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http://epi.grants.cancer.gov/CFR/

The Breast Cancer Family Registry (Breast CFR) and the Colon Cancer Family Registry (Colon CFR) were established by the National Cancer Institute (NCI) as a unique resource for investigators to use in conducting studies on the genetics and molecular epidemiology of breast and colon cancer. Known collectively as the CFRs, they share a central goal: the translation of research to the clinical and prevention settings for the benefit of Registry participants and the general public. The CFRs are particularly interested in: * Identifying and characterizing cancer susceptibility genes; * Defining gene-gene and gene-environment interactions in cancer etiology; and * Exploring the translational, preventive, and behavioral implications of research findings. The CFRs do not provide funding for studies; however, researchers can apply to access CFR data and biospecimens contributed by thousands of families from across the spectrum of risk for these cancers and from population-based or relative controls. Special features of the CFRs include: * Population-based and clinic-based ascertainment; * Systematic collection of validated family history; * Epidemiologic risk factor , clinical, and followup data; * Biospecimens (including tumor blocks and Epstein-Barr virus (EBV)-transformed cell lines); * Ongoing molecular characterization of the participating families; and * A combined informatics center.

Proper citation: NCI Breast and Colon Cancer Family Registries (RRID:SCR_006664) Copy   

•   Source: SciCrunch Registry

http://rulai.cshl.edu/cgi-bin/tools/ESE3/esefinder.cgi?process=home

A web-based resource that facilitates rapid analysis of exon sequences to identify putative exonic splicing enhancers (ESEs) responsive to the human SR proteins SF2/ASF, SC35, SRp40 and SRp55, and to predict whether exonic mutations disrupt such elements.

Proper citation: ESEfinder 3.0 (RRID:SCR_007088) Copy   

•   Source: SciCrunch Registry

http://proteogenomics.musc.edu/ma/arrayQuest.php?page=home&act=manage

A web-accessible program for the analysis of DNA microarray data. ArrayQuest is designed to apply any type of DNA microarray analysis program executable on a Linux system (i.e., Bioconductor statistical and graphical methods written in R as well as BioPerl and C++ based scripts) to DNA microarray data stored in the MUSC DNA Microarray Database, the Gene Expression Omnibus (GEO) or in a password protected private database uploaded to the center point server. ArrayQuest analyses are performed on a computer cluster.

Proper citation: ArrayQuest (RRID:SCR_010935) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/whs-sd-atlas/

Open access volumetric atlas of anatomical delineations of rat brain based on structural contrast in isotropic magnetic resonance and diffusion tensor images acquired ex vivo from 80 day old male Sprague Dawley rat at Duke Center for In Vivo Microscopy. Spatial reference is provided by Waxholm Space coordinate system. Location of bregma and lambda are identified as anchors towards stereotaxic space. Application areas include localization of signal in non structural images. Atlas, MRI and DTI volumes, and diffusion tensor data are shared in NIfTI format.

Proper citation: Waxholm Space Atlas of the Sprague Dawley Rat Brain (RRID:SCR_017124) Copy   

•   Source: SciCrunch Registry

http://www.midasplatform.org/

Open-source toolkit that enables the rapid creation of tailored, web-enabled data storage and provides a cohesive system for data management, visualization, and processing. At its core, Midas Platform is implemented as a PHP modular framework with a backend database (PostGreSQL, MySQL and non-relational databases). While the Midas Platform system can be installed and deployed without any customization, the framework has been designed with customization in mind. As building one system to fit all is not optimal, the framework has been extended to support plugins and layouts. Through integration with a range of other open-source toolkits, applications, or internal proprietary workflows, Midas Platform offers a solid foundation to meet the needs of data-centric computing. Midas Platform provides a variety of data access methods, including web, file system and DICOM server interfaces, and facilitates extending the methods in which data is stored to other relational and non-relational databases.

Proper citation: Midas Platform (RRID:SCR_002186) Copy   

•   Source: SciCrunch Registry

https://cibersort.stanford.edu/

Software tool to provide an estimation of the abundances of member cell types in a mixed cell population, using gene expression data. Used for characterizing cell composition of complex tissues from their gene expression profiles, large scale analysis of RNA mixtures for cellular biomarkers and therapeutic targets.

Proper citation: CIBERSORT (RRID:SCR_016955) Copy   

•   Source: SciCrunch Registry

https://sourceforge.net/projects/saint-apms/files/

Software tool for upgraded implementation of probabilistic scoring of affinity purification mass spectrometry data. Used for filtering high confidence interaction data from affinity purification mass spectrometry experiments. Used for assigning confidence scores to protein-protein interactions based on quantitative proteomics data in AP-MS experiments.

