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https://med.stanford.edu/cancer/research/shared-resources/biostatistics_research_informatics.html

Core provides statistical support to SCI members by engages them on their data related needs. Specifically, BSR members assist researchers at each stage of study’s lifecycle, including project design, mid study evaluation and interpretation and reporting of results. In addition, BSR members mentor SCI investigators in research methods. BSR assists with development and review of proposed studies and planning of research related data management systems.

Proper citation: Stanford University School of Medicine Cancer Institute Biostatistics Shared Resource Core Facility (RRID:SCR_023696) Copy   

•   Source: SciCrunch Registry

http://www.pathology.med.ohio-state.edu/HTRN/apc/default.asp

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 29, 2016. The Adenoma Polyp Tissue Bank (APTB) receives whole blood from patients enrolled in the Prevention of Sporadic Colorectal Adenomas with Celecoxib clinical trial. We have reached our accrual on blood submissions, so we will no longer be receiving blood specimens The objectives of this trial are as follows: A. To determine the efficacy and safety of celecoxib versus placebo in preventing the occurrence of newly detected colorectal adenomas in subjects at increased risk for colorectal carcinoma. In addition to incidence, other established risk factors will be evaluated for their association with occurrence of new colorectal adenomas, including cancer family history and adenoma size, histopathologic grade, multiplicity and location. Primary assessment of treatment efficacy will be the reduction in the number of subjects with adenomas at colonoscopy after Year 1 and Year 3 of study drug use. Secondary assessments of treatment efficacy will be 1) the number of adenomas 2) the histopathologic grade of adenomas and 3) the size of adenomas, also measured after one year and three years of study drug use. These factors will be incorporated into a risk model for predicting adenoma occurrence and response to celecoxib. B. To determine the efficacy of celecoxib versus placebo in modulating one or more of a panel of biomarkers for colorectal cancer at the cellular and molecular level sampled in a subset of subjects at selective sites at baseline and after Year 1 and Year 3 of study drug use. These biomarkers will include measurements of aberrant crypt foci (ACF), proliferation (index and crypt distribution), apoptosis (index and crypt distribution), COX expression and activity. If modulation of one or more mucosal biomarkers occur, we will explore whether it correlates with the development of incident colorectal neoplasia (adenomas/carcinomas), thereby attempting to validate the surrogacy of that biomarker. C. To develop a specimen bank. Serum and white blood cells are isolated from whole blood and adenoma tissue blocks and slides are banked. Banked specimens will become available for use in correlative science studies at a later point. This project began in 1999 and will be extended through 2006. The lead principal investigator is Monica M. Bertagnolli, MD, Brigham and Women''s Hospital, Boston, MA, and the APTB Director is Scott Jewell, Ph.D., Department of Pathology, The Ohio State University. The APTB is supported by the NIH, NCI Division of Cancer Prevention, in connection with the Strang Cancer Prevention Center, Cornell University, New York., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Adenoma Polyp Tissue Bank (RRID:SCR_005366) Copy   

•   Source: SciCrunch Registry

https://sourceforge.net/projects/sivic/

Software framework and application suite for processing and visualization of DICOM MR Spectroscopy data. Through the use of DICOM, SIVIC aims to facilitate the application of MRS in medical imaging studies.

Proper citation: Spectroscopic Imaging, VIsualization, and Computing (SIVIC) (RRID:SCR_027875) Copy   

•   Source: SciCrunch Registry

https://bioconductor.org/packages/release/bioc/html/tximeta.html

Software R package for reference sequence checksums for provenance identification in RNA-seq. Performs numerous annotation and metadata gathering tasks on behalf of users during the import of transcript counts and abundance from quantification tools such as salmon. Data are imported as SummarizedExperiment objects with associated GenomicRanges metadata. Correct metadata is added automatically via reference sequence digests, facilitating genomic analyses and assisting in computational reproducibility.

Proper citation: tximeta (RRID:SCR_028005) Copy   

•   Source: SciCrunch Registry

https://github.com/SalasLab/HiTIMED

Software DNA methylation-based algorithm, to estimate cell proportions in tumor microenvironment. Profiles tumor, immune, and angiogenic components, allowing researchers to study tumor composition and its clinical implications using archival biospecimens.

Proper citation: HiTIMED (RRID:SCR_028180) Copy   

•   Source: SciCrunch Registry

https://github.com/brentp/somalier

Software application for rapid relatedness estimation for cancer and germline studies using efficient genome sketches extract informative sites, evaluate relatedness, and perform quality-control on BAM/CRAM/BCF/VCF/GVCF. Used for rapid relatedness estimation for cancer and germline studies using efficient genome sketches.

