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http://hrsonline.isr.umich.edu/

A data set of a longitudinal panel study of health, retirement, and aging that surveys a representative sample of more than 26,000 Americans over the age of 50 every two years. The HRS explores the changes in labor force participation and the health transitions that individuals undergo toward the end of their work lives and in the years that follow. The study captures a dynamic picture of an aging America''s physical and mental health, insurance coverage, financial status, family support systems, labor market status, and retirement planning. The sample in 2006 numbered over 22,000 persons in 13,100 households, with oversamples of Hispanics, Blacks and Florida residents. Beginning in 2006, half the sample received enhanced face-to-face follow-ups that included the collection of physical measures and biomarkers HRS provides a research data base that can simultaneously support continuous cross-sectional descriptions of the US population over the age of fifty-five, longitudinal studies of a given cohort over a substantial period of time (up to 18 years by 2010 for the original HRS cohort, following them from age 51-61 to age 69-79) and research on cross-cohort trends. By 2010 the HRS will be able to support cross-cohort comparisons of trajectories of health, labor supply, or wealth accumulation for persons who entered their 50s in 1992, 1998 and 2004. The HRS also has provided the sampling frame for targeted sub-studies. The Aging, Demographics, and Memory Study (ADAMS) supplement on dementia involved a field assessment of a sample of about 930 HRS panel members aged 75+ to clinically assess their dementia status and dementia severity. Special topics including consumption and time use, prescription drug use and the impact of Medicare Part D, parents'' human capital investments in children, and diabetes management by self-reported diabetics, have appeared on mail surveys that have used the HRS as a sampling frame. The HRS also can accommodate a number of experimental topics using Internet interviewing. The HRS is also characterized by links to a rich array of administrative data, including: Employer Pension Plans; National Death Index; Social Security Administration earnings and (projected) benefits data; W-2 self-employment data; and Medicare and Medicaid files. The HRS has actively collaborated with other longitudinal studies of aging in other countries (e.g., ELSA, SHARE, MHAS), providing both scientific and technical assistance. Data Availability: All publicly available data may be downloaded after registration. Early Release data files are typically available within three months of the end of each data collection, with the Final Release following at 24 months after the close of data collection activities. Files linked with administrative data are released only as restricted data through an application process, as outlined on the HRS website. * Dates of Study: 1992-present * Study Features: Longitudinal, Minority Oversamples, Anthropometric Measures, Biospecimens * Sample Size: 22,000+ Link * ICPSR: http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/06854

Proper citation: Health and Retirement Study (RRID:SCR_008930) Copy   

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http://neurogenetics.nia.nih.gov

A suite of web-based open source software programs for clinical and genetic study. The aims of this software development in the Laboratory of Neurogenetics, NIA, NIH are * Build retrievable clinical data repository * Set up genetic data bank * Eliminate redundant data entries * Alleviate experimental error due to sample mix-up and genotyping error. * Facilitate clinical and genetic data integration. * Automate data analysis pipelines * Facilitate data mining for genetic as well as environmental factors associated with a disease * Provide an uniformed data acquisition framework, regardless the type of a given disease * Accommodate the heterogeneity of different studies * Manage data flow, storage and access * Ensure patient privacy and data confidentiality/security. The GERON suite consists of several self contained and yet extensible modules. Currently implemented modules are GERON Clinical, Genotyping, and Tracking. More modules are planned to be added into the suite, in order to keep up with the dynamics of the research field. Each module can be used separately or together with others into a seamless pipeline. With each module special attention has been given in order to remain free and open to the academic/government user., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: GERON (RRID:SCR_008531) Copy   

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http://dsarm.niapublications.org/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on February 18, 2014.

A networking site for investigators using animal models to study aging, developed to provide a venue for sharing information about research models for aging studies. If you have tissue or data from animal models relevant to aging research that you are willing to share with other investigators, D-SARM allows you to identify the model and provides a secure, blinded email contact for investigators who would like to contact you about acquiring tissue or related resources. Investigators looking for resources from a particular model enter search terms describing the model of interest and then use the provided link to send emails to the contacts (names blinded) listed in the search results to initiate dialog about tissue or resources available for sharing. The database is housed on a secure server and admission to the network is moderated by the NIA Project Officer and limited to investigators at academic, government and non-profit research institutions. The goal is to provide a secure environment for sharing information about models used in aging research, promoting the sharing of resources, facilitating new research on aging in model systems, and increasing the return on the investment in research models.

