SlideShare a Scribd company logo
1 of 9
Biology

Chemistry

Biochemical Enrichment Analysis

Informatics

Identification of altered
biochemical domains between
pumpkin and tomatillo leaf
metabolites

Goal: Identify significantly over represented biological
pathways based on significant differences in leaf
metabolites (Use DATA: Pathway Enrichment data.csv)
Topics:
1. KEGG Database
2. MetaboAnalyst: Pathway enrichment analysis
3. MBrole: Over Representation Analysis
4. Hypergeometric test for enrichment
Biology

KEGG Pathway Visualization
Chemistry

Biochemical Enrichment Analysis

Informatics

Goals:
Use KEGG to:
1. Overview glutamate entry in KEGG (C00025)
2. Visualize a pathway of interest
3. Map metabolite of interest to pathway
•
•

http://www.kegg.jp/dbget-bin/www_bget?C00025
http://www.kegg.jp/keggbin/show_pathway?org_name=ath&mapno=00250

• Mapping example
C00064 green, black
C00025 green, black
Biology

Pathway Visualization
Chemistry

Biochemical Enrichment Analysis

Informatics
Biology

Chemistry

Biochemical Enrichment Analysis

Informatics

Pathway over representation
analysis (ORA)

Steps:
1. Use MBrole to conduct:
• Pathway over representation analysis
• url: http://csbg.cnb.csic.es/mbrole/

ORA:
• is used to evaluate whether a particular set of
metabolites is represented more than expected by
chance within a given compound list
[doi: 10.1093/nar/gkq329].
• p-value is calculated using hypergeometric or
Fisher’s exact test
Biology

Chemistry
Informatics

MBRole:
Pathway Over Representation
Analysis (ORA)

Biochemical Enrichment Analysis

Goal: Identify an over represented pathway and visualize it in KEGG
MBRole

Biology

Chemistry

Biochemical Enrichment Analysis

Informatics

http://www.genome.jp/keggbin/show_pathway?map01070+C06427+C00158+C00049+C00493+C00079+C00026+C00042+C00751+C00149+C00078+C00073+
Biology

Chemistry

Test for significance:
Hypergeometric Test

Biochemical Enrichment Analysis

Informatics

How to calculate statistics to determine network enrichment?
hit.num = 51 # number of significantly changed pathway metabolites
set.num = 1455 # number of metabolites in pathway
full = 3358 # all possible metabolites in organism
q.size = 72 # number of significantly changed metabolites

phyper(hit.num-1, set.num, full-set.num, q.size, lower.tail=F)
= 1.717553e-06
Biology

Chemistry

Biochemical Enrichment Analysis

Informatics

MetaboAnalyst:
Pathway Enrichment Analysis
(PEA)

Use MetaboAnalyst to conduct:
• Pathway enrichment Analysis
• url: http://www.metaboanalyst.ca/MetaboAnalyst/faces/UploadView.jsp
PEA:
• is an advanced form of over representation analysis (ORA) which takes
into account pathway topology and is based on gene set enrichment
analysis (GSEA) [doi:10.1093/bioinformatics/btq418]
• p-value is calculated using hypergeometric or Fisher’s exact test

Questions:
1. What pathway is the most important based on ORA and topology?
Biology

KEGG Pathway Enrichment
Chemistry

Biochemical Enrichment Analysis

Informatics

More Related Content

What's hot

General Concepts in QSAR for Using the QSAR Application Toolbox Part 3
General Concepts in QSAR for Using the QSAR Application Toolbox Part 3General Concepts in QSAR for Using the QSAR Application Toolbox Part 3
General Concepts in QSAR for Using the QSAR Application Toolbox Part 3International QSAR Foundation
 
Data analysis workflows part 2 2015
Data analysis workflows part 2 2015Data analysis workflows part 2 2015
Data analysis workflows part 2 2015Dmitry Grapov
 
Normalization of Large-Scale Metabolomic Studies 2014
Normalization of Large-Scale Metabolomic Studies 2014Normalization of Large-Scale Metabolomic Studies 2014
Normalization of Large-Scale Metabolomic Studies 2014Dmitry Grapov
 
Metabolomic Data Analysis Case Studies
Metabolomic Data Analysis Case StudiesMetabolomic Data Analysis Case Studies
Metabolomic Data Analysis Case StudiesDmitry Grapov
 
Prote-OMIC Data Analysis and Visualization
Prote-OMIC Data Analysis and VisualizationProte-OMIC Data Analysis and Visualization
Prote-OMIC Data Analysis and VisualizationDmitry Grapov
 
