Abstract
The cBioPortal for Cancer Genomics is an open-source software platform that enables interactive, exploratory analysis of large-scale cancer genomics data sets with a biologist-friendly ...interface. It integrates genomic and clinical data, and provides a suite of visualization and analysis options, including OncoPrint, mutation diagram, variant interpretation, survival analysis, expression correlation analysis, alteration enrichment analysis, cohort and patient-level visualization, among others.
The public site (https://www.cbioportal.org) hosts data from more than 280 studies from diverse sources including individual labs and large consortia. All data is also available in the cBioPortal Datahub (https://github.com/cBioPortal/datahub/). Data from 40 studies, totaling more than 10,000 samples, was added in 2019, including the latest release from the Cancer Cell Line Encyclopedia and the Pediatric Preclinical Testing Consortium. The site is accessed by over 30,000 unique visitors per month. cBioPortal also supports AACR Project GENIE with a dedicated instance hosting the GENIE cohort of 80,000 clinically sequenced samples from 19 institutions worldwide (http://genie.cbioportal.org).
In addition, more than 40 instances are installed locally at academic institutions and pharmaceutical/biotechnology companies. In support of these local installations, cBioPortal now has improved documentation and simplified installation via container technologies such as Docker and Kubernetes.
Building on our successful refactoring of the code base, we have released a variety of new features and enhancements to cBioPortal over the past year. Most notably, we released a group comparison feature, enabling users to define groups of interest based on any clinical or genomic features. User-defined groups can be compared simultaneously across genomic and clinical data, including survival analysis and genomic alteration enrichment analysis. Additional new features include: integration of mutation annotations from dbSNP, ClinVar and gnomAD; support for waterfall plots to enable treatment response analysis; saving user preferences for chart layout on study view.
The cBioPortal remains under active development. The portal is fully open source (https://github.com/cBioPortal/) under a GNU Affero GPL license. Development is a collaborative effort among groups at Memorial Sloan Kettering Cancer Center, Dana-Farber Cancer Institute, Children's Hospital of Philadelphia, Princess Margaret Cancer Centre, and The Hyve. Ongoing and future development is focused on: (1) building the open source community; (2) continued performance improvements; (3) expanding user support, documentation and training resources; (4) supporting longitudinal data analysis and visualization; (5) developing novel features to support immunogenomics and immunotherapy; (6) enhancing individual variants and overall patient interpretation; (7) supporting single cell data visualizations and analysis.
Citation Format: Jianjiong Gao, Tali Mazor, Adam Abeshouse, Ino de Bruijn, Benjamin Gross, Karthik Kalletla, Priti Kumari, Ritika Kundra, Xiang Li, James Lindsay, Aaron Lisman, Pieter Lukasse, Ramyasree Madupuri, Angelica Ochoa, Oleguer Plantalech, Sander Rodenburg, Fedde Schaeffer, Robert Sheridan, Lucas Sikina, Jing Su, S. Onur Sumer, Yichao Sun, Paul van Dijk, Sjoerd van Hagen, Pim van Nierop, Avery Wang, Manda Wilson, Hongxin Zhang, Gaofei Zhao, Kelsey Zhu, Kees van Bochove, Ugur Dogrusoz, Allison Heath, Adam Resnick, Trevor J. Pugh, Chris Sander, Ethan Cerami, Nikolaus Schultz. The cBioPortal for Cancer Genomics abstract. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 3209.
Dynamic visual exploration of detailed pathway information can help researchers digest and interpret complex mechanisms and genomic datasets.
ChiBE is a free, open-source software tool for ...visualizing, querying, and analyzing human biological pathways in BioPAX format. The recently released version 2 can search for neighborhoods, paths between molecules, and common regulators/targets of molecules, on large integrated cellular networks in the Pathway Commons database as well as in local BioPAX models. Resulting networks can be automatically laid out for visualization using a graphically rich, process-centric notation. Profiling data from the cBioPortal for Cancer Genomics and expression data from the Gene Expression Omnibus can be overlaid on these networks.
ChiBE's new capabilities are organized around a genomics-oriented workflow and offer a unique comprehensive pathway analysis solution for genomics researchers. The software is freely available at http://code.google.com/p/chibe.
