Agilent Technologies, Inc. · NYSE:A
Agilent Technologies — Technical Presentation (February 2017)
47 slides from Agilent Technologies's technical presentation, February 2017
Slide 1: Extracting new insights from cancer genomics and proteomics data
Extracting new insights from cancer genomics and proteomics data Shweta Shukradas Product Manager For Research Use Only. Not for use in diagnostic procedures
Slide 2: The Cross Technology Challenge
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 Me
Slide 3: GeneSpring Suite of Products
GeneSpring Suite of Products GeneSpring GX mRNA Expression microRNA Expression Genome-wide Association Copy Number Variation Variant Analysis with vcf qPCR Mass Profiler Professional Proteomics Metabolomics Strand NGS DNA-Seq, RNA-Seq, ChIP-Seq, Methyl-Seq and small RNA-Seq Pathway Architect Multi-o
Slide 4: Proteomics Workflow in MPP
PROTEOMICS WORKFLOW IN MPP For Research Use Only. Not for use in diagnostic procedures
Slide 5: Most Extensive Software Portfolio for Proteomics Data Analysis
Most Extensive Software Portfolio for Proteomics Data Analysis Identify proteins from discovery Protein Identification data-dependent analysis Spectrum Mill and/or Target peptides for proteins of • Pathway Architect • Agilent Bridge DB Pathway Analysis Target Proteins interest • Quant • Skyline Prot
Slide 6: Agilent's Discovery Proteomics Workflow
Agilent’s Discovery Proteomics Workflow Identification Separate Statistical Pathway and and Detect Analysis Analysis Quantitation 6500 Series Spectrum Mill Mass Profiler Pathway LC/Q-TOF Professional Architect Pathway-directed targeted protein(s) experiment For Research Use Only. Not for use in diag
Slide 7: Two MPP Export Modes in Spectrum Mill
Two MPP Export Modes in Spectrum Mill Generic • Support all data • Protein abundance information only Agilent Proteomics Results (.apr) • Support only Agilent data • Protein abundance and peptide abundance included in export • Supports label-free, SILAC, iTRAQ, TMT • Requires MPP 14.0 release For Re
Slide 8: Mass Profiler Professional
Statistical Analysis Mass Profiler Get from data to answers Professional using statistical tests such as PCA Find differences in mass spec data sets and reach Dive deeper into results statistically valid conclusions using visualizations e.g. heat maps, volcano plots Generate target lists for Q- TOF
Slide 9: Proteomics Workflow in MPP
Proteomics Workflow in MPP • Designed for new .apr format export with protein and peptide-level information • Filters available for peptide-level and protein- level (abundance, frequency, PTMs) • Protein/Peptide Entity Inspector For Research Use Only. Not for use in diagnostic procedures
Slide 10: Protein List Inspector
Protein List Inspector For Research Use Only. Not for use in diagnostic procedures
Slide 11: Protein Inspector Visualization
Protein Inspector Visualization • Works at both the protein and the peptide level simultaneously • This workflow design truly answers the biologist’s questions of “what’s changing in my proteins?” as well as “what’s changing at the peptide level?” For Research Use Only. Not for use in diagnostic pro
Slide 12: Protein Inspector
Protein Inspector Review peptide level information For Research Use Only. Not for use in diagnostic procedures
Slide 13: Protein Inspector Visualization
Protein Inspector Visualization For Research Use Only. Not for use in diagnostic procedures
Slide 14: Filtering on Peptides
Filtering on Peptides • Modifications filter at the level of peptides • The filter dialog lists all the available peptide modifications that are present in the selected entity list • Filtering results in a list of proteins that only consist of specific peptides selected as allowed For Research Use O
Slide 15: Pathway Architect: Pathway analysis using multi-omic data
Pathway Architect Pathway Pathway analysis using multi-omic data Analysis Customers can take the value of their data to another level. Pathway Architect helps them make sense of the data by: Visualizing it on • KEGG Pathways • Wikipathways • BioCyc/MetaCyc Overlaying genomics, proteomics and metabol
Slide 16: Accelerate Your Research With a Complete Pathway Centric Workflow
