ICM Manual v.3.8
by Ruben Abagyan,Eugene Raush and Max Totrov
Copyright © 2018, Molsoft LLC
Jan 4 2018

Contents
 
Introduction
Reference Guide
 ICM options
 Editing
 Graph.Controls
 Alignment Editor
 Constants
 Subsets
 Molecules
 Selections
 Fingerprints
 Regexp
 Cgi programming with icm
 Xml drugbank example
 Tree cluster
  Tree representatives
 Arithmetics
 Flow control
 MolObjects
 Energy Terms
 Integers
 Reals
 Logicals
 Strings
 Preferences
 Tables
 Other
 Chemical
 Smiles
 Soap
 Gui programming
 Commands
 Functions
 Icm shell functions
 Macros
 Files
Command Line User's Guide
References
Glossary
 
Index
PrevICM Language Reference
Hierarchical cluster trees
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[ Tree representatives ]

The records, or rows, of any table can be clustered into a hierarchical tree, and one or several trees associated with this table can be stored with it, displayed and edited in the ICM GUI, and deleted.

A tree is created with the make tree command. We can decide 1) the tree type and, 2) the distance function between two table rows, as well as establish a number of arguments. Then a tree object is added to the header of the table and is stored together with the table. The table gets a new column with the tree order, and optionally two new elements: and a column with the branch number at a certain level, (option split) and the distance matrix (option matrix).

The related commands and functions:
make tree create tree object and attach it to the table
Split function to split cluster by threshold or number of clusters
split command to change the position of tree cursor (separator) and recalculate new cluster numbers
Name( table.cluster i_tree [index,label,matrix,sort,split] ) names of important table columns
Max( table.cluster ) the distance of the root node
Distance of the cluster splitting level
Nof( table.cluster tree ) clusters
Centers of clusters

Example:


# create a distance matrix
m=Matrix(5,3)
m[2,1:3]={1. 0. 0.}
m[3,1:3]={1. 1. 0.}
m[4,1:3]={1. 1. 1.}
m[5,1:3]={1. 0.1 0.1}
D = Distance( m )

# create a table and move distance matrix into header
group table t { "a" "b" "c" "d" "e" } "label" {1. 2. 2. 1. 4. } "val"
group table t append header D "dm"
make tree t distance = "dm"       # uses external distance matrix for clustering

# get cluster number with threshold set to the middle
cl = Split( t.cluster, Max( t.cluster )/2 ) 
add column t cl name="cl"

# group by cluster and take rows by smallest value of "val" column
group t.cl t.val "min" all "refmin" name="t1"

Selecting N representatives from clusters


This involves several steps:

  • creating a tree and a table column with cluster numbers
  • selecting cluster representatives according to a certain threshold in the cluster tree

Example:


read table mol s_icmhome + "drug_groups.sdf"
make tree drug_groups
I = Index( drug_groups.cluster center 0.4 ) # divide at threshold 0.4


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