Omic Data Integration Strategies
Omic Data Integration StrategiesOmic Data Integration Strategies
Omic Data Integration StrategiesDmitry Grapov
 
Mapping to the Metabolomic Manifold
Mapping to the Metabolomic ManifoldMapping to the Metabolomic Manifold
Mapping to the Metabolomic ManifoldDmitry Grapov
 
3 data normalization (2014 lab tutorial)
3  data normalization (2014 lab tutorial)3  data normalization (2014 lab tutorial)
3 data normalization (2014 lab tutorial)Dmitry Grapov
 
Data Normalization Approaches for Large-scale Biological Studies
Data Normalization Approaches for Large-scale Biological StudiesData Normalization Approaches for Large-scale Biological Studies
Data Normalization Approaches for Large-scale Biological StudiesDmitry Grapov
 
Metabolomic data analysis and visualization tools
Metabolomic data analysis and visualization toolsMetabolomic data analysis and visualization tools
Metabolomic data analysis and visualization toolsDmitry Grapov
 
Using spectral reflectance to estimate leaf
Using spectral reflectance to estimate leafUsing spectral reflectance to estimate leaf
Using spectral reflectance to estimate leafRama Prasad Vaddella
 
Metabolomics and Beyond Challenges and Strategies for Next-gen Omic Analyses
Metabolomics and Beyond Challenges and Strategies for Next-gen Omic Analyses Metabolomics and Beyond Challenges and Strategies for Next-gen Omic Analyses
Metabolomics and Beyond Challenges and Strategies for Next-gen Omic Analyses Dmitry Grapov
 
Lecture 11 developing qsar, evaluation of qsar model and virtual screening
Lecture 11  developing qsar, evaluation of qsar model and virtual screeningLecture 11  developing qsar, evaluation of qsar model and virtual screening
Lecture 11 developing qsar, evaluation of qsar model and virtual screeningRAJAN ROLTA
 

What's hot (20)

General Concepts in QSAR for Using the QSAR Application Toolbox Part 3
General Concepts in QSAR for Using the QSAR Application Toolbox Part 3General Concepts in QSAR for Using the QSAR Application Toolbox Part 3
General Concepts in QSAR for Using the QSAR Application Toolbox Part 3
 
0 introduction
0  introduction0  introduction
0 introduction
 
7 network mapping i
7  network mapping i7  network mapping i
7 network mapping i
 
Data analysis workflows part 2 2015
Data analysis workflows part 2 2015Data analysis workflows part 2 2015
Data analysis workflows part 2 2015
 
Normalization of Large-Scale Metabolomic Studies 2014
Normalization of Large-Scale Metabolomic Studies 2014Normalization of Large-Scale Metabolomic Studies 2014
Normalization of Large-Scale Metabolomic Studies 2014
 
Metabolomic Data Analysis Case Studies
Metabolomic Data Analysis Case StudiesMetabolomic Data Analysis Case Studies
Metabolomic Data Analysis Case Studies
 
Prote-OMIC Data Analysis and Visualization
Prote-OMIC Data Analysis and VisualizationProte-OMIC Data Analysis and Visualization
Prote-OMIC Data Analysis and Visualization
 
Omic Data Integration Strategies
Omic Data Integration StrategiesOmic Data Integration Strategies
Omic Data Integration Strategies
 
GtoPdb_ITMAT_2017
GtoPdb_ITMAT_2017GtoPdb_ITMAT_2017
GtoPdb_ITMAT_2017
 
The EPA Comptox Chemistry Dashboard: A Web-Based Data Integration Hub for Tox...
The EPA Comptox Chemistry Dashboard: A Web-Based Data Integration Hub for Tox...The EPA Comptox Chemistry Dashboard: A Web-Based Data Integration Hub for Tox...
The EPA Comptox Chemistry Dashboard: A Web-Based Data Integration Hub for Tox...
 
Mapping to the Metabolomic Manifold
Mapping to the Metabolomic ManifoldMapping to the Metabolomic Manifold
Mapping to the Metabolomic Manifold
 
3 data normalization (2014 lab tutorial)
3  data normalization (2014 lab tutorial)3  data normalization (2014 lab tutorial)
3 data normalization (2014 lab tutorial)
 
Data Normalization Approaches for Large-scale Biological Studies
Data Normalization Approaches for Large-scale Biological StudiesData Normalization Approaches for Large-scale Biological Studies
Data Normalization Approaches for Large-scale Biological Studies
 
US-EPA CompTox Chemicals Dashboard as a web-based data resource to help ident...
US-EPA CompTox Chemicals Dashboard as a web-based data resource to help ident...US-EPA CompTox Chemicals Dashboard as a web-based data resource to help ident...
US-EPA CompTox Chemicals Dashboard as a web-based data resource to help ident...
 
