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CLVREADME
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CLVREADME
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//##########################################################################
//# This software is part of the Treescaper i
//# -- Version 0.1
//# Copyright (C) 2010 Wen Huang
//#
//# This program is free software; you can redistribute it and/or
//# modify it under the terms of the GNU General Public License
//# as published by the Free Software Foundation; either version 2
//# of the License, or (at your option) any later version.
//#
//# This program is distributed in the hope that it will be useful,
//# but WITHOUT ANY WARRANTY; without even the implied warranty of
//# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
//# GNU General Public License for more details.
//# http://www.gnu.org/copyleft/gpl.html
//##########################################################################
This file indicates the methods of using command line version.
Suppose the binary file obtained is called "CLVTreeScaper".
There are three options for CLVTreeScaper.
1, -trees
Under this option, user can compute majority/strict consensus tree, distance matrices,
bipartition matrix, covariance matrix, affinity matrix of a distance matrix, communities
of an affinity matrix or covariance matrix.
-f: indicate the file name that contain the data
-ft: the file type
'Trees': the file contains trees. The tree format can be either Newick or Nexus.
'Dist': the file contains distance matrix which can be used to compute affinity matrix or communities.
'Cova': the file contains covariance matrix which can be used to compute communities.
-w: indicate whether trees are weighted
'1': weighted
'0': unweighted
-r: indicate whether trees are rooted
'1': rooted
'0': unrooted
-o: this option is used to indicate what user eventually need. Available options have
'BipartMatrix', 'Consensus', 'Dist', 'Affinity', 'Convariance', 'Community'
'BipartMatrix' : output bipartition matrix. -bfm is option for it.
-bfm is used to indicate the output format
'list' : output sparse matrix in (row, column, value)
'matrix': output as if it is a full matrix
'Consensus' : output majority or strict consensus tree. -if, -cfm are options for it.
-if: is used to indicate the name of a list file. Consensus tree only consider the trees
indicated in the file.
-ct: shows what type of consensus tree is computed
'Majority' : Majority consensus tree
'Strict' : Strict consensus tree
-cfm: is used to indicate the format of consensus tree
'Newick': Newick format
'Nexus' : Nexus format
'Dist' : compute distance matrix
-dm: indicates metric
'URF': Unweighted Robinson Foulds distance
'RF': Weighted Robinson Foulds distance
'Mat': Matching distance
'SPR': SPR distance
'Affinity' : compute affinity matrix based on some distance matrix
-dm: indicates metric
'URF': Unweighted Robinson Foulds distance
'RF': Weighted Robinson Foulds distance
'Mat': Matching distance
-am: indicates function to get affinity matrix
'Rec': Reciprocal
'Exp': Exponential
'Covariance': compute covariance matrix of bipartitions
'Community'
-t: target matrix which is used to compute community
'Affinity': affinity matrix
'Covariance': covariance matrix
-cm: model that is used to compute community
'CNM': Configuration Null Model
'CPM': Constant Potts Model
'ERNM': Erdos-Renyi Null Model
'NNM': No Null Model;
-lm: 'auto': automatically choose lambdas and find plateaus
'manu': specify intervals by users to find plateaus
-lp, -lps, -lpe, -lpiv, -ln, -lns, -lne, -lniv are used to specified the values of lambdas.
-lp: lambda + , it is used when -lpiv is zero.
a number between 0 and 1
-lps -lpe -lpiv: indicate the interval for lambda +, it is used when -lpiv is not zero.
[-lps:-lpiv:-lpe]
-ln: lambda -, it is used when -lniv is zero.
a number between 0 and 1
-lns -lne -lniv: indicate the interval for lambda -, it is used when -lniv is not zero.
[-lns:-lniv:-lne]
-hf: frequency upper bound
a number between 0 and 1
-lf: frequency lower bound
a number between 0 and 1
Examples of run the command line version, A/B/C means either A or B or C can be used.
