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Web app that allows users to search for the most important paths connecting any two nodes in Hetionet.
Proper citation: Hetnet Connectivity Search (RRID:SCR_023630) Copy
Web server application that infers overrepresentation of upstream kinases whose putative substrates are in user inputted list of proteins. Used to analyze data from phosphoproteomics and proteomics studies to predict upstream kinases responsible for observed differential phosphorylations.
Proper citation: Kinase Enrichment Analysis 3 (RRID:SCR_023623) Copy
https://generanger.maayanlab.cloud/gene/A2M?database=ARCHS4
Web server application that provides access to processed data about expression of human genes and proteins across human cell types, tissues, and cell lines from several atlases. Used to explore single gene expression across tissues and cell types.
Proper citation: GeneRanger (RRID:SCR_023622) Copy
https://targetranger.maayanlab.cloud/
Web server application that identifies targets from user inputted RNA-seq samples collected from cells we wish to target. By comparing inputted samples with processed RNA-seq and proteomics data from several atlases, TargetRanger identifies genes that are highly expressed in target cells while lowly expressed across normal human cell types, tissues, and cell lines.
Proper citation: TargetRanger (RRID:SCR_023621) Copy
Medical wiki of interventions, regimens, and general information relevant to fields of hematology and oncology. Knowledge base for hematology and oncology providers, containing details about hematology/oncology drugs and treatment regimens. Any healthcare professional can sign up to contribute. Acuracy and completeness of content is overseen by Editorial Board.
Proper citation: HemOnc Knowledgebase (RRID:SCR_023436) Copy
http://cancer.gov/cancertopics/pdq/cancerdatabase
NCI''s comprehensive cancer database that contains summaries on a wide range of cancer topics; a registry of 8,000+ open and 19,000+ closed cancer clinical trials from around the world; a directory of professionals who provide genetics services; the NCI Dictionary of Cancer Terms, with definitions for 6,800+ cancer and medical terms; and the NCI Drug Dictionary, which has information on 2,300+ agents used in the treatment of cancer or cancer-related conditions. The PDQ cancer information summaries are peer reviewed and updated monthly by six editorial boards comprised of specialists in adult treatment, pediatric treatment, supportive care, screening and prevention, genetics, and complementary and alternative medicine. The Boards review current literature from more than 70 biomedical journals, evaluate its relevance, and synthesize it into clear summaries. Many of the summaries are also available in Spanish.
Proper citation: Physician Data Query (RRID:SCR_006833) Copy
A cloud-based collaborative platform which co-locates data, code, and computing resources for analyzing genome-scale data and seamlessly integrates these services allowing scientists to share and analyze data together. Synapse consists of a web portal integrated with the R/Bioconductor statistical package and will be integrated with additional tools. The web portal is organized around the concept of a Project which is an environment where you can interact, share data, and analysis methods with a specific group of users or broadly across open collaborations. Projects provide an organizational structure to interact with data, code and analyses, and to track data provenance. A project can be created by anyone with a Synapse account and can be shared among all Synapse users or restricted to a specific team. Public data projects include the Synapse Commons Repository (SCR) (syn150935) and the metaGenomics project (syn275039). The SCR provides access to raw data and phenotypic information for publicly available genomic data sets, such as GEO and TCGA. The metaGenomics project provides standardized preprocessed data and precomputed analysis of the public SCR data.
Proper citation: Synapse (RRID:SCR_006307) Copy
https://ccb.jhu.edu/software/stringtie/
Software application for assembling of RNA-Seq alignments into potential transcripts. It enables improved reconstruction of a transcriptome from RNA-seq reads. This transcript assembling and quantification program is implemented in C++ .
Proper citation: StringTie (RRID:SCR_016323) Copy
https://bioconductor.org/packages/release/bioc/html/DESeq2.html
Software package for differential gene expression analysis based on the negative binomial distribution. Used for analyzing RNA-seq data for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates.
Proper citation: DESeq2 (RRID:SCR_015687) Copy
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
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
http://rulai.cshl.edu/cgi-bin/tools/ESE3/esefinder.cgi?process=home
A web-based resource that facilitates rapid analysis of exon sequences to identify putative exonic splicing enhancers (ESEs) responsive to the human SR proteins SF2/ASF, SC35, SRp40 and SRp55, and to predict whether exonic mutations disrupt such elements.
Proper citation: ESEfinder 3.0 (RRID:SCR_007088) Copy
http://proteogenomics.musc.edu/ma/arrayQuest.php?page=home&act=manage
A web-accessible program for the analysis of DNA microarray data. ArrayQuest is designed to apply any type of DNA microarray analysis program executable on a Linux system (i.e., Bioconductor statistical and graphical methods written in R as well as BioPerl and C++ based scripts) to DNA microarray data stored in the MUSC DNA Microarray Database, the Gene Expression Omnibus (GEO) or in a password protected private database uploaded to the center point server. ArrayQuest analyses are performed on a computer cluster.
Proper citation: ArrayQuest (RRID:SCR_010935) Copy
http://www.nitrc.org/projects/whs-sd-atlas/
Open access volumetric atlas of anatomical delineations of rat brain based on structural contrast in isotropic magnetic resonance and diffusion tensor images acquired ex vivo from 80 day old male Sprague Dawley rat at Duke Center for In Vivo Microscopy. Spatial reference is provided by Waxholm Space coordinate system. Location of bregma and lambda are identified as anchors towards stereotaxic space. Application areas include localization of signal in non structural images. Atlas, MRI and DTI volumes, and diffusion tensor data are shared in NIfTI format.
Proper citation: Waxholm Space Atlas of the Sprague Dawley Rat Brain (RRID:SCR_017124) Copy
Open-source toolkit that enables the rapid creation of tailored, web-enabled data storage and provides a cohesive system for data management, visualization, and processing. At its core, Midas Platform is implemented as a PHP modular framework with a backend database (PostGreSQL, MySQL and non-relational databases). While the Midas Platform system can be installed and deployed without any customization, the framework has been designed with customization in mind. As building one system to fit all is not optimal, the framework has been extended to support plugins and layouts. Through integration with a range of other open-source toolkits, applications, or internal proprietary workflows, Midas Platform offers a solid foundation to meet the needs of data-centric computing. Midas Platform provides a variety of data access methods, including web, file system and DICOM server interfaces, and facilitates extending the methods in which data is stored to other relational and non-relational databases.
Proper citation: Midas Platform (RRID:SCR_002186) Copy
Repository of person centered measures that evaluates and monitors physical, mental, and social health in adults and children.
Proper citation: Patient-Reported Outcomes Measurement Information System (RRID:SCR_004718) Copy
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
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
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
THIS RESOURCE IS NO LONGER IN SERVICE. Documented August 23, 2017.
Annotated database of fluorescence microscope images depicting subcellular location proteins with two interfaces: a text and image content search interface, and a graphical interface for exploring location patterns grouped into Subcellular Location Trees. The annotations in PSLID provide a description of sample preparation and fluorescence microscope imaging.
Proper citation: Protein Subcellular Location Image Database (RRID:SCR_008663) Copy
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