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Abstract
The cBioPortal for Cancer Genomics is an open-source software platform that enables interactive, exploratory analysis of large-scale cancer genomics data sets with a biologist-friendly ...interface. It integrates genomic and clinical data, and provides a suite of visualization and analysis options, including OncoPrint, mutation diagram, variant interpretation, survival analysis, expression correlation analysis, alteration enrichment analysis, cohort and patient-level visualization, among others.
The public site (http://www.cbioportal.org) hosts data from more than 200 studies from individual labs and large consortia, including the newly added TCGA Pan-Cancer Atlas data and the Count Me In project. These studies can be explored and queried individually or combined together into “virtual studies”. Users are now allowed to login and save virtual studies for query and analysis. The site is currently accessed by approximately 30,000 unique visitors per month. The software is also installed locally at dozens of academic institutions and pharmaceutical/biotechnology companies. A notable instance is the cBioPortal for AACR GENIE (http://www.cbioportal.org/genie/) hosting 60,000 clinically sequenced samples from multiple institutions.
Over the past year, the code base has been fully refactored, resulting in a more responsive and interactive website. A new web API is in beta facilitating easier programmatic access to data. In addition, all public studies are available for download from the new datahub (https://github.com/cBioPortal/datahub/).
The cBioPortal remains under active development. The portal is fully open source (https://github.com/cBioPortal/) under a GNU Affero GPL license. Development is a collaborative effort among groups at Memorial Sloan Kettering Cancer Center, Dana-Farber Cancer Institute, Children’s Hospital of Philadelphia, Princess Margaret Cancer Centre, and The Hyve. Ongoing and future development is focused on: (1) building the open source community; (2) continued performance improvements; (3) expanding user support, documentation and training resources; (4) developing novel features to support immunogenomics and immunotherapy; (5) enhancing individual variants and overall patient interpretation; (6) creating a simplified query interface; and (7) enabling comparative analysis of user-defined patient cohorts.
Citation Format: Jianjiong Gao, Tali Mazor, Adam Abeshouse, Ersin Ciftci, Ino de Bruijn, Benjamin Gross, Karthik Kalletla, Priti Kumari, Ritika Kundra, James Lindsay, Aaron Lisman, Pieter Lukasse, Ramyasree Madupuri, Angelica Ochoa, Oleguer Plantalech, Pichai Raman, Fedde Schaeffer, Robert Sheridan, Jing Su, S. Onur Sumer, Yichao Sun, Sander Tan, Sjoerd van Hagen, Avery Wang, Manda Wilson, Hongxin Zhang, Gaofei Zhao, Kelsey Zhu, Kees van Bochove, Ugur Dogrusoz, Trevor J. Pugh, Adam Resnick, Chris Sander, Ethan Cerami, Nikolaus Schultz. The cBioPortal for cancer genomics abstract. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 910.
Proteins that modulate the activity of transcription factors, often called modulators, play a critical role in creating tissue- and context-specific gene expression responses to the signals cells ...receive. GEM (Gene Expression Modulation) is a probabilistic framework that predicts modulators, their affected targets and mode of action by combining gene expression profiles, protein-protein interactions and transcription factor-target relationships. Using GEM, we correctly predicted a significant number of androgen receptor modulators and observed that most modulators can both act as co-activators and co-repressors for different target genes.
Abstract
Introduction Graphical representations of participants and their relationships are essential for exchanging knowledge about complex biological processes. To convey this information clearly ...and unambiguously, it is necessary to assign standard meanings to symbols and their connectivity. For this purpose, the System Biology Graphical Notation (SBGN) has been developed.As SBGN is becoming more widely adopted, and used in various software tools, there is an increasing need for a standard file format able to capture the SBGN maps. Exchange using graphics-only file formats (such as SVG) is insufficient, because the biological meaning of elements is lost. There is a need for a toolset that enables diagram exchange while preserving biological meaning and relations.
