# HG changeset patch
# User devteam
# Date 1400517283 14400
# Node ID f568051cdf2e70b7354045cbba99cc60cb201fe6

Imported from capsule None

diff -r 000000000000 -r f568051cdf2e pca.py
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/pca.py	Mon May 19 12:34:43 2014 -0400
@@ -0,0 +1,129 @@
+#!/usr/bin/env python
+
+import sys, string
+from rpy import *
+import numpy
+
+def stop_err(msg):
+    sys.stderr.write(msg)
+    sys.exit()
+
+infile = sys.argv[1]
+x_cols = sys.argv[2].split(',')
+method = sys.argv[3]
+outfile = sys.argv[4]
+outfile2 = sys.argv[5]
+
+if method == 'svd':
+    scale = center = "FALSE"
+    if sys.argv[6] == 'both':
+        scale = center = "TRUE"
+    elif sys.argv[6] == 'center':
+        center = "TRUE"
+    elif sys.argv[6] == 'scale':
+        scale = "TRUE"
+    
+fout = open(outfile,'w')
+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([])
+
+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 k,col in enumerate(x_cols):
+                try:
+                    xval = float(fields[col])
+                except:
+                    skipped += 1 
+                    valid_line = False
+                    break
+            if valid_line:
+                for k,col in enumerate(x_cols):
+                    xval = float(fields[col])
+                    x_vals[k].append(xval)
+        except:
+            skipped += 1
+
+x_vals1 = numpy.asarray(x_vals).transpose()
+dat= r.list(array(x_vals1))
+
+set_default_mode(NO_CONVERSION)
+try:
+    if method == "cor":
+        pc = r.princomp(r.na_exclude(dat), cor = r("TRUE"))
+    elif method == "cov":
+        pc = r.princomp(r.na_exclude(dat), cor = r("FALSE"))
+    elif method=="svd":
+        pc = r.prcomp(r.na_exclude(dat), center = r(center), scale = r(scale))
+except RException, rex:
+    stop_err("Encountered error while performing PCA on the input data: %s" %(rex))
+
+set_default_mode(BASIC_CONVERSION)
+summary = r.summary(pc, loadings="TRUE")
+ncomps = len(summary['sdev'])
+
+if type(summary['sdev']) == type({}):
+    comps_unsorted = summary['sdev'].keys()
+    comps=[]
+    sd = summary['sdev'].values()
+    for i in range(ncomps):
+        sd[i] = summary['sdev'].values()[comps_unsorted.index('Comp.%s' %(i+1))]
+        comps.append('Comp.%s' %(i+1))
+elif type(summary['sdev']) == type([]):
+    comps=[]
+    for i in range(ncomps):
+        comps.append('Comp.%s' %(i+1))
+        sd = summary['sdev']
+
+print >>fout, "#Component\t%s" %("\t".join(["%s" % el for el in range(1,ncomps+1)]))
+print >>fout, "#Std. deviation\t%s" %("\t".join(["%.4g" % el for el in sd]))
+total_var = 0
+vars = []
+for s in sd:
+    var = s*s
+    total_var += var
+    vars.append(var)
+for i,var in enumerate(vars):
+    vars[i] = vars[i]/total_var
+       
+print >>fout, "#Proportion of variance explained\t%s" %("\t".join(["%.4g" % el for el in vars]))
+
+print >>fout, "#Loadings\t%s" %("\t".join(["%s" % el for el in range(1,ncomps+1)]))
+xcolnames = ["c%d" %(el+1) for el in x_cols]
+if 'loadings' in summary: #in case of princomp
+    loadings = 'loadings'
+elif 'rotation' in summary: #in case of prcomp
+    loadings = 'rotation'
+for i,val in enumerate(summary[loadings]):
+    print >>fout, "%s\t%s" %(xcolnames[i], "\t".join(["%.4g" % el for el in val]))
+
+print >>fout, "#Scores\t%s" %("\t".join(["%s" % el for el in range(1,ncomps+1)]))
+if 'scores' in summary: #in case of princomp
+    scores = 'scores'
+elif 'x' in summary: #in case of prcomp
+    scores = 'x'
+for obs,sc in enumerate(summary[scores]):
+    print >>fout, "%s\t%s" %(obs+1, "\t".join(["%.4g" % el for el in sc]))
+
+r.pdf( outfile2, 8, 8 )
+r.biplot(pc)
+r.dev_off()
\ No newline at end of file
diff -r 000000000000 -r f568051cdf2e pca.xml
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/pca.xml	Mon May 19 12:34:43 2014 -0400
