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https://amp.pharm.mssm.edu/geneshot/

Software tool as search engine for ranking genes from arbitrary text queries. Enables to enter arbitrary search terms, to receive ranked lists of genes relevant to search terms. Returned ranked gene lists contain genes that were previously published in association with search terms, as well as genes predicted to be associated with terms based on data integration from multiple sources. Search results are presented with interactive visualizations.

Proper citation: Geneshot (RRID:SCR_017582) Copy   

•   Source: SciCrunch Registry

http://taylor0.biology.ucla.edu/structureHarvester/

Web based program for collating results generated by program STRUCTURE. Provides assess and visualize likelihood values across multiple values of K and hundreds of iterations for easier detection of number of genetic groups that best fit data. Reformats data for use in downstream programs, such as CLUMPP.It is complement for using software Structure in genetics population. Website and program for visualizing STRUCTURE output and implementing Evanno method., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Structure Harvester (RRID:SCR_017636) Copy   

•   Source: SciCrunch Registry

http://statistika.mfub.bg.ac.rs/interactive-linegraph/

Interactive web based tool for creating line graphs for scientific publications. Users can view different summary statistics, examine lines for any individual in data, focus on time points or groups of interest, and view changes between any two time points and conditions.

Proper citation: Interactive Line Graph (RRID:SCR_018334) Copy   

•   Source: SciCrunch Registry

https://cadd.gs.washington.edu/

Web tool for predicting deleteriousness of variants throughout human genome. Software tool for scoring deleteriousness of single nucleotide variants as well as insertion and deletions variants in human genome.

Proper citation: Combined Annotation Dependent Depletion (RRID:SCR_018393) Copy   

•   Source: SciCrunch Registry

https://geodacenter.github.io/

Software program for spatial analysis for non geographic information systems specialists. Includes functionality ranging from simple mapping to exploratory data analysis, visualization of global and local spatial autocorrelation, and spatial regression.

Proper citation: GeoDa (RRID:SCR_018559) Copy   

•   Source: SciCrunch Registry

https://delaney.shinyapps.io/FairSubset/

Web tool to choose representative subsets of data for use with replicates or groups of different sample sizes. Used to retain distribution information at single datum level and may be considered for standardized use in fair publishing practices.

Proper citation: FairSubset (RRID:SCR_019102) Copy   

•   Source: SciCrunch Registry

https://www.archrproject.com/

Software R package for processing and analyzing single-cell ATAC-seq data. Used for integrative single cell chromatin accessibility analysis.Provides intuitive, user focused interface for complex single cell analysis, including doublet removal, single cell clustering and cell type identification, unified peak set generation, cellular trajectory identification, DNA element-to-gene linkage, transcription factor footprinting, mRNA expression level prediction from chromatin accessibility and multi-omic integration with single-cell RNA sequencing.

Proper citation: ArchR (RRID:SCR_020982) Copy   

•   Source: SciCrunch Registry

http://amp.pharm.mssm.edu/L1000CDS2

LINCS L1000 characteristic direction signatures search engine. Software tool to find consensus signatures that match user’s input gene lists or input signatures. Underlying dataset is LINCS L1000 small molecule expression profiles generated at Broad Institute by Connectivity Map team. Differentially expressed genes of these profiles were calculated using multivariate method called Characteristic Direction.

Proper citation: L1000 Characteristic Direction Signature Search Engine (RRID:SCR_016177) Copy   

•   Source: SciCrunch Registry

http://amp.pharm.mssm.edu/Harmonizome/

Web application that allows for searching, visualization, and prediction about genes and proteins. It contains a collection of processed datasets gathered to serve and mine knowledge about genes and proteins from major online resources.

Proper citation: Harmonizome (RRID:SCR_016176) Copy   

•   Source: SciCrunch Registry

https://github.com/hakyimlab/PrediXcan

Software tool to detect known and novel genes associated with disease traits and provide insights into the mechanism of these associations. Used to test the molecular mechanisms through which genetic variation affects phenotype.

