treebuild package

Submodules

treebuild.tree_build module

class treebuild.tree_build.TreeBuild(input_file, output_file, id_column, fps, properties)

There are assumptions for the data format of the input file. It is very important to understand these assumptions:

1. potency (e.g. IC50/Ka/Ki) unit is nM
2. the file must have a id column, you can set the column name with id_column
3. the file must have a SMILES column, with ‘Canonical_Smiles’ as column name
4. the file must have at least one potency column (IC50/Ka/Ki).

To build the tree

1. the identity column needs to be specified with id_column
2. a list of fingerprints and a list of properties need to be specified with rdkit
3. the directories for input and output file need to be specified

static dot2dict(dot_outfile)

static gen_dist_file(liganddict, fp_func)

generate distance file which is the input of rapidnj program.

Parameters:

• liganddict – ligand information
• fp_func – fingerprint function

Returns:

filename for distance file

static gen_properties(ligand_dict, activities, properties, ext_cols)

Generate properties for each molecule.

Parameters:

• ligand_dict – ligand dictionary which keep all ligand information
• activities – a list of PropertyType objects
• properties – a list of PropertyType objects
• ext_cols – the column name for external links

Returns:

static make_structures_for_smiles(ligand_dict)

Make structure figures from smile strings. All image files will be in the IMG_DIR

Parameters:ligand_dict – ligand dictionary which keep all ligand information Returns:

static parse_lig_file(in_file, identifier)

parse ligand file and return a dictionary with identifier as IDs

Parameters:

• in_file – input file directory
• identifier – name for the identifier

Returns:

a dictionray with ligand information

run_rapidnj(distance_file)

run rapidnj program on distance_file

Parameters:distance_file – directory of distance file Returns:newick string

sfdp_dot(dot_infile, size)

run sdfp on dot file

Parameters:

• dot_infile – directory for dot file
• size – parameter for the sfdp

Returns:

new filename

static write_dotfile(newick)

write newick string as dot file

Parameters:newick – newick string Returns:dot file

treebuild.types module

class treebuild.types.FingerPrintType(name, fp_func, metadata)

representing fingerprint types

to_dict()

Show the information for this fingerprint

Returns:dictionary with basic info

class treebuild.types.PropertyType(name, metadata, transfunc=None, colname=None)

representing biological or chemical properties

gen_property(mol_dict=None)

generate value for this property type

Parameters:

• prop_name – the name of the property
• mol_dict – other information about the molecule

Returns:

a generated value for this property

set_col_name(col_name)

Set the property name from the input file

Parameters:col_name – original column name in the input file Returns:

to_dict()

Show the information

Returns:dictionary with basic info

treebuild.util module

Provide utility functions

treebuild.util.AddNewChild(contents, a_node, new_node_name, edge_length, children, currentlist)

Add a new child to a node.

Parameters:

• contents – a string, a line from DOT
• a_node – a node object
• new_node_name – new node name
• edge_length – the length of edge
• children – existing children
• currentlist – current list of node name

Returns:

void

treebuild.util.CleanAttribute(attr)

Clean attribute, remove ‘,’.

Parameters:attr – old attribute string Returns:new string

treebuild.util.ConvertToFloat(line, colnam_list)

Convert some columns (in colnam_list) to float, and round by 3 decimal.

Parameters:

• line – a dictionary from DictReader.
• colnam_list – float columns

Returns:

a new dictionary

treebuild.util.Dot2Dict(dotfile, moldict)

Read a DOT file to generate a tree and save it to a dictionary.

Parameters:

• dotfile – DOT file name
• moldict – a dictionary with ligand information

Returns:

a dictionary with the tree

treebuild.util.GetAttributeValue(attrname, attr)

Get node attribute.

Parameters:

• attrname – name of the attribute
• attr – the attribute string

Returns:

the value for the attribute

treebuild.util.GetNodeProperty(line)

Get node property from a string.

Parameters:line – a string Returns:name, size, and position of the node

treebuild.util.GetRoot(dotfile, rootname)

Return root name with rootname.

