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http://brainmap.wisc.edu/monkey.html

NO LONGER AVAILABLE. Documented on September 17, 2019. A set of multi-subject atlas templates to facilitate functional and structural imaging studies of the rhesus macaque. These atlases enable alignment of individual scans to improve localization and statistical power of the results, and allow comparison of results between studies and institutions. This population-average MRI-based atlas collection can be used with common brain mapping packages such as SPM or FSL.

Proper citation: Rhesus Macaque Atlases for Functional and Structural Imaging Studies (RRID:SCR_008650) Copy   

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http://www.nia.nih.gov/research/blog

Blog intended for grantees of the National Institute on Aging (NIA) at the NIH, as well as applicants for funding, those with an application in mind, application reviewers, and students pursuing careers in research on aging and Alzheimer's disease.

Proper citation: Inside NIA: A Blog for Researchers (RRID:SCR_012812) Copy   

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

Atlas for studies of older adult brain. Includes T1-weighted template of older adult brain and tissue probability maps. Exhibits high image sharpness, provides higher inter-subject spatial normalization accuracy compared to other standardized templates and similar normalization accuracy to well-constructed study-specific templates.

Proper citation: MIITRA atlas (RRID:SCR_017566) Copy   

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https://alzped.nia.nih.gov

Publicly available, searchable, data resource that aims to increase transparency, reproducibility and translatability of preclinical efficacy studies of candidate therapeutics for Alzheimer’s disease. Knowledge platform for dissemination of data and analysis to scientists, from academic centers, industry, disease focused foundations. Provides quick access and visibility to integrated preclinical efficacy data from published and unpublished studies.

Proper citation: Alzheimer Disease Preclinical Efficacy Database (RRID:SCR_021230) Copy   

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https://github.com/nskvir/RepEnrich

Software tool to profile enrichment of next generation sequencing reads at transposable elements. Method to estimate repetitive element enrichment using high throughput sequencing data. Used to study genome wide transcriptional regulation of repetitive elements.RepEnrich2 is updated method to estimate repetitive element enrichment using high-throughput sequencing data.

Proper citation: RepEnrich (RRID:SCR_021733) Copy   

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https://github.com/evarol/HYDRA

Software tool as novel non-linear learning algorithm for simultaneous binary classification and subtype identification. Can handle imaging and non-imaging data and can find applications in exploratory analyses other than clustering of brain images.Software performs clustering of heterogenous disease patterns within patient group.

Proper citation: Heterogeneity through Discriminative Analysis (RRID:SCR_021958) Copy   

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https://lsom.uthscsa.edu/dcsa/research/cores-facilities/optical-imaging/

Service resource which makes imaging technology available to investigators on UTHSCSA campus and neighboring scientific community. Core Optical Imaging Facility offers access to technology for imaging of living cells, tissues, and animals, consultation, education and assistance regarding theory and application of optical imaging techniques, technical advice on specimen preparation techniques and probe selection.

Proper citation: Texas University Health Science Center at San Antonio Long School of Medicine Department of Cell Systems and Anatomy Optical Imaging Core Facility (RRID:SCR_012171) Copy   

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https://masst.gnps2.org/microbemasst/

Web taxonomically informed mass spectrometry search tool, tackles limited microbial metabolite annotation in untargeted metabolomics experiments. Leveraging database of over 60,000 microbial monocultures, users can search known and unknown MS/MS spectra and link them to their respective microbial producers via MS/MS fragmentation patterns.

Proper citation: microbeMASST (RRID:SCR_024713) Copy   

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

Software for the analysis of multiple diffusion properties along fiber bundle as functions in an infinite dimensional space and their association with a set of covariates of interest, such as age, diagnostic status and gender, in real applications. The resulting analysis pipeline can be used for understanding normal brain development, the neural bases of neuropsychiatric disorders, and the joint effects of environmental and genetic factors on white matter fiber bundles.

Proper citation: Functional Regression Analysis of DTI Tract Statistics (RRID:SCR_002293) Copy   

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http://picsl.upenn.edu/software/histolozee/

Software tool that integrates histology reconstruction, MRI co-registration, and manual segmentation tools in easy-to-use and intuitive interface. Permits real-time interaction with complex and large histology datasets during co-registration steps of histology reconstruction. Software tool for interactively mapping 2D and 3D molecular and anatomical histology into Common Coordinate Frameworks. Has simple, interactive registration workflows that connect user images with CCFs.

