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SciCrunch Registry is a curated repository of scientific resources, with a focus on biomedical resources, including tools, databases, and core facilities - visit SciCrunch to register your resource.
https://github.com/mskcc/facets
Software tool for estimating genome copy numbers from high throughput DNA sequencing data. Allele-specific copy number and clonal heterogeneity analysis tool for high-throughput DNA sequencing. Used to implement Fraction and Copy number Estimate from Tumor/normal Sequencing.
Proper citation: FACETS (RRID:SCR_026264) Copy
https://ecog-acrin.org/resources/ecog-performance-status/
ECOG Performance Scale describes patient’s level of functioning in terms of their ability to care for themself, daily activity, and physical ability (walking, working, etc.). Standard criteria for measuring how the disease impacts patient’s daily living abilities. Used to assess the functional status of patient.
Proper citation: Eastern Cooperative Oncology Group Performance Status Scale (RRID:SCR_026432) Copy
https://github.com/dpeerlab/Palantir/
Algorithm to align cells along differentiation trajectories. Models trajectories of differentiating cells by treating cell fate as probabilistic process and leverages entropy to measure cell plasticity along the trajectory. Generates high-resolution pseudo-time ordering of cells and, for each cell state, assigns probability of differentiating into each terminal state.
Proper citation: Palantir (RRID:SCR_027194) Copy
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
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
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
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
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
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
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
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
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
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
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
http://www.genetics.ucla.edu/labs/horvath/CoexpressionNetwork/
Software R package for weighted correlation network analysis. WGCNA is also available as point-and-click application. Unfortunately this application is not maintained anymore. It is known to have compatibility problems with R-2.8.x and newer, and the methods it implements are not all state of the art., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.
Proper citation: Weighted Gene Co-expression Network Analysis (RRID:SCR_003302) Copy
http://caintegrator-info.nci.nih.gov/rembrandt
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on April 28,2023. An initiative to develop a molecular classification schema that is both clinically and biologically meaningful, based on gene expression and genomic data from tumors (Gliomas) of patients who will be prospectively followed through natural history and treatment phase of their illness. The study will also explore gene expression profiles to determine the responsiveness of the patients and correlate with discrete chromosomal abnormalities. The initiative was designed to obtain a large amount of molecular data on DNA and RNA of freshly collected tumor samples that were collected, processed and analyzed in a standardized fashion to allow for large-scale cross sample analysis. The sample collection is accompanied by careful and prospective clinical data acquisition, allowing a variety of matched molecular and clinical data permitting a wide variety of analyses. GMDI has accrued fresh frozen tumors in the retrospective phase (all from the Henry Ford Hospital, without germline DNA) and fresh frozen tumors in the prospective phase (from a variety of institutions). In addition to characterizing the samples from patients enrolled in GMDI, the microarray group has generated genomic-scale analyses of the many human and canine glioma initiating cells/glioma stem cells (GIC/GSC) lines, as well as many canine and murine normal neural stem cell (NSC) lines produced in laboratory.
Proper citation: Glioma Molecular Dignostic Initiatives (RRID:SCR_003329) Copy
http://www.broadinstitute.org/gsea/
Software package for interpreting gene expression data. Used for interpretation of a large-scale experiment by identifying pathways and processes.
Proper citation: Gene Set Enrichment Analysis (RRID:SCR_003199) Copy
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
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
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
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