Parameters:

• dotfile – DOT file
• rootname – the name of the root

Returns:

the object of the root

treebuild.util.GetSize(width)

Get the size.

Parameters:width – Returns:

treebuild.util.GuessByFirstLine(firstline)

Guess the number of columns with floats by the first line of the file

Parameters:firstline – Returns:

treebuild.util.IsEdge(line)

Whether this line in DOT file is an edge.

Parameters:line – a string line in DOT file Returns:True or False

treebuild.util.NameAndAttribute(line)

Split name and attribute.

Parameters:line – DOT file name Returns:name string and attribute string

class treebuild.util.Node(name, **attr)

Bases: dict

class for node of tree, each node can only have one parent

add_child(a_node)

Add child to the node.

Parameters:a_node – Node object Returns:void

get_dist(a_node)

get the node as a dictionary.

Parameters:a_node – Node object Returns:a dictionary

set_dist(dist)

set the dictionary attribute for the Node object.

Parameters:dist – Returns:

set_parent(a_node)

Set the parent for a node.

Parameters:a_node – Node object Returns:void

treebuild.util.NodeByName(name, contents)

Create node with name name.

Parameters:

• name – a string with node name
• contents – a list of string from DOT file

Returns:

node object

treebuild.util.NodeNameExist(line)

Functions for parsing DOT file.

Parameters:line – a line from DOT file Returns:whether there is a node name in this line

treebuild.util.ParseLigandFile(infile, identifier)

Parse ligand file to an dictionary, key is ligand id and value is a dictionary with properties and property values. This program will guess the type for each column based on the first row. The program will assume there is only two types of data: number and string.

Parameters:

• infile – input filename
• identifier – the identifier column name

Returns:

a dictionary

treebuild.util.ProcessName(name, isedge)

Process the name of the node.

Parameters:

• name – name of the node
• isedge – whether this is a edge

Returns:

new name

treebuild.util.RecursiveNode2Dict(node, info_dict)

Recursively populate information to the tree object with info_dict.

Parameters:

• node – tree object with all info
• info_dict – information for each ligand.

Returns:

a tree dictionary

treebuild.util.RemoveBackSlash(dotfile)

Rewrite dot file, with removing back slash of dot file.

Parameters:dotfile – DOT file name Returns:void

treebuild.util.SelectColumn(lig_dict, colname)

Prune the dictionary, only attribute in colname will be left.

Parameters:

• lig_dict – a tree like dictionary
• colname – what attribute you want to keep.

Returns:

a new dictionary

treebuild.util.SizeScale(size)

Rescale the size (currently only convert to float).

Parameters:size – a string Returns:a float

treebuild.util.ToFPObj(alist, fp_func)

A list of SMILE string object with (id, smiles) to a list of fingerprint object with (id, fp_obj)

Parameters:

• alist – two element list, the first item is ligand name, the second is smile
• fp_func – the fingerprint function

Returns:

two element list, with first item as ligand name, second item as a fingerprint object.

treebuild.util.WriteAsPHYLIPFormat(smile_list, fp_func)

Prepare the input for RapidNJ.

Parameters:

• smile_list – a list of smiles string
• fp_func – the fingerprint function

Returns:

the filename with PHYLIP format (input for rapidnj)

treebuild.util.WriteDotFile(newick)

Write newick string to a DOT file

Parameters:newick – a string with newick tree structure Returns:DOT file name

treebuild.util.WriteJSON(dict_obj, outfile, write_type)

Dump json object to a file.

Parameters:

• dict_obj – dictionary object
• outfile – output file name
• write_type – append or rewrite (‘a’ or ‘w’)

Returns:

void

treebuild.util.extendChildren(a_node, contents, cur_list)

Find all children of a node in a tree.

Parameters:

• a_node – a node in a tree
• contents – contents from DOT file
• cur_list – current children

Returns:

a list of node objects (children)

treebuild.util.getSimilarity(fp1, fp2)

Generate similarity score for two smiles strings.

Parameters:

• fp1 – fingerprint object (rdkit)
• fp2 – fingerprint object (rdkit)

Returns:

Tanimoto similarity