Proper citation: somalier (RRID:SCR_028167) Copy   

•   Source: SciCrunch Registry

https://oncodb.org/

Database offers integrated multi-omic data for patients across 33 cancer types. It encompasses gene expression, DNA methylation, somatic mutations, proteomic profiles, and chromatin accessibility, drawing from TCGA, GTEx, and CPTAC projects. Users can compare gene expression, DNA methylation, and protein levels between tumor and normal tissues, identifying differentially expressed genes and proteins, and examining gene-to-gene correlations. Provides oncogene mutation profiles and allows for survival analysis based on gene expression and methylation, linked to clinical parameters. Facilitates exploration of multi-omic correlations, such as gene expression with DNA methylation, and their variations with mutation status. Extends its analytical capabilities to include six major oncoviruses, offering insights into their impact on gene expression, methylation, and patient survival.

Proper citation: OncoDB (RRID:SCR_028340) Copy   

•   Source: SciCrunch Registry

https://github.com/andygxzeng/BoneMarrowMap

Software R package to enable rapid reference mapping and annotation of new scRNA-seq data across the spectrum of normal and malignant hematopoietic contexts. Single cell RNA-seq reference map of human hematopoietic development in the bone marrow, with balanced representation of hematopoietic stem and progenitor cells and differentiated populations.

Proper citation: BoneMarrowMap (RRID:SCR_028324) Copy   

•   Source: SciCrunch Registry

https://github.com/KarchinLab/mhcnuggets

Software tool that predicts how protein pieces bind to Major Histocompatibility Complex (MHC) molecules. It uses deep learning to process peptide sequences, handle variable lengths, and evaluate both common and rare alleles. Used to predicts peptide-MHC binding. Can predict binding for common or rare alleles of MHC class I or II with a single neural network architecture.

Proper citation: MHCnuggets (RRID:SCR_028674) Copy   

•   Source: SciCrunch Registry

https://www.bioconductor.org/packages/release/bioc/html/sesame.html

Software R package for reducing artifactual detection of DNA methylation by Infinium BeadChips in genomic deletions.

Proper citation: SeSAMe (RRID:SCR_027388) Copy   

•   Source: SciCrunch Registry

https://weghornlab.org/software.html

Software tool which derives gene-specific probabilistic estimates of the strength of negative and positive selection in cancer.

Proper citation: CBaSE (RRID:SCR_027765) Copy   

•   Source: SciCrunch Registry

https://github.com/McGranahanLab/TcellExTRECT

Software R package to calculate T cell fractions from WES data from hg19 or hg38 aligned genomes.

Proper citation: T Cell ExTRECT (RRID:SCR_027742) Copy   

•   Source: SciCrunch Registry

https://github.com/vanallenlab/comut

Software Python library for creating comutation plots to visualize genomic and phenotypic information. Used for visualizing genomic and phenotypic information via comutation plots.

Proper citation: CoMUT (RRID:SCR_027745) Copy   

•   Source: SciCrunch Registry

http://biospecimens.cancer.gov/

The NCI Office of Biorepositories and Biospecimen Research (OBBR) was established in 2005 in recognition of the critical role that biospecimens play in cancer research. The OBBR is responsible for developing a common biorepository infrastructure that promotes resource sharing and team science, in order to facilitate multi-institutional, high throughput genomic and proteomic studies. OBBR is focused on the following objectives: * Establish biobanking as a new area of research, in order to determine the impact of various collection and processing protocols on the usefulness of biospecimens in genomic and proteomic studies * Disseminate first-generation Best Practices in order to harmonize policies and procedures of NCI-supported biorepositories * Develop future generations of biorepository best practices, based on the data generated in the biobanking research programs above * Promote professional oversight of biospecimen standards development by standards organizations * Develop new technologies for biorepository operations * Develop a biorepository accreditation program * Coordinate with the international biobanking community to harmonize policies and procedures to facilitate multi-national research

Proper citation: NCI Office of Biospecimens (RRID:SCR_007076) Copy   

•   Source: SciCrunch Registry

http://senselab.med.yale.edu/modeldb/

Curated database of published models so that they can be openly accessed, downloaded, and tested to support computational neuroscience. Provides accessible location for storing and efficiently retrieving computational neuroscience models.Coupled with NeuronDB. Models can be coded in any language for any environment. Model code can be viewed before downloading and browsers can be set to auto-launch the models. The model source code has to be available from publicly accessible online repository or WWW site. Original source code is used to generate simulation results from which authors derived their published insights and conclusions.

