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Provides a web resource for exploring, visualizing, and analyzing multidimensional cancer genomics data. cBioPortal reduces molecular profiling data from cancer tissues and cell lines into readily understandable genetic, epigenetic, gene expression, and proteomic events. The query interface, combined with customized data storage, enables researchers to interactively explore genetic alterations across samples, genes, and pathways and, when available in the underlying data, to link these to clinical outcomes.
Authorizes to retrieve, assemble and process public data from The Cancer Genome Atlas (TCGA). TCGA-assembler is an open source software which is composed of two modules: (i) the first module earns the public data including TCGA somatic mutation and proteomics data and gathers the individual files into local data tables, and (ii) the second module furnishes multiple features for preparing information for downstream analysis such as a way for separating different types of measurements into their own data tables.
GEPIA / Gene Expression Profiling Interactive Analysis
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Enables to perform a diverse range of gene expression analyses. GEPIA is an interactive web application which analyzes the RNA sequencing expression data of 9,736 tumors and 8,587 normal samples from the TCGA and the GTEx projects. It provides customizable functions such as tumor/normal differential expression analysis, profiling according to cancer types or pathological stages, patient survival analysis, similar gene detection, correlation analysis and dimensionality reduction analysis.
Aids in querying, downloading, analyzing and integrating The Cancer Genome Atlas (TCGA) data. TCGAbiolinks can: i) facilitate the TCGA open-access data retrieval, ii) prepare the data using the appropriate pre-processing strategies, iii) provide the means to carry out different standard analyses and iv) allow user to download a specific version of the data and thus to easily reproduce earlier research results. It provides multiple methods for analysis and methods for visualization in order to easily develop complete analysis pipelines.
A software tool that integrates multi-resource omics data. CrossHub was designed to analyze TCGA transcriptomic and epigenomic data in the context of ENCODE, Jaspar and various miRNA target prediction algorithms. This approach is intended to reveal gene expression regulation mechanisms such as methylation, transcription factor (TF)-mediated transcription repression/activation and microRNA interference. CrossHub has a scalable design intended to analyze more various cancer types available in TCGA. This tool may be a starting point for integrating the data of several major projects such as TCGA and ENCODE.
A web application that can be used for studying prognostic implications of mRNA biomarkers in a variety of cancers. We have compiled data from public repositories such as GEO, EBI Array Express and The Cancer Genome Atlas for creating PROGgene. Survival analysis can be performed on a) single genes b) multiple genes as a signature, c) ratio of expression of two genes, and d) curated/published gene signatures. Users can also adjust the survival analysis models for available covariates. Users can study prognostic implications of entire gene signatures in different cancer types, which are searchable by keywords. PROGgene is useful in accelerating biomarker discovery in cancer and quickly providing results that may indicate disease-specific prognostic value of specific biomarkers.
An open source software package to obtain the TCGA data, wrangle it, and pre-process it into a format ready for multivariate and integrated statistical analysis in the R environment. In a user-friendly format with one single function call, our package downloads and fully processes the desired TCGA data to be seamlessly integrated into a computational analysis pipeline. No further technical or biological knowledge is needed to utilize our software, thus making TCGA data easily accessible to data scientists without specific domain knowledge.
Offers a visual web editor for cancer pathways. PathwayMapper can be used for viewing pre-curated cancer pathways with the ability to overlay genomic alteration data, and as an interactive graphical editing tool for creating and modifying pathways. It supports remote users collaborating on pathway editing. The tool supports alignment operations by showing guidelines as two nodes are aligned as well as facilitating operations for horizontal and vertical alignment of two or more nodes based on the first selected node.
OASISPRO / Omics Analysis System for Precision Oncology
Allows oncological clinical prediction. OASISPRO is a cloud-based omics analysis tool that integrates quantitative omics data and builds prediction models for cancer phenotypes. The software enables quantitative omics analysis, provides insights into the biology of cancer and empowers accurate clinical predictions. The data mining system is extensible to other diseases and health conditions. OASISPRO can contribute to establish personalized cancer treatment plans, thereby increasing the quality of care and reducing the cost of cancer management.
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Securely analyzes and visualizes private functional genomics data set in the context of public and shared genomic/phenotypic data sets. UCSC Xena is a Functional Genomics Browser with analytics, visualization and Galaxy integration for analyzing and viewing the public data hubs. It gives access to public databases (Xena Public Data Hubs) and allows to mix in and compare private data (Xena Private Data Hubs).
