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NAME

SimilarityMatrixSDFiles.pl - Calculate similarity matrices using fingerprints data in SDFile(s)

SYNOPSIS

SimilarityMatrixSDFiles.pl SDFile(s)...

SimilarityMatrixSDFiles.pl [-a, --alpha number] [b, --beta number] [--CompoundID DataFieldName or LabelPrefixString] [--CompoundIDMode DataField | MolName | LabelPrefix | MolNameOrLabelPrefix] [-d, --detail InfoLevel] [-f, --fast] [--FingerprintsField FieldLabel] [--FingerprintsFormatMode Internal | Specify] [--FingerprintsString Hexadecimal | Binary | RawBinary] [-h, --help] [-m, --mode All | ''Tanimoto,[Tversky,...]''] [--OutDelim comma | tab | semicolon] [-o, --overwrite] [-p, --precision number] [-q, --quote Yes | No] [-r, --root RootName] [-w, --WorkingDir dirname] SDFile(s)...

DESCRIPTION

Calculate similarity matrices using fingerprints data field in SDFile(s) and generate CSV/TSV text files containing values for specified similarity coefficients.

Multiple SDFile names are separated by spaces. The valid file extensions are .sdf and .sd. All other file names are ignored. All the SD files in a current directory can be specified either by *.sdf or the current directory name.

OPTIONS

-a, --alpha number

Value of alpha parameter for calculating Tversky similarity coefficient specified for -m, --mode option. It corresponds to weights assigned for bits set to ''1'' in a pair of fingerprint bit vectors during the calculation of similarity coefficient. Possible values: 0 to 1. Default value: 0.5.

b, --beta number

Value of alpha parameter for calculating WeightedTanimoto and WeightedTversky similarity coefficients specified for -m, --mode option. It is used to weight the contributions of bits set to ''0'' during the calculation of similarity coefficients. Possible values: 0 to 1. Default value of 1 makes WeightedTanimoto and WeightedTversky equivalent to Tanimoto and Tversky.

--CompoundID DataFieldName or LabelPrefixString

This value is --CompoundIDMode specific and indicates how compound ID is generated.

For DataField value of --CompoundIDMode option, this option corresponds to datafield label name whose value is used as compound ID; otherwise, it's a prefix string used for generating compound IDs like LabelPrefixString<Number>. Default value, Cmpd, generates compound IDs which look like Cmpd<Number>.

Examples for DataField value of --CompoundIDMode:

MolID
ExtReg

Examples for LabelPrefix or MolNameOrLabelPrefix value of --CompoundIDMode:

Compound

The values specified above generates compound IDs which correspond to Compound<Number> instead of default value of Cmpd<Number>.

--CompoundIDMode DataField | MolName | LabelPrefix | MolNameOrLabelPrefix

Specify how to generate compound IDs for similarity matrix CSV/TSV text file(s): use a SDFile(s) datafield value; use molname line from SDFile(s); generate a sequential ID with specific prefix; use combination of both MolName and LabelPrefix with usage of LabelPrefix values for empty molname lines.

Possible values: DataField | MolName | LabelPrefix | MolNameOrLabelPrefix. Default: LabelPrefix.

For MolNameAndLabelPrefix value of --CompoundIDMode, molname line in SDFile(s) takes precedence over sequential compound IDs generated using LabelPrefix and only empty molname values are replaced with sequential compound IDs.

-d, --detail InfoLevel

Level of information to print about lines being ignored. Default: 1. Possible values: 1, 2 or 3

-f, --fast

In this mode, fingerprints field specified using --FingerprintsField is assumed to contain valid fingerprints data and no checking is performed before calculating similarity matrices. By default, fingerprints data is validated before computing pairwise similarity coefficiets.

--FingerprintsField FieldLabel

Fingerprints field label to use during calculation similarity matrices for SDFile(s). Default value: first data field label containing the word Fingerprints in its label

--FingerprintsFormatMode Internal | Specify

Specify format of fingerprints data in SDFile(s): use default format which MayaChemTools fingerprint generation scripts use to write out fingerprints data or explicitly specify format of fingerprints. Possible values: Internal | Specify. Default value: Internal.

Internal fingerprints string format consists of four parts delimited by semicolon: <Type:StringType:Size:String>. For example:

"PathLength:Binary:512:010011..."
"MDLKeys166FP:Binary:166:010011..."
"MDLKeys166Count:Vector:166:0 1 2..."

For Specify value of --FingerprintsFormatMode option, --FingerprintsString is used to interpret fingerprints string.

--FingerprintsString Hexadecimal | Binary | RawBinary

Format of fingerprints string during Specify value of --FingerprintsFormatMode option. Possible values: Hexadecimal, Binary, or RawBinary. Default value: none; its value must be explicitly specified.