Accelerate Your Research With a Complete Pathway Centric Workflow Accelerate Visualize with Database Acquire statistical and Map results to LC/MS data Search or your correlation pathways Quantitation research analysis Spectrum Mill Mass Profiler Pathway 6550 iFunnel Professional Architect Q-TOF Skyl
Slide 17: Genomics Workflows in GeneSpring GX
GENOMICS WORKFLOWS IN GENESPRING GX For Research Use Only. Not for use in diagnostic procedures
Slide 18: Genomics Research Solutions
Genomics Research Solutions Prepare Process Design Data Analysis Samples Samples For Research Use Only. Not for use in diagnostic procedures
Slide 19: Gene Expression Analysis Workflow
Gene Expression Analysis Workflow Filtering Statistical Analysis Pathway Analysis Filtering Probe sets on Statistical analysis Pathway Analysis expression Probe sets filtered Performed to find Enrichment test based on the differentially expressed performed with percentile criteria probes pathways of
Slide 20: Clustering - Hierarchical with preview window
Clustering - Hierarchical with preview window For Research Use Only. Not for use in diagnostic procedures
Slide 21: Metadata Framework: adding plots to clustered heatmap
Metadata Framework: adding plots to clustered heatmap For Research Use Only. Not for use in diagnostic procedures
Slide 22: Metadata Framework
Metadata Framework From Experimental Grouping Table information For Research Use Only. Not for use in diagnostic procedures
Slide 23: Correlation Analysis
Correlation Analysis Researchers can view relationships between entities (compounds or proteins) or samples. Clicking on a cell of a heat map, they can quickly view the specific parameters of the correlation For Research Use Only. Not for use in diagnostic procedures
Slide 24: Integrated Analysis: Genomics and Proteomics
INTEGRATED ANALYSIS Genomics and Proteomics For Research Use Only. Not for use in diagnostic procedures
Slide 25: Brain Tumor Study - Quality Control of Discovery Proteomics Data
Brain Tumor Study - Quality Control of Discovery Proteomics Data Sample 5-T Principle Component Analysis Plot Sample Clustered Correlation Plot T – Tumor samples E – Epilepsy samples For Research Use Only. Not for use in diagnostic procedures
Slide 26: Brain Tumor Study - Sample-sample Correlation and PCA
Brain Tumor Study - Sample-sample Correlation and PCA of Discovery Proteomics Data Tumor subgroups demonstrated, using 587 differential proteins, in both PCA and sample correlation showing the sample heterogeneity within tumors PCA Sample-Sample Correlation For Research Use Only. Not for use in diag
Slide 27: Brain Tumor Study - Metadata Analysis of Discovery Proteomics Data
Brain Tumor Study - Metadata Analysis of Discovery Proteomics Data • Hierarchical Clustering of samples provided similar classification as PCA • Tumor subgroups aligned to sample metadata such as age, sex, tumor location and methylation status of MGMT • The metadata did not explain the sub-grouping
Slide 28: Brain Tumor Study - Hierarchical Clustering of Genomic Signatures
Brain Tumor Study - Hierarchical Clustering of Genomic Signatures Hierarchical clustering of 840 mRNA profiles from 173 GBM tumors The four GBM subtypes were re-created Cancer Cell. 2010 January 19; 17(1): 98 For Research Use Only. Not for use in diagnostic procedures
Slide 29: Brain Tumor Study - Metadata Analysis of Genomic Signatures
Brain Tumor Study - Metadata Analysis of Genomic Signatures Metadata obtained from TCGA was imported into the project Metadata framework analysis of batch and sex was used to assess batch affects or bias For Research Use Only. Not for use in diagnostic procedures
Slide 30: Brain Tumor Study - Principal Component Analysis of Genomic Signatures
Brain Tumor Study - Principal Component Analysis of Genomic Signatures Principal component analysis of confirms subtypes in GBM samples from TCGA For Research Use Only. Not for use in diagnostic procedures
Slide 31: Brain Tumor Study - Venn Analysis of Genomic and Proteomic Data Set
Brain Tumor Study - Venn Analysis of Genomic and Proteomic Data Set 587 840 Gene Differential Signatures Proteins 54 Common Proteins and Genes For Research Use Only. Not for use in diagnostic procedures