Results
To meet this need, we are developing an Extensible Markup Language (XML) schema definition. In addition we are developing a software library called LibSBGN. Besides reading and writing files, this library will also be used to validate SBGN maps against the specifications, and convert to and from related systems biology standards, such as SBML and BioPAX.LibSBGN is still under development, but is already being adopted by several tools (See the LibSBGN project page for an up-to-date list of client software). The early adoption of LibSBGN by those tools helps to ensure that LibSBGN is independent of a specific software application, and does not contain artifacts for specific tools. LibSBGN is currently implemented in Java, a parallel C++ version is planned for the future.A test-suite of dozens of LibSBGN documents, covering every possible feature of SBGN maps, was created. This test-suite can be used by developers to check for compliance with the standard, and compare rendering capabilities with other tools.LibSBGN is a community effort, involving people from institutes all around the world, representing a wide selection of pathway tools. The community is organized around a sourceforge project site (http://libsbgn.sourceforge.net), a mailing list and monthly online meetings.A first release of LibSBGN, covering only the Process Description (PD) language, is planned in October 2010. Support for all three languages of SBGN is planned for a later release.
Abstract
The cBioPortal for Cancer Genomics is an open source software platform that enables interactive, exploratory analysis of large-scale cancer genomics data sets. It integrates genomic and ...clinical data, and provides a suite of visualization and analysis options, including cohort and patient-level visualization, mutation visualization, survival analysis, alteration enrichment analysis, and network analysis. The user interface is user-friendly, responsive, and makes genomic data easily accessible to scientists and clinicians. The public site (http://www.cbioportal.org) hosts data from more than 165 studies, including data from large consortia (TCGA and ICGC) and individual labs. With newly released functionality, users can now explore and query these studies individually or can combine multiple studies into new “virtual studies”. The main features of the portal include OncoPrints, a compact graphical representation of alterations in multiple genes across a cohort, mutational diagrams that show locations and frequencies of mutations in a single gene, Kaplan-Meier survival curves, plots that allow the visualization of correlation between different data types for a single or multiple genes (e.g. the correlation between DNA copy number and mRNA expression), among others. To facilitate interpretation of genomic data, the cBioPortal also now integrates annotations from several leading knowledgebases (OncoKB, CIViC, MyCancerGenome and COSMIC), as well as other resources that can guide variant interpretation (CancerHotspots, MutationAssessor, SIFT and PolyPhen).
The cBioPortal has been widely adopted by the cancer community, with dozens of private instances at academic institutions and pharmaceutical/biotechnology companies. The public portal is currently accessed by approximately 25K unique visitors per month. Another notable instance is the cBioPortal for AACR GENIE (http://www.cbioportal.org/genie/), which hosts 31,706 samples from AACR Project GENIE. The cBioPortal is fully open source and all code is available on GitHub (https://github.com/cBioPortal/) under a GNU Affero GPL license. Development is a collaborative effort among groups at Memorial Sloan Kettering Cancer Center, Dana-Farber Cancer Institute, Children's Hospital of Philadelphia, Princess Margaret Cancer Centre, and The Hyve, an open source bioinformatics company based in the Netherlands. Ongoing development efforts are focused on (1) building the open source community; (2) implementing architectural and performance improvements; (3) expanding user support, documentation and training resources; (4) developing novel features to support immunogenomics and immunotherapy; (5) enhancing visualization of patient timelines, multiple tumor profiles, and cohort response; and (6) releasing a new public Application Programming Interface (API).
Citation Format: Jianjiong Gao, Tali Mazor, Ersin Ciftci, Pichai Raman, Pieter Lukasse, Istemi Bahceci, Alexandros Sigaras, Adam Abeshouse, Ino de Bruijn, Benjamin Gross, Ritika Kundra, Aaron Lisman, Angelica Ochoa, Robert Sheridan, Jing Su, Selcuk O. Sumer, Yichao Sun, Avery Wang, Jiaojiao Wang, Manda Wilson, Hongxin Zhang, Priti Kumari, James Lindsay, Karthik Kalletla, Kelsey Zhu, Oleguer Plantalech, Fedde Schaeffer, Sander Tan, Dionne Zaal, Sjoerd van Hagen, Kees van Bochove, Ugur Dogrusoz, Trevor J. Pugh, Adam Resnick, Chris Sander, Nikolaus Schultz, Ethan Cerami. The cBioPortal for Cancer Genomics: An intuitive open-source platform for exploration, analysis and visualization of cancer genomics data abstract. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 923.
