1. Statistics evaluation and graphics
with ChemAxon tools and Statistica and WEKA
towards QSPR and QSAR development
Tobias Kind FiehnLab at UC Davis Genome Center
November 2006
Free Academic Licenses for JChem and Instant JChem provided by ChemAxon
Academic License for Statistica Dataminer provided by Statsoft
Technical presentation  See notes and comments for deeper discussion
ChemAxon
Fiehnlab (fiehnlab.ucdavis.edu)
Statistics - QSPR/QSAR - with JChem and Statistica and WEKA and Yale
GNU general public license for WEKA provided by WEKA Machine Learning Project

2. Metabolomics - The science of the small molecules
Compound Classes:
sugars
amino acids
steroids
fatty acids
lipids
phospholipids
organic acids ...
Molecules under investigation
Visit us!
3D model of a molecule with surface plot

3. Techniques and tools
Analytical techniques (LC-MS, GC-MS, FT-MS, NMR, IR)
BioInformatics, ChomoInformatics
Liquid Chromatography LC-MS
Gas Chromatography GC-MS
BioInformatics and Cheminformatics Statistics (Statistica Dataminer) Open Source Tools

4. ChemAxon JChem has now PCA and PLS
Create new library with JCHEM Manager GUI (testcase here: fingerprints)
Exctract fingerprints and do dimension reduction with principal component analysis (PCA) with command line tool PCA.bat or pca.sh
PCA – principal component analysis
PLS – partial least squares

5. ChemAxon JChem Principal Component Analysis (PCA)
Start PCA by getting information from DB (here Access, but can be Oracle, Derby, MySQL)
Test case chemicals from NCI DB
PCA can be done from any descriptor, chemical fingerprints, BCUT etc. This is just a simple example made from the 16 standard fingerprints.
Be sure only to select descriptors you want (and not the molecule ID)
PCA -d "sun.jdbc.odbc.JdbcOdbcDriver" -u "jdbc:odbc:jchem-z" -l test -p test -P JChemProperties -q "SELECT cd_fp1, cd_fp2, cd_fp3, cd_fp4, cd_fp5, cd_fp6, cd_fp7, cd_fp8, cd_fp9, cd_fp10, cd_fp11, cd_fp12, cd_fp13, cd_fp14, cd_fp15, cd_fp16 FROM nci99 WHERE cd_id <= " -o PCA-scores.txt -t PCA-Eigenvalues.txt
TimeThis : Command Line : run-pca.bat
TimeThis : Start Time : Mon Nov 27 17:02:
TimeThis : End Time : Mon Nov 27 17:19:
TimeThis : Elapsed Time : 00:17:49.812
Testsystem AMD Dual Opteron 2,8 Ghz 2,8 GByte RAM; WINXP-32 bit
---
TimeThis : Command Line : pca -i test-25kx16.txt -o PCA250k-scores-external.txt -t PCA250k-eigen-external.txt
TimeThis : Start Time : Mon Nov 27 22:24:
activeColumns
TimeThis : End Time : Mon Nov 27 22:40:
TimeThis : Elapsed Time : 00:15:45.375
----
PCA -d "sun.jdbc.odbc.JdbcOdbcDriver" -u "jdbc:odbc:jchem-z" -l test -p test -P JChemProperties -q "SELECT cd_fp1, cd_fp2, cd_fp3, cd_fp4, cd_fp5, cd_fp6, cd_fp7, cd_fp8, cd_fp9, cd_fp10, cd_fp11, cd_fp12, cd_fp13, cd_fp14, cd_fp15, cd_fp16 FROM nci99 WHERE cd_id <= " -o PCA-scores.txt -t PCA-Eigenvalues.txt
TimeThis : Command Line : run-pca.bat
TimeThis : Start Time : Mon Nov 27 17:02:
TimeThis : End Time : Mon Nov 27 17:19:
TimeThis : Elapsed Time : 00:17:49.812
Z:\>pca -h
PCA 3.2, (C) ChemAxon Ltd.
Principal Component Analisis.
Usage:
pca [options]
General options:
-h --help this help message
-d --driver <JDBC driver> JDBC driver
-u --dburl <url> URL of database
-l --login <login> login name
-p --password <password> password
-s --saveconf save settings into
"C:\Documents and Settings\Tobi\chemaxon\.jchem"
-m --meancenter Don't autoscale just mean center data
-s --noStandardize Don't mean center and autoscale the data
-e --maxerr maximal error during the iteration
Input options (default: standard input):
-i --input <path> input file
-q --query <sql> SQL query string for reading input
(database input)
Output options (default: standard output):
-o --scoreOutput <filepath> output file path for principal components
scores (text file output)
-t --infoOutput <filepath> output file path for Eigenvalues,
Cumulated variance ...
(text file output)
Problem here: A) JDBC extraction not tuned - DB extraction of values nearly 2 minutes.
B) PCA calculation time too long - 15 minutes for a matrix x 16
The current PCA algorithm needs to be changed, its very inefficent (faster matrix routines exist for JAVA)
Database extraction time with Statistica: 8 seconds.
The same PCA with Statistica is finished in: 1 second (no joke – thats a factor of 1:900).