-h, --help

Print this help message

-m, --mode All | ''Tanimoto,[Tversky,...]''

Specify what similarity coefficients to use for calculating similarity matrices for fingerprints data values in TextFile(s): calculate similarity matrices for all supported similarity coefficients or specify a comma delimited list of similarity coefficients. Possible values: All | ''Tanimoto,[Tversky,...]. Default: Tanimoto

All uses complete list of supported similarity coefficients: BaroniUrbani, Buser, Cosine, Dice, Dennis, Euclid, Forbes, Fossum, Hamann, Jacard, Kulczynski1, Kulczynski2, Manhattan, Matching, McConnaughey, Ochiai, Pearson, RogersTanimoto, RussellRao, Simpson, SkoalSneath1, SkoalSneath2, SkoalSneath3, Tanimoto, Tversky, Yule, WeightedTanimoto, WeightedTversky. These similarity coefficients are described below.

For two fingerprints bit vectors A and B of same size, let:

Na = Number of bits set to "1" in A
Nb = Number of bits set to "1" in B
Nc = Number of bits set to "1" in both A and B
Nd = Number of bits set to "0" in both A and B

Nt = Number of bits set to "1" or "0" in A or B (Size of A or B)
Nt = Na + Nb - Nc + Nd

Na - Nc = Number of bits set to "1" in A but not in B
Nb - Nc = Number of bits set to "1" in B but not in A

Then, various similarity coefficients [ Ref. 40 - 42 ] for a pair of bit vectors A and B are defined as follows:

BaroniUrbani: ( SQRT( Nc * Nd ) + Nc ) / ( SQRT ( Nc * Nd ) + Nc + ( Na - Nc ) + ( Nb - Nc ) ) ( same as Buser )

Buser: ( SQRT ( Nc * Nd ) + Nc ) / ( SQRT ( Nc * Nd ) + Nc + ( Na - Nc ) + ( Nb - Nc ) ) ( same as BaroniUrbani )

Cosine: Nc / SQRT ( Na * Nb ) (same as Ochiai)

Dice: (2 * Nc) / ( Na + Nb )

Dennis: ( Nc * Nd - ( ( Na - Nc ) * ( Nb - Nc ) ) ) / SQRT ( Nt * Na * Nb)

Euclid: SQRT ( ( Nc + Nd ) / Nt )

Forbes: ( Nt * Nc ) / ( Na * Nb )

Fossum: ( Nt * ( ( Nc - 1/2 ) ** 2 ) / ( Na * Nb )

Hamann: ( ( Nc + Nd ) - ( Na - Nc ) - ( Nb - Nc ) ) / Nt

Jaccard: Nc / ( ( Na - Nc) + ( Nb - Nc ) + Nc ) = Nc / ( Na + Nb - Nc ) (same as Tanimoto)

Kulczynski1: Nc / ( ( Na - Nc ) + ( Nb - Nc) ) = Nc / ( Na + Nb - 2Nc )

Kulczynski2: ( ( Nc / 2 ) * ( 2 * Nc + ( Na - Nc ) + ( Nb - Nc) ) ) / ( ( Nc + ( Na - Nc ) ) * ( Nc + ( Nb - Nc ) ) ) = 0.5 * ( Nc / Na + Nc / Nb )

Manhattan: ( ( Na - Nc ) + (Nb - Nc) ) / Nt = ( Na + Nb - 2Nc ) / Nt

Matching: ( Nc + Nd ) / Nt

McConnaughey: ( Nc ** 2 - ( Na - Nc ) * ( Nb - Nc) ) / ( Na * Nb )

Ochiai: Nc / SQRT ( Na * Nb ) (same as Cosine)

Pearson: ( ( Nc * Nd ) - ( ( Na - Nc ) * ( Nb - Nc ) ) / SQRT ( Na * Nb * ( Na - Nc + Nd ) * ( Nb - Nc + Nd ) )

RogersTanimoto: ( Nc + Nd ) / ( ( Na - Nc) + ( Nb - Nc) + Nt) = ( Nc + Nd ) / ( Na + Nb - 2Nc + Nt)

RussellRao: Nc / Nt

Simpson: Nc / MIN ( Na, Nb)

SkoalSneath1: Nc / ( Nc + 2 * ( Na - Nc) + 2 * ( Nb - Nc) ) = Nc / ( 2 * Na + 2 * Nb - 3 * Nc )

SkoalSneath2: ( 2 * Nc + 2 * Nd ) / ( Nc + Nd + Nt )

SkoalSneath3: ( Nc + Nd ) / ( ( Na - Nc ) + ( Nb - Nc ) ) = ( Nc + Nd ) / ( Na + Nb - 2 * Nc )

