Gonzalo G ómez, PhD. [email protected]

Gonzalo Gómez, PhD. [email protected] Gómez, PhD. [email protected]

Madrid, Feb 16th, 2010.Madrid, Feb 16th, 2010.

::: An Introduction to Ingenuity Pathway Analysis. ::: An Introduction to Ingenuity Pathway Analysis.

Course on Functional AnalysisCourse on Functional Analysis

Bioinformatics UnitStructural Biology and Biocomputing program

CNIO

Bioinformatics UnitStructural Biology and Biocomputing program

CNIO

::: Schedule.

1. Introduction.2. Running into IPA3. Quick Search4. Toolbar5. Gene Lists6. IPA Analysis7. Sharing Projects

::: Introduction.

Ingenuity Pathways Analysis (IPA)

Ingenuity Pathways Analysis v8.5Release Date: Feb 2010Customer Support: [email protected]://www.ingenuity.com/products/pathways_analysis.html

Integrated approach to “Omics” analysis :::

mailto:[email protected]


::: Introduction.


::: Introduction.

Types of analysis :::


::: Introduction.

Answering biological questions :::

::: Schedule.


::: Web Accession.


https://analysis.ingenuity.com/pa/

::: Running into IPA.

Project Manager

Menu.


::: Running into IPA.

File > Preferences ::: Ingenuity Pathways Analysis (IPA)

::: Help and tutorials.


::: Help and tutorials.

Help > Tutorials ::: Ingenuity Pathways Analysis (IPA)

::: IPA Networks Legend.

Help >Legend ::: Ingenuity Pathways Analysis (IPA)

::: IPA Networks Legend.

Network Explorer Tags Overlapping Networks Nodes and Edges

Help >Legend ::: Ingenuity Pathways Analysis (IPA)

::: Schedule.


::: Quick start searching a Single Gene.

Genes or chemicalsGenes/Chemicals associated with Functions/DiseasesGenes targeted by Drugs

GENES: Affymetrix, Agilent, Affymetrix SNP ID, Applied Biosystems, Code Link, Locus Link, Genbank,HUGO, Illumina, UniGene, RefSeq, Uniprot, etc.

DRUGS: Systematic names, IUPAC, CAS, Chemical formulaBrand Name.


::: Quick start exploring a Single Gene.


DescriptionGO AnnotationsHuman, Mouse, Rat detailsDatabase Information (Gene, RNA, Prot.)Functional rolesMutant InformationModifications and regulationDiseaseExpression and LocalizationPhysical interactionsLiterature entriesAdditional findings…

Which biological and disease processes are

most relevant to my genes of interest?

::: Explore and Advanced Search Options.

How do I query the Ingenuity Pathways Knowledge Base about specific genes, processes, diseases, drugs, famiies or subcellular locations?



DescriptionGO AnnotationsHuman, Mouse, Rat detailsDatabase Information (Gene, RNA, Prot.)Functional rolesMutant InformationModifications and regulationDiseaseExpression and LocalizationPhysical interactionsLiterature entriesAdditional findings…



Interactive gene networks ::: Ingenuity Pathways Analysis (IPA)

::: Schedule.


::: Network Explorer Toolbar.


Building a pathway :::

::: Exploring a Single Gene.


GrowPath explorer (shorstest path)ConnectTrim (remove)Keep (filter)Add Molecule/Relationship

Building pathways :::


Also…quick access:


Building pathways :::


Also…quick access:

Add molecule relationship


Expression valuesDrugFunctions and diseasesMy ListCanonical pathwayMy pathwayIngenuity tox listHighlight

Expression valuesDrugFunctions and diseasesMy ListCanonical pathwayMy pathwayIngenuity tox listHighlight

Overlaying pathways :::



Designing pathways :::



View options :::



::: Schedule.


::: Exploring Gene Lists.

Gene, drug, AffyID1, Oxal*,CASP*,RefSeq X,cisplatin,…

::: Searching Lists.Ingenuity Pathways Analysis (IPA)

::: Gene Lists.

Saving a gene list :::Ingenuity Pathways Analysis (IPA)

::: Gene Lists.

Stored gene lists :::Ingenuity Pathways Analysis (IPA)

Creating pathways with Gene Lists :::

::: Gene Lists.

Etc.What regulatory effects relationships exists between the genes/proteins in my dataset?


::: Schedule.

1. Introduction.2. Running into IPA3. Quick Search4. Bar Tools5. Gene Lists6. IPA Analysis7. Sharing Projects

::: Analysis using IPA.

Expression data analysis

Toxicology analysis

Biomarker analysis

Metabolomics analysis


Core Analysis:Core Analysis: Core Analysis allows you to interpret datasets in the context of biological processes, pathways and molecular networks.

Core Comparison Analysis:Core Comparison Analysis: Core Comparison allows you to analyze changes in biological states across time and dosages. First run a core analysis on your multiple datasetsthat represent multiple timepoints or dosage treatments and use core Comparison Analysis to understand which biological processes and/or diseasesare relevant to each timepoint or dose.

Tox Analysis:Tox Analysis: The tox solution allows you to assess toxicity and safety of compounds of interest early in the development process and rapidly understand the relevant toxicity phenotypes and clinical pathology endpoints associated with a dataset.

Tox Comparison Analysis:Tox Comparison Analysis: Allows you to analyze changes in relevant toxicity phenotypes and clinical pathology endpointsacross time and dosages. First run a Tox Analysis on your multiple datasets that represent multiple timepoints or dosage treatments, use Tox Comparison Analysis to understand which tox functions and/or pathways are relevant to each timepoint or dose.

