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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://cerad.mc.duke.edu/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 4, 2023.Consortium that developed brief, standardized and reliable procedures for the evaluation and diagnosis of patients with Alzheimer's disease (AD) and other dementias of the elderly. These procedures included data forms, flipbooks, guidebooks, brochures, instruction manuals and demonstration tapes, which are now available for purchase. The CERAD assessment material can be used for research purposes as well as for patient care. CERAD has developed several basic standardized instruments, each consisting of brief forms designed to gather data on normal persons as well as on cognitively impaired or behaviorally disturbed individuals. Such data permit the identification of dementia based on clinical, neuropsychological, behavioral or neuropathological criteria. Staff at participating CERAD sites were trained and certified to administer the assessment instruments and to evaluate the subjects enrolled in the study. Cases and controls were evaluated at entry and annually thereafter including (when possible) autopsy examination of the brain to track the natural progression of AD and to obtain neuropathological confirmation of the clinical diagnosis. The CERAD database has become a major resource for research in Alzheimer's disease. It contains longitudinal data for periods as long as seven years on the natural progression of the disorder as well as information on clinical and neuropsychological changes and neuropathological manifestations., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: CERAD - Consortium to Establish a Registry for Alzheimer's Disease (RRID:SCR_003016) Copy   

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http://www.demogr.mpg.de/databases/ktdb/

A database that includes data on death counts and population counts classified by sex, age, year of birth, and calendar year for more than 30 countries. This database was established for estimating the death rates at the highest ages (above age 80). The core set of data in the database was assembled, tested for quality, and converted into cohort mortality histories by V��in�� Kannisto, the former United Nations advisor on demographic and social statistics. Comparable materials on England and Wales, was made available by A. Roger Thatcher, the former Director of the Office of Population Censuses and Surveys and Registrar-General of England and Wales (Kannisto, 1994). The Kannisto-Thatcher database was computerized under the supervision of James W. Vaupel at the Aging Research Unit of the Centre for Health and Social Policy at Odense University Medical School in 1993. Currently, the database is maintained by the Max Planck Institute for Demographic Research, Germany.

Proper citation: Kannisto-Thatcher Database on Old Age Mortality (RRID:SCR_008936) Copy   

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http://www.icpsr.umich.edu/icpsrweb/NACDA/Pledge/all.jsp

A data set of cross-nationally comparable microdata samples for 15 Economic Commission for Europe (ECE) countries (Bulgaria, Canada, Czech Republic, Estonia, Finland, Hungary, Italy, Latvia, Lithuania, Romania, Russia, Switzerland, Turkey, UK, USA) based on the 1990 national population and housing censuses in countries of Europe and North America to study the social and economic conditions of older persons. These samples have been designed to allow research on a wide range of issues related to aging, as well as on other social phenomena. A common set of nomenclatures and classifications, derived on the basis of a study of census data comparability in Europe and North America, was adopted as a standard for recoding. This series was formerly called Dynamics of Population Aging in ECE Countries. The recommendations regarding the design and size of the samples drawn from the 1990 round of censuses envisaged: (1) drawing individual-based samples of about one million persons; (2) progressive oversampling with age in order to ensure sufficient representation of various categories of older people; and (3) retaining information on all persons co-residing in the sampled individual''''s dwelling unit. Estonia, Latvia and Lithuania provided the entire population over age 50, while Finland sampled it with progressive over-sampling. Canada, Italy, Russia, Turkey, UK, and the US provided samples that had not been drawn specially for this project, and cover the entire population without over-sampling. Given its wide user base, the US 1990 PUMS was not recoded. Instead, PAU offers mapping modules, which recode the PUMS variables into the project''''s classifications, nomenclatures, and coding schemes. Because of the high sampling density, these data cover various small groups of older people; contain as much geographic detail as possible under each country''''s confidentiality requirements; include more extensive information on housing conditions than many other data sources; and provide information for a number of countries whose data were not accessible until recently. Data Availability: Eight of the fifteen participating countries have signed the standard data release agreement making their data available through NACDA/ICPSR (see links below). Hungary and Switzerland require a clearance to be obtained from their national statistical offices for the use of microdata, however the documents signed between the PAU and these countries include clauses stipulating that, in general, all scholars interested in social research will be granted access. Russia requested that certain provisions for archiving the microdata samples be removed from its data release arrangement. The PAU has an agreement with several British scholars to facilitate access to the 1991 UK data through collaborative arrangements. Statistics Canada and the Italian Institute of statistics (ISTAT) provide access to data from Canada and Italy, respectively. * Dates of Study: 1989-1992 * Study Features: International, Minority Oversamples * Sample Size: Approx. 1 million/country Links: * Bulgaria (1992), http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/02200 * Czech Republic (1991), http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/06857 * Estonia (1989), http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/06780 * Finland (1990), http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/06797 * Romania (1992), http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/06900 * Latvia (1989), http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/02572 * Lithuania (1989), http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/03952 * Turkey (1990), http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/03292 * U.S. (1990), http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/06219

Proper citation: Census Microdata Samples Project (RRID:SCR_008902) Copy   

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http://bloodexposome.org

Collection of chemical compounds and associated information that were automatically extracted by text mining content of PubMed and PubChem databases. Unifies chemical lists from metabolomics, systems biology, environmental epidemiology, occupational expossure, toxiology and nutrition fields.

Proper citation: Blood Exposome Database (RRID:SCR_017610) 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://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://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.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://github.com/kukionfr/VAMPIRE_open

Software tool for analysis of cell and nuclear morphology from fluorescence or bright field images. Enables profiling and classification of cells into shape modes based on equidistant points along cell and nuclear contours. Robust method to quantify cell morphological heterogeneity.

Proper citation: VAMPIRE (RRID:SCR_021721) Copy   

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Issue

https://www.nature.com/articles/nprot.2014.042

Software tool as scripts for calculating NMR chemical shifts. Warning - this group of Python scripts used to process NMR data, described in Willoughby et al, 2014, has been found to contain bug. Please see PMID:31591889.

Proper citation: Willoughby–Hoye Python Scripts A-D (RRID:SCR_017562) Copy   

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https://exrna-atlas.org

Software tool as data and metadata repository of Extracellular RNA Communication Consortium. Atlas includes small RNA sequencing and qPCR derived exRNA profiles from human and mouse biofluids. All RNAseq datasets are processed using version 4 of exceRpt small RNAseq pipeline. Atlas accepts submissions for RNAseq or qPCR data.

Proper citation: exRNA Atlas (RRID:SCR_017221) 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