6. JChem PCA output
Eigenvalues, % and Cumulated variance (in rows)=
Loadings (in rows)=
------
PCA scores
The PCA results matrix is inverted and values *(-1) from Statistica.
Problem: Currently no graphics. But multivariate statistics lives from graphics.
Follwing simple graphic examples are made with Statistica or WEKA via DB query.

7. Following slides  „What could be“ in the future.
or  „What can be done“ right now.
Check the pretty comprehensive statistics link

8. Machine Learning and statistic tools
PLS
Machine Learning (KNN)
Feature selection
Tree model
Neural Network
Cluster Analysis
Response curves
Try matlab if you want to die from command line sickness 
BUT MatLab is very fast and compiled for each specifc CPU 
YALE
We use Statistica Dataminer as a comprehensive statistics work tool. WEKA or YALE are free but (not yet :-) as powerful as the Statistica Dataminer.

9. Connection of a JCHEM molecule DB via JDBC with Statistica
For Oracle and Apache Derby and multi core CPU speed with JCHEM calculations check here:
Check my other presentation for JCHEM (See )
Or copy this
Or this (not mine)
Time for query + copy of 4,000,000 values with 250k molecules 16 fingerprints = 8 seconds.
Test system JChem 3.2 with MS Access with Statistica Dataminer 7.1
Dual Opteron 2.8 GHz

10. Statistica with JChem data
Statistica has inbuilt functions and most (if not all) statistical routines.
Its way more comfortable than R or matlab – R has only a commandline
Try also Yale or WEKA

11. PCA Scree plot – determine optimal factors to retain
Visible Step
Technical presentation  See notes and comments for deeper discussion
ChemAxon
Fiehnlab (fiehnlab.ucdavis.edu)
Statistica Dataminer 7.1
Four factors can be retained. The 16 dimensional space can be
compressed into a 4-dimensional space. (Scree plot is not optimal here)

12. PCA Loadings plot – which variables are influential?
If you want to cluster loadings you have to put the loadings output into a cluster analysis.
Statistica Dataminer 7.1
Which of the 16 fingerprints are similar? Those who “cluster” together are similar (fp_11 and fp_14).
The variables fp_5 and fp_16 influence factor 1 in the same way. Variables inside or near the center (0,0) have no discrimination power. Remember PCA is no cluster analysis!

13. PCA Scores plot – picture of the reduced dimensionality.
Technical presentation  See notes and comments for deeper discussion
ChemAxon
Fiehnlab (fiehnlab.ucdavis.edu)
Statistica Dataminer 7.1
The 16 fingerprints are compressed into 2D. We can use other high dimensionality descriptors for
enhanced examples. Cases (molecules) which „cluster“ together may have same properties or functional groups (depending on input). Here we see the KOW molecule set covers the whole NCI dataset based on 16 pfs.

14. PCA Scores 3D plot – KOWWIN versus silicon compound test set
Statistica Dataminer 7.1
The 16 fingerprints are compressed into 3D. The KOWWIN test set does not cover the whole molecules space of important silicon containing molecules. You can also do an Overlap Analysis
(compare two databases) within the all-new Instant-JChem.

