Research Powered by Agilent’s GeneSpring Power… · Mass Profiler Professional February 17, 2015 28 Designed primarily for MS data •Also supports NMR Performs many types of statistical

Research Powered by Agilent’s GeneSpring

Carolina Livi, Bioinformatics Segment Manager

Agilent Technologies, Inc.

Research Powered by GeneSpring

Topics

• GeneSpring (GS) platform

• New features in GS 13

• What’s coming in 13.1

• Strand NGS

• GeneSpring Demo

• The Cross Technology Challenge

• Agilent’s Integrated Biology Platform

February 17, 2015

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For Research Use Only. Not For Use in Diagnostic Procedures.

Research Powered by GeneSpring Topics

• GeneSpring 13

• Metadata Visualization Framework

• Correlation Analysis

• KEGG pathways

• GeneSpring 13.1

• Support for CGH microarray data from AGW and Cytogenomics

• GeneSpring Demo

• Metadata framework in gene expression experiment

• mRNA and miRNA with MOA correlation

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GeneSpring is a data visualization and statistical

analysis tool used by biologists for

bioinformatics analysis and research.

What is GeneSpring?

• Analyzes data from Microarrays, qPCR, NGS, and Mass

Spectrometry.

• Enables biologists to apply powerful statistical methods without

requiring expertise in statistics and mathematics.

• Interprets data results in a biological context, including multi-omics


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Proteomics

Metabolomics

Applied Markets

SureSelect Target

Enrichment:

DNA-Seq, RNA-Seq, Methyl-Seq

Whole Genome Sequencing:

ChIP-Seq, Small RNA-Seq

Multi-Omic Analysis

Network Discovery

mRNA

microRNA

QPCR

SNPs

The GeneSpring Family

Data Storage and Analysis


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February 17, 2015

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New Features in GeneSpring 13


KEGG Pathways in GeneSpring GX/MPP/PA 13


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Metadata Visualization Framework

Allows for addition of experimental and non-experimental

parameters

Allows for categorical and numerical data

Allows for filtering on metadata

More details during live demonstration

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Example: Metadata of 202 TCGA Glioblastoma Samples

Sam

ple

QC

para

mete

rs

Copy

Num

ber

Variations

Cop

y N

um

be

r

Cancer Cell. 2010, 17(1): 98

Features

• Entity-Sample (e.g. Gene-Sample)

clustering h/m with entity associated

values

• Correlate with metadata: phenotype,

clinical outcome, physiological

values

• Table, scatter plot, bar chart,

metadata heatmap

• Categorical or continuous attributes

• Ability to sort on numerical and

categorical metadata; re-clustering

• Zoom in/out, select tree nodes

updates metadata plots

• Metadata for grouped samples

Metadata framework


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© Strand Life Sciences


Example: Visualization of Clinical Attributes

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• Cluster Tree with NAC response noted

• Tumor sizes before and after treatment

• Correlation with Sinn score (RS0, RS1, RS2, RS3)

• Role of molecular subtype (basal or non-basal) in response to NAC

• Changes in HER4 (down-regulated or up-regulated)

• Tumor stage assessment by pathologist

From: Oncol. Rep. 2011 26(4):1037; GSE21974

• Study of 32 patients with primary invasive breast cancer

• Tumor specimens obtained by before and after chemotherapy

(neoadjuvant chemotherapy, NAC)

• Tumor lesions were sonographically measured before and after

NAC; histological regression assessed by Sinn score

• Molecular subtype (basal/non-basal), expression microarrays

(Agilent 44K, Single Color) and marker genes (HER4,PSR, ESR)

are predictive of response to NAC

HER4

(A_23_P423853)

HER4

(A_32_P183765)

http://www.ncbi.nlm.nih.gov/pubmed/21769435



Entity-Entity Correlation Heatmap

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Gene1 Gene2

Sample1 0.989 1.456

Sample2 0.195 0.223

Sample3 0.270 0.752

Sample4 0.885 1.073

Sample5 0.737 0.948

Sample6 0.937 1.013

Sample7 0.629 0.657

Sample8 0.776 0.975

Sample9 0.414 0.707

Sample10 0.468 0.786

Sample11 0.645 0.747

Sample12 0.255 0.273

Pearson 0.877

Features

• Finds similar responders and groups across all samples

• Any within-technology entities, e.g. MA-MA

• Any X-technology: mRNA(MA)-Protein(LCMS); mRNA(MA)-mRNA(RNASEQ),

mRNA(MA)-miRNA(MA), etc.

• X-technology mapping is not required for this type of plot

• X-tech normalization is not required


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Clustered heat map indicates abundance values Correlation heat-map indicates correlation coefficients

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Human Toxome Consortium (unpublished data): Microarray analysis of 36 E2-induced MCF7 cultures;

concentration and time series

Standard Entity-Sample Heatmap Entity-Entity Correlation Heatmap


mRNA1 miRNA1

Sample1 0.793 11.856

Sample2 0.675 7.444

Sample3 0.943 12.166

Sample4 0.635 10.770

Sample5 0.780 9.295

Sample6 0.292 5.160

Sample7 0.569 10.637

Sample8 0.042 0.835

Sample9 0.859 13.948

Sample10 0.880 14.000

Sample11 0.151 2.405

Sample12 0.083 1.538

Pearson 0.952

mRNA/miRNA Correlation Heatmap Cross-Technology Correlation Analysis

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Features

Clustering in correlation space

Finds correlated and anti-correlated mRNA/miRNA groups

Filter, sort by mRNA or miRNA expression

Filter on significance statistics (mRNA & miRNA)