Proper citation: Database for Sharing Aging Research Models (RRID:SCR_008691) Copy   

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http://www.flinders.edu.au/sabs/fcas/alsa/alsa_home.cfm

The general purpose of ALSA is to examine how social, biomedical, psychological, economic, and environmental factors are associated with age-related changes in the health and wellbeing of persons aged 70 years and older. The aim is to analyze the complex relationships between individual and social factors and changes in health status, health care needs and service utilization dimensions, with emphasis given to the effects of social and economic factors on morbidity, disability, acute and long-term care service use, and mortality. The study was designed to have common instrumentation with US studies. ALSA collected data from a random, stratified sample of all persons (both community and institution-dwelling) aged 70 years and older living in the metropolitan area of Adelaide, South Australia, using the State Electoral Database as the sampling frame. Spouses aged 65 and older and other household members aged 70 years and older also were invited to participate. The initial baseline data collection for ALSA began in September 1992 and was completed in March 1993. In the first wave, personal interviews were carried out for 2,087 participants, including 566 couples (that is, persons 70 years of age and over and their spouse, if 65 and over). Clinical assessments were obtained for 1,620 of the participants. Respondents were recontacted by telephone a year after initial interview (wave 2). The third wave of the study began in September 1994 and involved a complete reassessment, with a total of 1,679 interviews and 1,423 clinical assessments. To date, eleven waves of data have been collected, with the latest collection in May 2010, from 168 participants. Six of these waves were conducted via face-to-face interviews and clinical assessments, and five were telephone interviews. Future waves are planned, however are dependent on grant funding. Ancillary data collection has been ongoing since the initiation of the study, e.g., from secondary providers. Lists of ALSA participants are compared biannually with the agencies'' lists to determine the prevalence and incidence of receipt of services from these organizations. Another source of information has been the collection of data from the participants'' general practitioners about the respondent''s health status, history of services received, medication use, referrals to specialists, and current services provided. Baseline Sample Size: 2087 Dates of Study: 1992����������2010 (potentially ongoing) Study Features: * Longitudinal * International * Anthropometric Measures * Biospecimens Waves 1-5 (ICPSR), http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/06707 Wave 6 (ICPSR), http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/03679

Proper citation: ALSA - The Australian Longitudinal Study of Ageing (RRID:SCR_013146) Copy   

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https://portal.brain-map.org/explore/seattle-alzheimers-disease

Open atlas based on single cell profiling technologies with quantitative neuropathology and deep clinical phenotyping from middle temporal gyrus from neurotypical reference brains and brains from SEA-AD aged cohort that span spectrum of Alzheimer’s disease. Produced via collaboration between Allen Institute for Brain Science, University of Washington Alzheimer Disease Research Center and Kaiser Permanente Washington Health Research Institute.

Proper citation: Seattle Alzheimer Disease Brain Cell Atlas (RRID:SCR_023110) Copy   

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http://lgsun.grc.nia.nih.gov/cDNA/cDNA.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23,2022. Project portal housing NIA Mouse EST Project, NIA Mouse cDNA Clone Sets, a NIA Mouse Gene Index, NIA Mouse cDNA Database, and NIA Mouse Microarrays. Characteristics of NIA 15K Mouse cDNA Clone Set * ~15,000 unique cDNA clones were rearrayed among 52,374 ESTs from pre- and periimplantation embryos, E12.5 female gonad/mesonephros, and newborn ovary. * Up to 50% are derived from novel genes. * ~1.5 kb average insert size. * Clones were sequenced from 5' and 3' termini to obtain longer reads and verify sequence. Sequence information is available at this Web Site. Clone names are from H3001A01 to H3159G07. * Handling of NIA 15k cDNA Clone Set(June3, 2000) Characteristics of NIA mouse 7.4K cDNA Clone Set * ~7407 cDNA clones with no redundancy within the set or with NIA Mouse 15K. * ~1.5 kb average insert size for short insert clones and ~2.5-3.0 kb average insert size for long-insert enriched clones.. * Clones were sequenced from 5' and 3' termini to obtain longer reads and verify sequence. Sequence information is available at this Web Site. Clone names are from H4001A01 to H4079G07. * Handling of NIA mouse 7.4k cDNA Clone Set (similar to handling of NIA mouse 15K, to be updated) Individual Clones are available from ATCC and MRC geneservice, UK. To obtain Clone, search the database using either the rearrayed clone name or GenBank accession number at the Key Word Search page. Follow the link to the sequence information page for the rearrayed clone to obtain source clone ATCC number. Clicking the ATCC number will bring up the ATCC ordering page for the source clone. There is essentially no overlap between the two clone sets (7.4K and 15K) said Minoru S.H. Ko, M.D., Ph.D., head of the Developmental Genomics and Aging Section in the NIA's Laboratory of Genetics. In addition, all cDNA clones in the NIA 7.4K set were purified by single colony isolation and sequence-verified, and more than half were prepared by a new procedure that yields long full-length cDNAs (average size 3-4 kb). The NIA Mouse 15k and 7.4k Clone Set Data and Published Microarray Data are available for download. NIA Mouse Microarrays *Microarray Data Download * 60-mer Oligo Array Platform ** (A) NIA 22k Oligo Microarray Gene List (21939 gene features) ( Carter et al 2003 ) ** (B) Agilent Mouse Development Oligo Microarray Gene List ** ( Subset of Microarray (A): 20,280 gene features ) * Data Analysis Tools

