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http://ibi.imim.es/osirisform.html

Software tool for the retrieval of articles from MEDLINE related to the sequence variants reported for a human gene. The variations considered are single nucleotide polymorphisms (SNPs), insertion/deletion polymorphisms (indel), microsatellite, and named variations (e.g. Alu sequences). (entry from Genetic Analysis Software), THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: OSIRIS (RRID:SCR_009313) Copy   

•   Source: SciCrunch Registry

http://csg.sph.umich.edu/boehnke/p_act.php

An R program that adjusts sets of up to 1000 p-values from association tests between correlated traits and SNPs for multiple testing, accounting for the correlation between tests. (entry from Genetic Analysis Software)

Proper citation: P ACT (RRID:SCR_009314) Copy   

•   Source: SciCrunch Registry

http://www.sanger.ac.uk/resources/software/margarita/

Software application that infers genealogies from population genotype data and uses these to map disease loci. These genealogies take the form of the Ancestral Recombination Graph (ARG). The ARG defines a genealogical tree for each locus, and as one moves along the chromosome the topologies of consecutive trees shift according to the impact of historical recombination events. (entry from Genetic Analysis Software)

Proper citation: MARGARITA (RRID:SCR_009279) Copy   

•   Source: SciCrunch Registry

http://www.dpw.wau.nl/pv/PUB/MapComp/

Software application that can be used to compare linkage maps obtained from different sources/populations/etc.. It will draw the linkage maps and look for common marker names, these are then connected in the drawing with dashed lines. All neighboring maps are compared in this way. Images can be printed and saved. Orders of the MAPs (ie which map is compared with which other map) can be changed and maps can be flipped (right mouse button). remark: MapComp bears close relationships with the GGT software package (entry from Genetic Analysis Software), THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: MAPINSPECT (RRID:SCR_009277) Copy   

•   Source: SciCrunch Registry

http://gaow.github.io/genetic-analysis-software/n-1.html#nocom

Software application to estimate parameters for mixture of normal distributions (entry from Genetic Analysis Software)

Proper citation: NOCOM (RRID:SCR_009310) Copy   

•   Source: SciCrunch Registry

http://mapdisto.free.fr/

Software program for mapping genetic markers in experimental segregating populations like backcross, doubled haploids, single-seed descent. Its specificity is to propose recombination fraction estimates in case of segregation distortion. It can (1) compute and draw genetic maps easily and quickly through a graphical interface; (2) facilitate the analysis of marker data showing segregation distortion due to differential viability of gametes or zygotes. (entry from Genetic Analysis Software), THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: MAPDISTO (RRID:SCR_009275) Copy   

•   Source: SciCrunch Registry

http://www.marksgeneticsoftware.net/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 16,2023. Software application that tests for population structure through the use of Mantel tests (entry from Genetic Analysis Software)

Proper citation: MANTEL-STRUCT (RRID:SCR_009271) Copy   

•   Source: SciCrunch Registry

http://www.biology.duke.edu/noorlab/multsim.html

Software application to analyze the numbers of individuals that founded new populations following a bottleneck or founding event (entry from Genetic Analysis Software)

Proper citation: MULTISIM (RRID:SCR_009308) Copy   

•   Source: SciCrunch Registry

http://darwin.cwru.edu/sage/

Software application that provides researchers with the tools necessary for various types of statistical genetic analysis of human family data. (entry from Genetic Analysis Software)

Proper citation: SAGE (RRID:SCR_009302) Copy   

•   Source: SciCrunch Registry

http://ftp://linkage.rockefeller.edu/software/lrtae/

Software application to compute a likelihood ratio test statistic that increases power to detect genetic association in the presence of phenotype, genotype, and/or haplotype misclassification errors. In addition, the program produces asymptotically unbiased estimates of frequency parameters. (entry from Genetic Analysis Software)

