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-rw-r--r--wqflask/wqflask/wgcna/wgcna_analysis.py37
1 files changed, 33 insertions, 4 deletions
diff --git a/wqflask/wqflask/wgcna/wgcna_analysis.py b/wqflask/wqflask/wgcna/wgcna_analysis.py
index 5316fcd4..74bb6f8e 100644
--- a/wqflask/wqflask/wgcna/wgcna_analysis.py
+++ b/wqflask/wqflask/wgcna/wgcna_analysis.py
@@ -6,6 +6,11 @@ import scipy as sp # SciPy
import rpy2.robjects as ro # R Objects
import rpy2.rinterface as ri
+from base import webqtlConfig # For paths and stuff
+
+import base64
+import array
+
from utility import helper_functions
from rpy2.robjects.packages import importr
@@ -22,8 +27,8 @@ r_paste = ro.r["paste"] # Map the paste function
r_unlist = ro.r["unlist"] # Map the unlist function
r_unique = ro.r["unique"] # Map the unique function
r_length = ro.r["length"] # Map the length function
-r_matrix = ro.r["matrix"] # Map the matrix function
-r_list = ro.r["list"] # Map the list function
+r_list = ro.r.list # Map the list function
+r_matrix = ro.r.matrix # Map the matrix function
r_seq = ro.r["seq"] # Map the seq function
r_table = ro.r["table"] # Map the table function
r_names = ro.r["names"] # Map the names function
@@ -82,19 +87,43 @@ class WGCNA(object):
print(trait, strain, " in python: ", self.input[trait].get(strain), "in R:", rM.rx(strain,trait)[0])
sys.stdout.flush()
- # TODO:
+ # TODO: Get the user specified parameters
+
self.results = {}
# Calculate a good soft threshold
+ powers = r_c(r_c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10), r_seq(12, 20, 2))
+ sft = self.r_pickSoftThreshold(rM, powerVector = powers, verbose = 5)
+
# Create block wise modules using WGCNA
+ network = self.r_blockwiseModules(rM, power = 6, verbose = 3)
+
+ self.results['network'] = network
+
# How many modules and how many gene per module ?
- # Show the iconic WCGNA plot of the modules in the hanging tree
+ print(r_table(network[1]))
+
+ # The iconic WCGNA plot of the modules in the hanging tree
+ self.results['imgurl'] = webqtlConfig.TMPDIR + "WGCNAoutput.png"
+ r_png(self.results['imgurl'])
+ mergedColors = self.r_labels2colors(network[1])
+ self.r_plotDendroAndColors(network[5][0], mergedColors, "Module colors",dendroLabels = False, hang = 0.03, addGuide = True, guideHang = 0.05)
+ r_dev_off()
sys.stdout.flush()
+ def render_image(self, results):
+ print("pre-loading imgage results:", self.results['imgurl'])
+ imgfile = open(self.results['imgurl'], 'rb')
+ imgdata = imgfile.read()
+ imgB64 = imgdata.encode("base64")
+ bytesarray = array.array('B', imgB64)
+ self.results['imgdata'] = bytesarray
+
def process_results(self, results):
print("Processing WGCNA output")
template_vars = {}
template_vars["input"] = self.input
template_vars["results"] = self.results
+ self.render_image(results)
#r_sink(type = "message") # This restores R output to the stdout/stderr
#r_sink() # We should end the Rpy session more or less
return(dict(template_vars))