Proper citation: NIA Mouse cDNA Project Home Page (RRID:SCR_001472) Copy   

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http://www.mhasweb.org/

A dataset of a prospective panel study of health and aging in Mexico. The study was designed to ensure comparability with the U.S. Health and Retirement Study in many domains, and the NHANES III. The baseline survey in 2001 is nationally representative of the 13 million Mexicans born prior to 1951. The six Mexican states which are home to 40% of all migrants to the U.S. were over-sampled at a rate of 1.7:1. Spouse/partners of eligible respondents were interviewed also, even if the spouse was born after 1950. Completed interviews were obtained in 9,862 households, for a total of 15,186 individual interviews. All interviews were face-to-face, with average duration of 82 minutes. A direct interview (on the Basic questionnaire) was sought, and Proxy interviews were obtained when poor health or temporary absence precluded a direct interview. Questionnaire topics included the following: * HEALTH MEASURES: self-reports of conditions, symptoms, functional status, hygienic behaviors (e.g., smoking & drinking history), use/source/costs of health care services, depression, pain, reading and cognitive performance; * BACKGROUND: Childhood health and living conditions, education, ability to read/write and count, migration history, marital history; * FAMILY: rosters of all children (including deceased children); for each, demographic attributes, summary indicators of childhood and current health, education, current work status, migration. Parent and sibling migration experiences; * TRANSFERS: financial and time help given to and received by respondent from children, indexed to specific child; time and financial help to parent; * ECONOMIC: sources and amounts of income, including wages, pensions, and government subsidies; type and value of assets. All amount variables are bracketed in case of non-response. * HOUSING ENVIRONMENT: type, location, building materials, other indicators of quality, and ownership of consumer durables; * ANTHROPOMETRIC: for a 20% sub-sample, measured weight, height; waist, hip, and calf circumference; knee height, and timed one-leg stands. Current plans are to conduct another two follow-up surveys in 2012 and 2014 and will field the 3rd and 4th waves of survey data collection in Mexico. For the 2012 wave, interviews will be sought for: every person who was part of the panel in 2003 and their new spouse / partner, if applicable, and a new sample of persons born between 1952 and 1962. For the 2014 wave, we will follow-up the whole sample from 2012. Interviews will be conducted person-to-person. Direct interviews will be sought with all informants, but proxy interviews are allowed for those unable to complete their own interview for health or cognitive reasons. A next-of-kin interview will be completed with a knowledgeable respondent for those who were part of the panel but have died since the last interview. A sub-sample will be selected to obtain objective markers such as blood sample and anthropometric measures. Data Availability: The 2001 baseline data, 2003 follow-up data, and documentation can be downloaded. * Dates of Study: 2001-2003 * Study Features: Longitudinal, International, Anthropometric Measures * Sample Size: 2001: 15,186 (Baseline) Link: * ICPSR: http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/00142

Proper citation: Mexican Health and Aging Study (RRID:SCR_000818) Copy   

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http://senselab.med.yale.edu

The SenseLab Project is a long-term effort to build integrated, multidisciplinary models of neurons and neural systems. It was founded in 1993 as part of the original Human Brain Project, which began the development of neuroinformatics tools in support of neuroscience research. It is now part of the Neuroscience Information Framework (NIF) and the International Neuroinformatics Coordinating Facility (INCF). The SenseLab project involves novel informatics approaches to constructing databases and database tools for collecting and analyzing neuroscience information, using the olfactory system as a model, with extension to other brain systems. SenseLab contains seven related databases that support experimental and theoretical research on the membrane properties: CellPropDB, NeuronDB, ModelDB, ORDB, OdorDB, OdorMapDB, BrainPharmA pilot Web portal that successfully integrates multidisciplinary neurocience data.

Proper citation: SenseLab (RRID:SCR_007276) Copy   

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http://www.mayo.edu/research/centers-programs/alzheimers-disease-research-center

A clinical research department that specializes in the study of Alzheimer's disease. The Mayo Clinic Alzheimer's Disease Research Center conducts many types of research studies related to dementia, as well as normal or successful aging. The purpose of the center is to provide care for dementia patients and promote research and education on Alzheimer's Disease and related dementias.

