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http://www.cdc.gov/genomics/hugenet/default.htm

Human Genome Epidemiology Network, or HuGENet, is a global collaboration of individuals and organizations committed to the assessment of the impact of human genome variation on population health and how genetic information can be used to improve health and prevent disease. Its goals include: establishing an information exchange that promotes global collaboration in developing peer-reviewed information on the relationship between human genomic variation and health and on the quality of genetic tests for screening and prevention; providing training and technical assistance to researchers and practitioners interested in assessing the role of human genomic variation on population health and how such information can be used in practice; developing an updated and accessible knowledge base on the World Wide Web; and promoting the use of this knowledge base by health care providers, researchers, industry, government, and the public for making decisions involving the use of genetic information for disease prevention and health promotion. HuGENet collaborators come from multiple disciplines such as epidemiology, genetics, clinical medicine, policy, public health, education, and biomedical sciences. Currently, there are 4 HuGENet Coordinating Centers for the implementation of HuGENet activities: CDC''s Office of Public Health Genomics, Atlanta, Georgia; HuGENet UK Coordinating Center, Cambridge, UK; University of Ioannina, Greece; University of Ottawa , Ottawa, Canada. HuGENet includes: HuGE e-Journal Club: The HuGE e-Journal Club is an electronic discussion forum where new human genome epidemiologic (HuGE) findings, published in the scientific literature in the CDC''s Office of Public Health Genomics Weekly Update, will be abstracted, summarized, presented, and discussed via a newly created HuGENet listserv. HuGE Reviews: A HuGE Review identifies human genetic variations at one or more loci, and describes what is known about the frequency of these variants in different populations, identifies diseases that these variants are associated with and summarizes the magnitude of risks and associated risk factors, and evaluates associated genetic tests. Reviews point to gaps in existing epidemiologic and clinical knowledge, thus stimulating further research in these areas. HuGE Fact Sheets: HuGE Fact Sheets summarize information about a particular gene, its variants, and associated diseases. HuGE Case Studies: An on-line presentation designed to sharpen your epidemiological skills and enhance your knowledge on genomic variation and human diseases. Its purpose is to train health professionals in the practical application of human genome epidemiology (HuGE), which translates gene discoveries to disease prevention by integrating population-based data on gene-disease relationships and interventions. Students will acquire conceptual and practical tools for critically evaluating the growing scientific literature in specific disease areas. HUGENet Publications: Articles related to the HuGENet movement written by our HuGENet collaborators. HuGE Navigator: An integrated, searchable knowledge base of genetic associations and human genome epidemiology, including information on population prevalence of genetic variants, gene-disease associations, gene-gene and gene- environment interactions, and evaluation of genetic tests. HuGE Workshops: HuGENet has sponsored meetings and workshops with national and international partners since 2001. Available are detailed summaries, agendas or the ability to download speaker slides. HuGE Book: Human Genome Epidemiology: A Scientific Foundation for Using Genetic Information to Improve Health and Prevent Disease. (The findings and conclusions in this book are those of the author(s) and do not necessarily represent the views of the funding agency.) HuGENet Collaborators: HuGENet is interested in establishing collaborations with individuals and organizations working on population based research involving genetic information. HuGE Funding: Funding opportunities for specific population-based genetic epidemiology research projects are available. Research initiatives whose aims include assessing the prevalence of human genetic variation, the association between genetic variants and human diseases, the measurement of gene-gene or gene-environment interaction, and the evaluation of genetic tests for screening and prevention are compiled to create a posted listing. Additional information and application details can be found by clicking on the respective links.

