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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   

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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   

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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   

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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   

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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

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

https://www.lifegene.se/In-english/

Swedish study to get a better understanding of how genes, environment and way of life affect health that will enable access to the longitudinal data on 500,000 participants after ethical approval. Half a million people in Sweden between the ages of 0 and 45 will be recruited as volunteers for 6 to 8 years. People between 18 and 45 will be invited and they may, in turn, bring children and other people that they live with into the project. Participants will be followed for many years with regular online surveys and health checks. Their blood and urine samples will also be stored in a biobank. All the data will form a very large information base, where researchers can follow what happens with people''''s health. The LifeGene test center will measure height, hip, waist and chest measurements. A so-called spirometry test will be conducted which measures lung function, a hearing test and bioimpedance measurement (includes weight, BMI and distribution of body fat and muscle mass). They also take blood and urine samples and measure blood pressure and pulse. LifeGene foresees a lot of different research cooperation. Everything from simple withdrawal of longitudinal data, leverage of LifeGene infrastructure and cooperation between LifeGene and complementing scientific projects covering specific areas in more depth. LifeGene will enable access to unique longitudinal data on 500,000 participants available for researchers after ethical approval. LifeGene is also an infrastructure with Test Centers covering most of Sweden, logistics for sample management from arm-to-freezer and state-of-the-art large scale automatic biobanking enabling low cost, high quality, fast withdrawal of biological samples.

Proper citation: LifeGene (RRID:SCR_010524) Copy   

•   Source: SciCrunch Registry

https://cran.r-project.org/web/packages/rmetasim/index.html

An R package that uses an individual-based approach to simulate distributions of genotypes that result from arbitrary within and among population demographies (including extinction/recolonization). These distributions can be used to test new or existing population-genetics summary statistics or develop null distributions under various demographies. (entry from Genetic Analysis Software)

Proper citation: R/METASIM (RRID:SCR_009370) Copy   

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https://www.genetics.ucla.edu/software/download?package=4

Software application for analysis of sperm typing data. (entry from Genetic Analysis Software), THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: SPERM (RRID:SCR_009409) Copy   

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

Software tools optimized for performing univariate and multivariate imaging genetics analyses while providing practical correction strategies for multiple testing. The goal of this project is to merge two important research directions in modern science, genetics and neuroimaging. This entails combining modern statistical genetic methods and quantitative phenotyping performed with high dimensional neuroimaging modalities. So far, however, standard imaging tools are unable to deal with large-scale genetics data, and standard genetics tools, in turn, are unable to accommodate large size and binary format of the image data. Their focus is to create imaging genetics tools for classical genetic and epigenetic epidemiological analyses such as heritability, pleiotropy, quantitative trait loci (QTL) and genome-wide association (GWAS), gene expression, and methylation analyses optimized for traits derived from structural and functional brain imaging data

Proper citation: Solar Eclipse Imaging Genetics tools (RRID:SCR_009645) Copy   

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https://www.dynacom.co.jp/english/product/snpalyze_e/

Software application (entry from Genetic Analysis Software)

Proper citation: SNPALYZE (RRID:SCR_009401) Copy   

•   Source: SciCrunch Registry

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

An automated toolbox for a generalized form of psychophysiological interactions for SPM and FSFAST. The automated toolbox can do the following: (a1) produce identical results to the current implementation in SPM (a2) use the current implementation of PPI in SPM but using the regional mean instead of the eigenvariate (a3) use a generalized form that allows a PPI for each task to be in the same model using either the regional mean of eigenvariate (b) create the model using the output of one of the (a) options and the first level design (c) estimate the model (/results directory) (d) compute the contrasts specified.