Proper citation: HistoloZee (RRID:SCR_019263) Copy   

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https://miracl.readthedocs.io/en/latest/

Automated software resource that combines histologically cleared volumes with connectivity atlases and MRI, enabling analysis of histological features across multiple fiber tracts and networks, and their correlation with in vivo biomarkers.Multimodal image registration and connectivity analysis for integration of connectomic data from microscopy to MRI. Open source pipeline for automated registration of mice clarity data to Allen reference atlas, segmentation and feature extraction of mice clarity data in 3D, registration of mice multimodal imaging data to Allen reference atlas, tract or label specific connectivity analysis based on Allen connectivity atlas,comparison of diffusion tensort imaging/tractography, virus tracing using CLARITY and Allen connectivity atlas, statistical analysis of CLARITY and Imaging data, atlas generation and label manipulation.

Proper citation: MIRACL (RRID:SCR_020945) Copy   

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https://github.com/parklab/NGSCheckMate

Software package for validating sample identity in next generation sequencing studies within and across data types. Used for identifying next generation sequencing data files from the same individual. Used for checking sample matching for NGS data.

Proper citation: NGSCheckMate (RRID:SCR_022994) Copy   

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http://ki.se/en/meb/satsa-the-swedish-adoptiontwin-study-of-aging

Longitudinal twin study to understand individual differences in aging with corresponding data and biological samples. The twin design and the inclusion of twins reared apart makes it possible to study the importance of genetic and environmental factors that may underlie differing aging outcomes. Further, the broad spectrum of biological, psychological, and social domains assessed across the life span makes it possible to study patterns of change within and across domains and how these predict health and diseases of aging. The study is comprised of several longitudinal components including, a comprehensive questionnaire that was sent to all twins in the Swedish Twin Registry who were separated at an early age and reared apart and a control sample of twins reared together. The questionnaires include items concerning rearing, family, adult, and working environment, health status, health related behaviors (e.g. alcohol, tobacco, and dietary habits) as well as relationships, and personality measures. The questionnaires were sent again at 3 year intervals in 1987, 1990, 1993 and after a break again in 2004, 2007, and 2010. Thus far more than 2,000 twins have responded to at least one of the seven questionnaire assessments conducted between 1984 and 2010. Additionally there is information about midlife life style factors from the Swedish Twin Registry that were collected about twenty years before SATSA started. In the second component a subsample of 861 individuals have participated in at least one wave of in-person testing (IPT). The first IPT started in 1986 and since then eight IPTs have been collected and the last wave will be collected during 2012-2013. The IPT includes a health examination, structured interviews, tests of functional capacity, and memory and thinking abilities. To date, over 76% of the sample has participated in 3 or more measurement waves. At IPT9 a third component was added to SATSA, a measure of day-to-day fluctuations in memory and thinking abilities, and emotions. Information about social interactions is also collected. After the visit by the research nurses the twins fill out the day-to-day booklet during the next five days. This procedure will be repeated in IPT10. This will add information about small and short-term changes and more changes are supposed to indicate the beginning of poor health. Data from SATSA can be used to study various aspects of aging. For example, the relative importance of genetic and environmental factors for individual differences in aging especially in cognitive and physical domains has been studied. A further main focus is to study changes within and across domains and which genetic and life style factors predict these changes. Given the wide spectrum of data from measured genes to social relationships collected over more than two decades they dare to say that SATSA is a unique study, with the possibility to answer many questions within gerontology and geriatrics. Types of samples * Serum * DNA Number of sample donors: 674 (June 2010)

Proper citation: KI Biobank - SATSA (RRID:SCR_005966) Copy   

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http://www.nltcs.aas.duke.edu/index.htm

A data set of a longitudinal survey designed to study changes in the health and functional status of older Americans (aged 65+). It also tracks health expenditures, Medicare service use, and the availability of personal, family, and community resources for caregiving. The survey began in 1982, and follow-up surveys were conducted in 1984, 1989, 1994, 1999, and 2004. The surveys are of the entire Medicare-enrolled aged population with a particular emphasis on the functionally impaired. As sample persons are followed through the Medicare record system, virtually 100% of cases can be longitudinally tracked so that declines, as well as increases, in disability may be identified as well as exact dates of death. NLTCS sample persons are followed until death and are permanently and continuously linked to the Medicare record system from which they are drawn. Linkage to the Medicare Part A and B service use records extends from 1982 to 2004, so that detailed Medicare expenditures and types of service use may be studied. Through the careful application of methods to reduce non-sampling error, the surveys provide nationally representative data on: * The prevalence and patterns of functional limitations, both physical and cognitive; * Longitudinal and cohort patterns of change in functional limitation and mortality over 22 years; * Medical conditions and recent medical problems; * Health care services used; * The kind and amount of formal and informal services received by impaired individuals and how it is paid for; * Demographic and economic characteristics like age, race, sex, marital status, education, and income and assets; * Out-of-pocket expenditures for health care services and other sources of payment; * Housing and neighborhood characteristics. In each of the six surveys, large samples (N~20,000) of the oldest-old population (i.e., those 85 and over) are obtained. The survey data (i.e., detailed community and institutional interviews. The linkage to Medicare enrollment files between 1982 and 2004 was 100%, i.e., there was complete follow-up of all cases (including survey non-respondents) for Medicare eligibility (and for most years, detailed Part A and B use), mortality, and date of death. Medicare mortality records (and dates of death) are available for 1982 to 2005. The number of deaths (i.e., about 32,000 from 1982 to 2005) is large enough that detailed mortality analyses can be done. Over the 22 years spanned by the six surveys, a total of 49,242 distinct individuals were followed from and linked to Medicare records. Data Availability: The data are available through ICPSR as Study No. 9681. The data are available only on CD-ROM and only upon completion of a signed Data Use Agreement. Continuously linked Medicare data (1982 through 2004) for the National Long Term Care Surveys are only available from CMS. * Dates of Study: 1982-2004 * Study Features: Longitudinal, Anthropometric Measures * Sample Size: ** 1982: 20,485 ** 1984: 25,401 ** 1989: 17,565 ** 1994: 19,171 ** 1999: 19,907 ** 2004: 20,474 Link: * ICPSR: http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/09681

