# HG changeset patch
# User devteam
# Date 1400511611 14400
# Node ID f89438602243073f79cf75a933e9c31841012a3c
Imported from capsule None
diff -r 000000000000 -r f89438602243 kcca.py
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/kcca.py Mon May 19 11:00:11 2014 -0400
@@ -0,0 +1,147 @@
+#!/usr/bin/env python
+
+"""
+Run kernel CCA using kcca() from R 'kernlab' package
+
+usage: %prog [options]
+ -i, --input=i: Input file
+ -o, --output1=o: Summary output
+ -x, --x_cols=x: X-Variable columns
+ -y, --y_cols=y: Y-Variable columns
+ -k, --kernel=k: Kernel function
+ -f, --features=f: Number of canonical components to return
+ -s, --sigma=s: sigma
+ -d, --degree=d: degree
+ -l, --scale=l: scale
+ -t, --offset=t: offset
+ -r, --order=r: order
+
+usage: %prog input output1 x_cols y_cols kernel features sigma(or_None) degree(or_None) scale(or_None) offset(or_None) order(or_None)
+"""
+
+import sys, string
+from rpy import *
+import numpy
+from bx.cookbook import doc_optparse
+import logging
+log = logging.getLogger('kcca')
+
+def stop_err(msg):
+ sys.stderr.write(msg)
+ sys.exit()
+
+#Parse Command Line
+options, args = doc_optparse.parse( __doc__ )
+#{'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'}
+
+infile = options.input
+x_cols = options.x_cols.split(',')
+y_cols = options.y_cols.split(',')
+kernel = options.kernel
+outfile = options.output1
+ncomps = int(options.features)
+fout = open(outfile,'w')
+
+if ncomps < 1:
+ print "You chose to return '0' canonical components. Please try rerunning the tool with number of components = 1 or more."
+ sys.exit()
+elems = []
+for i, line in enumerate( file ( infile )):
+ line = line.rstrip('\r\n')
+ if len( line )>0 and not line.startswith( '#' ):
+ elems = line.split( '\t' )
+ break
+ if i == 30:
+ break # Hopefully we'll never get here...
+
+if len( elems )<1:
+ stop_err( "The data in your input dataset is either missing or not formatted properly." )
+
+x_vals = []
+for k,col in enumerate(x_cols):
+ x_cols[k] = int(col)-1
+ x_vals.append([])
+y_vals = []
+for k,col in enumerate(y_cols):
+ y_cols[k] = int(col)-1
+ y_vals.append([])
+NA = 'NA'
+skipped = 0
+for ind,line in enumerate( file( infile )):
+ if line and not line.startswith( '#' ):
+ try:
+ fields = line.strip().split("\t")
+ valid_line = True
+ for col in x_cols+y_cols:
+ try:
+ assert float(fields[col])
+ except:
+ skipped += 1
+ valid_line = False
+ break
+ if valid_line:
+ for k,col in enumerate(x_cols):
+ try:
+ xval = float(fields[col])
+ except:
+ xval = NaN
+ x_vals[k].append(xval)
+ for k,col in enumerate(y_cols):
+ try:
+ yval = float(fields[col])
+ except:
+ yval = NaN
+ y_vals[k].append(yval)
+ except:
+ skipped += 1
+
+x_vals1 = numpy.asarray(x_vals).transpose()
+y_vals1 = numpy.asarray(y_vals).transpose()
+
+x_dat= r.list(array(x_vals1))
+y_dat= r.list(array(y_vals1))
+
+try:
+ r.suppressWarnings(r.library('kernlab'))
+except:
+ stop_err('Missing R library kernlab')
+
+set_default_mode(NO_CONVERSION)
+if kernel=="rbfdot" or kernel=="anovadot":
+ pars = r.list(sigma=float(options.sigma))
+elif kernel=="polydot":
+ pars = r.list(degree=float(options.degree),scale=float(options.scale),offset=float(options.offset))
+elif kernel=="tanhdot":
+ pars = r.list(scale=float(options.scale),offset=float(options.offset))
+elif kernel=="besseldot":