@@ -0,0 +1,102 @@
+<tool id="pca1" name="Principal Component Analysis" version="1.0.2">
+  <description> </description>
+  <requirements>
+    <requirement type="package" version="1.0.3">rpy</requirement>
+    <requirement type="package" version="2.11.0">R</requirement>
+    <requirement type="package" version="1.7.1">numpy</requirement>
+  </requirements>
+  <command interpreter="python">
+    pca.py 
+      $input1
+      $var_cols
+      $methodChoice.method
+      $out_file1
+      $out_file2
+      #if $methodChoice.method == "svd":
+      $methodChoice.scale
+      #end if
+  </command>
+  <inputs>
+    <param format="tabular" name="input1" type="data" label="Select data" help="Dataset missing? See TIP below."/>
+    <param name="var_cols" label="Select columns containing input variables " type="data_column" data_ref="input1" numerical="True" multiple="true" >
+        <validator type="no_options" message="Please select at least one column."/>
+    </param>
+    <conditional name="methodChoice">
+        <param name="method" type="select" label="Method" help="The correlation matrix can only be used if there are no constant variables">
+            <option value="cor" selected="true">Eigenvectors of Correlation (princomp)</option>
+            <option value="cov">Eigenvectors of Covariance (princomp)</option>
+            <option value="svd">Singular Value Decomposition (prcomp)</option>
+        </param>
+        <when value="cor" />
+        <when value="cov" />
+        <when value="svd">
+            <param name="scale" type="select" label="Centering and Scaling" help="Can be used to center and/or scale variables">
+                <option value="none" selected="true">None</option>
+                <option value="center">Center only</option>
+                <option value="scale">Scale only</option>
+                <option value="both">Center and Scale</option>
+            </param>        
+        </when>
+    </conditional>
+  </inputs>
+  <outputs>
+    <data format="input" name="out_file1" metadata_source="input1" />
+    <data format="pdf" name="out_file2" />
+  </outputs>
+  <tests>
+    <test>
+        <param name="input1" value="iris.tabular"/>
+        <param name="var_cols" value="1,2,3,4"/>
+        <param name="method" value="cor"/>
+        <output name="out_file1" file="pca_out1.tabular"/>
+        <output name="out_file2" file="pca_out2.pdf"/>
+    </test>
+    <test>
+        <param name="input1" value="iris.tabular"/>
+        <param name="var_cols" value="1,2,3,4"/>
+        <param name="method" value="cov"/>
+        <output name="out_file1" file="pca_out3.tabular"/>
+        <output name="out_file2" file="pca_out4.pdf"/>
+    </test>
+    <test>
+        <param name="input1" value="iris.tabular"/>
+        <param name="var_cols" value="1,2,3,4"/>
+        <param name="method" value="svd"/>
+        <param name="scale" value="both"/>
+        <output name="out_file1" file="pca_out5.tabular"/>
+        <output name="out_file2" file="pca_out6.pdf"/>
+    </test>
+  </tests>
+  <help>
+
+
+.. class:: infomark
+
+**TIP:** If your data is not TAB delimited, use *Edit Datasets-&gt;Convert characters*
+
+-----
+
+.. class:: infomark
+
+**What it does**
+
+This tool performs Principal Component Analysis on the given numeric input data using functions from R statistical package - 'princomp' function (for Eigenvector based solution) and 'prcomp' function (for Singular value decomposition based solution). It outputs two files, one containing the summary statistics of PCA, and the other containing biplots of the observations and principal components.   
+
+*R Development Core Team (2009). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. ISBN 3-900051-07-0, URL http://www.R-project.org.*
+
+-----
+
+.. 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.
