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159 lines
5.0 KiB
Python
159 lines
5.0 KiB
Python
#!/usr/bin/env python
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from galaxy import eggs
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import sys, string
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from rpy import *
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import numpy
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def stop_err(msg):
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sys.stderr.write(msg)
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sys.exit()
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infile = sys.argv[1]
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x_cols = sys.argv[2].split(',')
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y_cols = sys.argv[3].split(',')
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x_scale = x_center = "FALSE"
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if sys.argv[4] == 'both':
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x_scale = x_center = "TRUE"
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elif sys.argv[4] == 'center':
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x_center = "TRUE"
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elif sys.argv[4] == 'scale':
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x_scale = "TRUE"
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y_scale = y_center = "FALSE"
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if sys.argv[5] == 'both':
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y_scale = y_center = "TRUE"
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elif sys.argv[5] == 'center':
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y_center = "TRUE"
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elif sys.argv[5] == 'scale':
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y_scale = "TRUE"
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std_scores = "FALSE"
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if sys.argv[6] == "yes":
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std_scores = "TRUE"
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outfile = sys.argv[7]
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outfile2 = sys.argv[8]
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fout = open(outfile,'w')
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elems = []
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for i, line in enumerate( file ( infile )):
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line = line.rstrip('\r\n')
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if len( line )>0 and not line.startswith( '#' ):
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elems = line.split( '\t' )
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break
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if i == 30:
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break # Hopefully we'll never get here...
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if len( elems )<1:
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stop_err( "The data in your input dataset is either missing or not formatted properly." )
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x_vals = []
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for k,col in enumerate(x_cols):
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x_cols[k] = int(col)-1
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x_vals.append([])
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y_vals = []
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for k,col in enumerate(y_cols):
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y_cols[k] = int(col)-1
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y_vals.append([])
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skipped = 0
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for ind,line in enumerate( file( infile )):
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if line and not line.startswith( '#' ):
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try:
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fields = line.strip().split("\t")
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valid_line = True
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for col in x_cols+y_cols:
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try:
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assert float(fields[col])
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except:
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skipped += 1
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valid_line = False
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break
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if valid_line:
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for k,col in enumerate(x_cols):
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try:
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xval = float(fields[col])
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except:
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xval = NaN#
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x_vals[k].append(xval)
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for k,col in enumerate(y_cols):
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try:
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yval = float(fields[col])
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except:
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yval = NaN#
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y_vals[k].append(yval)
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except:
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skipped += 1
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x_vals1 = numpy.asarray(x_vals).transpose()
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y_vals1 = numpy.asarray(y_vals).transpose()
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x_dat= r.list(array(x_vals1))
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y_dat= r.list(array(y_vals1))
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try:
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r.suppressWarnings(r.library("yacca"))
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except:
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stop_err("Missing R library yacca.")
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set_default_mode(NO_CONVERSION)
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try:
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xcolnames = ["c%d" %(el+1) for el in x_cols]
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ycolnames = ["c%d" %(el+1) for el in y_cols]
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cc = r.cca(x=x_dat, y=y_dat, xlab=xcolnames, ylab=ycolnames, xcenter=r(x_center), ycenter=r(y_center), xscale=r(x_scale), yscale=r(y_scale), standardize_scores=r(std_scores))
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ftest = r.F_test_cca(cc)
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except RException, rex:
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stop_err("Encountered error while performing CCA on the input data: %s" %(rex))
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set_default_mode(BASIC_CONVERSION)
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summary = r.summary(cc)
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ncomps = len(summary['corr'])
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comps = summary['corr'].keys()
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corr = summary['corr'].values()
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xlab = summary['xlab']
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ylab = summary['ylab']
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for i in range(ncomps):
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corr[comps.index('CV %s' %(i+1))] = summary['corr'].values()[i]
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ftest=ftest.as_py()
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print >>fout, "#Component\t%s" %("\t".join(["%s" % el for el in range(1,ncomps+1)]))
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print >>fout, "#Correlation\t%s" %("\t".join(["%.4g" % el for el in corr]))
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print >>fout, "#F-statistic\t%s" %("\t".join(["%.4g" % el for el in ftest['statistic']]))
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print >>fout, "#p-value\t%s" %("\t".join(["%.4g" % el for el in ftest['p.value']]))
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print >>fout, "#X-Coefficients\t%s" %("\t".join(["%s" % el for el in range(1,ncomps+1)]))
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for i,val in enumerate(summary['xcoef']):
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print >>fout, "%s\t%s" %(xlab[i], "\t".join(["%.4g" % el for el in val]))
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print >>fout, "#Y-Coefficients\t%s" %("\t".join(["%s" % el for el in range(1,ncomps+1)]))
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for i,val in enumerate(summary['ycoef']):
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print >>fout, "%s\t%s" %(ylab[i], "\t".join(["%.4g" % el for el in val]))
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print >>fout, "#X-Loadings\t%s" %("\t".join(["%s" % el for el in range(1,ncomps+1)]))
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for i,val in enumerate(summary['xstructcorr']):
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print >>fout, "%s\t%s" %(xlab[i], "\t".join(["%.4g" % el for el in val]))
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print >>fout, "#Y-Loadings\t%s" %("\t".join(["%s" % el for el in range(1,ncomps+1)]))
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for i,val in enumerate(summary['ystructcorr']):
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print >>fout, "%s\t%s" %(ylab[i], "\t".join(["%.4g" % el for el in val]))
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print >>fout, "#X-CrossLoadings\t%s" %("\t".join(["%s" % el for el in range(1,ncomps+1)]))
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for i,val in enumerate(summary['xcrosscorr']):
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print >>fout, "%s\t%s" %(xlab[i], "\t".join(["%.4g" % el for el in val]))
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print >>fout, "#Y-CrossLoadings\t%s" %("\t".join(["%s" % el for el in range(1,ncomps+1)]))
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for i,val in enumerate(summary['ycrosscorr']):
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print >>fout, "%s\t%s" %(ylab[i], "\t".join(["%.4g" % el for el in val]))
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r.pdf( outfile2, 8, 8 )
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#r.plot(cc)
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for i in range(ncomps):
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r.helio_plot(cc, cv = i+1, main = r.paste("Explained Variance for CV",i+1), type = "variance")
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r.dev_off() |