Proper citation: Mayo Alzheimer's Disease Research Center (RRID:SCR_008727) Copy   

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http://surfer.nmr.mgh.harvard.edu/fswiki/Tracula

Software tool developed for automatically reconstructing a set of major white matter pathways in the brain from diffusion weighted images using probabilistic tractography. This method utilizes prior information on the anatomy of the pathways from a set of training subjects. By incorporating this prior knowledge in the reconstruction procedure, our method obviates the need for manual intervention with the tract solutions at a later stage and thus facilitates the application of tractography to large studies. The trac-all script is used to preprocess raw diffusion data (correcting for eddy current distortion and B0 field inhomogenities), register them to common spaces, model and reconstruct major white matter pathways (included in the atlas) without any manual intervention. trac-all may be used to execute all the above steps or parts of it depending on the dataset and user''''s preference for analyzing diffusion data. Alternatively, scripts exist to execute chunks of each processing pipeline, and individual commands may be run to execute a single processing step. To explore all the options in running trac-all please refer to the trac-all wiki. In order to use this script to reconstruct tracts in Diffusion images, all the subjects in the dataset must have Freesurfer Recons.

Proper citation: TRACULA (RRID:SCR_013152) Copy   

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http://www.omicsdi.org/

Portal for dataset discovery across a heterogeneous, distributed group of transcriptomics, genomics, proteomics and metabolomics data resources. These resources span eight repositories in three continents and six organisations, including both open and controlled access data resources.

Proper citation: Omics Discovery Index (RRID:SCR_010494) Copy   

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

A software application developed to support computational anatomy and shape analysis. The capabilities of CAWorks include: interactive landmark placement to create segmentation (mask) of desired region of interest; specialized landmark placement plugins for subcortical structures such as hippocampus and amygdala; support for multiple Medical Imaging data formats, such as Nifti, Analyze, Freesurfer, DICOM and landmark data; Quadra Planar view visualization; and shape analysis plugin modules, such as Large Deformation Diffeomorphic Metric Mapping (LDDMM). Specific plugins are available for landmark placement of the hippocampus, amygdala and entorhinal cortex regions, as well as a browser plugin module for the Extensible Neuroimaging Archive Toolkit.

Proper citation: CAWorks (RRID:SCR_014185) Copy   

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https://github.com/kstreet13/slingshot

Software R package for identifying and characterizing continuous developmental trajectories in single cell data. Cell lineage and pseudotime inference for single-cell transcriptomics.

Proper citation: Slingshot (RRID:SCR_017012) Copy   

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https://knightadrc.wustl.edu/professionals-clinicians/request-center-resources/

Provides on request resources including Data: clinical and cognitive measures as well as MRI and amyloid imaging scans; Tissue: frozen brain tissue, paraffin brain sections, antemortem CSF, DNA, fibroblast, dermal fibroblasts, plasma (fasting and non-fasting) and iPSC; Participants: eligible participants may be invited to enroll in research of other investigators after appropriate review. Researchers can use the request portal to review Center guidelines and policies; view available data and tissue; access data tables and codebooks; and submit request for resources.

Proper citation: Washington University School of Medicine Knight ADRC Request Center Resources Core Facility (RRID:SCR_025254) Copy   

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https://github.com/bsml320/Scupa/

Software R package for immune cell polarization assessment of scRNA-seq data. Single-cell unified polarization assessment of immune cells using single-cell foundation model. Used for comprehensive immune cell polarization analysis.

Proper citation: Scupa (RRID:SCR_025755) Copy   

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https://pypi.org/project/SpaGCN/

Software graph convolutional network to integrate gene expression and histology to identify spatial domains and spatially variable genes. SpaGCN integrates information from gene.

Proper citation: SpaGCN (RRID:SCR_025978) Copy   

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https://github.com/cafferychen777/ggpicrust2

Software R package for analyzing and interpreting results of PICRUSt2 functional prediction. Offers range of features, including pathway name/description annotations, advanced differential abundance methods, and visualization of differential abundance results. Used for PICRUSt2 predicted functional profile analysis and visualization.

Proper citation: ggpicrust2 (RRID:SCR_025965) Copy   

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https://github.com/j-rub/scVital

Software tool to embed scRNA-seq data into species-agnostic latent space to overcome batch effect and identify cell states shared between species. Deep learning algorithm for cross-species integration of scRNA-seq data.

Proper citation: scVital (RRID:SCR_026215) Copy   

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https://www.c4r-nih.org

Portal provides information about nationwide study of more than 50,000 individuals to determine factors that predict disease severity and long-term health impacts of COVID-19.

Proper citation: Collaborative Cohort of Cohorts for COVID-19 Research (RRID:SCR_026322) Copy   

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https://github.com/Washington-University/HCPpipelines

Software package as set of tools, primarily shell scripts, for processing multi-modal, high-quality MRI images for the Human Connectome Project. Minimal preprocessing pipelines for structural, functional, and diffusion MRI that were developed by the HCP to accomplish many low level tasks, including spatial artifact/distortion removal, surface generation, cross-modal registration, and alignment to standard space.

Proper citation: HCP Pipelines (RRID:SCR_026575) Copy   

•   Source: SciCrunch Registry