Metabolomic data analysis and visualization tools
Metabolomic data analysis and visualization toolsMetabolomic data analysis and visualization tools
Metabolomic data analysis and visualization tools
 
IUPHAR/BPS Guide to Pharmacology
IUPHAR/BPS Guide to PharmacologyIUPHAR/BPS Guide to Pharmacology
IUPHAR/BPS Guide to Pharmacology
 
Using spectral reflectance to estimate leaf
Using spectral reflectance to estimate leafUsing spectral reflectance to estimate leaf
Using spectral reflectance to estimate leaf
 
Metabolomics and Beyond Challenges and Strategies for Next-gen Omic Analyses
Metabolomics and Beyond Challenges and Strategies for Next-gen Omic Analyses Metabolomics and Beyond Challenges and Strategies for Next-gen Omic Analyses
Metabolomics and Beyond Challenges and Strategies for Next-gen Omic Analyses
 
Pharmacophore mapping joon
Pharmacophore mapping joonPharmacophore mapping joon
Pharmacophore mapping joon
 
Lecture 11 developing qsar, evaluation of qsar model and virtual screening
Lecture 11  developing qsar, evaluation of qsar model and virtual screeningLecture 11  developing qsar, evaluation of qsar model and virtual screening
Lecture 11 developing qsar, evaluation of qsar model and virtual screening
 

Similar to 6 metabolite enrichment analysis

JBEI Research Highlights - March 2022
JBEI Research Highlights - March 2022JBEI Research Highlights - March 2022
JBEI Research Highlights - March 2022SaraHarmon4
 
JBEI Research Highlights - November 2018
JBEI Research Highlights - November 2018 JBEI Research Highlights - November 2018
JBEI Research Highlights - November 2018 Irina Silva
 
JBEI Science Highlights - January 2023
JBEI Science Highlights - January 2023JBEI Science Highlights - January 2023
JBEI Science Highlights - January 2023SaraHarmon5
 
Metabolic Engineering
Metabolic EngineeringMetabolic Engineering
Metabolic Engineeringp18lsbc8071
 
JBEI Highlights June 2016
JBEI Highlights June 2016JBEI Highlights June 2016
JBEI Highlights June 2016Irina Silva
 
Systems biotechnology
Systems biotechnologySystems biotechnology
Systems biotechnologymiguel
 
JBEI Research Highlights Slides - September 2022
JBEI Research Highlights Slides - September 2022JBEI Research Highlights Slides - September 2022
JBEI Research Highlights Slides - September 2022SaraHarmon4
 
Flux balance analysis
Flux balance analysisFlux balance analysis
Flux balance analysisJyotiBishlay
 
JBEI Research Highlights - May 2019
JBEI Research Highlights - May 2019JBEI Research Highlights - May 2019
JBEI Research Highlights - May 2019Irina Silva
 
JBEI Research Highlights - June 2014
JBEI Research Highlights - June 2014 JBEI Research Highlights - June 2014
JBEI Research Highlights - June 2014 Irina Silva
 
JBEI highlights March 2016
JBEI highlights March 2016JBEI highlights March 2016
JBEI highlights March 2016Irina Silva
 
Research Highlights
Research HighlightsResearch Highlights
Research HighlightsEmily Scott
 
Continued development of ChEBI towards better usability for the systems biolo...
Continued development of ChEBI towards better usability for the systems biolo...Continued development of ChEBI towards better usability for the systems biolo...
Continued development of ChEBI towards better usability for the systems biolo...Neil Swainston
 
JBEI Highlights February 2016
JBEI Highlights February 2016JBEI Highlights February 2016
JBEI Highlights February 2016Irina Silva
 
Objectives Of Protein Engineerihg BY Akash Das
Objectives Of Protein Engineerihg BY Akash DasObjectives Of Protein Engineerihg BY Akash Das
Objectives Of Protein Engineerihg BY Akash DasAkashDas169
 
JBEI Research Highlight Slides - March 2023
JBEI Research Highlight Slides - March 2023JBEI Research Highlight Slides - March 2023
JBEI Research Highlight Slides - March 2023SaraHarmon5
 
