level Imputation of Statistic Maps (RRID:SCR_002397) Copy   

•   Source: SciCrunch Registry

http://www.ncbi.nlm.nih.gov/CBBresearch/Schaffer/pedhunter.html

Software package that facilitates creation and verification of pedigrees within large genealogies. The pedigrees are produced as files in LINKAGE format ready for linkage analysis and for drawing with a variety of drawing programs, such as PEDDRAW and cranefoot.

Proper citation: PEDHUNTER (RRID:SCR_002031) Copy   

•   Source: SciCrunch Registry

http://www.sph.umich.edu/csg/abecasis/LAMP/

Software for linkage and association modeling in pedigrees that uses a maximum likelihood model to extract information on genetic linkage and association from samples of unrelated individuals, sib pairs, trios and larger pedigrees (Li et al, 2005; Li et al, 2006). It provides estimates of genetic model parameters and powerful tests of association in settings where population stratification is not a concern.

Proper citation: LAMP (RRID:SCR_001740) Copy   

•   Source: SciCrunch Registry

http://www.broadinstitute.org/software/syzygy/

A targeted sequencing post processing analysis software tool that allows: 1. SNP and indel detection; 2. Allele frequency estimation; 3. Single-marker association test; 4. Group-wise marker test association; 5. Experimental QC summary (%dbSNP, Ts/Tv, Ns/S); 6. Power to detect variant. (entry from Genetic Analysis Software)

Proper citation: SYZYGY (RRID:SCR_002157) Copy   

•   Source: SciCrunch Registry

http://www.ncbcs.org/biositemaps/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on April 27,2023. Biositemaps represent a mechanism for computational biologists and bio-informaticians to openly broadcast and retrieve meta-data about biomedical data, tools and services (i.e., biomedical resources) over the Internet. All Institutions with an interest in biomedical research can publish a biositemap.rdf file on their Internet site. The technology, developed by the Biositemaps Working Group of the NIH Roadmap National Centers of Biomedical Computing (NCBC), addresses (i) locating, (ii) querying, (iii) composing or combining, and (iv) mining biomedical resources. Each site which intends to contribute to the inventory instantiates a file on its Internet site biositemap.rdf which conforms to a defined RDF schema and uses concepts from the Biomedical Resource Ontology to describe the resources. Each biositemap.rdf file is simply a list of controlled metadata about resources (software tools, databases, material resources) that your organization uses or believes are important to biomedical research. The key enabling technologies are the Information Model (IM) which is the list of metadata fields about each resource (resource_name, description, contact_person, resource_type,...) and the Biomedical Resource Ontology (BRO) which is a controlled terminology for the resource_typeand which is used to improve the sensitivity and specificity of web searches. Biositemaps blend the features of Sitemaps (enabling efficient web-content exploration) and RSS Feeds (a mechanism for wide and effective news dissemination). As a hybrid between Sitemaps and RSS feeds, the Biositemap infrastructure facilitates a decentralized, portable, extensible and computationally tractable generation and consumption of meta-data about existent, revised and new resources for biomedical computation. Web browsers, crawlers and robots can discover, accumulate, process, integrate and deliver Biositemaps content to (human or machine) users in a variety of graphical, tabular, computational formats. Biositemaps content allows such web browsers to pool resource-associated metadata from disparate and diverse sites and present it to the user in an integrated fashion. The Biositemaps protocol provides clues, information and directives for all Biositemap web harvesters that point to the existence and content of such biomedical resources at different sites.

Proper citation: Biositemaps (RRID:SCR_001976) Copy   

•   Source: SciCrunch Registry

http://sccn.ucsd.edu/wiki/MPT

This toolbox is an EEGLAB plugin for performing Measure Projection Analysis. Measure Projection Analysis (MPA) is a novel probabilistic multi-subject inference method that overcomes EEG Independent Component (IC) clustering issues by abandoning the notion of distinct IC clusters. Instead, it searches voxel by voxel for brain regions having event-related IC process dynamics that exhibit statistically significant consistency across subjects and/or sessions as quantified by the values of various EEG measures. Local-mean EEG measure values are then assigned to all such locations based on a probabilistic model of IC localization error and inter-subject anatomical and functional differences.

