Building Biochemical + Chemical Similarity Networks

Dmitry Grapov, PhD040413

The ingredients

1. List of chemical identifiers

• Preferably - Pubchem compound identifiers (CIDs)

2. Edge List (calculate from identifiers or database)

3. Table of Edge/Node Attributes (calculate from data or database)

4. Visualization

Some Examples

Biochemical relationships + chemical similarity + correlation + statistics + PLS-DA

Biochemical relationships + chemical similarity + correlation + statistics + PLS-DA + graphs

partial correlation + PLS-DA + statistics + graphs

correlation + class information + clustering + PLS-DA + MDS

correlation + clustering + OSC-PLS-DA + Statistics

The ingredients

1. List of chemical identifiers

• Preferably - Pubchem compound identifiers (CIDs)

2. Edge List (calculate from identifiers or database)

3. Table of Edge/Node Attributes (calculate from data or database)

4. Visualization

Edge List

1. KEGG RPAIRS

2. Tanimoto distances

3. Other options

• correlations

• partial-correlations

• similarity/dissimilarity measures

4. (optional) edge attributes

Node Attributes Table

Options for node mapping

1. Continuous: size, transparency, boarder width, color

2. Discreet: color, shape, label

3. Other: node graphics

Demonstration

1. Get nessesary R code2. chemical identifiers 3. Import into R 4. Create KEGG RPAIRs edge list5. Create Tanimoto similarity edge list 6. Node attributes table

Visualizing network in Cytoscape

1) Up load edge list(save as excel file first)

Visualizing network in Cytoscape

1) Up load edge list

Visualizing network in Cytoscape

Change layout

Visualizing network in Cytoscape2) Up load node attributes file

Visualizing network in Cytoscape2) Up load node attributes file

Visualizing network in Cytoscape3) Map node and edge attributes

Visualizing network in Cytoscape

4)When done export network to favorite file format