July 2021 - JBEI Research Highlights
July 2021 - JBEI Research HighlightsJuly 2021 - JBEI Research Highlights
July 2021 - JBEI Research HighlightsSaraHarmon4
 
Introduction to FAIR principles about Data, Metadata and Protocols in Metabo...
Introduction to FAIR principles about  Data, Metadata and Protocols in Metabo...Introduction to FAIR principles about  Data, Metadata and Protocols in Metabo...
Introduction to FAIR principles about Data, Metadata and Protocols in Metabo...Panagiotis Arapitsas
 

Similar to 6 metabolite enrichment analysis (20)

JBEI Research Highlights - March 2022
JBEI Research Highlights - March 2022JBEI Research Highlights - March 2022
JBEI Research Highlights - March 2022
 
JBEI Research Highlights - November 2018
JBEI Research Highlights - November 2018 JBEI Research Highlights - November 2018
JBEI Research Highlights - November 2018
 
JBEI Science Highlights - January 2023
JBEI Science Highlights - January 2023JBEI Science Highlights - January 2023
JBEI Science Highlights - January 2023
 
Metabolomics
MetabolomicsMetabolomics
Metabolomics
 
Metabolic Engineering
Metabolic EngineeringMetabolic Engineering
Metabolic Engineering
 
JBEI Highlights June 2016
JBEI Highlights June 2016JBEI Highlights June 2016
JBEI Highlights June 2016
 
Systems biotechnology
Systems biotechnologySystems biotechnology
Systems biotechnology
 
JBEI Research Highlights Slides - September 2022
JBEI Research Highlights Slides - September 2022JBEI Research Highlights Slides - September 2022
JBEI Research Highlights Slides - September 2022
 
Flux balance analysis
Flux balance analysisFlux balance analysis
Flux balance analysis
 
JBEI Research Highlights - May 2019
JBEI Research Highlights - May 2019JBEI Research Highlights - May 2019
JBEI Research Highlights - May 2019
 
JBEI Research Highlights - June 2014
JBEI Research Highlights - June 2014 JBEI Research Highlights - June 2014
JBEI Research Highlights - June 2014
 
JBEI highlights March 2016
JBEI highlights March 2016JBEI highlights March 2016
JBEI highlights March 2016
 
Research Highlights
Research HighlightsResearch Highlights
Research Highlights
 
Continued development of ChEBI towards better usability for the systems biolo...
Continued development of ChEBI towards better usability for the systems biolo...Continued development of ChEBI towards better usability for the systems biolo...
Continued development of ChEBI towards better usability for the systems biolo...
 
JBEI Highlights February 2016
JBEI Highlights February 2016JBEI Highlights February 2016
JBEI Highlights February 2016
 
Final dissertation - Amir Abdo
Final dissertation - Amir AbdoFinal dissertation - Amir Abdo
Final dissertation - Amir Abdo
 
Objectives Of Protein Engineerihg BY Akash Das
Objectives Of Protein Engineerihg BY Akash DasObjectives Of Protein Engineerihg BY Akash Das
Objectives Of Protein Engineerihg BY Akash Das
 
JBEI Research Highlight Slides - March 2023
JBEI Research Highlight Slides - March 2023JBEI Research Highlight Slides - March 2023
JBEI Research Highlight Slides - March 2023
 
July 2021 - JBEI Research Highlights
July 2021 - JBEI Research HighlightsJuly 2021 - JBEI Research Highlights
July 2021 - JBEI Research Highlights
 
Introduction to FAIR principles about Data, Metadata and Protocols in Metabo...
Introduction to FAIR principles about  Data, Metadata and Protocols in Metabo...Introduction to FAIR principles about  Data, Metadata and Protocols in Metabo...
Introduction to FAIR principles about Data, Metadata and Protocols in Metabo...
 

More from Dmitry Grapov

R programming for Data Science - A Beginner’s Guide
R programming for Data Science - A Beginner’s GuideR programming for Data Science - A Beginner’s Guide
R programming for Data Science - A Beginner’s GuideDmitry Grapov
 
Network mapping 101 course
Network mapping 101 courseNetwork mapping 101 course
Network mapping 101 courseDmitry Grapov
 
Rise of Deep Learning for Genomic, Proteomic, and Metabolomic Data Integratio...
Rise of Deep Learning for Genomic, Proteomic, and Metabolomic Data Integratio...Rise of Deep Learning for Genomic, Proteomic, and Metabolomic Data Integratio...
Rise of Deep Learning for Genomic, Proteomic, and Metabolomic Data Integratio...Dmitry Grapov
 
