Tools   Select Another Resource Report Type

http://slicer.org/

A free, open source software package for visualization and image analysis including registration, segmentation, and quantification of medical image data. Slicer provides a graphical user interface to a powerful set of tools so they can be used by end-user clinicians and researchers alike. 3D Slicer is natively designed to be available on multiple platforms, including Windows, Linux and Mac Os X. Slicer is based on VTK (http://public.kitware.com/vtk) and has a modular architecture for easy addition of new functionality. It uses an XML-based file format called MRML - Medical Reality Markup Language which can be used as an interchange format among medical imaging applications. Slicer is primarily written in C++ and Tcl.

Proper citation: 3D Slicer (RRID:SCR_005619) Copy   

•   Source: SciCrunch Registry

http://www.karmanos.org/

Center for patient care, education and research on cancer. The institute focuses its research on prevention methods, early detection, treatment and finding cures.

Proper citation: Karmanos Cancer Institute (RRID:SCR_000508) Copy   

•   Source: SciCrunch Registry

https://openmm.org/

Software toolkit to run modern molecular simulations. It can be used either as a standalone application for running simulations, or as a library that enables accelerated calculations for molecular dynamics on high-performance computer architectures.

Proper citation: OpenMM (RRID:SCR_000436) Copy   

•   Source: SciCrunch Registry

http://dctd.cancer.gov/

Division of NCI that takes prospective cancer detection and treatment leads, facilitates their paths to clinical application, and expedites the initial and subsequent large-scale testing of new agents, biomarkers, imaging tests, and other therapeutic interventions (radiation, surgery, immunotherapy) in patients. DCTD, like all of NCI, supports many programs that could not be done without government funding - investigators supported by the division engage in scientifically sound, high-risk research that may yield great benefits for patients with cancer, but are too difficult or risky for industry or academia to pursue. This includes a particular emphasis on the development of distinct molecular signatures for cancer, refined molecular assays, and state-of-the-art imaging techniques that will guide oncologic therapy in the future. The division has eight major programs that work together to bring unique molecules, diagnostic tests, and therapeutic interventions from the laboratory bench to the patient bedside: * Cancer Diagnosis Program * Cancer Imaging Program * Cancer Therapy Evaluation Program * Developmental Therapeutics Program * Radiation Research Program * Translational Research Program * Biometrics Research Branch * Office of Cancer Complementary and Alternative Medicine

Proper citation: DCTD (RRID:SCR_004196) Copy   

•   Source: SciCrunch Registry

http://discover.nci.nih.gov/gominer/

GoMiner is a tool for biological interpretation of "omic" data including data from gene expression microarrays. Omic experiments often generate lists of dozens or hundreds of genes that differ in expression between samples, raising the question, What does it all mean biologically? To answer this question, GoMiner leverages the Gene Ontology (GO) to identify the biological processes, functions and components represented in these lists. Instead of analyzing microarray results with a gene-by-gene approach, GoMiner classifies the genes into biologically coherent categories and assesses these categories. The insights gained through GoMiner can generate hypotheses to guide additional research. GoMiner displays the genes within the framework of the Gene Ontology hierarchy in two ways: * In the form of a tree, similar to that in AmiGO * In the form of a "Directed Acyclic Graph" (DAG) The program also provides: * Quantitative and statistical analysis * Seamless integration with important public databases GoMiner uses the databases provided by the GO Consortium. These databases combine information from a number of different consortium participants, include information from many different organisms and data sources, and are referenced using a variety of different gene product identification approaches.

Proper citation: GoMiner (RRID:SCR_002360) Copy   

•   Source: SciCrunch Registry

https://www.med.upenn.edu/cbica/captk/

Software platform for analysis of radiographic cancer images. Used as quantitative imaging analytics for precision diagnostics and predictive modeling of clinical outcome.

Proper citation: Cancer Imaging Phenomics Toolkit (RRID:SCR_017323) Copy   

•   Source: SciCrunch Registry

https://github.com/caleblareau/mgatk

Software python-based command line interface for processing .bam files with mitochondrial reads and generating high-quality heteroplasmy estimation from sequencing data. This package places a special emphasis on mitochondrial genotypes generated from single-cell genomics data, primarily mtscATAC-seq, but is generally applicable across other assays.

Proper citation: mgatk (RRID:SCR_021159) Copy   

•   Source: SciCrunch Registry

https://github.com/humanlongevity/HLA

Software tool for fast and accurate HLA typing from short read sequence data. Iteratively refines mapping results at amino acid level to achieve four digit typing accuracy for both class I and II HLA genes, taking only 3 min to process 30× whole genome BAM file on desktop computer.

