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http://www.broadinstitute.org/cancer/software/genepattern

A powerful genomic analysis platform that provides access to hundreds of tools for gene expression analysis, proteomics, SNP analysis, flow cytometry, RNA-seq analysis, and common data processing tasks. A web-based interface provides easy access to these tools and allows the creation of multi-step analysis pipelines that enable reproducible in silico research.

Proper citation: GenePattern (RRID:SCR_003201) Copy   

•   Source: SciCrunch Registry

https://appyters.maayanlab.cloud

Collection of web-based software applications that enable users to execute bioinformatics workflows without coding. Turns Jupyter notebooks into fully functional standalone web-based bioinformatics applications. Each Appyter application introduces data entry form for uploading or fetching data, as well as for selecting options for various settings. Once user presses Submit, Appyter is executed in cloud and user is presented with Jupyter Notebook report that contain results. Report includes markdown text, interactive and static figures, and source code. Appyter users can share the link to the output report, as well as download the fully executable notebook for execution on other platforms.

Proper citation: Appyters (RRID:SCR_021245) Copy   

•   Source: SciCrunch Registry

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

Software tool as cloud based single cell genomics and spatial transcriptomics data analysis framework that is scalable to massive amounts of data and able to process variety of data types. Consists of cloud analysis workflow, Python analysis package and visualization application. Supports analysis of single-cell RNA-seq, CITE-seq, Perturb-seq, single-cell ATAC-seq, single-cell immune repertoire and spatial transcriptomics data.

Proper citation: Cumulus (RRID:SCR_021644) 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://github.com/genome/bam-readcount

Software tool that runs on BAM or CRAM file and generates low level information about sequencing data at specific nucleotide positions. Its outputs include observed bases, readcounts, summarized mapping and base qualities, strandedness information, mismatch counts, and position within the reads.

Proper citation: bam readcount (RRID:SCR_023653) 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://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://cabig.nci.nih.gov/tools/caTRIP

THIS RESOURCE IS NO LONGER IN SERVICE documented June 4, 2013. Allows users to query across a number of caBIG data services, join on common data elements (CDEs), and view results in a user-friendly interface. With an initial focus on enabling outcomes analysis, caTRIP allows clinicians to query across data from existing patients with similar characteristics to find treatments that were administered with success. In doing so, caTRIP can help inform treatment and improve patient care, as well as enable the searching of available tumor tissue, enable locating patients for clinical trials, and enable investigating the association between multiple predictors and their corresponding outcomes such as survival caTRIP relies on the vast array of open source caBIG applications, including: * Tumor Registry, a clinical system that is used to collect endpoint data * cancer Text Information Extraction System (caTIES), a locator of tissue resources that works via the extraction of clinical information from free text surgical pathology reports. while using controlled terminologies to populate caBIG-compliant data structures * caTissue CORE, a tissue bank repository tool for biospecimen inventory, tracking, and basic annotation * Cancer Annotation Engine (CAE), a system for storing and searching pathology annotations * caIntegrator, a tool for storing, querying, and analyzing translational data, including SNP data Requires Java installation and network connectivity.

Proper citation: caTRIP (RRID:SCR_003409) Copy   

•   Source: SciCrunch Registry

https://github.com/dpeerlab/phenograph

Software tool as clustering method designed for high dimensional single cell data. Algorithmically defines phenotypes in high dimensional single cell data. Used for large scale analysis of single cell heterogeneity.

Proper citation: Phenograph (RRID:SCR_016919) Copy   

•   Source: SciCrunch Registry

http://tissues.jensenlab.org

Database that integrates evidence on tissue expression from manually curated literature, proteomics and transcriptomics screens, and automatic text mining. It maps all evidence to common protein identifiers and Brenda Tissue Ontology terms, and further unifies it by assigning confidence scores that facilitate comparison of the different types and sources of evidence.

Proper citation: TISSUES (RRID:SCR_015665) 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://www.genenetwork.org/

Web platform that provides access to data and tools to study complex networks of genes, molecules, and higher order gene function and phenotypes. Sequence data (SNPs) and transcriptome data sets (expression genetic or eQTL data sets). Quantitative trait locus (QTL) mapping module that is built into GN is optimized for fast on-line analysis of traits that are controlled by combinations of gene variants and environmental factors. Used to study humans, mice (BXD, AXB, LXS, etc.), rats (HXB), Drosophila, and plant species (barley and Arabidopsis). Users are welcome to enter their own private data.

