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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://www.paradigmexperiments.com

Software application for millisecond accurate experimental control for cognitive neuroscience, psychology and linguistics research. Presents text, images, sounds, movies, self-paced reading trials and rating scales. An integrated Python scripting API is available. Joystick and microphone response are available. Supports button boxes from PST, Cedrus, fORP and custom built response boxes. Paradigm can detect fMRI triggers through serial and parallel ports. Includes sample experiments that implement many of the most popular experiment designs., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Paradigm (RRID:SCR_009634) 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://hadoop.apache.org/

Software library providing a framework that allows for the distributed processing of large data sets across clusters of computers using simple programming models. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage. Rather than rely on hardware to deliver high-availability, the library itself is designed to detect and handle failures at the application layer, so delivering a highly-available service on top of a cluster of computers, each of which may be prone to failures. The project includes these modules: * Hadoop Common: The common utilities that support the other Hadoop modules. * Hadoop Distributed File System (HDFS): A distributed file system that provides high-throughput access to application data. * Hadoop YARN: A framework for job scheduling and cluster resource management. * Hadoop MapReduce: A YARN-based system for parallel processing of large data sets.

Proper citation: Apache Hadoop (RRID:SCR_011879) 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

https://www.nitrc.org/projects/gmac_2012/

Open-source software toolbox implemented multivariate spectral Granger Causality Analysis for studying brain connectivity using fMRI data. Available features are: fMRI data importing, network nodes definition, time series preprocessing, multivariate autoregressive modeling, spectral Granger causality indexes estimation, statistical significance assessment using surrogate data, network analysis and visualization of connectivity results. All functions are integrated into a graphical user interface developed in Matlab environment. Dependencies: Matlab, BIOSIG, SPM, MarsBar.

Proper citation: GMAC: A Matlab toolbox for spectral Granger causality analysis of fMRI data (RRID:SCR_009581) Copy   

•   Source: SciCrunch Registry

http://archive.broadinstitute.org/mpg/tagger/

Software application (entry from Genetic Analysis Software)

Proper citation: TAGGER (RRID:SCR_009419) Copy   

•   Source: SciCrunch Registry

https://watson.hgen.pitt.edu/docs/splink108.html

Software application for linkage analysis using affected sib pairs (entry from Genetic Analysis Software)

Proper citation: SPLINK (RRID:SCR_009414) Copy   

•   Source: SciCrunch Registry

http://www.sanger.ac.uk/science/tools/ssahasnp-0

A polymorphism detection tool that 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. For those less repetitive or non-repetitive reads, we place them uniquely on the reference genome sequence and find the best alignment according to the pair-wise alignment score if there are multiple seeded regions. From the best alignment, SNP candidates are screened, taking into account the quality value of the bases with variation as well as the quality values in the neighbouring bases, using neighbourhood quality standard (NQS). For insertions/deletions, we check if the same indel is mapped by more than one read, ensuring the detected indel with high confidence. (entry from Genetic Analysis Software)

Proper citation: SSAHASNP (RRID:SCR_009415) Copy   

•   Source: SciCrunch Registry

http://www.loni.usc.edu/Software/moreinfo.php?package=BGE

A JAVA application designed to create taxonomies or hierarchies in order to classify and organize information.

Proper citation: BrainGraph Editor (RRID:SCR_009536) Copy   

•   Source: SciCrunch Registry

https://swfsc.noaa.gov/textblock.aspx?Division=FED&id=3434

Software application that simulate pedigrees and genetic data in age-structured populations (entry from Genetic Analysis Software)

Proper citation: SPIP (RRID:SCR_009410) Copy   

•   Source: SciCrunch Registry

http://www.joslinresearch.org/LabSites/Krolewski/splat/

Software application that can calculate virtually any linkage test statistic under several sib pair study designs: affected, discordant, unaffected, and pairs defined by threshold values for quantitative traits, such as extreme discordant sib pairs. It uses the EM algorithm to compute maximum likelihood estimates of sharing (subject to any user-specified domain restrictions or null hypotheses) and then plots lod scores versus chromosomal position. It includes a novel grid scanning capability that enables simultaneous visualization of multiple test statistics. Phenotype definitions can be modified without recalculating inheritance vectors, thereby providing considerable analytical flexibility. (entry from Genetic Analysis Software), THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: SPLAT (RRID:SCR_009411) Copy   

•   Source: SciCrunch Registry

https://plant-breeding.uni-hohenheim.de/software.html#jfmulticontent_c110647-2

Software application (entry from Genetic Analysis Software)

Proper citation: PLABQTL (RRID:SCR_012789) Copy   

•   Source: SciCrunch Registry

http://www.bonebank.com

Biotechnology company dedicated to enhancing quality of patient care through development and manufacture of safe, high quality allograft solutions for healthcare professionals.

Proper citation: Texas Human Biologics (RRID:SCR_010523) Copy   

•   Source: SciCrunch Registry

http://econpapers.repec.org/software/bocbocode/s438902.htm

Software application (entry from Genetic Analysis Software)

Proper citation: HAPBLOCK 2 (RRID:SCR_012788) Copy   

•   Source: SciCrunch Registry