Dmitry Grapov Resume and CV
Dmitry Grapov Resume and CVDmitry Grapov Resume and CV
Dmitry Grapov Resume and CVDmitry Grapov
 
Machine Learning Powered Metabolomic Network Analysis
Machine Learning Powered Metabolomic Network AnalysisMachine Learning Powered Metabolomic Network Analysis
Machine Learning Powered Metabolomic Network AnalysisDmitry Grapov
 
Complex Systems Biology Informed Data Analysis and Machine Learning
Complex Systems Biology Informed Data Analysis and Machine LearningComplex Systems Biology Informed Data Analysis and Machine Learning
Complex Systems Biology Informed Data Analysis and Machine LearningDmitry Grapov
 
Data analysis workflows part 1 2015
Data analysis workflows part 1 2015Data analysis workflows part 1 2015
Data analysis workflows part 1 2015Dmitry Grapov
 
Case Study: Overview of Metabolomic Data Normalization Strategies
Case Study: Overview of Metabolomic Data Normalization StrategiesCase Study: Overview of Metabolomic Data Normalization Strategies
Case Study: Overview of Metabolomic Data Normalization StrategiesDmitry Grapov
 
Gene Ontology Enrichment Network Analysis -Tutorial
Gene Ontology Enrichment Network Analysis -TutorialGene Ontology Enrichment Network Analysis -Tutorial
Gene Ontology Enrichment Network Analysis -TutorialDmitry Grapov
 
American Society of Mass Spectrommetry Conference 2014
American Society of Mass Spectrommetry Conference 2014American Society of Mass Spectrommetry Conference 2014
American Society of Mass Spectrommetry Conference 2014Dmitry Grapov
 
Automation of (Biological) Data Analysis and Report Generation
Automation of (Biological) Data Analysis and Report GenerationAutomation of (Biological) Data Analysis and Report Generation
Automation of (Biological) Data Analysis and Report GenerationDmitry Grapov
 

More from Dmitry Grapov (12)

R programming for Data Science - A Beginner’s Guide
R programming for Data Science - A Beginner’s GuideR programming for Data Science - A Beginner’s Guide
R programming for Data Science - A Beginner’s Guide
 
Network mapping 101 course
Network mapping 101 courseNetwork mapping 101 course
Network mapping 101 course
 
Rise of Deep Learning for Genomic, Proteomic, and Metabolomic Data Integratio...
Rise of Deep Learning for Genomic, Proteomic, and Metabolomic Data Integratio...Rise of Deep Learning for Genomic, Proteomic, and Metabolomic Data Integratio...
Rise of Deep Learning for Genomic, Proteomic, and Metabolomic Data Integratio...
 
Dmitry Grapov Resume and CV
Dmitry Grapov Resume and CVDmitry Grapov Resume and CV
Dmitry Grapov Resume and CV
 
Machine Learning Powered Metabolomic Network Analysis
Machine Learning Powered Metabolomic Network AnalysisMachine Learning Powered Metabolomic Network Analysis
Machine Learning Powered Metabolomic Network Analysis
 
Complex Systems Biology Informed Data Analysis and Machine Learning
Complex Systems Biology Informed Data Analysis and Machine LearningComplex Systems Biology Informed Data Analysis and Machine Learning
Complex Systems Biology Informed Data Analysis and Machine Learning
 
Data analysis workflows part 1 2015
Data analysis workflows part 1 2015Data analysis workflows part 1 2015
Data analysis workflows part 1 2015
 
Case Study: Overview of Metabolomic Data Normalization Strategies
Case Study: Overview of Metabolomic Data Normalization StrategiesCase Study: Overview of Metabolomic Data Normalization Strategies
Case Study: Overview of Metabolomic Data Normalization Strategies
 
Modeling poster
Modeling posterModeling poster
Modeling poster
 
Gene Ontology Enrichment Network Analysis -Tutorial
Gene Ontology Enrichment Network Analysis -TutorialGene Ontology Enrichment Network Analysis -Tutorial
Gene Ontology Enrichment Network Analysis -Tutorial
 
American Society of Mass Spectrommetry Conference 2014
American Society of Mass Spectrommetry Conference 2014American Society of Mass Spectrommetry Conference 2014
American Society of Mass Spectrommetry Conference 2014
 
Automation of (Biological) Data Analysis and Report Generation
Automation of (Biological) Data Analysis and Report GenerationAutomation of (Biological) Data Analysis and Report Generation
Automation of (Biological) Data Analysis and Report Generation
 

6 metabolite enrichment analysis