Abstract
Over the past decade, The Cancer Genome Atlas (TCGA) has profiled more than 11,000 tumors spanning 33 distinct cancer types. The TCGA PanCanAtlas is a collaborative project by the TCGA ...Research Network that aims to address relevant overarching questions in oncology based on a cross-cancer analysis of the full, uniformly reprocessed TCGA data set. Here, we present results from our analysis of genetic alterations in mitogenic signaling pathways across cancer.
Genetic alterations in signaling pathways that control cell cycle progression, apoptosis, and cell growth are common hallmarks of cancer, but the extent, mechanisms, and co-occurrence of alterations in these pathways differ between individual tumors and tumor types. Using mutations and copy-number changes in 9,125 tumor samples profiled by TCGA, we analyzed the mechanisms and patterns of alterations in 10 canonical pathways: cell cycle, Hippo, Myc, Notch, beta-catenin / WNT, PI-3-Kinase / Akt, receptor-tyrosine kinase / RAS / MAP-kinase signaling, TP53, and TGF-beta signaling, as well as oxidative stress response. For each of these pathways, we propose an expert-curated description (or “template”) that includes the relevant (altered) genes and the connections between them, as well as a detailed catalogue of the driver mutations and copy number changes with known oncogenic relevance. We provide a high-level map of pathway alteration frequencies across tissues and relevant cancer subtypes as well as detailed frequencies of alteration at the gene level for each individual pathway. We also investigate relationships of co-occurrence and mutual exclusivity across pathways and evaluate therapeutic implications, including drug combinations. Forty-nine percent of tumors had at least one potentially targetable alteration in the evaluated pathways, and 31% of tumors had multiple targetable alterations, making them candidates for combination therapy.
Our work delineates the full landscape of oncogenic alterations in mitogenic signaling pathways across cancer, and the pathway templates as well as the richly annotated data set that we provide will constitute an invaluable public resource for future use by the cancer genomics and precision oncology communities.
Citation Format: Francisco Sanchez-Vega, Marco Mina, Joshua Armenia, Walid K. Chatila, Augustin Luna, Konnor La, Sofia Dimitriadoy, David L. Liu, Havish S. Kantheti, Zachary Heins, Angelica Ochoa, Benjamin Gross, Jianjiong Gao, Hongxin Zhang, Ritika Kundra, Cyriac Kandoth, Istemi Bahceci, Leonard Dervishi, Ugur Dogrusoz, Wanding Zhou, Hui Shen, Peter W. Laird, Alice H. Berger, Trever G. Bivona, Alexander J. Lazar, Gary Hammer, Thomas Giordano, Lawrence Kwong, Grant McArthur, Chenfei Huang, Mitchell J. Frederick, Frank McCormick, Matthew Meyerson, The Cancer Genome Atlas Research Network, Eliezer Van Allen, Andrew D. Cherniack, Giovanni Ciriello, Chris Sander, Nikolaus Schultz. The molecular landscape of oncogenic signaling pathways in The Cancer Genome Atlas abstract. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 3302.
Abstract
Introduction Graphical representations of participants and their relationships are essential for exchanging knowledge about complex biological processes. To convey this information clearly ...and unambiguously, it is necessary to assign standard meanings to symbols and their connectivity. For this purpose, the System Biology Graphical Notation (SBGN) has been developed.As SBGN is becoming more widely adopted, and used in various software tools, there is an increasing need for a standard file format able to capture the SBGN maps. Exchange using graphics-only file formats (such as SVG) is insufficient, because the biological meaning of elements is lost. There is a need for a toolset that enables diagram exchange while preserving biological meaning and relations.