Proper citation: PrediXcan (RRID:SCR_016739) 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

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

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://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

http://chtn.nci.nih.gov

The Cancer Diagnosis Program of the National Cancer Institute (NCI) initiated the Cooperative Human Tissue Network (CHTN) in 1987 to provide increased access to human tissue for basic and applied scientists from academia and industry to accelerate the advancement of discoveries in cancer diagnosis and treatment. This unique resource provides remnant human tissues and fluids from routine procedures to investigators who utilize human biospecimens in their research. Unlike tissue banks, the CHTN works prospectively with each investigator to tailor specimen acquisition and processing to meet their specific project requirements. Because the CHTN is funded by the NCI, the CHTN is able to maintain nominal processing fees for its services. The CHTN is comprised of five adult divisions and one pediatric division. Each of the adult divisions coordinates investigator applications/requests based upon the investigator's geographic location within North America. The Pediatric Division manages all investigators who request pediatric specimens only. The CHTN divisions share coordination for requests from outside North America. The CHTN divisions work both independently with individual investigators and together as a seamless unit to fulfill requests that are difficult to serve by any single division. The CHTN's unique informatics system allows each division to effectively communicate and network the needs of its investigators to all CHTN divisions. The Network as a whole can then help fulfill an investigator's request. Biospecimens from surgeries, autopsies and other routine procedures: Malignant, Benign, Diseased, Normal, Biofluids (urine, serum, plasma, buffy coat) High quality specimens at LOW processing fees: Fresh, Frozen, Floating in fixative, RNAlater, Paraffin embedded or and/or unstained slides, THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Cooperative Human Tissue Network (RRID:SCR_004446) Copy   

•   Source: SciCrunch Registry

https://htrn.osu.edu/Services/Biorepository/Pages/default.aspx

The HTRN biospecimen bank is comprised of samples for the Ohio State University Cancer and Leukemia Group B Pathology Coordinating Office (CALGB-PCO) and the Ohio State University Midwestern Division of the Cooperative Human Tissue Network (CHTN). The CALGB-PCO banks biospecimens donated by patients enrolled in clinical trials. Samples can include tumor and normal tissue, plasma, serum, whole blood and white blood cells and urine. All of these samples are used later in correlative studies. The Midwestern Division of the CHTN stores a temporary biospecimen bank of tumor and normal tissue, tissue slides and paraffin embedded tissue blocks for research investigators throughout the country and Canada who are trying to find a cure for cancer. As part of the HTRN biospecimen bank, a Rees Scientific equipment monitoring system helps to secure the integrity and quality of samples stored in the biorepository. Scientific research within the HTRN is currently underway to determine the best methods in tissue storage for long term use. The NCI First-Generation Guidelines for NCI-Supported Biorepositories and the NCI Best Practices for Biospecimen Resources are continuously reviewed and adapted by the HTRN.

Proper citation: Ohio State Biorepository (RRID:SCR_004714) Copy   

•   Source: SciCrunch Registry

http://pilgrm.princeton.edu

PILGRM (the platform for interactive learning by genomics results mining) puts advanced supervised analysis techniques applied to enormous gene expression compendia into the hands of bench biologists. This flexible system empowers its users to answer diverse biological questions that are often outside of the scope of common databases in a data-driven manner. This capability allows domain experts to quickly and easily generate hypotheses about biological processes, tissues or diseases of interest. Specifically PILGRM helps biologists generate these hypotheses by analyzing the expression levels of known relevant genes in large compendia of microarray data. PILGRM is for the biologist with a set of proteins relevant to a disease, biological function or tissue of interest who wants to find additional players in that process. It uses a data driven method that provides added value for literature search results by mining compendia of publicly available gene expression datasets using lists of relevant and irrelevant genes (standards). PILGRM produces publication quality PDFs usable as supplementary material to describe the computational approach, standards and datasets. Each PILGRM analysis starts with an important biological question (e.g. What genes are relevant for breast cancer but not mammary tissue in general?). For PILGRM to discover relevant genes, it needs examples of both genes that you would (positive) and would not (negative) find interesting. Lists of these genes are what we call standards and in PILGRM you can build your own standards or you can use standards from common sources that we pre-load for your convenience. PILGRM lets you build your own literature-documented standards so that processes, disease, and tissues that are not well covered in databases of tissue expression, disease, or function can still be used for an analysis.