A Web-based application for in-depth analysis and rapid evaluation of disease-causative genome sequence alterations. Vanno integrates information from biomedical databases, functional predictions from available evaluation models, and mutation landscapes from TCGA cancer types. A highly integrated framework that incorporates filtering, sorting, clustering, and visual analytic modules is provided to facilitate exploration of oncogenomics datasets at different levels, such as gene, variant, protein domain, or three-dimensional structure. Such design is crucial for the extraction of knowledge from sequence alterations and translating biological insights into clinical applications. Taken together, Vanno supports almost all disease-associated gene tests and exome sequencing panels designed for NGS, providing a complete solution for targeted and exome sequencing analysis.
Enables researchers to study the expression level of genes to compare primary tumor with normal tissue samples. UALCAN is an interactive web resource that provides critical information and graphic ability to make stage, grade, race and other sub status specific expression features from transcriptome sequencing data. This portal can aid in the identification of candidate biomarkers of specific cancer subclasses, with diagnostic, prognostic or therapeutic implications. It can also be used as a platform for in silico validation of target genes.
Enables data processing and prioritization of candidate cancer genes. OncoScape is a method for integrating several genome-wide datasets to characterize the molecular aberration landscape of human cancer. The software provides functionality to assess alterations of single genes for each data type and each cancer type individually. It can be applied in several additional contexts, such as the comparison of patients responding or being resistant to specific treatments or to identify specific characteristics of different subtypes of a certain disease.
Allows the integration and visualization of the expression, DNA methylation and clinical TCGA (The Cancer Genome Atlas) data on a single-gene level. MEXPRESS was designed after the principles of graphical excellence to ensure that the complex and multidimensional TCGA data would be presented in a clear, precise and efficient way to the user. MEXPRESS was therefore developed to have virtually no learning curve, allowing especially clinical researchers to get their results fast without having to invest time in learning yet another tool. MEXPRESS offers a unique set of features, including its ease of use and the integrated visualization of different data types over hundreds of samples. It may therefore help to quickly test hypotheses that concern the discovery of DNA methylation or expression-based biomarkers.
Allows users to systematically access Firehose pre-processed data, and to organize it for easy management and analysis. The library also allows users to create data matrices from TCGA data, without any pre-processing. RTCGAToolbox can also access the Firehose analysis pipeline to get GISTIC2 results for questions related to copy number data. In addition, basic analysis functions of RTCGAToolbox facilitate basic comparisons and analyses as well as visualization without having to call external tools. The RTCGAToolbox can also be integrated with other analysis pipelines for further data processing.
A web based, freely accessible online tool, which can also be run in a private instance, for integrated analysis of molecular cancer data sets provided by TCGA. In contrast to already available tools, Web-TCGA utilizes different methods for analysis and visualization of TCGA data, allowing users to generate global molecular profiles across different cancer entities simultaneously. In addition to global molecular profiles, Web-TCGA offers highly detailed gene and tumor entity centric analysis by providing interactive tables and views. The user can focus analyses on results from single genes and cancer entities or perform a global analysis (multiple cancer entities and genes simultaneously).
Allows investigation of molecular interactions in cancer. Zodiac integrates big-data analysis on multimodal TCGA data and produces knowledge of molecular interactions in cancer. It is based on Bayesian graphical models. This tool contains a whole-genome and pair-wise interaction map, which offers intragenic and intergenic interactions of all pairs of genes in cancer. It is composed of the following features: data retrieval, computation, results assembly, and results dissemination.
Automatically generates, testes and deploys such clients for rapid response to API changes. Firebrowse provides a raw construct of an R function including all the comments, which will be rendered as the documentation when the final package is built. Firebrowse can be integrated into existing analysis workflows. Using such API clients over the download of flat files has several advantages, including having the latest data available, making the process of data importing obsolete and avoiding data re-formatting, which often serves as an additional source of errors.
Provides data structures and methods to represent, manipulate, and integrate multi-assay genomic experiments. MultiAssayExperiment permits to integrate any data class that supports basic subsetting and dimension names. It supports many data classes by default without additional accommodations. The tool was used to visualize the overlap in assays performed for adrenocortical carcinoma patients. It had permit to confirm correlations between somatic mutation and copy number burden in colorectal cancer and breast cancer.
Enables exploration and interpretation of gene-associated profiles of expression and DNA methylation for all the cancer types available at TCGA. Wanderer is a viewer that allows real-time access and visualization of gene expression and DNA methylation profiles from TCGA data using gene targeted queries. The software also offers batch analysis capabilities as well as data sharing and linking from other Web resources through a Wanderer application programming interface (API).
CELLX / Cell Index Database
Enables integration of expression, copy number variation, mutation, compound activity, and meta data from cancer cells. CELLX is an informatics infrastructure that permits users to integrate data, perform analysis, and visualize results from public as well as private internal sources to support precision medicine activities. The software can be used to generate responder / non-responder hypotheses from cell line screening data, for supporting precision medicine.