+ pars = r.list(degree=float(options.degree),sigma=float(options.sigma),order=float(options.order))
+elif kernel=="anovadot":
+ pars = r.list(degree=float(options.degree),sigma=float(options.sigma))
+else:
+ pars = rlist()
+
+try:
+ kcc = r.kcca(x=x_dat, y=y_dat, kernel=kernel, kpar=pars, ncomps=ncomps)
+except RException, rex:
+ raise
+ log.exception( rex )
+ stop_err("Encountered error while performing kCCA on the input data: %s" %(rex))
+
+set_default_mode(BASIC_CONVERSION)
+kcor = r.kcor(kcc)
+if ncomps == 1:
+ kcor = [kcor]
+xcoef = r.xcoef(kcc)
+ycoef = r.ycoef(kcc)
+
+print >>fout, "#Component\t%s" %("\t".join(["%s" % el for el in range(1,ncomps+1)]))
+
+print >>fout, "#Correlation\t%s" %("\t".join(["%.4g" % el for el in kcor]))
+
+print >>fout, "#Estimated X-coefficients\t%s" %("\t".join(["%s" % el for el in range(1,ncomps+1)]))
+for obs,val in enumerate(xcoef):
+ print >>fout, "%s\t%s" %(obs+1, "\t".join(["%.4g" % el for el in val]))
+
+print >>fout, "#Estimated Y-coefficients\t%s" %("\t".join(["%s" % el for el in range(1,ncomps+1)]))
+for obs,val in enumerate(ycoef):
+ print >>fout, "%s\t%s" %(obs+1, "\t".join(["%.4g" % el for el in val]))
diff -r 000000000000 -r f89438602243 kcca.xml
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/kcca.xml Mon May 19 11:00:11 2014 -0400
@@ -0,0 +1,154 @@
+
+
+
+ rpy
+ R
+ kernlab
+ numpy
+ bx-python
+
+
+ kcca.py
+ --input=$input1
+ --output1=$out_file1
+ --x_cols=$x_cols
+ --y_cols=$y_cols
+ --kernel=$kernelChoice.kernel
+ --features=$features
+ #if $kernelChoice.kernel == "rbfdot" or $kernelChoice.kernel == "anovadot":
+ --sigma=$kernelChoice.sigma
+ --degree="None"
+ --scale="None"
+ --offset="None"
+ --order="None"
+ #elif $kernelChoice.kernel == "polydot":
+ --sigma="None"
+ --degree=$kernelChoice.degree
+ --scale=$kernelChoice.scale
+ --offset=$kernelChoice.offset
+ --order="None"
+ #elif $kernelChoice.kernel == "tanhdot":
+ --sigma="None"
+ --degree="None"
+ --scale=$kernelChoice.scale
+ --offset=$kernelChoice.offset
+ --order="None"
+ #elif $kernelChoice.kernel == "besseldot":
+ --sigma=$kernelChoice.sigma
+ --degree=$kernelChoice.degree
+ --scale="None"
+ --offset="None"
+ --order=$kernelChoice.order
+ #elif $kernelChoice.kernel == "anovadot":
+ --sigma=$kernelChoice.sigma
+ --degree=$kernelChoice.degree
+ --scale="None"
+ --offset="None"
+ --order="None"
+ #else:
+ --sigma="None"
+ --degree="None"
+ --scale="None"
+ --offset="None"
+ --order="None"
+ #end if
+
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+
+
+.. class:: infomark
+
+**TIP:** If your data is not TAB delimited, use *Edit Datasets->Convert characters*
+
+-----
+
+.. class:: infomark
+
+**What it does**
+
+This tool uses functions from 'kernlab' library from R statistical package to perform Kernel Canonical Correlation Analysis (kCCA) on the input data.
+
+*Alexandros Karatzoglou, Alex Smola, Kurt Hornik, Achim Zeileis (2004). kernlab - An S4 Package for Kernel Methods in R. Journal of Statistical Software 11(9), 1-20. URL http://www.jstatsoft.org/v11/i09/*
+
+-----
+
+.. class:: warningmark
+
+**Note**
+
+This tool currently treats all variables as continuous numeric variables. Running the tool on categorical variables might result in incorrect results. Rows containing non-numeric (or missing) data in any of the chosen columns will be skipped from the analysis.