Drill down as scatter plot for 1 entity at a time

Export data as spreadsheet


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Sample1 Sample2

Gene1 0.651 1.372

Gene2 0.818 1.590

Gene3 0.945 1.716

Gene4 0.578 0.643

Gene5 0.464 1.186

Gene6 0.675 0.947

Gene7 0.323 0.642

Gene8 0.304 0.774

Gene9 0.043 0.783

Gene10 0.943 1.452

Gene11 0.908 1.686

Gene12 0.415 0.808

Pearson 0.822

Sample/Sample Correlation

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Finds similar samples and groups of samples across all entities (e.g. genes)


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Cross Technology Correlation Analysis

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Cross Technology Correlation Analysis

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Highlighting GeneSpring 13.0 Workflows

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The ability to analyse NGS experiments along with existing experiments

in GeneSpring is an all important utility enabling:

• Identifying common pathways that are of significance in

gene expression, metabolite abundance and sequencing

experiments using KEGG.

• Correlation Analysis and Metadata Framework between

sequencing studies and microarray expression data or

metabolite abundance measured using mass

spectrometry.

• Cross- platform investigation leading to exploratory

analysis.

• Visualization of sequencing and array data in same

project


Two Applications will now Support NGS Analysis

GX

MPP

GENESPRING 13

(GX, MPP and PA will be used for Gene

Expression, Proteomics, Metabolomics and

Integrated Biology)

STRAND NGS 2.1 (will be used for NGS data

functionality)

NGS Read,

Regions,

Gene

Protein

Metabolite List

PA


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• Methyl Seq Enhancement - choose either the positive and/or the negative strand

during Methylation Detection in targeted experiments.

• Alignment - the built-in aligner allows raw read alignment

• QC manager - the various plots are available for data analysis: Alignment Score,

Pre-alignment, Targeted Region, Mapping Quality

• Optimization - Up to 4X faster

Data Transfer between Strand NGS and GeneSpring


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The Cross Technology Challenge

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DNA RNA Protein Metabolite

RNA Protein Metabolite


DNA

DNA RNA

Protein

Protein Metabolite





DNA

DNA RNA

Protein

Protein Metabolite


“-Omics” Biological Processes

• Identify novel biomarkers

• Develop new therapeutic targets


Integrating Biological Analysis Using Pathways

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R

R

HO

Protein B

Protein A

Protein X

R

R

HO

Protein B

Protein A

Protein X R

R

HO

Protein B

Protein A

Protein X

• Identifies why the pathway is active

• Suggests follow-on experiments


Agilent’s Platform for Integrated Biology

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LC/MS

GC/MS

Microarrays Biological

Pathways

MassHunter Qual/Quant

ChemStation AMDIS

Feature Extraction GeneSpring Platform

Alignment to Reference Genome NGS

Public Tools & Databases

Agilent’s OpenLAB Suite Electronic Lab Notebook, DataStore, etc


● GC/MS RT Correction

● Proteomics (Part 1)

● CGH workflows

● Data Overlay on Pathway

● GX/MPP GeneSpring Viewer – “light” version to remain

competitive

● Usability Enhancements

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Multi-omic focus for GeneSpring 13.1

GeneSpring continues to build upon its industry gold-standard platform for

genomics analysis, expanding the portfolio for proteomics and metabolomics.

The GeneSpring Integrated Biology solution includes CGH, Proteomics and

the Metabolomic features for 13.1:


New in GeneSpring GX/MPP 13.1 Agilent’s CGH and Proteomics Workflows

Spectrum Mill / Skyline Mass Profiler Professional Agilent LC/MS

process discover detect

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Agilent Microarray Agilent Genomics Workbench

Feature Extraction GeneSpring GX


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Perpetual licenses

Contact us to find out more

GeneSpring GX is now also

available under a perpetual

license.


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GeneSpring Tutorials and

Support

GeneSpring.com

Free trials, training videos and

more


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GeneSpring Features and Videos at

Agilent/Genomics.com


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Viewer only license


GeneSpring will soon have a

viewer license option.


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GeneSpring CSP program


GeneSpring licenses and data

loading support as well as

extended free trial for your

users.


Thank you!

Learn more at

GeneSpring.com

and Agilent.com

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Agilent Software Solutions for Integrated Biology

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Proteomics Genomics Metabolomics

Profinder

Qual & Quant

CRAFT (NMR)

MSC

GeneSpring GX

GeneSpring NGS

Bridge (Strand NGS)

Spectrum Mill

Skyline

Scaffold

GeneSpring

MPP, PA


Multi-Omic Pathway Analysis Full view Amino Acid Metabolism

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February 17, 2015


Multi-omic Pathway Result Zoomed in view of Amino Acid Metabolism Pathway

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February 17, 2015


Multi-omic Pathway Result Amino Acid Metabolism with all Metabolites and Genes Displayed

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February 17, 2015


Statistics and Pathway Analysis Mass Profiler Professional

February 17, 2015

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Designed primarily for MS data

• Also supports NMR

Performs many types of statistical

analysis

• ANOVA, clustering, PCA, class

prediction tools

ID Browser for compound annotation

and identification

Export MS/MS target list

Pathway Architect for biological

context


Examples of MPP Data Processing

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Documents

Research Powered by Agilent’s GeneSpring Power… · Mass Profiler Professional February 17, 2015 28 Designed primarily for MS data •Also supports NMR Performs many types of statistical