Proper citation: LRTAE (RRID:SCR_009265) Copy   

•   Source: SciCrunch Registry

http://mvz.berkeley.edu/Collections.html

A collection of over 640,000 specimens of amphibians, reptiles, birds, bird eggs or nests, and mammals, as well as over 50,000 tissue samples from these vertebrate groups. These research collections are ranked as one of the largest in the United States, and the largest of any university museum. In addition, the Museum has numerous special collections that include archived field notes and photographs, historical annotated maps and correspondence, avian sound recordings, chromosome and histology preparations, Milton Hildebrand anatomical and film collections, artwork related to terrestrial vertebrate natural history, and a library of books, reprints, and journals for curation and research activities. Specimen data are accessible online, and the Museum is working to improve data access to the other collections. Museum Collections * Mammal Collection * Herpetological Collection * Bird Collection * Egg & Nest Collection * Tissue Collection * Fieldnotes, Photos, & Map Collection * Other Collections The Museum of Vertebrate Zoology (MVZ) welcomes donations of amphibians, reptiles, birds, bird eggs and nests, mammals and related materials. Acceptance of a donation is at the discretion of MVZ Curators. * Specimens -- May include preserved specimens and/or parts (e.g., tissue samples) as well as unpreserved material (e.g., frozen carcasses, live animals) that will be prepared by Museum Curators, curatorial staff, or students. * Related Materials -- Donations of images (digital or printed photographs or slides), sound recordings, field notes, and other natural history archival material. Materials must be connected to specimens or research projects. Donated material and associated data will be made available for research, education, or public exhibit according to the mission and policies of the Museum and Regents, except by prior signed agreement between the donor and the Museum.

Proper citation: MVZ Collections (RRID:SCR_010608) Copy   

•   Source: SciCrunch Registry

http://www.pstnet.com/eprime.cfm

A suite of applications to fulfill all of your computerized experiment needs. Used by more than 15,000 professionals in the research community, E-Prime provides a truly easy-to-use environment for computerized experiment design, data collection, and analysis. E-Prime provides millisecond precision timing to ensure the accuracy of your data. E-Prime's flexibility to create simple to complex experiments is ideal for both novice and advanced users. The E-Prime suite of applications includes: * E-Studio ? Drag and drop graphical interface for experiment design * E-Basic ? Underlying scripting language of E-Prime * E-Run ? Once the experiment is generated with a single click, E-Run affords you the millisecond precision of stimulus presentation, synchronizations, and data collection. * E-Merge ? Merges your single session data files for group analysis * E-DataAid ? Data management utility * E-Recovery ? Recovers data files

Proper citation: E-Prime (RRID:SCR_009567) Copy   

•   Source: SciCrunch Registry

http://www.lifelines.net/

Overall aim of the LifeLines Study is to unravel the interaction between genetic and environmental factors in the development of multifactorial diseases, their concurrent development in individuals and their complications as a complex trait. The LifeLines database contains questionnaire data, physical measurements and biological samples from different health examinations. Collaboration is encouraged as it helps to maximize the scientific value of the wealth of epidemiologic data made possible by the participation of more than 165,000 individuals in the LifeLines Cohort Study. Primary objectives of the LifeLines Cohort Study are: a. Which are the disease overriding risk factors which predict the development of a multifactorial disease during lifetime? b. How are these universal risk factors modified, or what determines the effect of a universal risk factor in an individual? Specific research questions will focus on risk factors and modifiers (genetic, environmental and combined or complex factors) for single and multiple diseases. In addition to co-morbidity, LifeLines focuses on co-determinants. The primary endpoints include measures of aging, metabolic and endocrine diseases, cardiovascular and renal diseases, pulmonary and musculoskeletal diseases, and psychopathology. Secondary aims include the assessment of the prevalence and incidence of multifactorial diseases, their risk factors and their treatment in individuals as well as in families. The burden of disease for the society will be quantified in terms of care needed, and total costs of care. Until November 3, 2011, almost 68,000 subjects have been included in the study. The 60,000th participant was screened in the beginning of September 2011. Recruitment rate at present is between 700 and 800 subjects per week. The laboratory measurements which are performed has changed. As of October 2011, LifeLines will continue to measure: hematologic parameters, including hemoglobin, white blood cells, platelets, WBC differentiation, blood glucose, cholesterol, HDL-cholesterol, triglycerides, serum creatinin and sodium/potassium. Liver enzymes, thyroid hormones, calcium, phosphate, albumin, uric acid and microalbuminuria will not be measured routinely. The samples that are available for almost all participants, are: # serum (taken either with or without gel separator) # EDTA plasma # citrate plasma # DNA # early morning urine sample # urine samples of 24-hour urine collection Any researcher who is member of an internationally recognized academic institution and who is interested in utilizing the research possibilities, data and materials of LifeLines may apply for access. The applicant who is acting as Principal Investigator must be connected to a department or institution with the competence to carry out the research project to term. A contract will give the right to use the data for a pre-determined period of time. This contract also comprises the costs for the LifeLines Biobank which the investigator needs to reimburse. To apply for access, refer to the electronic application process.