Results
To meet this need, we are developing an Extensible Markup Language (XML) schema definition. In addition we are developing a software library called LibSBGN. Besides reading and writing files, this library will also be used to validate SBGN maps against the specifications, and convert to and from related systems biology standards, such as SBML and BioPAX.LibSBGN is still under development, but is already being adopted by several tools (See the LibSBGN project page for an up-to-date list of client software). The early adoption of LibSBGN by those tools helps to ensure that LibSBGN is independent of a specific software application, and does not contain artifacts for specific tools. LibSBGN is currently implemented in Java, a parallel C++ version is planned for the future.A test-suite of dozens of LibSBGN documents, covering every possible feature of SBGN maps, was created. This test-suite can be used by developers to check for compliance with the standard, and compare rendering capabilities with other tools.LibSBGN is a community effort, involving people from institutes all around the world, representing a wide selection of pathway tools. The community is organized around a sourceforge project site (http://libsbgn.sourceforge.net), a mailing list and monthly online meetings.A first release of LibSBGN, covering only the Process Description (PD) language, is planned in October 2010. Support for all three languages of SBGN is planned for a later release.
Abstract 1249: cBioPortal for Cancer Genomics Mazor, Tali; de Bruijn, Ino; AlHamad, Rima ...
Cancer research (Chicago, Ill.),
03/2024, Volume:
84, Issue:
6_Supplement
Journal Article
Peer reviewed
Abstract cBioPortal for Cancer Genomics is an open-source platform for interactive, exploratory analysis of large-scale clinico-genomic data. cBioPortal provides a suite of user-friendly ...visualizations and analyses, including OncoPrints, mutation lollipop plots, variant interpretation, group comparison, survival analysis, expression correlation analysis, alteration enrichment analysis, cohort and patient-level visualization. The public site (https://www.cbioportal.org) is accessed by >35,000 unique visitors each month and hosts data from >390 studies spanning individual labs and large consortia. All data is available in the cBioPortal Datahub: https://github.com/cBioPortal/datahub; in 2023 we added 35 studies (~16,000 samples). In addition, >86 instances of cBioPortal are installed at academic institutions and companies worldwide. We also host a dedicated instance for AACR Project GENIE, enabling access to the GENIE cohort of >197,000 clinically sequenced samples from 19 institutions (https://genie.cbioportal.org). The GENIE Biopharma Collaborative (BPC) enables the collection of comprehensive clinical annotations including response, outcome, and treatment history, which can all be visualized in cBioPortal. BPC cohorts for non-small cell lung cancer (~2,000 samples) and colorectal cancer (~1,500 samples) are available, with more cancer types to come. This past year, we significantly enhanced existing features. Group comparison now includes a Mutations tab showing a mirrored lollipop plot and outcomes analysis now supports hazard ratios and landmark analysis. Arm-level copy number can now be compared across groups, as can any data in the generic assay format. We also enhanced the study view. Users can now add charts to summarize the copy number of a specific gene across the cohort. The option to add custom data charts now supports numerical data as well as categorical data. Filters in study view can now be manually submitted, which provides a performance improvement when applying multiple filters in a large cohort. Larger-scale performance improvements are currently underway. We continue to improve support for multimodal datasets incorporating derived data elements, including cell type counts and fractions per sample from imaging or single cell data. The MSK-SPECTRUM ovarian cancer study has samples profiled with bulk sequencing, scRNASeq, H&E and mpIF imaging. Through integrations with CELLxGENE (single cell data) and Minerva (imaging), users can explore these data modalities in detail in isolation and query them jointly in cBioPortal. cBioPortal is open source (https://github.com/cBioPortal/). Development is a collaborative effort among groups at Memorial Sloan Kettering Cancer Center, Dana-Farber Cancer Institute, Childrens Hospital of Philadelphia, Princess Margaret Cancer Centre, Caris Life Sciences, Bilkent University and The Hyve. We welcome open source contributions from others in the cancer research community. Citation Format: Tali Mazor, Ino de Bruijn, Rima AlHamad, Calla Chennault, Corey Dubin, Jeremy Easton-Marks, Zhaoyuan Fu, Benjamin Gross, Charles Haynes, David M. Higgins, Jason Hwee, Prasanna K. Jagannathan, Mirella Kalafati, Karthik Kalletla, James Ko, Tim Kuijpers, Sowmiyaa Kumar, Priti Kumari, Ritika Kundra, Bryan Lai, Xiang Li, James Lindsay, Aaron Lisman, Qi-Xuan Lu, Ramyasree Madupuri, Angelica Ochoa, Yusuf Z. Özgül, Oleguer Plantalech, Matthijs N. Pon, Baby A. Satravada, Jessica Singh, Selcuk Onur Sumer, Pim van Nierop, Floris Vleugels, Avery Wang, Manda Wilson, Hongxin Zhang, Gaofei Zhao, Ugur Dogrusoz, Allison Heath, Adam Resnick, Trevor J. Pugh, Chris Sander, Ethan Cerami, Jianjiong Gao, Nikolaus Schultz. cBioPortal for Cancer Genomics abstract. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1249.