Proper citation: National Long Term Care Survey (RRID:SCR_008943) Copy   

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http://www.ohsu.edu/xd/research/centers-institutes/neurology/alzheimers/research/data-tissue/biomarkers-genetics.cfm

A center that works with the Oregon Alzheimer's Disease Center's Data Core, and collects and stores tissue samples, family history and genotype data of various populations. These include samples and data from subjects from the following sources: OADC clinical studies, the Oregon Brain Aging Study, the Community Brain Donor Program, the Preventing Cognitive Decline with Alternative Therapies program (informally called the Dementia Prevention Study or DPS), the African American Dementia and Aging Project, and the Klamath Exceptional Aging Project. The collected data samples include genomic DNA, lymphoblast cell lines, genome-wide and candidate region SNP marker data, APOE, AD candidate gene markers.

Proper citation: Layton Center Biomarkers and Genetics (RRID:SCR_008824) Copy   

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http://www.icpsr.umich.edu/icpsrweb/NACDA/studies/09915/version/3

A data set and sister study to the Established Populations for Epidemiologic Study of the Elderly (EPESE). It complements the findings of the three other EPESE sites (East Boston, MA; New Haven, CT; and north-central North Carolina) and has common items and methods in many domains. The target population was all persons 65 years and older in two rural counties in east central Iowa: Iowa and Washington counties. In 1981 a census of older persons in the target area was conducted by the investigators, creating an ascertainment list having 99% of the persons identified in the previous year by the US Decennial Census. The baseline survey was conducted between December 1991 and August 1992. Overall, 3,673 persons, or 80% of the target population were interviewed: 65-69 (N = 986), 70-74 (N = 988), 75-79 (N = 815), 80-84 (N = 523), and 85+ (N = 361). The population is virtually entirely Caucasian. Subsequently, personal follow-up surveys were conducted 3, 6, and 10 years after the baseline survey. Telephone surveys were conducted 1, 2, 4, 5, and 7 years after the baseline survey. Data collected from respondents included information about demographics, major health conditions, health care utilization, hearing and vision, weight and height, elements of nutrition, sleep problems, depressive and anxiety symptoms, alcohol and tobacco use, cognitive performance and dementia screening, incontinence measures, life satisfaction index, social networks and support, worries, medication use, activities of daily living, dental problems, satisfaction with medical care, life events, brief economic status, automobile driving habits, multiple measures of physical and disability status, and blood pressure. At follow-up #6, there were a series of physical function performance tests, the so-called NIA-MacArthur Battery, and blood was drawn for biochemical tests and potentially other determinations. In addition, some datasets were linked to the EPESE dataset under appropriate restrictions, including Iowa state driving records and clinical diagnoses and medical care utilization from the Centers for Medicare and Medicaid Services. Data Availability: The dataset has been shared with several investigative teams under special arrangement with the Principal Investigator. Early surveys are available from ICPSR. A small storage of blood is available for exploratory analyses. * Dates of Study: 1991-2001 * Study Features: Longitudinal, Anthropometric Measures, Biomarkers * Sample Size: 1991-2: 3,673 (baseline) Link: EPESE 1981-93 ICPSR: http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/09915

Proper citation: Iowa 65+ Rural Health Study (RRID:SCR_008937) Copy   

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http://www.norc.org/Research/Projects/Pages/national-social-life-health-and-aging-project.aspx

