Research Powered by Agilent s GeneSpring

Transcription

1 Research Powered by Agilent s GeneSpring Agilent Technologies, Inc. Carolina Livi, Bioinformatics Segment Manager

2 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 2

3 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 3

4 What is GeneSpring? GeneSpring is a data visualization and statistical analysis tool used by biologists for bioinformatics analysis and research. 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 4

5 The GeneSpring Family mrna microrna QPCR SNPs Proteomics Metabolomics Applied Markets Multi-Omic Analysis Network Discovery Data Storage and Analysis SureSelect Target Enrichment: DNA-Seq, RNA-Seq, Methyl-Seq Whole Genome Sequencing: ChIP-Seq, Small RNA-Seq 5

6 New Features in GeneSpring 13 6

7 KEGG Pathways in GeneSpring GX/MPP/PA 13 7

8 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 8

9 Copy Number Sample QC parameters Copy Number Variations Metadata framework 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 Cancer Cell. 2010, 17(1): 98 Example: Metadata of 202 TCGA Glioblastoma Samples 9

10 Example: Visualization of Clinical Attributes Cluster Tree with NAC response noted HER4 (A_23_P423853) HER4 (A_32_P183765) 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 (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 Strand Life Sciences 10

11 Entity-Entity Correlation Heatmap Gene1 Gene2 Sample Sample Sample Sample Sample Sample Sample Sample Sample Sample Sample Sample Pearson 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 11 11

12 Clustered heat map indicates abundance values Correlation heat-map indicates correlation coefficients Standard Entity-Sample Heatmap Entity-Entity Correlation Heatmap Human Toxome Consortium (unpublished data): Microarray analysis of 36 E2-induced MCF7 cultures; concentration and time series 12

13 mrna/mirna Correlation Heatmap Cross-Technology Correlation Analysis mrna1 mirna1 Sample Sample Sample Sample Sample Sample Sample Sample Sample Sample Sample Sample Pearson 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 13 13

14 Sample/Sample Correlation Sample1 Sample2 Gene Gene Gene Gene Gene Gene Gene Gene Gene Gene Gene Gene Pearson Finds similar samples and groups of samples across all entities (e.g. genes) 14 14

15 Cross Technology Correlation Analysis 15

16 Cross Technology Correlation Analysis 16

17 Highlighting GeneSpring 13.0 Workflows 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 17

18 Two Applications will now Support NGS Analysis STRAND NGS 2.1 (will be used for NGS data functionality) GENESPRING 13 (GX, MPP and PA will be used for Gene Expression, Proteomics, Metabolomics and Integrated Biology) NGS Read, Regions, Gene Protein Metabolite List GX MPP PA 18

19 Data Transfer between Strand NGS and GeneSpring 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 19

20 The Cross Technology Challenge DNA RNA Protein Metabolite DNA RNA Protein Metabolite DNA RNA Protein Metabolite DNA RNA Protein Metabolite RNA Protein Metabolite RNA Protein Metabolite DNA DNA RNA Protein Metabolite RNA Protein Metabolite Protein Protein DNA RNA DNA RNA Protein Metabolite Protein Metabolite -Omics Biological Processes Identify novel biomarkers Develop new therapeutic targets 20

21 Integrating Biological Analysis Using Pathways Protein A R Protein A HO R R HO Protein B Protein A R R Protein B Protein X HO R Protein B Protein X Protein X Identifies why the pathway is active Suggests follow-on experiments 21

22 Agilent s Platform for Integrated Biology Agilent s OpenLAB Suite Electronic Lab Notebook, DataStore, etc LC/MS GC/MS MassHunter Qual/Quant ChemStation AMDIS Microarrays Feature Extraction GeneSpring Platform Biological Pathways NGS Alignment to Reference Genome Public Tools & Databases 22

23 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: GC/MS RT Correction Proteomics (Part 1) CGH workflows Data Overlay on Pathway GX/MPP GeneSpring Viewer light version to remain competitive Usability Enhancements 23

24 New in GeneSpring GX/MPP 13.1 Agilent s CGH and Proteomics Workflows detect process discover Agilent LC/MS Spectrum Mill / Skyline Mass Profiler Professional Agilent Microarray Agilent Genomics Workbench Feature Extraction GeneSpring GX 24

25 Perpetual licenses GeneSpring GX is now also available under a perpetual license. Contact us to find out more 31

26 GeneSpring Tutorials and Support Free trials, training videos and more GeneSpring.com 30

27 GeneSpring Features and Videos at Agilent/Genomics.com 34

28 35

29 Viewer only license GeneSpring will soon have a viewer license option. Contact us to find out more 32

30 GeneSpring CSP program GeneSpring licenses and data loading support as well as extended free trial for your users. Contact us to find out more 33

31 Thank you! Learn more at GeneSpring.com and Agilent.com 36

32 Agilent Software Solutions for Integrated Biology GeneSpring MPP, PA Metabolomics Genomics Proteomics Profinder GeneSpring GX Spectrum Mill Qual & Quant GeneSpring NGS Bridge (Strand NGS) Skyline MSC Scaffold CRAFT (NMR) 37

33 Multi-Omic Pathway Analysis Full view Amino Acid Metabolism 25

34 Multi-omic Pathway Result Zoomed in view of Amino Acid Metabolism Pathway 26

35 Multi-omic Pathway Result Amino Acid Metabolism with all Metabolites and Genes Displayed 27

36 Statistics and Pathway Analysis Mass Profiler Professional 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 28

37 Examples of MPP Data Processing 29