Proper citation: GeneNetwork (RRID:SCR_002388) Copy   

•   Source: SciCrunch Registry

http://sumsdb.wustl.edu/sums/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on May 11, 2016. Repository of brain-mapping data (surfaces and volumes; structural and functional data) derived from studies including fMRI and MRI from many laboratories, providing convenient access to a growing body of neuroimaging and related data. WebCaret is an online visualization tool for viewing SumsDB datasets. SumsDB includes: * data on cerebral cortex and cerebellar cortex * individual subject data and population data mapped to atlases * data from FreeSurfer and other brainmapping software besides Caret SumsDB provides multiple levels of data access and security: * Free (public) access (e.g., for data associated with published studies) * Data access restricted to collaborators in different laboratories * Owner-only access for work in progress Data can be downloaded from SumsDB as individual files or as bundles archived for offline visualization and analysis in Caret WebCaret provides online Caret-style visualization while circumventing software and data downloads. It is a server-side application running on a linux cluster at Washington University. WebCaret "scenes" facilitate rapid visualization of complex combinations of data Bi-directional links between online publications and WebCaret/SumsDB provide: * Links from figures in online journal article to corresponding scenes in WebCaret * Links from metadata in WebCaret directly to relevant online publications and figures

Proper citation: SumsDB (RRID:SCR_002759) Copy   

•   Source: SciCrunch Registry

http://cgap.nci.nih.gov/

Project to determine the gene expression profiles of normal, precancer, and cancer cells, whose generated resources are available to the cancer community. Interconnected modules provide access to all CGAP data, bioinformatic analysis tools, and biological resources allowing the user to find in silico answers to biological questions in a fraction of the time it once took in the laboratory. * Genes * Tissues * Pathways * RNAi * Chromosomes * SAGE Genie * Tools

Proper citation: Cancer Genome Anatomy Project (RRID:SCR_003072) Copy   

•   Source: SciCrunch Registry

http://www.dtp.nci.nih.gov

Portal for preclinical information and research materials, including web-accessible data and tools, NCI-60 Tumor Cell Line Screen, compounds in vials and plates, tumor cells, animals, and bulk drugs for investigational new drug (IND)-directed studies. DTP has been involved in the discovery or development of more than 70 percent of the anticancer therapeutics on the market today, and will continue helping the academic and private sectors to overcome various therapeutic development barriers, particularly through supporting high-risk projects and therapeutic development for rare cancers. Initially DTP made its drug discovery and development services and the results from the human tumor cell line assay publicly accessible to researchers worldwide. At first, the site offered in vitro human cell line data for a few thousand compounds and in vitro anti-HIV screening data for roughly 42,000 compounds. Today, visitors can find: * Downloadable in vitro human tumor cell line data for some 43,500 compounds and 15,000 natural product extracts * Results for 60,000 compounds evaluated in the yeast assay * In vivo animal model results for 30,000 compounds * 2-D and 3-D chemical structures for more than 200,000 compounds * Molecular target data, including characterizations for at least 1,200 targets, plus data from multiple cDNA microarray projects In addition to browsing DTP's databases and downloading data, researchers can request individual samples or sets of compounds on 96-well plates for research, or they can submit their own compounds for consideration for screening via DTP's online submission form. Once a compound is submitted for screening, researchers can follow its progress and retrieve data using a secure web interface. The NCI has collected information on almost half a million chemical structures in the past 50 years. DTP has made this information accessible and useful for investigators through its 3-D database, a collection of three-dimensional structures for more than 200,000 drugs. Investigators use the 3-D database to screen compounds for anticancer therapeutic activity. Also available on DTP's website are 127,000 connection tables for anticancer agents. A connection table is a convenient way of depicting molecular structures without relying on drawn chemical structures. As unique lists of atoms and their connections, the connection tables can be indexed and stored in computer databases where they can be used for patent searches, toxicology studies, and precursor searching, for example., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Developmental Therapeutics Program (RRID:SCR_003057) Copy   

•   Source: SciCrunch Registry

https://pvactools.readthedocs.io/en/latest/

Software toolkit to identify and visualize cancer neoantigens. Cancer immunotherapy tools suite consisting of following tools: pVACseq as cancer immunotherapy pipeline for identifying and prioritizing neoantigens from VCF file; pVACbind as cancer immunotherapy pipeline for identifying and prioritizing neoantigens from FASTA file; pVACfuse as tool for detecting neoantigens resulting from gene fusions; pVACvector as tool designed to aid specifically in construction of DNA-based cancer vaccines; pVACview as application based on R Shiny that assists users in reviewing, exploring and prioritizing neoantigens from results of pVACtools processes for personalized cancer vaccine design.

Proper citation: pVACtools (RRID:SCR_025435) Copy   

•   Source: SciCrunch Registry

http://www.bios.unc.edu/research/genomic_software/Matrix_eQTL/

Software tool for ultra fast eQTL analysis via large matrix operations.

Proper citation: MatrixEQTL (RRID:SCR_025513) Copy   

•   Source: SciCrunch Registry