Proper citation: ModelDB (RRID:SCR_007271) Copy   

•   Source: SciCrunch Registry

http://www.mouseatlas.org/

A portal to the Mouse Atlas of Gene Expression Project and Dissecting Gene Expression Networks in Mammalian Organogenesis Project. This Atlas will define the normal state for many tissues by determining, in a comprehensive and quantitative fashion, the number and identity of genes expressed throughout development. The resource will be comprehensive, quantitative, and publicly accessible, containing data on essentially all genes expressed throughout select stages of mouse development. Serial Analysis of Gene Expression (SAGE) is the gene expression methodology of choice for this work. Unlike expressed sequence tags (ESTs) and gene chip data, SAGE data are independent of prior gene discovery and are quantitative. Furthermore, SAGE data are digital, easily exchanged between laboratories for comparison and can be added to by scientists for years to come. Thus, this Atlas will include a data structure and data curation strategy that will facilitate the ongoing collection of gene expression data, even after the completion of this project. The Mouse Atlas project compromises 202 SAGE Libraries from 198 tissues. The list of libraries is available in a number of different groupings, including groups of libraries taken from specific tissue locations and libraries taken from specific developmental stages. Furthermore, this atlas will assemble gene expression profiles for a few focused experiments that will test hypotheses related to the techniques employed, tumor models and models of abnormal development. This will test the resource and provide quality control, validation and demonstrate applicability. Additionally, The Mammalian Organogenesis - Regulation by Gene Expression Networks (MORGEN) project will provide a complete, permanent, and accurate picture of mouse gene expression in the heart (atrioventricular canal and outflow tract), pancreas, and liver; new techniques to understand the interplay of proteins governing the expression of genes key to the development of these organ systems; and the identification of the master regulatory switches that control development of the tissues.

Proper citation: Mouse Gene Expression at the BC Cancer Agency (RRID:SCR_008091) Copy   

•   Source: SciCrunch Registry

http://www.pathwaycommons.org/

Data management software that runs the Pathway Commons web service. It makes it easy to aggregate custom pathway data sets available in standard exchange formats from multiple databases, present pathway data to biologists via a customizable web interface, and export pathway data via a web service to third-party software, such as Cytoscape, for visualization and analysis. cPath is software only, and does not include new pathway information. Main features: * Import pipeline capable of aggregating pathway and interaction data sets from multiple sources, including: MINT, IntAct, HPRD, DIP, BioCyc, KEGG, PUMA2 and Reactome. * Import/Export support for the Proteomics Standards Initiative Molecular Interaction (PSI-MI) and the Biological Pathways Exchange (BioPAX) XML formats. * Data visualization and analysis via Cytoscape. * Simple HTTP URL based XML web service. * Complete software is freely available for local install. Easy to install and administer. * Partly funded by the U.S. National Cancer Institute, via the Cancer Biomedical Informatics Grid (caBIG) and aims to meet silver-level requirements for software interoperability and data exchange.

Proper citation: cPath (RRID:SCR_001749) Copy   

•   Source: SciCrunch Registry

http://www.phosphosite.org

A freely accessible on-line systems biology resource devoted to all aspects of protein modification, as well as other post-translational modifications. It provides valuable and unique tools for both cell biologists and mass spectroscopists. PhosphoSite is a human- and mouse-centric database. It includes features such as: viewing the locations of modified residues on molecular models; browsing and searching MS2 records by disease, tissue, and cell line; submitting lists of peptides to identify previously reported genes; searching by sub-cellular localization, treatment, tissues, cell types, cell lines and diseases, and protein types and protein domains; searching for experimentally-verified kinase substrates and viewing preferred substrate motifs; and viewing MS2 spectra for peptides and sites not previously published.

Proper citation: PhosphoSitePlus: Protein Modification Site (RRID:SCR_001837) Copy   

•   Source: SciCrunch Registry

https://david.ncifcrf.gov/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025. Bioinformatics resource system including web server and web service for functional annotation and enrichment analyses of gene lists. Consists of comprehensive knowledgebase and set of functional analysis tools. Includes gene centered database integrating heterogeneous gene annotation resources to facilitate high throughput gene functional analysis.

Proper citation: DAVID (RRID:SCR_001881) Copy   

•   Source: SciCrunch Registry

http://www.dukecancerinstitute.org/

One of 40 centers in the country designated by the National Cancer Institute (NCI) as a comprehensive cancer center, it combines cutting-edge research with compassionate care. Its vision is to accelerate research advances related to cancer and improve Duke''s ability to translate these discoveries into the most advanced cancer care to patients by uniting hundreds of cancer physicians, researchers, educators, and staff across the medical center, medical school, and health system under a shared administrative structure.

Proper citation: Duke Cancer Institute (RRID:SCR_004338) Copy   

•   Source: SciCrunch Registry