OASIS: web-based platform for exploring cancer multi-omics data

  title={OASIS: web-based platform for exploring cancer multi-omics data},
  author={Julio Fernandez-Banet and Anthony Esposito and Scott Coffin and Istvan Boerner Horvath and Heather Estrella and Sabine Schefzick and Shibing Deng and Kai Wang and Keith AChing and Ying Ding and Peter Roberts and Paul A. Rejto and Zhengyan Kan},
  journal={Nature Methods},
subdiffractional fiber crossings (Fig. 1b). Images of a crossing of three fibers (Fig. 1c–e) demonstrate that a plot of the modulation amplitudes alone (Fig. 1d,e) revealed the gap between the fibers; this was not visible in the diffraction-limited image (Fig. 1c). We examined two crossing fibers with labels differing by 40° in polarization and direction (Fig. 1h). Profile plots of the modulation amplitudes allowed separation of the fibers down to a distance of ~150 nm (Fig. 1j), and plots from… 
GlioVis data portal for visualization and analysis of brain tumor expression datasets.
Results showed that ANA-12 effectively and dose-dependently reduces the viability of a human glioblastoma cell line with almost complete disappearance of cultured cells 72 hours after treatment, suggesting selective TrkB inhibition might prove to be an effective experimental therapeutic strategy, possibly with fewer off-target toxicities compared with multitarget drugs in patients with astrocytomas harboring oncogenic TrkB.
CVCDAP: an integrated platform for molecular and clinical analysis of cancer virtual cohorts
CVCDAP is presented, a web-based platform to deliver an interactive and customizable toolbox off the shelf for cohort-level analysis of TCGA and CPTAC public datasets, as well as user uploaded datasets, and it is demonstrated that CVCDAP can conveniently reproduce published findings and reveal novel insights by two applications.
LinkedOmics: analyzing multi-omics data within and across 32 cancer types
It is demonstrated that LinkedOmics provides a unique platform for biologists and clinicians to access, analyze and compare cancer multi-omics data within and across tumor types.
OmicsView: omics data analysis through interactive visual analytics
An open source analytics and visualization platform for expression data called OmicsView is released and the power and ease-of-use of the platform is demonstrated by means of a Crohn’s disease data mining exercise where it can quickly uncover disease pathology and identify strong biomarkers of disease and response to treatment.
Unifying cancer and normal RNA sequencing data from different sources
A pipeline is developed that processes and unifies RNA-seq data from different studies, which includes uniform realignment, gene expression quantification, and batch effect removal, finding that uniform alignment and quantification is not sufficient when combining RNA- sequencing data fromDifferent sources and that the removal of other batch effects is essential to facilitate data comparison.
Multi-omics Data Integration, Interpretation, and Its Application
This review collected the tools and methods that adopt integrative approach to analyze multiple omics data and summarized their ability to address applications such as disease subtyping, biomarker prediction, and deriving insights into the data.
BRCA-Pathway: a structural integration and visualization system of TCGA breast cancer data on KEGG pathways
BRCA-Pathway helps researchers navigate omics data towards potentially important genes, regulators, and discover complex patterns involving mutations, CNV, and gene expression data of various patient groups in the biological pathway context.
Enabling cross-study analysis of RNA-Sequencing data
It is found that uniform alignment and quantification is not sufficient when combining RNA-seq data from different sources and that the removal of other batch effects is essential to facilitate data comparison.
Onco-proteogenomics: Multi-omics level data integration for accurate phenotype prediction
How each “omics” technology has individually contributed to cancer research is reviewed, technological and computational advances that have contributed to the realization of onco-proteogenomics are discussed, and current and future translational applications are summarized.
Computational strategies for single-cell multi-omics integration
This review first introduces recent developments in single-cell multi-omics in general and then focuses on the available data integration strategies, which are divided into three categories: early, intermediate, and late data integration.


Visualizing multidimensional cancer genomics data
Cancer genomics projects employ high-throughput technologies to identify the complete catalog of somatic alterations that characterize the genome, transcriptome and epigenome of cohorts of tumor
The cBio cancer genomics portal: an open platform for exploring multidimensional cancer genomics data.
The cBio Cancer Genomics Portal significantly lowers the barriers between complex genomic data and cancer researchers who want rapid, intuitive, and high-quality access to molecular profiles and clinical attributes from large-scale cancer genomics projects and empowers researchers to translate these rich data sets into biologic insights and clinical applications.
The Cancer Cell Line Encyclopedia enables predictive modeling of anticancer drug sensitivity
The results indicate that large, annotated cell-line collections may help to enable preclinical stratification schemata for anticancer agents and the generation of genetic predictions of drug response in the preclinical setting and their incorporation into cancer clinical trial design could speed the emergence of ‘personalized’ therapeutic regimens.
The OASIS web portal
  • Database (Oxford) 2011,
  • 2011