+
+
+
diff -r 000000000000 -r f89438602243 test-data/1.tabular
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/1.tabular Mon May 19 11:00:11 2014 -0400
@@ -0,0 +1,6 @@
+chr22 1000 NM_17
+chr22 2000 NM_18
+chr10 2200 NM_10
+chr10 hap test
+chr10 1200 NM_11
+chr22 1600 NM_19
\ No newline at end of file
diff -r 000000000000 -r f89438602243 test-data/2.tabular
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/2.tabular Mon May 19 11:00:11 2014 -0400
@@ -0,0 +1,10 @@
+1 68 4.1
+2 71 4.6
+3 62 3.8
+4 75 4.4
+5 58 3.2
+6 60 3.1
+7 67 3.8
+8 68 4.1
+9 71 4.3
+10 69 3.7
diff -r 000000000000 -r f89438602243 test-data/cca_out1.tabular
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/cca_out1.tabular Mon May 19 11:00:11 2014 -0400
@@ -0,0 +1,22 @@
+#Component 1 2
+#Correlation 0.9409 0.1311
+#F-statistic 144.4 2.57
+#p-value 6.213e-68 0.1111
+#X-Coefficients 1 2
+c3 1.507 -3.378
+c4 -0.5372 3.659
+#Y-Coefficients 1 2
+c1 6.35 3.379
+c2 -2.66 6.67
+#X-Loadings 1 2
+c3 0.9894 0.1452
+c4 0.9133 0.4073
+#Y-Loadings 1 2
+c1 0.9289 0.3704
+c2 -0.4698 0.8828
+#X-CrossLoadings 1 2
+c3 0.9309 0.01904
+c4 0.8593 0.05339
+#Y-CrossLoadings 1 2
+c1 0.874 0.04855
+c2 -0.442 0.1157
diff -r 000000000000 -r f89438602243 test-data/iris.tabular
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/iris.tabular Mon May 19 11:00:11 2014 -0400
@@ -0,0 +1,151 @@
+5.1 3.5 1.4 0.2 Iris-setosa
+4.9 3.0 1.4 0.2 Iris-setosa
+4.7 3.2 1.3 0.2 Iris-setosa
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+4.6 3.4 1.4 0.3 Iris-setosa
+5.0 3.4 1.5 0.2 Iris-setosa
+4.4 2.9 1.4 0.2 Iris-setosa
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+5.4 3.7 1.5 0.2 Iris-setosa
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+4.8 3.0 1.4 0.1 Iris-setosa
+4.3 3.0 1.1 0.1 Iris-setosa
+5.8 4.0 1.2 0.2 Iris-setosa
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+5.3 3.7 1.5 0.2 Iris-setosa
+5.0 3.3 1.4 0.2 Iris-setosa
+7.0 3.2 4.7 1.4 Iris-versicolor
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+5.5 2.3 4.0 1.3 Iris-versicolor
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+6.9 3.1 5.4 2.1 Iris-virginica
+6.7 3.1 5.6 2.4 Iris-virginica
+6.9 3.1 5.1 2.3 Iris-virginica
+5.8 2.7 5.1 1.9 Iris-virginica
+6.8 3.2 5.9 2.3 Iris-virginica
+6.7 3.3 5.7 2.5 Iris-virginica
+6.7 3.0 5.2 2.3 Iris-virginica
+6.3 2.5 5.0 1.9 Iris-virginica
+6.5 3.0 5.2 2.0 Iris-virginica
+6.2 3.4 5.4 2.3 Iris-virginica
+5.9 3.0 5.1 1.8 Iris-virginica
+