::: Types of Analysis.


::: Types of Analysis.

Biomarker Filter:Biomarker Filter: The biomarker analysis solution allows you to identify and prioritize the most relevant and promising molecular biomarker candidatesfrom datasets from nearly any step of the drug discovery process or any type of disease research. Use the Biomarker Filter to prioritize molecular biomarkercandidates based on contextual information such as mechanistic connection to diseases, detection in bodily fluids. Then, use the Biomarker Comparison Analysis to identify biomarker candidates that discriminate between or are common to a disease state and/or drug response.

Biomarker Comparison Analysis:Biomarker Comparison Analysis: To identify biomarker candidates that discriminate between or are common to a disease state and/or drug response. First run the Biomarker Filter to prioritize molecular biomarker candidates based on contextual information such as mechanistic connection to diseases, detection in bodily fluids, and use the Biomarker Comparison Analysis to identify biomarker candidates that discriminate between multiple samples.

Metabolomics Analysis:Metabolomics Analysis: The metabolomics analysis solution allows you to gain biological insight into cell physiology and metabolism from metabolite (endogenous chemicals)data.If you have multiple time points or dosage treatments, use Comparison Analysis to understand which biological processes and/or diseases are relevant to each time point or dose.

Metabolomics Comparison Analysis:Metabolomics Comparison Analysis: Comparison Core/ Metabolomics Analysis allows you to compare multiple experimental conditions in the context of biological processes, pathways and molecular networks


::: Importing data for analysis.

File format A :::- Single observation- .xls datasheet accepted- Up to 18 MB- 50000 row size limit


::: Importing data for analysis.

File format B :::

- Multiple observations (up to 10)- .xls datasheet accepted- Up to 18 MB- 50000 row size limit

Ingenuity Pathways Analysis 7.1 (IPA)

::: Sample Analyses.

Useful examples to learn how to deal with Ingenuity IPA…


::: Core Analysis.Expression Data Analysis.

Accession and workflow :::

Core Analysis:Core Analysis: Core Analysis allows you to interpret datasets in the context of biological processes, pathways and molecular networks.



Core analysis output :::

Right-tailed Fisher Exact test

Resultstabs


Right-tailed Fisher Exact test


Some statistics :::

2x2 Contingency Table.

= 0.05p < 0.05 + FDR are considered significant



Results tabs :::Networks

Functions(Bio)

Canonical Pathways

Lists(Tox)

Network explorer

Overlapping networks


::: Networks & Canonical Pathways

Which well characterized cell signaling and metabolicpathways are most relevant in my data?


::: Canonical Pathways


::: Core Comparison Analysis.Expression Data Analysis.

Core Comparison Analysis:Core Comparison Analysis: Core Comparison allows you to analyze changes in biological states across time and dosages. First run a core analysis on your multiple datasetsthat represent multiple timepoints or dosage treatments and use core Comparison Analysis to understand which biological processes and/or diseasesare relevant to each timepoint or dose.


::: Core Comparison Analysis.Expression Data Analysis.

Core comparison analysis output :::

Which functions and pathways are regulatedat different times, doses, or in different tissuesin my experiment?


::: IPA-Tox Analysis.Toxicology Analysis.

Tox Analysis:Tox Analysis: The tox solution allows you to assess toxicity and safety of compounds of interest early in the development process and rapidly understand the relevant toxicity phenotypes and clinical pathology endpoints associated with a dataset.



IPA-Tox List Library :::



IPA-Tox List Library :::

･ Toxicity lists are lists of genes that are known to be involved in a particular typeof toxicity.

･Manually-curated by Ph.D. Scientists

･ Relevant to drug metabolism

･ Cover oxidative stress response

･ Include panel of P450s, xenobiotic metabolism

･ Relevant to hepatic, renal, and cardiac toxicity and function

･ Contain fibrosis, cardiac hypertrophy and cell death



Does this drug treatment cause any toxic effect?



IPA-Tox analysis output :::

Resultstabs



IPA-Tox analysis output :::

Toxicity Functions link expression data to clinical pathology endpoints for mechanistic hypothesis generation.

Categories cover a wide spectrum of well known drug induced injuries and pathologies useful for the drug discovery and development process, such as:

HepatoxicitySteatosis, Necrosis, Fibrosis, and moreCardiotoxicityCardiomyopathy, cardiac dilation, fibrosisNephrotoxicityTubular nephrosis, Phospholipidosis, kidney weight increase, etc.


::: IPA-Tox Comparison Analysis.Toxicology Analysis.


::: IPA-Biomarker Analysis.Biomarker Analysis.

Are there any potential biomarkers in my samples?What are the unique and common potential biomarkers?


::: IPA-Biomarker Analysis.Biomarker Analysis.


::: IPA-Biomarker Comparison Analysis.Biomarker Analysis.


::: IPA-Metabolomics Analysis.Metabolomics Analysis


::: IPA-Metabolomics Comparison Analysis.Metabolomics Analysis


::: Schedule.

1. Introduction.2. Running into IPA3. Quick Search4. Bar Tools5. Gene Lists6. IPA Analysis7. Sharing Projects

::: Sharing Projects.

File > Share > Invitations Manager :::

Accept or decline invitations…


::: Sharing Projects.

File > Share > Share Manager :::

Inviting to share projects…


Thanks [email protected]

Gonzalo G ómez, PhD. [email protected]

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Transcript of Gonzalo G ómez, PhD. [email protected]