Proper citation: Measure Projection Toolbox (RRID:SCR_002429) Copy   

•   Source: SciCrunch Registry

https://sites.google.com/a/brain.org.au/ctp/

Software package with functions that will help researchers plan how many subjects per group need to be included in an MRI-based cortical thickness study to ensure a thickness difference is detected. The package requires cortical thickness mapping and co-registration to be carried out using Freesurfer. The power analyses are implemented in the R software package., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: cortex (RRID:SCR_002467) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/ukftractography/

Software framework which uses an unscented Kalman filter for performing tractography. At each point on the fiber the most consistent direction is found as a mixture of previous estimates and of the local model. It is very easy to expand the framework and to implement new fiber representations for it. Currently it is possible to tract fibers using two different 1-, 2-, or 3-tensor methods. Both methods use a mixture of Gaussian tensors. One limits the diffusion ellipsoids to a cylindrical shape (the second and third eigenvalue are assumed to be identical) and the other one uses a full tensor representation. The project is written in C++. It could be used both as a Slicer3 module and as a standalone commandline application.

Proper citation: Diffusion Tractography with Kalman Filter (RRID:SCR_002585) Copy   

•   Source: SciCrunch Registry

http://jena.sourceforge.net/

Java framework for building Semantic Web applications, it provides a collection of tools and Java libraries to help you to develop semantic web and linked-data apps, tools and servers. It provides extensive Java libraries for helping developers develop code that handles RDF, RDFS, RDFa, OWL and SPARQL in line with published W3C recommendations. Jena includes a rule-based inference engine to perform reasoning based on OWL and RDFS ontologies, and a variety of storage strategies to store RDF triples in memory or on disk. The Jena Framework includes: * an API for reading, processing and writing RDF data in XML, N-triples and Turtle formats; * an ontology API for handling OWL and RDFS ontologies; * a rule-based inference engine for reasoning with RDF and OWL data sources; * stores to allow large numbers of RDF triples to be efficiently stored on disk; * a query engine compliant with the latest SPARQL specification * servers to allow RDF data to be published to other applications using a variety of protocols, including SPARQL In April 2012, Jena graduated from the Apache incubator process and was approved as a top-level Apache project.

Proper citation: JENA: A Semantic Web Framework for Java (RRID:SCR_001766) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/shape_mancova/

shapeAnalysisMANCOVA offers statistical shape analysis based on a parametric boundary description (SPHARM) as the point-based model computing method. The point-based models will be analyzed with the methods here proposed using multivariate analysis of covariance (MANCOVA). Here, the number of variates being tested is the dimensionality of our observations. Each point of these observations is a three dimensional displacement vector from the mean. The number of contrasts is the number of equations involved in the null-hypothesis. In order to encompass varying numbers of variates and contrasts, and to account for independent variables, a matrix computation is performed. This matrix represents the multidimensional aspects of the correlation significance and it can be transformed into a scalar measure by manipulation of its eigenvalues. Details of the methods can be found in its Insight Journal publication: http://hdl.handle.net/10380/3124

Proper citation: shapeAnalysisMANCOVA - SPHARM tools (RRID:SCR_002578) Copy   

•   Source: SciCrunch Registry

https://pydicom.github.io/

Software Python package for working with DICOM files, made for inspecting and modifying DICOM data in an easy pythonic way. The modifications can be written again to a new file. As a pure python package, it should run anywhere python runs without any other requirements.

Proper citation: pydicom (RRID:SCR_002573) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/segadapter/

An open source learning-based software that automatically learns how to transfer the output of a host segmentation tool closer to the user's manual segmentation using the image data and manual segmentation provided by the user. The motivation of this project is to bridge the gap between the segmentation tool developer and the tool users such that the existing segmentation tools can more effectively serve the community. More and more automatic segmentation tools are publicly available to today's researchers. However, when applied by their end-users, these segmentation tools usually can not achieve the performance that the tool developer reported. Discrepancies between the tool developer and its users in manual segmentation protocols and imaging modalities are the main reasons for such inconsistency.

Proper citation: Automatic Segmentation Tool Adapter (RRID:SCR_002481) Copy   

•   Source: SciCrunch Registry