diff -r 000000000000 -r f89438602243 test-data/kcca_out1.tabular
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/kcca_out1.tabular Mon May 19 11:00:11 2014 -0400
@@ -0,0 +1,304 @@
+\#Component\ 1\ 2\ 3\ 4
+\#Correlation\ \-?0\.99\d*\ \-?0\.99\d*\ \-?0\.93\d*\ \-?0\.93\d*
+\#Estimated\ X\-?coefficients\ 1\ 2\ 3\ 4
+1\ \-?0\.0015\d*\ \-?0\.0015\d*\ \-?0\.034\d*\ \-?0\.034\d*
+2\ \-?0\.001\d*\ \-?0\.001\d*\ \-?0\.032\d*\ \-?0\.032\d*
+3\ \-?0\.0001\d*\ \-?0\.0001\d*\ \-?0\.018\d*\ \-?0\.018\d*
+4\ \-?0\.0010\d*\ \-?0\.0010\d*\ \-?0\.0048\d*\ \-?0\.0048\d*
+5\ \-?0\.000\d*\ \-?0\.000\d*\ \-?0\.052\d*\ \-?0\.052\d*
+6\ \-?0\.0023\d*\ \-?0\.0023\d*\ \-?0\.019\d*\ \-?0\.019\d*
+7\ \-?0\.0014\d*\ \-?0\.0014\d*\ \-?0\.0057\d*\ \-?0\.0057\d*
+8\ \-?0\.0015\d*\ \-?0\.0015\d*\ \-?0\.038\d*\ \-?0\.038\d*
+9\ \-?0\.0036\d*\ \-?0\.0036\d*\ \-?0\.07\d*\ \-?0\.07\d*
+\d*\ \-?0\.0013\d*\ \-?0\.0013\d*\ \-?0\.031\d*\ \-?0\.031\d*
+\d*\ \-?0\.0008\d*\ \-?0\.0008\d*\ \-?0\.0013\d*\ \-?0\.0013\d*
+\d*\ \-?0\.00\d*\ \-?0\.00\d*\ \-?0\.039\d*\ \-?0\.039\d*
+\d*\ \-?0\.00037\d*\ \-?0\.00037\d*\ \-?0\.029\d*\ \-?0\.029\d*
+\d*\ \-?0\.0042\d*\ \-?0\.0042\d*\ \-?0\.13\d*\ \-?0\.13\d*
+\d*\ \-?0\.0044\d*\ \-?0\.0044\d*\ \-?0\.021\d*\ \-?0\.021\d*
+\d*\ \-?0\.015\d*\ \-?0\.015\d*\ \-?0\.041\d*\ \-?0\.041\d*
+\d*\ \-?0\.0023\d*\ \-?0\.0023\d*\ \-?0\.019\d*\ \-?0\.019\d*
+\d*\ \-?0\.0015\d*\ \-?0\.0015\d*\ \-?0\.034\d*\ \-?0\.034\d*
+\d*\ \-?0\.00047\d*\ \-?0\.00047\d*\ \-?0\.033\d*\ \-?0\.033\d*
+\d*\ \-?0\.0017\d*\ \-?0\.0017\d*\ \-?0\.059\d*\ \-?0\.059\d*
+\d*\ \-?0\.0033\d*\ \-?0\.0033\d*\ \-?0\.021\d*\ \-?0\.021\d*
+\d*\ \-?0\.0003\d*\ \-?0\.0003\d*\ \-?0\.050\d*\ \-?0\.050\d*
+\d*\ \-?0\.0028\d*\ \-?0\.0028\d*\ \-?0\.019\d*\ \-?0\.019\d*
+\d*\ \-?0\.0025\d*\ \-?0\.0025\d*\ \-?0\.02\d*\ \-?0\.02\d*
+\d*\ \-?0\.00\d*\ \-?0\.00\d*\ \-?0\.039\d*\ \-?0\.039\d*
+\d*\ \-?0\.0017\d*\ \-?0\.0017\d*\ \-?0\.028\d*\ \-?0\.028\d*
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diff -r 000000000000 -r f89438602243 test-data/kcca_out2.tabular
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/kcca_out2.tabular Mon May 19 11:00:11 2014 -0400
@@ -0,0 +1,304 @@
+\#Component\ 1\ 2
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diff -r 000000000000 -r f89438602243 tool_dependencies.xml
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/tool_dependencies.xml Mon May 19 11:00:11 2014 -0400
@@ -0,0 +1,18 @@
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