Compute Bipartition matrix:
./CLVTreeScaper -trees -f Trees.txt -ft Trees -w 1/0 -r 1/0 -o BipartMatrix -bfm list/matrix
Compute Consensus tree:
./CLVTreeScaper -trees -f Trees.txt -ft Trees -w 1/0 -r 1/0 -o Consensus -if IndicesFileName -ct Majority/Strict -cfm Newick/Nexus
Compute Distance matrix:
./CLVTreeScaper -trees -f Trees.txt -ft Trees -w 1/0 -r 1/0 -o Dist -dm URF/RF/Mat
Compute Affinity matrix:
./CLVTreeScaper -trees -f Trees.txt -ft Trees -w 1/0 -r 1/0 -o Affinity -dm URF/RF/Mat -am Exp/Rec
Compute Covariance matrix:
./CLVTreeScaper -trees -f Trees.txt -ft Trees -w 1/0 -r 1/0 -o Covariance
Compute Communities with lambda positive fixed:
./CLVTreeScaper -trees -f Trees.txt -ft Trees -w 1/0 -r 1/0 -o Community -t Affinity/Covariance -cm CNM/CPM/ERNM/NNM -lm manu -lp NumberBetween0and1 -lns NumberBetween0and1 -lne NumberBetween0and1 -lniv NumberBetween0and1 -hf NumberBetween0and1 -lf NumberBetween0and1
Compute Communities with lambda negative fixed:
./CLVTreeScaper -trees -f Trees.txt -ft Trees -w 1/0 -r 1/0 -o Community -t Affinity/Covariance -cm CNM/CPM/ERNM/NNM -lm manu -ln NumberBetween0and1 -lps NumberBetween0and1 -lpe NumberBetween0and1 -lpiv NumberBetween0and1 -hf NumberBetween0and1 -lf NumberBetween0and1
Compute Communities with automatically chosen lambdas:
./CLVTreeScaper -trees -f Trees.txt -ft Trees -w 1/0 -r 1/0 -o Community -t Affinity/Covariance -dm SPR -cm CNM/CPM/ERNM/NNM -lm auto -hf NumberBetween0and1 -lf NumberBetween0and1
Load distance and compute affinity matrix
./CLVTreeScaper -trees -f dist.txt -ft Dist -o Affinity -am Exp/Rec
Load distance and compute communities of its affinity matrix using automatically search on lambda
./CLVTreeScaper -trees -f dist.txt -ft Dist -o Community -t Affinity -am Exp/Rec -cm CNM/CPM/ERNM/NNM -lm auto -hf NumberBetween0and1 -lf NumberBetween0and1
Load covariance and compute communities using automatically search on lambda
./CLVTreeScaper -trees -f cova.txt -ft Cova -o Community -cm CNM/CPM/ERNM/NNM -lm auto -hf NumberBetween0and1 -lf NumberBetween0and1
2, -nldr
Options:
-f: data file name.
-t: 'DIS' represents datum is a upper triangle matrix.
'COR' represents data are Euclidean coordinators.
-d: the dimension of Euclidean representations.
-c: cost function. For example, CLASSIC_MDS, KRUSKAL1, NORMALIZED, SAMMON, CCA.
-a: algorithm. For example, LINEAR_ITERATION, MAJORIZATION, GAUSS_SEIDEL, STOCHASTIC.
-i: initialize coordinators.
'RAND' represent that generate data randomly.
'CLASSIC_MDS' represent that compute low dimension representation by MDS, then
the low dimension representation is used as initial coordinators.
-o: suffix of output file names.
-s: random seed, if initial coordinators are generated randomly.
Example command:
./CLVTreeScaper -nldr -f test.out -t DIS -d 2 -c CCA -a STOCHASTIC -i RAND -o 0 -s 1
3, -dimest
-dimest: this is to indicate that run dimension estimator instead of NLDR.
Options:
-f: data file name
-e: 'CORR_DIM' represents correlation dimension estimator
'NN_DIM' represents nearest neighbor estimator
'MLE_DIM' represents Maximum likelihood estimator
-i: 'DIS' represents datum is a upper triangle matrix.
'COR' represents data are Euclidean coordinators.
Example command:
./CLVTreeScaper -dimest -f test.out -e CORR_DIM -i DIS