+
+- The summary statistics in the output are described below:
+
+  - Std. deviation: Standard deviations of the principal components
+  - Loadings: a list of eigen-vectors/variable loadings
+  - Scores: Scores of the input data on the principal components
+
+  </help>
+</tool>
diff -r 000000000000 -r f568051cdf2e test-data/1.tabular
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/1.tabular	Mon May 19 12:34:43 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 f568051cdf2e test-data/iris.tabular
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/iris.tabular	Mon May 19 12:34:43 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
+4.6	3.1	1.5	0.2	Iris-setosa
+5.0	3.6	1.4	0.2	Iris-setosa
+5.4	3.9	1.7	0.4	Iris-setosa
+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
+4.9	3.1	1.5	0.1	Iris-setosa
+5.4	3.7	1.5	0.2	Iris-setosa
+4.8	3.4	1.6	0.2	Iris-setosa
+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
+5.7	4.4	1.5	0.4	Iris-setosa
+5.4	3.9	1.3	0.4	Iris-setosa
+5.1	3.5	1.4	0.3	Iris-setosa
+5.7	3.8	1.7	0.3	Iris-setosa
+5.1	3.8	1.5	0.3	Iris-setosa
+5.4	3.4	1.7	0.2	Iris-setosa
+5.1	3.7	1.5	0.4	Iris-setosa
+4.6	3.6	1.0	0.2	Iris-setosa
+5.1	3.3	1.7	0.5	Iris-setosa
+4.8	3.4	1.9	0.2	Iris-setosa
+5.0	3.0	1.6	0.2	Iris-setosa
+5.0	3.4	1.6	0.4	Iris-setosa
+5.2	3.5	1.5	0.2	Iris-setosa
+5.2	3.4	1.4	0.2	Iris-setosa
+4.7	3.2	1.6	0.2	Iris-setosa
+4.8	3.1	1.6	0.2	Iris-setosa
+5.4	3.4	1.5	0.4	Iris-setosa
+5.2	4.1	1.5	0.1	Iris-setosa
+5.5	4.2	1.4	0.2	Iris-setosa
+4.9	3.1	1.5	0.1	Iris-setosa
+5.0	3.2	1.2	0.2	Iris-setosa
+5.5	3.5	1.3	0.2	Iris-setosa
+4.9	3.1	1.5	0.1	Iris-setosa
+4.4	3.0	1.3	0.2	Iris-setosa
+5.1	3.4	1.5	0.2	Iris-setosa
+5.0	3.5	1.3	0.3	Iris-setosa
+4.5	2.3	1.3	0.3	Iris-setosa
+4.4	3.2	1.3	0.2	Iris-setosa
+5.0	3.5	1.6	0.6	Iris-setosa
+5.1	3.8	1.9	0.4	Iris-setosa
+4.8	3.0	1.4	0.3	Iris-setosa
+5.1	3.8	1.6	0.2	Iris-setosa
+4.6	3.2	1.4	0.2	Iris-setosa
+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
+6.4	3.2	4.5	1.5	Iris-versicolor
+6.9	3.1	4.9	1.5	Iris-versicolor
+5.5	2.3	4.0	1.3	Iris-versicolor
+6.5	2.8	4.6	1.5	Iris-versicolor
+5.7	2.8	4.5	1.3	Iris-versicolor
+6.3	3.3	4.7	1.6	Iris-versicolor
+4.9	2.4	3.3	1.0	Iris-versicolor
+6.6	2.9	4.6	1.3	Iris-versicolor
+5.2	2.7	3.9	1.4	Iris-versicolor
+5.0	2.0	3.5	1.0	Iris-versicolor
+5.9	3.0	4.2	1.5	Iris-versicolor
+6.0	2.2	4.0	1.0	Iris-versicolor
+6.1	2.9	4.7	1.4	Iris-versicolor
+5.6	2.9	3.6	1.3	Iris-versicolor
+6.7	3.1	4.4	1.4	Iris-versicolor
+5.6	3.0	4.5	1.5	Iris-versicolor
+5.8	2.7	4.1	1.0	Iris-versicolor
+6.2	2.2	4.5	1.5	Iris-versicolor