Proper citation: SAINTexpress (RRID:SCR_018562) Copy   

•   Source: SciCrunch Registry

https://github.com/JonathanIrish/MEMv3

Software tool to calculate enrichment scores. Generates human and machine readable labels that quantify features enriched in sample. Used to identify multiple populations of cells and to compare each population to all of other remaining cells from original sample.

Proper citation: Marker Enrichment Modeling (RRID:SCR_022495) Copy   

•   Source: SciCrunch Registry

https://cellrank.readthedocs.io/en/stable/

Software package for directed single cell fate mapping in diverse scenarios, including regeneration, reprogramming and disease. Automatically detects initial, intermediate and terminal populations, predicts fate potentials and visualizes continuous gene expression trends along individual lineages. Applied to lineage traced cellular reprogramming data, predicted fate probabilities correctly recover reprogramming outcomes.

Proper citation: CellRank (RRID:SCR_022827) Copy   

•   Source: SciCrunch Registry

https://mcmicro.org

Software tool as scalable, modular image processing pipeline for multiplexed tissue imaging. Transforms multi channel whole slide images into single cell data.

Proper citation: MCMICRO (RRID:SCR_022832) Copy   

•   Source: SciCrunch Registry

https://github.com/mhammell-laboratory/TEtranscripts

Software package for including transposable elements in differential enrichment analysis of sequencing datasets. Used for including transposable elements in differential expression analysis of RNA-seq datasets. RNAseq TE quantification tool.

Proper citation: TEtranscripts (RRID:SCR_023208) Copy   

•   Source: SciCrunch Registry

https://www.roswellpark.edu/shared-resources/gene-targeting-and-transgenic

Facility which provides researchers with transgenic mouse technologies, methods, and animal models. Knockout mice, transgenic mice, and mice on multiple strain backgrounds are provided.

Proper citation: RPCI Gene Targeting and Transgenic Shared Resource (RRID:SCR_001020) Copy   

•   Source: SciCrunch Registry

http://www.broad.mit.edu/mpr/lung

Data set of a molecular taxonomy of lung carcinoma, the leading cause of cancer death in the United States and worldwide. Using oligonucleotide microarrays, researchers analyzed mRNA expression levels corresponding to 12,600 transcript sequences in 186 lung tumor samples, including 139 adenocarcinomas resected from the lung. Hierarchical and probabilistic clustering of expression data defined distinct sub-classes of lung adenocarcinoma. Among these were tumors with high relative expression of neuroendocrine genes and of type II pneumocyte genes, respectively. Retrospective analysis revealed a less favorable outcome for the adenocarcinomas with neuroendocrine gene expression. The diagnostic potential of expression profiling is emphasized by its ability to discriminate primary lung adenocarcinomas from metastases of extra-pulmonary origin. These results suggest that integration of expression profile data with clinical parameters could aid in diagnosis of lung cancer patients.

Proper citation: Classification of Human Lung Carcinomas by mRNA Expression Profiling Reveals Distinct Adenocarcinoma Sub-classes (RRID:SCR_003010) Copy   

•   Source: SciCrunch Registry

http://www.census.gov/did/www/nlms/

A database based on a random sample of the noninstitutionalized population of the United States, developed for the purpose of studying the effects of demographic and socio-economic characteristics on differentials in mortality rates. It consists of data from 26 U.S. Current Population Surveys (CPS) cohorts, annual Social and Economic Supplements, and the 1980 Census cohort, combined with death certificate information to identify mortality status and cause of death covering the time interval, 1979 to 1998. The Current Population Surveys are March Supplements selected from the time period from March 1973 to March 1998. The NLMS routinely links geographical and demographic information from Census Bureau surveys and censuses to the NLMS database, and other available sources upon request. The Census Bureau and CMS have approved the linkage protocol and data acquisition is currently underway. The plan for the NLMS is to link information on mortality to the NLMS every two years from 1998 through 2006 with research on the resulting database to continue, at least, through 2009. The NLMS will continue to incorporate data from the yearly Annual Social and Economic Supplement into the study as the data become available. Based on the expected size of the Annual Social and Economic Supplements to be conducted, the expected number of deaths to be added to the NLMS through the updating process will increase the mortality content of the study to nearly 500,000 cases out of a total number of approximately 3.3 million records. This effort would also include expanding the NLMS population base by incorporating new March Supplement Current Population Survey data into the study as they become available. Linkages to the SEER and CMS datasets are also available. Data Availability: Due to the confidential nature of the data used in the NLMS, the public use dataset consists of a reduced number of CPS cohorts with a fixed follow-up period of five years. NIA does not make the data available directly. Research access to the entire NLMS database can be obtained through the NIA program contact listed. Interested investigators should email the NIA contact and send in a one page prospectus of the proposed project. NIA will approve projects based on their relevance to NIA/BSR''s areas of emphasis. Approved projects are then assigned to NLMS statisticians at the Census Bureau who work directly with the researcher to interface with the database. A modified version of the public use data files is available also through the Census restricted Data Centers. However, since the database is quite complex, many investigators have found that the most efficient way to access it is through the Census programmers. * Dates of Study: 1973-2009 * Study Features: Longitudinal * Sample Size: ~3.3 Million Link: *ICPSR: http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/00134