Tanimoto: Nc / ( ( Na - Nc) + ( Nb - Nc ) + Nc ) = Nc / ( Na + Nb - Nc ) (same as Jaccard)

Tversky: Nc / ( alpha * ( Na - Nc ) + ( 1 - alpha) * ( Nb - Nc) + Nc ) = Nc / ( alpha * ( Na - Nb ) + Nb)

Yule: ( ( Nc * Nd ) - ( ( Na - Nc ) * ( Nb - Nc ) ) ) / ( ( Nc * Nd ) + ( ( Na - Nc ) * ( Nb - Nc ) ) )

Values of Tanimoto/Jaccard and Tversky coefficients are dependent on only those bit which are set to ''1'' in both A and B. In order to take into account all bit positions, modified versions of Tanimoto [ Ref. 42 ] and Tversky [ Ref. 43 ] have been developed.

Let:

Na' = Number of bits set to "0" in A
Nb' = Number of bits set to "0" in B
Nc' = Number of bits set to "0" in both A and B

Tanimoto': Nc' / ( ( Na' - Nc') + ( Nb' - Nc' ) + Nc' ) = Nc' / ( Na' + Nb' - Nc' )

Tversky': Nc' / ( alpha * ( Na' - Nc' ) + ( 1 - alpha) * ( Nb' - Nc' ) + Nc' ) = Nc' / ( alpha * ( Na' - Nb' ) + Nb')

Then:

WeightedTanimoto = beta * Tanimoto + (1 - beta) * Tanimoto'

WeightedTversky = beta * Tversky + (1 - beta) * Tversky'

--OutDelim comma | tab | semicolon

Delimiter for output CSV/TSV text file(s). Possible values: comma, tab, or semicolon Default value: comma

-o, --overwrite

Overwrite existing files

-p, --precision number

Precision of calculated values in the output file. Default: up to 2 decimal places. Valid values: positive integers

-q, --quote Yes | No

Put quote around column values in output CSV/TSV text file(s). Possible values: Yes or No. Default value: Yes

-r, --root RootName

New file name is generated using the root: <Root><Mode>.<Ext>. Default for new file names: <TextFileName><Mode>.<Ext>.The csv, and tsv <Ext> values are used for comma/semicolon, and tab delimited text files respectively. This option is ignored for multiple input files.

-w, --WorkingDir DirName

Location of working directory. Default: current directory

EXAMPLES

To generate a similarity matrix corresponding to Tanimoto similarity coefficient for fingerprints data in any internal fingerprint format present in a data field with Fingerprint substring in its label and create a SampleFPTanimoto.csv file containing sequentially generated compound IDs with Cmpd prefix, type:

To generate similarity matrices corresponding to all supported similarity coefficient for fingerprints data in any internal fingerprint format present in a data field with Fingerprint substring in its label and create a SampleFPTanimoto.csv file containing sequentially generated compound IDs with Cmpd prefix, type:

To generate a similarity matrix corresponding to Buser, Dice and Tanimoto similarity coefficient for fingerprints data in any internal fingerprint format present in a data field with Fingerprint substring in its label and create a SampleFPTanimoto.csv file containing sequentially generated compound IDs with Cmpd prefix, type:

To generate a similarity matrix corresponding to Tanimoto similarity coefficient for fingerprints data in any internal fingerprint format present in a data field name PathLengthFingerprints and create a SampleFPTanimoto.csv file containing compound IDs present in data field name Cmpd_ID with Cmpd prefix, type:

To generate a similarity matrix corresponding to Tanimoto similarity coefficient for fingerprints data in any binary bit-string format present in a data field with Fingerprint substring in its label and create a SampleFPTanimoto.csv file containing sequentially generated compound IDs with Cmpd prefix, type:

To generate a similarity matrix corresponding to Tanimoto similarity coefficient for fingerprints data in any internal fingerprint format present in a data field with Fingerprint substring in its label and create a SampleFPTanimoto.csv file containing compound IDs from molname line or sequentially generated compound IDs with Mol prefix, type generated compound IDs with Cmpd prefix, type:

To generate a similarity matrix corresponding to Tanimoto similarity coefficient for fingerprints data in any internal fingerprint format present in a data field with Fingerprint substring in its label and create a SampleFPTanimoto.tsv file without any quotes aroud values along with sequentially generated compound IDs with Cmpd prefix, type:

AUTHOR

Manish Sud

SEE ALSO

InfoFingerprintsSDFiles.pl, PathLengthFingerprints.pl, SimilarityMatrixTextFiles.pl

COPYRIGHT

Copyright (C) 2004-2008 Manish Sud. All rights reserved.

This file is part of MayaChemTools.

MayaChemTools is free software; you can redistribute it and/or modify it under the terms of the GNU Lesser General Public License as published by the Free Software Foundation; either version 3 of the License, or (at your option) any later version.