ACE / Atlas Correlation Explorer
Investigates possible association among the cancer genome atlas (TCGA) database attributes. ACE proposes a standalone application dedicated to the highlighting of correlations within combination of user-defined clinical and genomic data. It is organized through two main sections intending to facilitate the browsing, the selection and the overviewing of information. The software supports seven types of cancers including Breast invasive carcinoma (BRCA) or Head and Neck squamous carcinoma (HNSC).
Regulome Explorer
Enables users to search, filter, and visualize analytical results generated from the Cancer Genome Atlas (CGA) data. Regulome Explorer is a visualization resource that permits to illustrate example associations identified by pairwise statistical tests between binary somatic mutation annotations and other data types. It also offers the observation of mutual exclusivity and co-occurrence of genomic events, subtype or other phenotype-associated mutations, and significant changes in gene and miRNA expression.
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TANRIC / The Atlas of Noncoding RNAs in Cancer
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A user-friendly, open-access web resource for interactive exploration of long non-coding RNAs (lncRNAs) in cancer. TANRIC characterizes the expression profiles of lncRNAs in large patient cohorts of 20 cancer types, including TCGA and independent datasets (>8,000 samples overall). TANRIC has several unique features (Table 2): (i) It provides extensive, intuitive, and interactive analyses on lncRNAs of interest for their interactions with other TCGA genomic/proteomic/epigenomic and clinical data types, both within a tumor type and across tumor types; (ii) it enables users to query expression profiles of user-defined lncRNAs quickly; (iii) it includes RNA-seq data from well-characterized cell lines and other large, non-TCGA patient cohorts, thereby allowing users to validate a pattern of interest or identify model cell lines for experimental characterization.
A resource for the cancer research community that facilitates interrogation of a substantial amount of data from genome-wide analyses. The current version contains data from almost 800 independent experiments studying transcriptomic alterations, genomic gains and losses and somatic mutation information. We designed the system to incorporate data from new experiments and from other alteration types when available (for example, epigenomic and proteomic data). IntOGen bridges the gap between biological and clinical information in cancer.
A database comprising a systematic integration of a large collection of DNA methylation data and mRNA/microRNA expression profiles in human cancer. MethHC integrates data such as DNA methylation, mRNA expression, DNA methylation of microRNA gene and microRNA expression to identify correlations between DNA methylation and mRNA/microRNA expression from TCGA (The Cancer Genome Atlas), which includes 18 human cancers in more than 6000 samples, 6548 microarrays and 12 567 RNA sequencing data.
TCGA SpliceSeq / The Cancer Genome Atlas SpliceSeq
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A web-based resource that provides a quick, user-friendly, highly visual interface for exploring the alternative splicing patterns of TCGA tumors. Percent Spliced In (PSI) values for splice events on samples from 33 different tumor types, including available adjacent normal samples, have been loaded into TCGA SpliceSeq. Investigators can interrogate genes of interest, search for the genes that show the strongest variation between or among selected tumor types, or explore splicing pattern changes between tumor and adjacent normal samples. The interface presents intuitive graphical representations of splicing patterns, read counts and various statistical summaries, including percent spliced in. Splicing data can also be downloaded for inclusion in integrative analyses.
GDISC / Gene-Drug Interaction for Survival in Cancer
Provides a searchable set of survival analyses for the discovery of cancer. GDISC contains the integrative analysis on gene copy number data, drug exposure data and survival data of all 32 cancer types in The Cancer Genome Atlas (TCGA), which generated hypotheses of gene-drug interactions that may impact cancer patient survival. This resource allows biologists and clinicians to specify their cancer, drug and/or gene of interest and returns the identified interaction associated with their query. It also offers a cleaned list of drug names found in all cancer types, patient numbers analysed and other summary tablehttps://gdisc.bme.gatech.edu/ .
TCGA Clinical Explorer / The Cancer Genome Atlas Clinical Explorer
Enhances the clinical utility of The Cancer Genome Atlas (TCGA) data for biomedical scientist and clinicians. The Cancer Genome Atlas Clinical Explorer facilitates the clinical use of TCGA data by the broader cancer research and clinical community by providing a simple interface for exploring the clinically relevant associations from TCGA genomic data sets. This resource also complements existing databases and webpages by providing clinically oriented summaries that are easily accessible by a variety of devices.
EDGE in TCGA / Exploring drivers of gene expression in TCGA cancer genomes
Facilitates rapid exploration of the drivers of gene expression in TCGA. EDGE in TCGA offers a way to compare the relative effects of these genetic and epigenetic drivers of gene expression for each gene and cancer type. The goal of this analysis application was to partition the variance in gene expression (for each gene) due to promoter methylation, somatic mutations, copy number alterations, microRNA abundance, transcription factor expression, and germ-line genetic variability.
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