Proper citation: PILGRM (RRID:SCR_004749) Copy   

•   Source: SciCrunch Registry

http://cancer.case.edu/sharedresources/tissue/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 11, 2023. The Case Comprehensive Cancer Center''s Biorepository and Tissue Processing Core Facility (BTPC) serves two primary functions: 1. To build an inventory of remnant human tissues, blood and other body fluids (collectively termed biospecimens) targeted towards cancer and other medical research, for later assignment to investigators; and 2. To provide long term, controlled storage of biospecimens for specific researchers. These samples are for research purposes only and may not be used for clinical diagnosis or implantation into humans. Clinical information relating to the samples and donors are collected and maintained in a secure database. Samples and data are de-identified or de-linked before release to the researcher unless he/she has specific IRB approval to gain access to this information. Remnant biospecimens are prospectively collected from surgical procedures, autopsies and clinical laboratories for the BTPC by the Human Tissue Procurement Facility (HTPF), which operates under UH-IRB Protocol 01-02-45. Blood and bone marrow specimens are collected for the BTPC by the Hematopoietic Stem Cell Core Facility (HSCC), which operates under UH-IRB Protocol 09-90-195. The Division of Surgical Pathology at University Hospitals Case Medical Center (UHCMC) has clinical archives of paraffin blocks that can be made available through the BTPC for retrospective research studies under the approval of the Vice Chair for Clinical Affairs at UHCMC. Surgical Pathologists associated with the BTPC are responsible for determining which blocks can be made available and how much material can be removed from the blocks. Types of Tissue Available * Malignant, benign, diseased, normal and normal human tissues * Normal adjacent tissues available paired with tumor specimens in many cases * Tissues are collected from over 50 anatomic sites * Frozen specimens, OCT-embedded and paraffin-embedded tissues * Large array of paraffin-embedded specimens from clinical archives of paraffin blocks and QC research blocks maintained by the HTPF * Peripheral blood and bone marrow samples from initial visits and follow-up procedures are processed to obtain serum and cell fractions for storage * No samples are collected from individuals with known infectious illnesses * Fetal biospecimens are not collected due to state and local statutes

Proper citation: Case Comprehensive Cancer Center Biorepository and Tissue Processing Core Facility (RRID:SCR_004382) Copy   

•   Source: SciCrunch Registry

http://www.uclaaidsinstitute.org/researchareas/clinical_malignancy.php

THIS RESOURCE IS NO LONGER IN SERVICE, documented on February 27, 2012. The National Cancer Institute established centers in the United States and its territories for the collection and distribution of tissues, blood and secretions from patients with clinically-characterized AIDS related malignancies in 1994. The AIDS Malignancy Bank makes these tissues available to qualified investigators in the United States for research on AIDS malignancies. It is hoped that by providing access to these high-quality specimens, research in AIDS-related malignancies will be encouraged and expanded. The AMB contains formalin-fixed paraffin-embedded tissues, fresh-frozen tissues, malignant-cell suspensions, fine-needle aspirates, and cell lines from AIDS-related malignancies. The bank also contains serum, plasma, urine, bone marrow, cervical secretions, anal swabs, saliva semen and multi-site autopsy tissues from patients with AIDS-related malignancies who have participated in clinical trials. The bank has an associated database that contains prognostic, staging, outcome and treatment data on patients from whom tissues were obtained. Researchers pay for preparation and shipping of specimens.

Proper citation: AIDS Malignancy Bank (RRID:SCR_004417) Copy   

•   Source: SciCrunch Registry

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