A longitudinal, population-based study of health and social factors, aiming to understand the well-being of older, community-dwelling Americans by examining the interactions among physical health and illness, medication use, cognitive function, emotional health, sensory function, health behaviors, social connectedness, sexuality, and relationship quality. NSHAP provides policy makers, health providers, and individuals with useful information and insights into these factors, particularly on social and intimate relationships. The study contributes to finding new ways to improve health as people age. In 2005 and 2006, NORC and Principal Investigators at the University of Chicago conducted the first wave of NSHAP, completing more than 3,000 interviews with a nationally representative sample of adults aged 57 to 85. In 2010 and 2011, nearly 3,400 interviews were completed for Wave 2 with these Wave 1 Respondents, Wave 1 Non-Interviewed Respondents, and their spouses or cohabiting romantic partners. The second wave of NSHAP is essential to understanding how social and biological characteristics change. NSHAP, by eliciting a variety of information from respondents over time, provides data that will allow researchers in a number of fields to examine how specific factors may or may not affect each other across the life course. For both waves, data collection included three measurements: in-home interviews, biomeasures, and leave-behind respondent-administered questionnaires. The face-to-face interviews and biomeasure collection took place in respondents'''' homes. NSHAP uses a national area probability sample of community residing adults born between 1920 and 1947 (aged 57 to 85 at the time of the Wave 1 interview), which includes an oversampling of African-Americans and Hispanics. The NSHAP sample is built on the foundation of the national household screening carried out by the Health and Retirement Study (HRS) in 2004. Through a collaborative agreement, HRS identified households for the NSHAP eligible population. A sample of 4,400 people was selected from the screened households. NSHAP made one selection per household. Ninety-two percent of the persons selected for the NSHAP interview were eligible. For Wave 2 in 2010 and 2011, NSHAP returned to Wave 1 Respondents and eligible non-interviewed respondents from Wave 1 (Wave 1 Non-Interviewed Respondents). NSHAP also extended the Wave 2 sample to include the cohabiting spouses and romantic partners of Wave 1 Respondents and Wave 1 Non-Interviewed Respondents. Partners were considered to be eligible to participate in NSHAP if they resided in the household with the Wave 1 Respondent/Wave 1 Non-Interviewed Respondent at the time of the Wave 2 interview and were at least 18 years of age. Wave I biomeasures: height; weight; waist circumference; blood pressure; smell; taste; vision; touch; respondent-administered vaginal swabs; oral mucosal transudate (OMT) for HIV-1 antibody screening; saliva; ����??get up and go����??; and blood spots. Technological advances in biomeasure collection methods have decreased respondent burden and increased ease of collection, storage, and yield of various biomeasures for the second wave of NSHAP. Wave II biomeasures: anthropometrics, including height, hip and waist circumference, and weight; cardiovascular function, including blood pressure, heart rate variability, and pulse; 2 of the 3 components of the short physical performance battery (SPPB) including chair stands and a timed walk; sensory function including smell; and actigraphy. In addition, we collect dried blood spots, microtainer blood, passive drool and salivettes, urine, and respondent-administered vaginal swabs, each of which are analyzed using multiple assays for a variety of measures and rationales. Furthermore, we assess respondents����?? cognition using the Montreal Cognitive Assessment (MoCA). Data Availability: NSHAP data made available to the public does not contain any identifiable respondent information and uses code numbers instead of names for all data. De-identified data from the 2005 and 2006 interviews are available to researchers through the National Archive of Computerized Data on Aging, located within Inter-University Consortium for Political and Social Research (ICPSR). Data from the Wave 2 interviews in 2010 and 2011 will be available in the summer of 2012. * Dates of Study: 2005-2006, 2010-2011 * Study Features: Biospecimens, Anthropometric Measures * Sample Size: ** Wave 1: 3,005 ** Wave 2: 3,377 Links: * ICPSR: http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/20541

Proper citation: National Social Life Health and Aging Project (NSHAP) (RRID:SCR_008950) Copy   

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https://github.com/dattalab/keypoint-moseq

Software application as machine learning-based platform for identifying behavioral modules from keypoint data without human supervision. Package provides tools for fitting MoSeq model to keypoint tracking data. Used to infer pose dynamics with keypoint data in addition to behavioral syllables.

Proper citation: Keypoint MoSeq (RRID:SCR_025032) Copy   

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https://fmug.amaral.northwestern.edu/

Software data-driven tool to identify understudied genes and characterize their tractability. Users submit list of human genes and can filter these genes down based on list of factors. Code to generate Find My Understudied Genes app for Windows, iOS and macOS platforms.

Proper citation: Find My Understudied Genes (RRID:SCR_025047) Copy   

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https://sea-ad.shinyapps.io/ACEapp/

Web application for comparing cell type assignments and other cell-based annotations (e.g., donor demographics, anatomic locations, batch variables, and quality control metrics). Used for connecting brain cell types across studies of health and Alzheimer's Disease.

Proper citation: Annotation Comparison Explorer (RRID:SCR_026496) Copy   

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