Abstract
The cBioPortal for Cancer Genomics is an open-access portal (http://cbioportal.org) that enables interactive, exploratory analysis of large-scale cancer genomics data. It integrates genomic ...and clinical data, and provides a suite of visualization and analysis options, including cohort and patient-level visualization, mutation visualization, survival analysis, enrichment analysis, and network analysis. The user interface is user-friendly, responsive, and makes genomic data easily accessible to translational scientists, biologists, and clinicians.
The cBioPortal is a fully open source platform. All code is available on GitHub (https://github.com/cBioPortal/) under GNU Affero GPL license. The code base is maintained by multiple groups, including Memorial Sloan Kettering Cancer Center, Dana-Farber Cancer Institute, Children’s Hospital of Philadelphia, Princess Margaret Cancer Centre, and The Hyve, an open source bioinformatics company based in the Netherlands. More than 30 academic centers as well as multiple pharmaceutical and biotech companies maintain private instances of the cBioPortal. This includes the recently launched cBioPortal instance at the NCI Genomic Data Commons (https://cbioportal.gdc.nci.nih.gov/), and two large cBioPortal instances hosting genomic and clinical data at MSK and DFCI, supporting the MSK-IMPACT and DFCI Profile projects, two of the largest clinical sequencing efforts in the world.
Our multi-institutional software team has accelerated the progress of evolving the core architectural technologies and developing new features to keep pace with the rapidly advancing fields of cancer genomics and precision cancer medicine. For example, we have integrated multi-platform genomics data with extensive clinical data including patient demographics, treatment history, and survival data. We have also developed a patient-centric view that visualizes both clinical and genomic data with annotation from OncoKB knowledge base. In the next few years, the development team will focus on the following areas:
(1) Implementing major architectural changes to ensure future scalability and performance.
(2) New features to support precision medicine, including (i) improved integration of knowledge base annotation, (ii) enhanced visualization of patient timeline, drug response, and tumor evolution, (iii) new patient similarity metrics, (iv) improved support for immunogenomics and immunotherapy, and (v) new visualization and analysis features for understanding response to therapy.
(3) New analysis and target discovery features for large cohorts, including (i) supporting user-defined virtual cohort by selecting samples from multiple studies, and (ii) comparison of genomic or clinical characteristics of two or more selected cohorts.
(4) Expanding community outreach, user support and training, and documentation.
Citation Format: Jianjiong Gao, Ersin Ciftci, Pichai Raman, Pieter Lukasse, Istemi Bahceci, Adam Abeshouse, Hsiao-Wei Chen, Ino de Bruijn, Benjamin Gross, Zachary Heins, Ritika Kundra, Aaron Lisman, Angelica Ochoa, Robert Sheridan, Onur Sumer, Yichao Sun, Jiaojiao Wang, Manda Wilson, Hongxin Zhang, James Xu, Andy Dufilie, Priti Kumari, James Lindsay, Anthony Cros, Karthik Kalletla, Fedde Schaeffer, Sander Tan, Sjoerd van Hagen, Jorge Reis-Filho, Kees van Bochove, Ugur Dogrusoz, Trevor Pugh, Adam Resnick, Chris Sander, Ethan Cerami, Nikolaus Schultz. The cBioPortal for Cancer Genomics: an open source platform for accessing and interpreting complex cancer genomics data in the era of precision medicine abstract. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 2607. doi:10.1158/1538-7445.AM2017-2607
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