Proper citation: Human Genome Epidemiology Network (RRID:SCR_013117) Copy   

•   Source: SciCrunch Registry

http://www.seattle.eric.research.va.gov/VETR/Home.asp

The Vietnam Era Twin (VET) Registry is a closed cohort composed of approximately 7,000 middle-aged male-male twin pairs both of whom served in the military during the time of the Vietnam conflict (1964-1975). The Registry is a United States Department of Veterans Affairs (VA) resource that was originally constructed from military records; the Registry has been in existence for almost 20 years. It is one of the largest national twin registries in the US and currently has members living in all 50 states. Initially formed to address questions about the long-term health effects of service in Vietnam, the Registry has evolved into a resource for genetic epidemiological studies of mental and physical health conditions. Several waves of mail and telephone surveys have collected a wealth of health-related information on Registry twins, referred to as members. In addition to twins, selected adult offspring of twins and the mothers of those offspring are also VET Registry members. More recent data collection efforts have focused on specific sets of twin pairs and have conducted detailed clinical or laboratory testing. Selected Vietnam Era Registry Research Studies: * Veteran Health Study * VETSA 2: A Longitudinal Study of Cognitive Aging * Alcoholism Course thought Midlife: A Twin Family Study and Offspring of Twins: G, E and GxE Risk for Alcoholism * GE: Offspring of Twins with Substance Use Disorder * Mechanisms Linking Depression to Cardiovascular Risk (Twins Heart Study 2) * Post-traumatic Stress Disorder and Cardiovascular Disease * Biological Markers for Post-traumatic Stress Disorder (T3) * Memory and the Hippocampus in Vietnam-era Twins with PTSD (Time 3)

Proper citation: Vietnam Era Twin Registry (RRID:SCR_008807) Copy   

•   Source: SciCrunch Registry

https://sites.google.com/site/fdudbridge/software/pelican

Software utility for graphically editing the pedigree data files used by programs such as FASTLINK, VITESSE, GENEHUNTER and MERLIN. It can read in and write out pedigree files, saving changes that have been made to the structure of the pedigree. Changes are made to the pedigree via a graphical display interface. The resulting display can be saved as a pedigree file and as a graphical image file.

Proper citation: PELICAN (RRID:SCR_001695) Copy   

•   Source: SciCrunch Registry

http://wwwchg.duhs.duke.edu/research/osa.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 19,2025. Software application that allows the researcher to evaluate evidence for linkage even when heterogeneity is present in a data set. This is not an unusual occurrence when studying diseases of complex origin. Families are ranked by covariate values in order to test evidence for linkage among homogeneous subsets of families. Because families are ranked, a priori covariate cutpoints are not necessary. Covariates may include linkage evidence at other genes, environmental exposures, or biological trait values such as cholesterol, age at onset, and so on.

Proper citation: OSA (RRID:SCR_002016) Copy   

•   Source: SciCrunch Registry

http://csg.sph.umich.edu//abecasis/Metal/

Software application designed to facilitate meta-analysis of large datasets (such as several whole genome scans) in a convenient, rapid and memory efficient manner. (entry from Genetic Analysis Software)

Proper citation: METAL (RRID:SCR_002013) Copy   

•   Source: SciCrunch Registry

http://www.omicsexpress.com/sva.php

Software package to annotate, visualize, and analyze the genetic variants identified through next-generation sequencing studies, including whole-genome sequencing (WGS) and exome sequencing studies. SVA aims to provide the research community with a user-friendly and efficient tool to analyze large amount of genetic variants, and to facilitate the identification of the genetic causes of human diseases and related traits.

Proper citation: SVA (RRID:SCR_002155) Copy   

•   Source: SciCrunch Registry

https://www.sfari.org/funding-opportunities/

The mission of SFARI is to improve the diagnosis, treatment, and prevention of autism and related developmental disorders. SFARI explores neuroscience from multiple directions, including molecular, cellular, systems, immunological, cognitive, behavioral, genetic, theoretical and computational perspectives. Funding for innovative scientific research is available through a peer-reviewed proposal process at regular intervals. Research projects are reviewed by a scientific advisory board and managed by the scientific director and a highly qualified staff. Proposals in multiple research areas are sought, to reflect the complex nature of autism. The Foundation supports innovative scientific projects where our involvement will play an essential role. In the course of this support, The Foundation is interested in partnering with other entities, or providing matching support where appropriate. The Simons Foundation has historically accepted only solicited grant proposals. These grant decisions are made by the Trustees of The Simons Foundation, who review applications on an ongoing basis. In the area of autism research, requests for proposals are issued on an annual basis. The Simons Foundation does not give grants to individuals, except through their institutions.