+5.6	2.5	3.9	1.1	Iris-versicolor
+5.9	3.2	4.8	1.8	Iris-versicolor
+6.1	2.8	4.0	1.3	Iris-versicolor
+6.3	2.5	4.9	1.5	Iris-versicolor
+6.1	2.8	4.7	1.2	Iris-versicolor
+6.4	2.9	4.3	1.3	Iris-versicolor
+6.6	3.0	4.4	1.4	Iris-versicolor
+6.8	2.8	4.8	1.4	Iris-versicolor
+6.7	3.0	5.0	1.7	Iris-versicolor
+6.0	2.9	4.5	1.5	Iris-versicolor
+5.7	2.6	3.5	1.0	Iris-versicolor
+5.5	2.4	3.8	1.1	Iris-versicolor
+5.5	2.4	3.7	1.0	Iris-versicolor
+5.8	2.7	3.9	1.2	Iris-versicolor
+6.0	2.7	5.1	1.6	Iris-versicolor
+5.4	3.0	4.5	1.5	Iris-versicolor
+6.0	3.4	4.5	1.6	Iris-versicolor
+6.7	3.1	4.7	1.5	Iris-versicolor
+6.3	2.3	4.4	1.3	Iris-versicolor
+5.6	3.0	4.1	1.3	Iris-versicolor
+5.5	2.5	4.0	1.3	Iris-versicolor
+5.5	2.6	4.4	1.2	Iris-versicolor
+6.1	3.0	4.6	1.4	Iris-versicolor
+5.8	2.6	4.0	1.2	Iris-versicolor
+5.0	2.3	3.3	1.0	Iris-versicolor
+5.6	2.7	4.2	1.3	Iris-versicolor
+5.7	3.0	4.2	1.2	Iris-versicolor
+5.7	2.9	4.2	1.3	Iris-versicolor
+6.2	2.9	4.3	1.3	Iris-versicolor
+5.1	2.5	3.0	1.1	Iris-versicolor
+5.7	2.8	4.1	1.3	Iris-versicolor
+6.3	3.3	6.0	2.5	Iris-virginica
+5.8	2.7	5.1	1.9	Iris-virginica
+7.1	3.0	5.9	2.1	Iris-virginica
+6.3	2.9	5.6	1.8	Iris-virginica
+6.5	3.0	5.8	2.2	Iris-virginica
+7.6	3.0	6.6	2.1	Iris-virginica
+4.9	2.5	4.5	1.7	Iris-virginica
+7.3	2.9	6.3	1.8	Iris-virginica
+6.7	2.5	5.8	1.8	Iris-virginica
+7.2	3.6	6.1	2.5	Iris-virginica
+6.5	3.2	5.1	2.0	Iris-virginica
+6.4	2.7	5.3	1.9	Iris-virginica
+6.8	3.0	5.5	2.1	Iris-virginica
+5.7	2.5	5.0	2.0	Iris-virginica
+5.8	2.8	5.1	2.4	Iris-virginica
+6.4	3.2	5.3	2.3	Iris-virginica
+6.5	3.0	5.5	1.8	Iris-virginica
+7.7	3.8	6.7	2.2	Iris-virginica
+7.7	2.6	6.9	2.3	Iris-virginica
+6.0	2.2	5.0	1.5	Iris-virginica
+6.9	3.2	5.7	2.3	Iris-virginica
+5.6	2.8	4.9	2.0	Iris-virginica
+7.7	2.8	6.7	2.0	Iris-virginica
+6.3	2.7	4.9	1.8	Iris-virginica
+6.7	3.3	5.7	2.1	Iris-virginica
+7.2	3.2	6.0	1.8	Iris-virginica
+6.2	2.8	4.8	1.8	Iris-virginica
+6.1	3.0	4.9	1.8	Iris-virginica
+6.4	2.8	5.6	2.1	Iris-virginica
+7.2	3.0	5.8	1.6	Iris-virginica
+7.4	2.8	6.1	1.9	Iris-virginica
+7.9	3.8	6.4	2.0	Iris-virginica
+6.4	2.8	5.6	2.2	Iris-virginica
+6.3	2.8	5.1	1.5	Iris-virginica
+6.1	2.6	5.6	1.4	Iris-virginica
+7.7	3.0	6.1	2.3	Iris-virginica
+6.3	3.4	5.6	2.4	Iris-virginica
+6.4	3.1	5.5	1.8	Iris-virginica
+6.0	3.0	4.8	1.8	Iris-virginica
+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 f568051cdf2e test-data/pca_out1.tabular
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/pca_out1.tabular	Mon May 19 12:34:43 2014 -0400
@@ -0,0 +1,159 @@
+#Component	1	2	3	4
+#Std. deviation	1.706	0.9598	0.3839	0.1436