Proper citation: National Longitudinal Mortality Study (RRID:SCR_008946) Copy   

•   Source: SciCrunch Registry

http://www.med.upenn.edu/genetics/dnaseq/index.shtml

Core facility that provides the following services: Large sequencing project support, Sanger sequencing service, High throughput DNA sequencing, Ion Torrent Personal Genome Machine sequencing, Template preparation and purification, Roche 454 sequencing, Sequence analysis and database search support, Construction of targeting vector for gene targeting, Genotyping and Fragment Analysis service, Molecular biology services, Mouse genotyping, and Ion Personal Genome Machine sequencing data analysis. The DNA Sequencing Facility provides long read, automated Sanger sequencing; microsatellite-based genotyping and fragment analysis; plasmid and BAC DNA preparation and purification; and related molecular biological services including PCR, cloning, sub-cloning, site-directed mutagenesis, and preparation of targeting vectors for gene targeting in mice. Core also provides services and support for analysis and interpretation of sequence data as well as the design of approaches to complex sequencing projects. For the last four years the facility has been providing Roche 454 sequencing service that includes library preparation, emulsion PCR and pyrosequencing for both genomic DNA and amplicons.

Proper citation: University of Pennsylvania Genomics Analysis Core (RRID:SCR_011061) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

https://www.moffitt.org/research-science/shared-resources/tissue/

Biorepository resource with mission of proper collection, handling, processing and storage of irreplaceable biological specimens to support spectrum of related basic science, translational and clinical research. Provides expertise in nucleic acid extractions, quantification, aliquoting and quality assurance; liquid specimen centrifugation, processing and aliquoting; histological tissue processing, immunohistochemistry and tissue microarray microtomy; pathologist consultation services. Tissue Core operations are divided into four distinct pillars of service that work collaboratively to ensure specimen quality is maintained from procurement to preservation.

Proper citation: Moffitt Cancer Center Tissue Core Facility (RRID:SCR_012364) Copy   

•   Source: SciCrunch Registry

https://www.mskcc.org/research/ski/core-facilities/monoclonal-antibody-core-facility

ABCF can provide MAbs from established hybridomas for RESEARCH PURPOSES ONLY, can assist in generating MAbs, offers a weekly mycoplasmal contamination screening service for tissue culture samples, distributes cell lines developed at Memorial Sloan Kettering Cancer Center and Rockefeller University.

Proper citation: Memorial Sloan Kettering Cancer Center Antibody and Bioresource Core Facility (RRID:SCR_017691) Copy   

•   Source: SciCrunch Registry

http://mass-spec.stanford.edu

Core mass spec and proteomic services include open access lab for trained users with GC/MS, LC/MS, high resolution LC/MS, and MALDI-TOF instruments, help with intact protein analysis, targeted quantitation, drug discovery support, pathway analysis, protein interactions, FFPE tissue analysis, both labeled and label-free proteomics, and more. Please contact SUMS to discuss these and other custom projects including new application development.

Proper citation: Stanford University Vincent Coates Foundation Mass Spectrometry Laboratory Core Facility (RRID:SCR_017801) Copy   

•   Source: SciCrunch Registry

http://rhlccflow.facilities.northwestern.edu

Provides 6 cell sorters and 5 benchtop analyzers. Helps investigators to define their projects in the early stages of development to make optimal and efficient use of flow cytometry. Educates ALL users (faculty and staff) in the science and technology of flow cytometry.

Proper citation: Northwestern University Cancer Center Flow Cytometry Core Facility (RRID:SCR_017766) Copy   

•   Source: SciCrunch Registry