comparison hetbox.py @ 2:3a1ce69571e5 draft

Allow commented lines, de-kludge data frame handling

1:a85dd9968af9

#!/usr/bin/env python

import os,sys,numpy
from rpy2.robjects import Formula
from rpy2.robjects.packages import importr
from rpy2 import robjects

if len(args) >= 3:
  report = args[2]
elif make_report:
  fail('Error: No output report filename provided (as argument 3).')

if not os.path.exists(infile):
  fail('Error: Input file '+infile+' could not be found.')


utils     = importr('utils')
graphics  = importr('graphics')
base      = importr('base')

grdevices = importr('grDevices')
grdevices.png(file=outfile, width=1024, height=768)

# Read file into a data frame
DATA    = utils.read_delim(infile)
# Multiply minor allele frequencies by 100 to get percentage
# Doing this in R, since I can't find a way to modify a column in a data frame
# in rpy2
robjects.r.assign('data', DATA)
robjects.r('data$MINOR.FREQ.PERC. = data$MINOR.FREQ.PERC. * 100')
DATA = robjects.r('data')
#index = data.names.index('MINOR.FREQ.PERC.')
##  .ro turns the returned object into one that can be operated on per-element
#DATA.rx2('MINOR.FREQ.PERC.') = DATA.rx('MINOR.FREQ.PERC.').ro * 100
# Formula() creates a Python object representing the R object returned by x ~ y
formula = Formula('MINOR.FREQ.PERC.~SAMPLE')
# The "environment" in .getenvironment() is the entire R workspace in which the
# Formula object exists. The R workspace meaning all the defined variables.
# Here, the .getenvironment() method is being used to set some variables in the
# R workspace
#   Note: .rx2() looks up a column by its label and returns it as a vector
formula.getenvironment()['MINOR.FREQ.PERC.'] = DATA.rx2('MINOR.FREQ.PERC.')
formula.getenvironment()['SAMPLE']           = DATA.rx2('SAMPLE')

# create boxplot - fill kwargs1 with the options for the boxplot function
kwargs1 = {'ylab':"Minor allele frequency (%)",'col':"gray", 'xaxt':"n", 'outpch':"*",'main':"Distribution of minor allele frequencies >= 2%", 'cex.lab':"1.5"}
p = graphics.boxplot(formula, **kwargs1)

tab    = base.table(DATA.rx2('SAMPLE'))
graphics.text(0.5,1,'N:',font=2)
for i in range(1,base.length(tab)[0]+1,1):
    graphics.text(i,1,tab[i-1], font=2)

graphlabels = base.names(tab)
kwargs3 = {'pos':"0", 'las':"2", 'cex.axis':"1"}
graphics.axis(1, at=range(1,len(graphlabels)+1,1),labels=graphlabels, **kwargs3)
grdevices.dev_off()

if not make_report:
  sys.exit(0)

####################################
# GENERATE REPORT
# report should be something like:
# SAMPLE NoHET MEDIAN MAD TEST 

2:3a1ce69571e5

#!/usr/bin/env python
# New in this version:
# - handle commented-out header lines
# - did everything through the Rpy2 interface instead of inline R code

import os,sys,numpy
from rpy2.robjects import Formula
from rpy2.robjects.packages import importr
from rpy2 import robjects

if len(args) >= 3:
  report = args[2]
elif make_report:
  fail('Error: No output report filename provided (as argument 3).')

# Check input file
if not os.path.exists(infile):
  fail('Error: Input file '+infile+' could not be found.')
with open(infile, 'r') as lines:
  line = lines.readline()
  if not line:
    fail('Error: Input file seems to be empty')
  line = line.strip().lstrip('#') # rm whitespace, comment chars
  labels = line.split("\t")
  if 'SAMPLE' not in labels or labels[11] != 'MINOR.FREQ.PERC.':
    fail('Error: Input file does not seem to have a proper header line.')


utils     = importr('utils')
graphics  = importr('graphics')
base      = importr('base')

grdevices = importr('grDevices')
grdevices.png(file=outfile, width=1024, height=768)

# Read file into a data frame
DATA    = utils.read_delim(infile)
# Remove comment from header, if 
labels = robjects.r.names(DATA)
if labels[0][0:2] == 'X.':
  labels[0] = labels[0][2:]
#robjects.r.assign('data', DATA)
#robjects.r('data$MINOR.FREQ.PERC. = data$MINOR.FREQ.PERC. * 100')
#DATA = robjects.r('data')
#index = data.names.index('MINOR.FREQ.PERC.')
# Multiply minor allele frequencies by 100 to get percentage
#  .rx2() looks up a column by its label and returns it as a vector
#  .ro turns the returned object into one that can be operated on per-element
minor_freq = DATA.rx2('MINOR.FREQ.PERC.').ro * 100
samples    = DATA.rx2('SAMPLE')
# Formula() creates a Python object representing the R object returned by x ~ y
formula = Formula('minor_freq ~ samples')
# The "environment" in .getenvironment() is the entire R workspace in which the
# Formula object exists. The R workspace meaning all the defined variables.
# Here, the .getenvironment() method is being used to set some variables in the
# R workspace
formula.getenvironment()['minor_freq'] = minor_freq
formula.getenvironment()['samples']    = samples

# create boxplot - fill kwargs1 with the options for the boxplot function
kwargs1 = {'ylab':"Minor allele frequency (%)", 'col':"gray", 'xaxt':"n", 'outpch':"*",'main':"Distribution of minor allele frequencies >= 2%", 'cex.lab':"1.5"}
p = graphics.boxplot(formula, **kwargs1)

table  = base.table(DATA.rx2('SAMPLE'))
graphics.text(0.5, 1, 'N:', font=2)
for i in range(1, base.length(table)[0]+1, 1):
    graphics.text(i, 1, table[i-1], font=2)

graphlabels = base.names(table)
kwargs3 = {'pos':"0", 'las':"2", 'cex.axis':"1"}
graphics.axis(1, at=range(1, len(graphlabels)+1, 1), labels=graphlabels, **kwargs3)
grdevices.dev_off()

if not make_report:
  sys.exit(0)


####################################
# GENERATE REPORT
# report should be something like:
# SAMPLE NoHET MEDIAN MAD TEST