15. Statistica – Random Forest Machine learning
1024-DIM FC descriptor space
Statistica generates all graphical output + SQL code
Z:\>timethis "generatemd c 10k-test.smi -T -2 -k CF >10k-fp.txt"
TimeThis : Command Line : generatemd c 10k-test.smi -T -2 -k CF >10k-fp.txt
TimeThis : Start Time : Wed Nov 29 20:35:
TimeThis : End Time : Wed Nov 29 20:35:
TimeThis : Elapsed Time : 00:00:05.421
On Dual Opteron 2,8 GHz (one core used only).
------
Miklos
Chemical fingerprint generation: 500/s
Pharmacophore fingerprint generation
calculated: 80/s
rule-based: 200/s
Screening: 12000/s
Optimization: 10s/metric
Hardware/software environment:
P4 3GHz, 1GB RAM
Red Hat Linux 9
Java 1.4.2
Chemical fingerprint descriptors generated with JCHEM GenerateMD GenerateMD performance 1800 molecules/second for 1024 dimensional fp
On Dual Opteron 2,8 GHz (one core used only).

16. CART tree method for QSPR and QSAR
Thats no joke, check out scholar.google.com
Classification trees, boosting trees, random forest, regression trees
and honest trees and adaptive trees – lots of wood and forests - did you hear about them?

17. Other machine learning techniques from Statistica Dataminer we use
Most of them work for classification and regression
Model class
specific model #
Generalized Linear Models (GLM)
General Discriminant Analysis 1
Binary logit (logistic) regression 2
Binary probit regression 3
Nonlinear model
Multivariate adaptive regression splines (MARS) 4
Tree models
Standard Classification Trees (CART) 5
Standard General Chi-square Automatic Interaction Detector (CHAID) 6
Exhaustive CHAID 7
Boosting classification trees 8
Neural Networks
Multilayer Perceptron neural network (MLP) 9
Radial Basis Function neural network (RBF) 10
Machine Learning
Support Vector Machines (SVM) 11
Naive Bayes classifier 12
k-Nearest Neighbors (KNN) 13
More than functions available

18. Now with open source datamining tool WEKA
URL
SQL
Data
For MS Access create from ADMIN tools, JDBC driver, add DNS file, create DB; or use Orcacle settings
File databaseutils.props in weka root DIR
jdbcDriver=sun.jdbc.odbc.JdbcOdbcDriver
jdbcURL=jdbc:odbc:jchem-z
SQL:
SELECT silicon.`cd_fp1`, silicon.`cd_fp2`, silicon.`cd_fp3`, silicon.`cd_fp4`, silicon.`cd_fp5`, silicon.`cd_fp6`, silicon.`cd_fp7`, silicon.`cd_fp8`, silicon.`cd_fp9`, silicon.`cd_fp10`, silicon.`cd_fp11`, silicon.`cd_fp12`, silicon.`cd_fp13`, silicon.`cd_fp14`, silicon.`cd_fp15`, silicon.`cd_fp16` FROM `Z:\access-DB\silicon`.`silicon` silicon
Yellow = OK
Easy: enter DB URL, enter SQL statement, import data. Try free AquaStudio for SQL!

19. WEKA - Machine learning algorithms in Java
Technical presentation  See notes and comments for deeper discussion
ChemAxon
Fiehnlab (fiehnlab.ucdavis.edu)

20. WEKA – fingerprint visualization
Data matrix 22,000x16

21. Conclusions regarding statistics:
JChem PCA and PLS output (Eigenvalues, scores, loadings)
are provided only as textfile. More univariate and multivariate tools needed.
JChem PCA and PLS results must have graphical output. (They must)
JChem PCA must be made faster (factor ) by using math routines.
Integration into Instant-JChem would be good or ChemAxon provides enhanced bundled statistics tools.
Currently JDBC query from JChem to other statistical packages like WEKA or Statistica or R or MATLAB or YALE is perfect. Each package works best in the field it was designed for.
Matlab and R and YALE database connection JDBC or ODBC not shown here
MATLAB R
YALE
Thats it.
Thanks