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     1 #!/usr/bin/env python
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     2 
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     3 """
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     4 Run kernel PCA using kpca() from R 'kernlab' package
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     5 
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     6 usage: %prog [options]
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     7    -i, --input=i: Input file
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     8    -o, --output1=o: Summary output
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     9    -p, --output2=p: Figures output
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    10    -c, --var_cols=c: Variable columns
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    11    -k, --kernel=k: Kernel function
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    12    -f, --features=f: Number of principal components to return
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    13    -s, --sigma=s: sigma
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    14    -d, --degree=d: degree
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    15    -l, --scale=l: scale
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    16    -t, --offset=t: offset
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    17    -r, --order=r: order
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    18 
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    19 usage: %prog input output1 output2 var_cols kernel features sigma(or_None) degree(or_None) scale(or_None) offset(or_None) order(or_None)
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    20 """
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    21 
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    22 from galaxy import eggs
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    23 import sys, string
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    24 #from rpy import *
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    25 import rpy2.robjects as robjects
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    26 import rpy2.rlike.container as rlc
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    27 from rpy2.robjects.packages import importr
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    28 r = robjects.r
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    29 grdevices = importr('grDevices')
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    30 import numpy
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    31 import pkg_resources; pkg_resources.require( "bx-python" )
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    32 from bx.cookbook import doc_optparse
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    33 
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    34 
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    35 def stop_err(msg):
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    36     sys.stderr.write(msg)
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    37     sys.exit()
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    38 
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    39 #Parse Command Line
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    40 options, args = doc_optparse.parse( __doc__ )
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    41 #{'options= kernel': 'rbfdot', 'var_cols': '1,2,3,4', 'degree': 'None', 'output2': '/afs/bx.psu.edu/home/gua110/workspace/galaxy_bitbucket/database/files/000/dataset_260.dat', 'output1': '/afs/bx.psu.edu/home/gua110/workspace/galaxy_bitbucket/database/files/000/dataset_259.dat', 'scale': 'None', 'offset': 'None', 'input': '/afs/bx.psu.edu/home/gua110/workspace/galaxy_bitbucket/database/files/000/dataset_256.dat', 'sigma': '1.0', 'order': 'None'}
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    42 
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    43 infile = options.input
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    44 x_cols = options.var_cols.split(',')
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    45 kernel = options.kernel
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    46 outfile = options.output1
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    47 outfile2 = options.output2
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    48 ncomps = int(options.features)
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    49 fout = open(outfile,'w')
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    50 
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    51 elems = []
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    52 for i, line in enumerate( file ( infile )):
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    53     line = line.rstrip('\r\n')
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    54     if len( line )>0 and not line.startswith( '#' ):
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    55         elems = line.split( '\t' )
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    56         break 
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    57     if i == 30:
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    58         break # Hopefully we'll never get here...
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    59 
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    60 if len( elems )<1:
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    61     stop_err( "The data in your input dataset is either missing or not formatted properly." )
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    62 
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    63 x_vals = []
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    64 
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    65 for k,col in enumerate(x_cols):
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    66     x_cols[k] = int(col)-1
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    67     #x_vals.append([])
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    68 
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    69 NA = 'NA'
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    70 skipped = 0
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    71 for ind,line in enumerate( file( infile )):
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    72     if line and not line.startswith( '#' ):
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    73         try:
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    74             fields = line.strip().split("\t")
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    75             for k,col in enumerate(x_cols):
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    76                 try:
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    77                     xval = float(fields[col])
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    78                 except:
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    79                     #xval = r('NA')
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    80                     xval = NaN#
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    81                 #x_vals[k].append(xval)
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    82                 x_vals.append(xval)