Proper citation: Lifelines Biobank (RRID:SCR_010730) Copy   

•   Source: SciCrunch Registry

https://github.com/hjmjohnson/DTIPrep

DTIPrep performs a Study-specific Protocol based automatic pipeline for DWI/DTI quality control and preparation. This is both a GUI and command line tool. The configurable pipeline includes image/diffusion information check, padding/Cropping of data, slice-wise, interlace-wise and gradient-wise intensity and motion check, head motion and Eddy current artifact correction, and DTI computing.

Proper citation: DWI/DTI Quality Control Tool: DTIPrep (RRID:SCR_009562) Copy   

•   Source: SciCrunch Registry

http://genome.sph.umich.edu/wiki/Mach2dat:_Association_with_MACH_output

Software that performs logistic regression, using imputed SNP dosage data and adjusting for covariates.

Proper citation: Mach2dat (RRID:SCR_009599) Copy   

•   Source: SciCrunch Registry

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

Light version of the existing tool Fiber Viewer. It includes every clustering methods of Fiber Viewer such as : Lenght, Gravity, Hausdorff, and Mean methods but also a Normalized Cut algorithm. As in the full version you can also display a plane on the fiber. This tool works faster than the full version due to simplified visualizations.

Proper citation: FiberViewerLight (RRID:SCR_009476) Copy   

•   Source: SciCrunch Registry

http://www.unc.edu/~yunmli/MaCH-Admix/

A genotype imputation software that is an extension to MaCH for faster and more flexible imputaiton, especially in admixed populations. It has incorporated a novel piecewise reference selection method to create reference panels tailored for target individual(s). This reference selection method generates better imputation quality in shorter running time. MaCH-Admix also separates model parameter estimation from imputation. The separation allows users to perform imputation with standard reference panels + pre-calibrated parameters in a data independent fashion. Alternatively, if one works with study-specific reference panels, or isolated target population, one has the option to simultaneously estimate these model parameters while performing imputation. MaCH-Admix has included many other useful options and supports VCF input files. All existing MaCH documentation applies to MaCH-Admix.

Proper citation: MaCH-Admix (RRID:SCR_009598) Copy   

•   Source: SciCrunch Registry

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

Software provided as a sub-project in the Finsler-tractography module: http://www.nitrc.org/projects/finslertract

Proper citation: Fiber-tracking based on Finsler distance (RRID:SCR_009475) Copy   

•   Source: SciCrunch Registry

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

Simple and efficient, this application performs the Weighted False Discovery Rate procedure of Benjamini and Hochberg (1997) to correct for multiple testing. The good think is that you can test virtually any number of p-values (even millions) obtained with any test-statistics for any data set. The bonus is that you can assign a-priori weights to give a better chance to those variables that you deem important. In practice, this procedure is powerful only with a relatively small number of p-values.

Proper citation: False Discovery Rate Weighted (RRID:SCR_009473) Copy   

•   Source: SciCrunch Registry

http://cis.jhu.edu/software

Software application which aims to assign metric distances on the space of anatomical images in Computational Anatomy thereby allowing for the direct comparison and quantization of morphometric changes in shapes. As part of these efforts the Center for Imaging Science at Johns Hopkins University developed techniques to not only compare images, but also to visualize the changes and differences. For additional information please refer to: Faisal Beg, Michael Miller, Alain Trouve, and Laurent Younes. Computing Large Deformation Metric Mappings via Geodesic Flows of Diffeomorphisms. International Journal of Computer Vision, Volume 61, Issue 2; February 2005. M.I. Miller and A. Trouve and L. Younes, On the Metrics and Euler-Lagrange Equations of Computational Anatomy, Annual Review of biomedical Engineering, 4:375-405, 2002. Software developed with support from National Institutes of Health NCRR grant P41 RR15241.

Proper citation: LDDMM (RRID:SCR_009590) Copy   

•   Source: SciCrunch Registry