Proper citation: Simons Foundation Autism Research Initiative: Grant Resource (RRID:SCR_001862) Copy   

•   Source: SciCrunch Registry

http://cedar.genetics.soton.ac.uk/pub/PROGRAMS/ldb;

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23,2022. Software application that integrate genetic linkage map and physical map (entry from Genetic Analysis Software)

Proper citation: LDB/LDB+ (RRID:SCR_000839) Copy   

•   Source: SciCrunch Registry

http://research.calit2.net/hap/

Software application (entry from Genetic Analysis Software)

Proper citation: HAP 1 (RRID:SCR_000837) Copy   

•   Source: SciCrunch Registry

http://www.reading.ac.uk/Statistics/genetics/software.html

Software application (entry from Genetic Analysis Software)

Proper citation: LAMBDAA (RRID:SCR_001128) Copy   

•   Source: SciCrunch Registry

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

Software application that is a combined functional annotation score of non-synonymous coding variants. A major challenge in interpreting whole-exome data is predicting which of the discovered variants are deleterious or neutral. To address this question in silico, they have developed a score called Combined Annotation scoRing toOL (CAROL), which combines information from two bioinformatics tools: PolyPhen-2 and SIFT, in order to improve the prediction of the effect of non-synonymous coding variants. The combination of annotation tools can help improve automated prediction of whole-genome/exome non-synonymous variant functional consequences. (entry from Genetic Analysis Software) The software should run on any UNIX or GNU/Linux system.

Proper citation: CAROL (RRID:SCR_001800) Copy   

•   Source: SciCrunch Registry

http://www.reading.ac.uk/Statistics/genetics/software.html

Software application (entry from Genetic Analysis Software)

Proper citation: LDMET (RRID:SCR_001127) Copy   

•   Source: SciCrunch Registry

http://www.biostat.harvard.edu/complab/dchip/snp.htm

THIS RESOURCE IS NO LONGER IN SERVCE, documented September 22, 2016.

Proper citation: DCHIP LINKAGE (RRID:SCR_000835) Copy   

•   Source: SciCrunch Registry

http://faculty.washington.edu/browning/floss/floss.htm

Software application that performs ordered subset analysis using MERLIN's ouput .lod file created with the --perFamily option. Ordered subset analysis uses covariate information to identify a more homogenous subset of families for linkage analysis. The homogeneous subset of families does not need to be specified a priori, and the covariates can include environmental exposures, quantitative traits, or linkage scores at another locus in the genome. The evidence for linkage is evaluated with a permutation test. (entry from Genetic Analysis Software)

Proper citation: FLOSS (RRID:SCR_000836) Copy   

•   Source: SciCrunch Registry

http://support.illumina.com/sequencing/sequencing_software/casava.html

Software package that creates genomic builds, calls SNPs, detects indels, and counts reads from data generated from one or more sequencing runs. In addition, CASAVA automatically generates a range of statistics, such as mean depth and percentage chromosome coverage, to enable comparison with previous builds or other samples. CASAVA analyzes sequencing reads in three stages: * FASTQ file generation and demultiplexing * Alignment to a reference genome * Variant detection and counting

Proper citation: CASAVA (RRID:SCR_001802) Copy   

•   Source: SciCrunch Registry

http://genome.sph.umich.edu/wiki/Polymutt

Software program that implemented a likelihood-based framework for calling single nucleotide variants and detecting de novo point mutation events in families for next-generation sequencing data. The program takes as input genotype likelihood format (GLF) files which can be generated following the Creation of GLF files instruction and outputs the result in the (VCF) format. The variant calling and de novo mutation detection are modelled jointly within families and can handle both nuclear and extended pedigrees without consanguinity loops. The input is a set of GLF files for each of family members and the relationships are specified through the .ped file. (entry from Genetic Analysis Software)

Proper citation: POLYMUTT (RRID:SCR_002051) Copy   

•   Source: SciCrunch Registry

http://null

Software application for calculating the heterozygosity, PIC, and LIC values for polymorphic markers (entry from Genetic Analysis Software), THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: POLYMORPHISM (RRID:SCR_000828) Copy   

•   Source: SciCrunch Registry

https://github.com/gaow/genetic-analysis-software/blob/master/pages/EDAC.md

THIS RESOURCE IS NO LONGER IN SERVCE, documented September 22, 2016.

Proper citation: EDAC (RRID:SCR_000829) Copy   

•   Source: SciCrunch Registry

https://github.com/gaow/genetic-analysis-software/blob/master/pages/2LD.md

Software program for calculating linkage disequilibrium (LD) measures between two polymorphic markers.

Proper citation: 2LD (RRID:SCR_000826) Copy   

•   Source: SciCrunch Registry

http://www.bios.unc.edu/~lin/software/SQTL/

Software application (entry from Genetic Analysis Software)

Proper citation: SQTL (RRID:SCR_000827) Copy   

•   Source: SciCrunch Registry