mirror of
https://github.com/galaxyproject/galaxy.git
synced 2026-09-24 16:30:27 +08:00
144 lines
4.0 KiB
Python
144 lines
4.0 KiB
Python
#!/usr/bin/env python
|
|
|
|
from galaxy import eggs
|
|
|
|
import sys, string
|
|
from rpy import *
|
|
import numpy
|
|
|
|
def stop_err(msg):
|
|
sys.stderr.write(msg)
|
|
sys.exit()
|
|
|
|
def sscombs(s):
|
|
if len(s) == 1:
|
|
return [s]
|
|
else:
|
|
ssc = sscombs(s[1:])
|
|
return [s[0]] + [s[0]+comb for comb in ssc] + ssc
|
|
|
|
|
|
infile = sys.argv[1]
|
|
y_col = int(sys.argv[2])-1
|
|
x_cols = sys.argv[3].split(',')
|
|
outfile = sys.argv[4]
|
|
|
|
print "Predictor columns: %s; Response column: %d" %(x_cols,y_col+1)
|
|
fout = open(outfile,'w')
|
|
|
|
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." )
|
|
|
|
y_vals = []
|
|
x_vals = []
|
|
|
|
for k,col in enumerate(x_cols):
|
|
x_cols[k] = int(col)-1
|
|
x_vals.append([])
|
|
"""
|
|
try:
|
|
float( elems[x_cols[k]] )
|
|
except:
|
|
try:
|
|
msg = "This operation cannot be performed on non-numeric column %d containing value '%s'." %( col, elems[x_cols[k]] )
|
|
except:
|
|
msg = "This operation cannot be performed on non-numeric data."
|
|
stop_err( msg )
|
|
"""
|
|
NA = 'NA'
|
|
for ind,line in enumerate( file( infile )):
|
|
if line and not line.startswith( '#' ):
|
|
try:
|
|
fields = line.split("\t")
|
|
try:
|
|
yval = float(fields[y_col])
|
|
except Exception, ey:
|
|
yval = r('NA')
|
|
#print >>sys.stderr, "ey = %s" %ey
|
|
y_vals.append(yval)
|
|
for k,col in enumerate(x_cols):
|
|
try:
|
|
xval = float(fields[col])
|
|
except Exception, ex:
|
|
xval = r('NA')
|
|
#print >>sys.stderr, "ex = %s" %ex
|
|
x_vals[k].append(xval)
|
|
except:
|
|
pass
|
|
|
|
x_vals1 = numpy.asarray(x_vals).transpose()
|
|
dat= r.list(x=array(x_vals1), y=y_vals)
|
|
|
|
set_default_mode(NO_CONVERSION)
|
|
try:
|
|
full = r.lm(r("y ~ x"), data= r.na_exclude(dat)) #full model includes all the predictor variables specified by the user
|
|
except RException, rex:
|
|
stop_err("Error performing linear regression on the input data.\nEither the response column or one of the predictor columns contain no numeric values.")
|
|
set_default_mode(BASIC_CONVERSION)
|
|
|
|
summary = r.summary(full)
|
|
fullr2 = summary.get('r.squared','NA')
|
|
|
|
if fullr2 == 'NA':
|
|
stop_error("Error in linear regression")
|
|
|
|
if len(x_vals) < 10:
|
|
s = ""
|
|
for ch in range(len(x_vals)):
|
|
s += str(ch)
|
|
else:
|
|
stop_err("This tool only works with less than 10 predictors.")
|
|
|
|
print >>fout, "#Model\tR-sq\tRCVE_Terms\tRCVE_Value"
|
|
all_combos = sorted(sscombs(s), key=len)
|
|
all_combos.reverse()
|
|
for j,cols in enumerate(all_combos):
|
|
#if len(cols) == len(s): #Same as the full model above
|
|
# continue
|
|
if len(cols) == 1:
|
|
x_vals1 = x_vals[int(cols)]
|
|
else:
|
|
x_v = []
|
|
for col in cols:
|
|
x_v.append(x_vals[int(col)])
|
|
x_vals1 = numpy.asarray(x_v).transpose()
|
|
dat= r.list(x=array(x_vals1), y=y_vals)
|
|
set_default_mode(NO_CONVERSION)
|
|
red = r.lm(r("y ~ x"), data= dat) #Reduced model
|
|
set_default_mode(BASIC_CONVERSION)
|
|
summary = r.summary(red)
|
|
redr2 = summary.get('r.squared','NA')
|
|
try:
|
|
rcve = (float(fullr2)-float(redr2))/float(fullr2)
|
|
except:
|
|
rcve = 'NA'
|
|
col_str = ""
|
|
for col in cols:
|
|
col_str = col_str + str(int(x_cols[int(col)]) + 1) + " "
|
|
col_str.strip()
|
|
rcve_col_str = ""
|
|
for col in s:
|
|
if col not in cols:
|
|
rcve_col_str = rcve_col_str + str(int(x_cols[int(col)]) + 1) + " "
|
|
rcve_col_str.strip()
|
|
if len(cols) == len(s): #full model
|
|
rcve_col_str = "-"
|
|
rcve = "-"
|
|
try:
|
|
redr2 = "%.4f" %(float(redr2))
|
|
except:
|
|
pass
|
|
try:
|
|
rcve = "%.4f" %(float(rcve))
|
|
except:
|
|
pass
|
|
print >>fout, "%s\t%s\t%s\t%s" %(col_str,redr2,rcve_col_str,rcve)
|