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    83         except:
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    84             skipped += 1
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    85 
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    86 #x_vals1 = numpy.asarray(x_vals).transpose()
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    87 #dat= r.list(array(x_vals1))
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    88 dat = r['matrix'](robjects.FloatVector(x_vals),ncol=len(x_cols),byrow=True)
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    89 
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    90 
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    91 try:
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    92     r.suppressWarnings(r.library('kernlab'))
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    93 except:
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    94     stop_err('Missing R library kernlab')
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    95             
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    96 #set_default_mode(NO_CONVERSION)
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    97 if kernel=="rbfdot" or kernel=="anovadot":
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    98     pars = r.list(sigma=float(options.sigma))
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    99 elif kernel=="polydot":
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   100     pars = r.list(degree=float(options.degree),scale=float(options.scale),offset=float(options.offset))
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   101 elif kernel=="tanhdot":
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   102     pars = r.list(scale=float(options.scale),offset=float(options.offset))
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   103 elif kernel=="besseldot":
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   104     pars = r.list(degree=float(options.degree),sigma=float(options.sigma),order=float(options.order))
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   105 elif kernel=="anovadot":
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   106     pars = r.list(degree=float(options.degree),sigma=float(options.sigma))
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   107 else:
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   108     pars = r.list()
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   109     
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   110 try:
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   111     #kpc = r.kpca(x=r.na_exclude(dat), kernel=kernel, kpar=pars, features=ncomps)
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   112     kpc = r.kpca(x=r['na.exclude'](dat), kernel=kernel, kpar=pars, features=ncomps)
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   113 #except RException, rex:
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   114 except Exception, rex:  # need to find rpy2 RException
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   115     stop_err("Encountered error while performing kPCA on the input data: %s" %(rex))
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   116 #set_default_mode(BASIC_CONVERSION)
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   117     
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   118 eig = r.eig(kpc)
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   119 pcv = r.pcv(kpc)
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   120 rotated = r.rotated(kpc)
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   121 
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   122 #comps = eig.keys()
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   123 comps = eig.names
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   124 #eigv = eig.values()
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   125 #for i in range(ncomps):
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   126 #    eigv[comps.index('Comp.%s' %(i+1))] = eig.values()[i]
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   127 
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   128 print >>fout, "#Component\t%s" %("\t".join(["%s" % el for el in range(1,ncomps+1)]))
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   129 
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   130 #print >>fout, "#Eigenvalue\t%s" %("\t".join(["%.4g" % el for el in eig.values()]))
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   131 print >>fout, "#Eigenvalue\t%s" %("\t".join(["%.4g" % el for el in eig]))
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   132 print >>fout, "#Principal component vectors\t%s" %("\t".join(["%s" % el for el in range(1,ncomps+1)]))
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   133 #for obs,val in enumerate(pcv):
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   134 #    print >>fout, "%s\t%s" %(obs+1, "\t".join(["%.4g" % el for el in val]))
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   135 for i in range(1,pcv.nrow+1):
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   136     vals = []
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   137     for j in range(1,pcv.ncol+1):
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   138        vals.append("%.4g" % pcv.rx2(i,j)[0])
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   139     print >>fout, "%s\t%s" %(i, "\t".join(vals))
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   140 
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   141 
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   142 print >>fout, "#Rotated values\t%s" %("\t".join(["%s" % el for el in range(1,ncomps+1)]))
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   143 #for obs,val in enumerate(rotated):
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   144 #    print >>fout, "%s\t%s" %(obs+1, "\t".join(["%.4g" % el for el in val]))
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   145 for i in range(1,rotated.nrow+1):
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   146     vals = []
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   147     for j in range(1,rotated.ncol+1):
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   148        vals.append("%.4g" % rotated.rx2(i,j)[0])
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   149     print >>fout, "%s\t%s" %(i, "\t".join(vals))
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   150 
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   151 r.pdf( outfile2, 8, 8 )
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   152 if ncomps != 1:
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   153     #r.pairs(rotated,labels=r.list(range(1,ncomps+1)),main="Scatterplot of rotated values")
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   154     r.pairs(rotated,labels=robjects.StrVector(range(1,ncomps+1)),main="Scatterplot of rotated values")
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   155 else:
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   156     r.plot(rotated, ylab='Comp.1', main="Scatterplot of rotated values")
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   157 #r.dev_off()
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   158 grdevices.dev_off()
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   159 
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