Slide 32: Brain Tumor Study - PCA Comparison of 587 Proteins to 54 Proteins
Brain Tumor Study - PCA Comparison of Original 587 Proteins to 54 Proteins Identified Using Integration 587 Differential Proteins 54 Proteins from Integration 54 of 587 proteins that overlap the genomics signatures were good enough to capture the sub grouping in tumor samples, indicating the relevan
Slide 33: Brain Tumor Study - Comparison of Differential Proteins to 54 Proteins
Brain Tumor Study - Comparison of 587 Differential Proteins to 54 Proteins Identified Using Integration 587 Differential Proteins 54 Proteins from Integration For Research Use Only. Not for use in diagnostic procedures
Slide 34: Brain Tumor Study - Performance of Genes Identified Using Proteomics Integration
Brain Tumor Study - Performance of 54 Genes Identified Using Proteomics Integration to Original 840 Signature Original Genomic 840 Signature Genomic-Proteomic 54 Signature For Research Use Only. Not for use in diagnostic procedures
Slide 35: Brain Tumor Study: Summary
Brain Tumor Study : Summary • Use sample correlation & PCA on discovery proteomics data to identify outlier sample • Identify a set of differential proteins for the tumor samples • Use correlation and PCA to identify subgroups within tumor samples Proteomics • Clinical metadata visualized to reason
Slide 36: MOA Correlation Analysis - Concordant Genes and Proteins
MOA Correlation Analysis - Concordant Genes and Proteins For Research Use Only. Not for use in diagnostic procedures
Slide 37: Common Pathways - Concordant Genes and Proteins
Common Pathways - Concordant Genes and Proteins Proteomics Genomics For Research Use Only. Not for use in diagnostic procedures
Slide 38: Downstream Processing and Biological Contextualization
DOWNSTREAM PROCESSING AND BIOLOGICAL CONTEXTUALIZATION For Research Use Only. Not for use in diagnostic procedures
Slide 39: CGH Analysis Workflow
CGH Analysis Workflow • Reports from Cytogenomics and AGW are • Genome browser enhancements to support imported in GeneSpring GX for further CGH data downstream analysis and data integration • Overlay on pathways will help cancer researchers visualize aberrations with other enriched entities For Res
Slide 40: Variant Analysis with VCF Import
Variant Analysis with VCF Import process discover Strand NGS VCF files GeneSpring GX SureCall Any other NGS analysis tool For Research Use Only. Not for use in diagnostic procedures
Slide 41: Variant Analysis in GeneSpring GX
Variant Analysis in GeneSpring GX Visualization Data Import and Filtering Pathway Analysis and Results Interpretation • Import files in VCF format • Genome Browser • Single experiment analysis • Annotate region list • Find Genic Parts • Multi-omic analysis • Region list operations • Gene Ontology an
Slide 42: Annotations Manager – Use available annotations or import from external sources
Annotations Manager – Use available annotations or import from external sources • Import annotations from ClinVar, COSMIC, dbNSFP, 1000 Genomes and more • Annotate region list using annotations from Annotations Manager • View annotations in Genome Browser For Research Use Only. Not for use in diagno
Slide 43: Filter genetic variants
Filter genetic variants • Create a new region list that only contains selected columns • Filter the input region list based on specified conditions on the retained columns • Add columns that are functions of selected existing columns For Research Use Only. Not for use in diagnostic procedures
Slide 44: Find Genic Parts
Find Genic Parts For Research Use Only. Not for use in diagnostic procedures
Slide 45: Data Visualization
Data Visualization 1000 genomes ENSEMBL transcripts For Research Use Only. Not for use in diagnostic procedures
Slide 46: Multi-Omic Pathway Analysis
Multi-Omic Pathway Analysis • Multi-omic experiment for data integration • Overlay gene level information for variants • Overlay other genomics, transcriptomics, proteomics or metabolomics data For Research Use Only. Not for use in diagnostic procedures
Slide 47: For Research Use Only. Not for use in diagnostic procedures
For Research Use Only. Not for use in diagnostic procedures
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