Proper citation: xHLA (RRID:SCR_022277) Copy   

•   Source: SciCrunch Registry

https://github.com/RabadanLab/arcasHLA

Software tool for high resolution HLA typing from RNAseq. Fast and accurate in silico inference of HLA genotypes from RNA-seq.

Proper citation: arcasHLA (RRID:SCR_022286) Copy   

•   Source: SciCrunch Registry

https://ccsp.hms.harvard.edu/

Center includes studies for responsiveness and resistance to anti cancer drugs. Committed to training students and postdocs, promoting junior faculty and ensuring that data and software are reproducible, reliable and publicly accessible. Member of National Cancer Institute’s Cancer Systems Biology Consortium.

Proper citation: Harvard Medical School Center for Cancer Systems Pharmacology (RRID:SCR_022831) Copy   

•   Source: SciCrunch Registry

http://crispor.tefor.net

Web application that helps design, evaluate and clone guide sequences for the CRISPR/Cas9 system. This sgRNA design tool assists with guide selection in a variety of genomes and pre-calculated results for all human coding exons as a UCSC Genome Browser track.

Proper citation: CRISPOR (RRID:SCR_015935) Copy   

•   Source: SciCrunch Registry

https://github.com/hetio/hetmatpy

Software Python package for matrix storage and operations on hetnets. Enables identifying relevant network connections between set of query nodes.

Proper citation: HetMatPy (RRID:SCR_023409) Copy   

•   Source: SciCrunch Registry

https://maayanlab.cloud/X2K

Web service to predict involvement of upstream cell signaling pathways, given signature of differentially expressed genes. Used to linking expression signatures to upstream cell signaling networks.

Proper citation: X2K Web (RRID:SCR_023624) Copy   

•   Source: SciCrunch Registry

https://www.cancermodels.org/

Cancer research platform that aggregates clinical, genomic and functional data from various types of patient derived cancer models, xenographs, organoids and cell lines. Open catalog of harmonised patient-derived cancer models. Standardises, harmonises and integrates clinical metadata, molecular and treatment-based data from academic and commercial providers worldwide. Data is FAIR and underpins generation and testing of new hypotheses in cancer mechanisms and personalised medicine development. PDCM Finder have expanded to organoids and cell lines and is now called CancerModels.Org. PDCM Finder was launched in April 2022 as successor of PDX Finder portal, which focused solely on patient-derived xenograft models.

Proper citation: CancerModels.Org (RRID:SCR_023931) Copy   

•   Source: SciCrunch Registry

http://rnainformatics.org.cn/RiboToolkit/

Integrated web server developed for Ribo-seq data analysis. Platform for analysis and annotation of ribosome profiling data to decode mRNA translation at codon resolution.Web based service to centralize Ribo-seq data analyses, including data cleaning and quality evaluation, expression analysis based on RPFs, codon occupancy, translation efficiency analysis, differential translation analysis, functional annotation, translation metagene analysis, and identification of actively translated ORFs.

Proper citation: RiboToolkit (RRID:SCR_024406) Copy   

•   Source: SciCrunch Registry

https://seer.cancer.gov/csr/1975_2016/

Platform to report outlining trends in cancer statistics and methods to derive various cancer statistics from the Surveillance, Epidemiology, and End Results (SEER) program. Authoritative source for cancer statistics in the United States.

Proper citation: NCI SEER Cancer Statistics Review (RRID:SCR_024685) Copy   

•   Source: SciCrunch Registry

https://seer.cancer.gov/lymphomarecode/lymphoma-2020.html

Website describing International Classification of Diseases codes that corresponds to lymphomas in the Surveillance, Epidemiology, and End Results (SEER) registry.

Proper citation: NCI Lymphoid Neoplasm Recode 2020 Revision Definition (RRID:SCR_024686) Copy   

•   Source: SciCrunch Registry

https://github.com/mikelove/tximport

Software R package for importing pseudoaligned reads into R for use with downstream differential expression analysis. Used for import and summarize transcript level estimates for transcript and gene level analysis.

Proper citation: tximport (RRID:SCR_016752) Copy   

•   Source: SciCrunch Registry

https://software.broadinstitute.org/cancer/cga/polysolver

Software tool for HLA typing based on whole exome sequencing data and infers alleles for three major MHC class I genes. Enables accurate inference of germline alleles of class I HLA-A, B and C genes and subsequent detection of mutations in these genes using inferred alleles as reference.

Proper citation: Polysolver (RRID:SCR_022278) Copy   

•   Source: SciCrunch Registry

https://cytotrace.stanford.edu/

Software tool that predicts differentiation state of cells from single cell RNA sequencing data. Used for predicting differentiation states from scRNA-seq data.

Proper citation: CytoTRACE (RRID:SCR_022828) Copy   

•   Source: SciCrunch Registry