+#Proportion of variance explained	0.7277	0.2303	0.03684	0.005152
+#Loadings	1	2	3	4
+c1	0.5224	-0.3723	0.721	0.262
+c2	-0.2634	-0.9256	-0.242	-0.1241
+c3	0.5813	-0.02109	-0.1409	-0.8012
+c4	0.5656	-0.06542	-0.6338	0.5235
+#Scores	1	2	3	4
+1	-2.265	-0.5057	0.1219	0.02307
+2	-2.086	0.6554	0.2273	0.1032
+3	-2.368	0.3185	-0.05148	0.02783
+4	-2.304	0.5754	-0.09886	-0.06631
+5	-2.389	-0.6748	-0.02143	-0.0374
+6	-2.071	-1.519	-0.03068	0.004399
+7	-2.446	-0.07456	-0.3422	-0.0381
+8	-2.234	-0.2476	0.08257	-0.02551
+9	-2.342	1.095	-0.1536	-0.02679
+10	-2.189	0.4486	0.2466	-0.03991
+11	-2.163	-1.071	0.264	0.0153
+12	-2.327	-0.1586	-0.1002	-0.1346
+13	-2.224	0.7091	0.2232	0.002631
+14	-2.64	0.9383	-0.1896	-0.01942
+15	-2.192	-1.89	0.4695	0.1928
+16	-2.251	-2.722	-0.0326	0.04713
+17	-2.203	-1.514	0.001363	0.1866
+18	-2.19	-0.5143	0.03862	0.09191
+19	-1.894	-1.431	0.3707	0.05953
+20	-2.34	-1.158	-0.1374	-0.03983
+21	-1.915	-0.4305	0.416	0.01036
+22	-2.205	-0.9525	-0.1647	0.05773
+23	-2.774	-0.4895	-0.3388	0.01785
+24	-1.82	-0.1068	-0.04006	0.1503
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diff -r 000000000000 -r f568051cdf2e test-data/pca_out3.tabular
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/pca_out3.tabular	Mon May 19 12:34:43 2014 -0400
@@ -0,0 +1,159 @@
+#Component	1	2	3	4
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+#Proportion of variance explained	0.9246	0.05302	0.01719	0.005183
+#Loadings	1	2	3	4
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diff -r 000000000000 -r f568051cdf2e test-data/pca_out5.tabular
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/pca_out5.tabular	Mon May 19 12:34:43 2014 -0400
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diff -r 000000000000 -r f568051cdf2e tool_dependencies.xml
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/tool_dependencies.xml	Mon May 19 12:34:43 2014 -0400
@@ -0,0 +1,12 @@
+<?xml version="1.0"?>
+<tool_dependency>
+  <package name="numpy" version="1.7.1">
+      <repository changeset_revision="0c288abd2a1e" name="package_numpy_1_7" owner="devteam" toolshed="http://toolshed.g2.bx.psu.edu" />
+    </package>
+    <package name="rpy" version="1.0.3">
+      <repository changeset_revision="82170c94ca7c" name="package_rpy_1_0_3" owner="devteam" toolshed="http://toolshed.g2.bx.psu.edu" />
+    </package>
+    <package name="R" version="2.11.0">
+      <repository changeset_revision="5824d2b3bc8b" name="package_r_2_11_0" owner="devteam" toolshed="http://toolshed.g2.bx.psu.edu" />
+    </package>
+</tool_dependency>