Proper citation: Generalized PPI Toolbox (RRID:SCR_009489) Copy   

•   Source: SciCrunch Registry

http://www.jcm.riken.go.jp/

The Microbe Division in RIKEN-BRC has been collecting, preserving, and distributing cultured microbial strains as one of the leading culture collections in the world since established as Japan Collection of Microorganisms (JCM) in 1981. JCM aims to contribute to scientific communities by maintaining and serving high-quality microbial resources useful for general microbial studies and various research fields particularly in health and environmental science. JCM has participated in the National BioResource Project supported by the Ministry of Education, Culture, Sports, Science and Technology of Japan as the core facility for General Microbes. JCM maintains approximately 19,900 strains as of Sept. 2010, and the approximate numbers of the available strains from JCM are: 7,400 strains of aerobic and anaerobic bacteria including actinomycetes, 300 strains of archaea, and 4,100 strains of fungi including yeasts (in total ca. 12,000 strains). Strains held at JCM are limited to those classified in Risk Group 1 or 2. Information of the available strains is opened to the public through the JCM On-line Catalogue Database. Genomic DNA samples of some strains are also distributed in cooperation with RIKEN BRC-DNA Bank. More than 3,500 strains are annually distributed to domestic and overseas researchers. JCM welcomes a deposit of microbial strains published or designed to be published in scientific papers as well as an order for microbial cultures.

Proper citation: JCM (RRID:SCR_010653) Copy   

•   Source: SciCrunch Registry

http://scirus.com/

Science-specific search engine with over 575 million scientific items indexed at last count (May 2013), it allows researchers to search for not only journal content but also scientists'' homepages, courseware, pre-print server material, patents and institutional repository and website information. Scirus helps you quickly locate scientific information on the Web: * Filters out non-scientific sites. For example, if you search on REM, Google finds the rock group - Scirus finds information on sleep, among other things * Finds peer-reviewed articles such as PDF and PostScript files, which are often invisible to other search engines. * Searches the most comprehensive combination of web information, preprint servers, digital archives, repositories and patent and journal databases. Scirus goes deeper than the first two levels of a Web site, thereby revealing much more relevant information. Scirus has proved so successful at locating science-specific results on the Web that the Search Engine Watch Awards voted Scirus ''Best Specialty Search Engine'' in 2001 and 2002 and ''Best Directory or Search Engine Website'' WebAward from Web Marketing Association in 2004, 2005, 2006 and 2007. Give your Web site greater functionality and enhance the experience of your users, by adding Scirus to your home page for free. Scirus uses the latest in search engine technology to pinpoint precise scientific information that other search engines can not reach, including pdf files and peer reviewed articles. Make your Web site more visible to the scientific community, by submitting it for inclusion on Scirus. You will increase the chance of scientists finding your site when looking for information and you could increase your visitor rate.

Proper citation: Scirus - for scientific information only (RRID:SCR_010657) Copy   

•   Source: SciCrunch Registry

https://www.wur.nl/en/show/SMOOTH.htm

Software tool that recognises and removes the most unrealistic data pointsfor the construction of accurate linkage maps, which is not so much depending on the quality of the mapping software, but mostly on the marker data quality. Missing values and scoring errors can severely influence the calculated marker order. This software was used to construct the 10,000 marker potato map. The removal of improbable data point is a good medicine for linkage maps, that is not easily overdosed. One error is more harmfull than ten missing values. The software was never intended as user-friendly software. In these days it would be more useful to re-do the programming of the pascal source code into a perl script. Anyone who takes the initiative to generate such a script is welcomed to contact the authors. SMOOTH works best in close cooperation with mapping algorithm RECORD (entry from Genetic Analysis Software)

Proper citation: SMOOTH (RRID:SCR_009398) Copy   

•   Source: SciCrunch Registry

http://www.jurgott.org/linkage/simulate.html

Software program to simulate genotypes in family members for a map of linked markers unlinked to a given affection status locus. the output is ready for analysis with UNKNOWN, ISIM, LSIM, or MSIM of the SLINK package. (entry from Genetic Analysis Software)

Proper citation: SIMULATE (RRID:SCR_009391) Copy   

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http://simupop.sourceforge.net

A forward-based population genetics simulation program capable of simulating very complex evolution processes on large (think of millions) populations. Major features include variable population size; many built-in and hybrid (write in python) mutation, migration, selection models. simuPOP can be extended in Python so there is no limit on what you can do with it. (entry from Genetic Analysis Software)

Proper citation: SIMUPOP (RRID:SCR_009392) Copy   

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http://www.molecular-haplotype.org/zaplo/zaplo_index.html

THIS RESOURCE IS NO LONGER IN SERVCE, documented September 6, 2016.

Proper citation: ZAPLO (RRID:SCR_009426) Copy   

•   Source: SciCrunch Registry