BaseSpace® Cohort Analyzer for Analysis andInterpretation of Clinical Omics Data
Empowering translational research.
The BaseSpace Cohort Analyzer (Figure 1) enables• • Molecular and patient data from research studies aretranslational research organizations to integrate andstandardized, normalized, and imported forinvestigate complex patient data from public andrigorous analysis.

private sources. It can be used for biomarker discovery,•• Simple and intuitive navigation provides seamless

identification and selection of patient populations foraccess to correlations between molecular and clinicalclinical trial studies, and generation of individualized

data, enabling users to explore markers of interest

Omics data–driven reports. The BaseSpace Cohort

across relevant patient cohorts (Figure 2).

Analyzer enables organizations to integrate internal
data from clinical trials seamlessly and securely withcollaborator and patient data from public sources. The
BaseSpace Cohort Analyzer has been used at large
pharmaceutical companies and translational research
centers, successfully integrating tens of thousands ofpatient records with corresponding molecular and clinicaldata.

Figure 1: Primary Features of the BaseSpace
Cohort Analyzer•• Intuitive queries can be used to select patient cohorts
based on clinical, molecular, project-based, andstudy-based criteria.
•• A simple interface enables one-click generation ofanalytical reports for one to thousands of patients.
•• Graphs and charts summarize complex information in
an intuitive and easy-to-understand format.

Figure 2: Data Exploration Across Patient CohortsBaseSpace Cohort Analyzer for Analysis andInterpretation of Clinical Omics Data
Aggregation of Complex Data into a Patient-Centric Record
The BaseSapce Cohort Analyzer integrates many types of clinical and molecular data into a patient-centric model. It
includes data collected for a single patient over time, so that researchers can monitor patients, analyze clinical trial
data, and gain a better understanding of disease progression. The integration of heterogeneous and temporal data in
the BaseSpace Cohort Analyzer enables translational researchers to gain a more comprehensive view of thepatient condition.

Individual Patient Analysis, Interpretation, and Reporting
With the BaseSpace Cohort Analyzer, researchers can analyze and interpret data at both the individual level and thepatient cohort level. Individual patient analysis enables researchers to view clinical data and monitor patient treatment
over time. Also, they can filter molecular data to identify biomarkers of interest and view reports identifying biologicallyor clinically significant biomarkers that were detected in the patient.

Patient Cohort Analysis and Dynamic Exploration
Researchers can use the flexible patient selection tool to define a patient cohort quickly by filtering patients based onclinical and molecular parameters. After a cohort is defined, researchers can access many informative metrics, suchas biomarker frequencies and their correlation to survival. This Real-Time Analysis enables investigators to identify
biologically important patterns quickly and discover novel driver mutations or putative prognostic markers easily. Also,groups of patients—such as responders and nonresponders—can be defined and analyzed to determine the differencesin survival, molecular profiles, or clinical attributes.

Access to a Large Repository of Public Data Sets
Using the BaseSpace Analyzer ontology, public data sources such as The Cancer Genome Atlas (TCGA), InternationalCancer Genome Consortium (ICGC), Cancer Cell Line Encyclopedia (CCLE), Gene Expression Omnibus (GEO), and thedatabase of Genotypes and Phenotypes (dbGaP) have been standardized and normalized so that they can be minedrigorously. BaseSpace Analyzer content is focused on disease-specific cohorts such as cancer, autoimmune diseases,
cardiovascular disorders, diabetes, and rare genetic disorders to maximize the analytical capabilities of clinical studies.
A cohort of healthy patients is also available for comparative analyses.

BaseSpace Correlation Engine for Biological
Data Mining
Bringing big data and biology together.
The BaseSpace Correlation Engine supports all stages of the biological discovery process. The BaseSpace Engine
provides life science researchers with unprecedented access to public molecular data and tools for making scientificdecisions. These range from understanding the mechanisms of disease to characterizing the targets of a potential
therapy (Figure 3). A constantly expanding library of genomic data enables researchers to identify billions of novel
correlations (Figure 4), all through a simple graphical interface. Subscribers can upload proprietary data for integrated
analysis, seamlessly share data across multiple geographic locations, and supplement internal knowledge bases withcorrelations and signatures derived from public data.

Gene Function
The BaseSpace Correlation Engine enables scientists to analyze gene function across more than 10,000 genomic
studies in major disease areas and across many kinds of molecular data. This information can be used to understandgene activity across studies in humans, model organisms, and cell lines.

Mechanisms of Drug Action or Disease
With the BaseSpace Correlation Engine, researchers can analyze candidate molecules for pharmacokinetic and toxicity
profiles and compare disease profiles across animal models, cohorts, and disease stages. The BaseSpace Engine
enables users to assess the pathways that play significant roles in disease development across multiple studies anddata types.

Cross-Species Analysis
The BaseSpace Correlation Engine provides a cross-species analysis framework, enabling scientists to optimize
experimental systems and test the mechanisms of disease progression or drug response. Researchers can compare
human data to experimental results from model organisms and harness this information to derive biological context.
Figure 3: The BaseSpace Engine Provides Curated
Studies by Disease Area

Figure 4: The BaseSpace Engine Data Library
Empowers Correlation Studies

With over 15,000 curated studies and more than 100,000 molecular lists,
the BaseSpace Correlation Engine is a constantly growing, data-driven
platform for correlating experimental results with public data for target assessment, biomarker discovery, and drug repositioning.
The BaseSpace Correlation Engine captures genomic and other molecular
data and compares them to tens of thousands of molecular signaturescontained in public data sets. Novel correlations and associations can be
identified automatically and summarized quickly.

© 2014 Illumina, Inc. All rights reserved.
Illumina, BaseSpace, the pumpkin orange color, and the Genetic Energy streaming bases design are trademarks of Illumina, Inc. in the US and/or
other countries. All other names, logos, and other trademarks are the property of their respective owners.
Pub. No. 970-2014-003 Current as of 22 March 2016