Working PheWAS in GN2, only for chromosome 1 on 25 megabases, but it's a start

2 files changed, 38 insertions, 9 deletions

diff --git a/wqflask/wqflask/auwerx/phewas_analysis.py b/wqflask/wqflask/auwerx/phewas_analysis.py
index 061d2bc8..db12ad98 100644
--- a/wqflask/wqflask/auwerx/phewas_analysis.py
+++ b/wqflask/wqflask/auwerx/phewas_analysis.py
@@ -23,24 +23,24 @@ from utility.tools import locate
 
 r_library       = ro.r["library"]             # Map the library function
 r_options       = ro.r["options"]             # Map the options function
-r_load          = ro.r["load"]                # Map the load function
 r_write_table   = ro.r["write.table"]         # Map the write.table function
 r_head          = ro.r["head"]                # Map the head function
+r_load          = ro.r["load"]                # Map the head function
 r_colnames      = ro.r["colnames"]            # Map the colnames function
 r_list          = ro.r["list"]                # Map the list function
 r_c             = ro.r["c"]                   # Map the c (combine) function
-r_rep           = ro.r["rep"]                 # Map the rep (repeat) function
+r_seq           = ro.r["seq"]                 # Map the rep (repeat) function
 
 class PheWAS(object):
     def __init__(self):
         print("Initialization of PheWAS")
         # TODO: Loading the package should only be done once, since it is quite expensive
         print(r_library("auwerx"))                                                         # Load the auwerx package
-        self.r_download_BXD_geno = ro.r["download.BXD.geno"]                               # Map the create.Pheno_aligner function
         self.r_create_Pheno_aligner = ro.r["create.Pheno_aligner"]                         # Map the create.Pheno_aligner function
-        self.r_create_SNP_aligner = ro.r["create.SNP_aligner"]                             # Map the create.SNP_aligner function
         self.r_calculate_all_pvalue_parallel = ro.r["calculate.all.pvalue.parallel"]       # Map the calculate.all.pvalue.parallel function
         self.r_PheWASManhattan = ro.r["PheWASManhattan"]                                   # Map the PheWASManhattan function
+        self.r_Stop = ro.r["throwStopError"]                                   # Map the PheWASManhattan function
+        self.r_PyLoadData    = ro.r["PyLoadData"]          # Map the load function
         print("Initialization of PheWAS done !")
 
     def run_analysis(self, requestform):
@@ -56,23 +56,46 @@ class PheWAS(object):
           snpinfo.append(marker["chr"]);
           snpinfo.append(marker["Mb"]);
 
-        rnames = r_rep(1, len(parser.markers))
+        rnames = r_seq(1, len(parser.markers))
         # Create the snp aligner object out of the BXD genotypes
         snpaligner = ro.r.matrix(snpinfo, nrow=len(parser.markers), dimnames = r_list(rnames, r_c("SNP", "Chr", "Pos")), ncol = 3, byrow=True)
+        r_write_table(snpaligner, "~/snpaligner_GN2.txt", row_names=False)
+
         # Create the phenotype aligner object using R
         phenoaligner = self.r_create_Pheno_aligner()
 
-        r_load(precompfilelocation)                 # Load the pre-computed EMMA results into R
-        allpvalues = ro.r['pval_all']               # Get a pointer to the pre-computed results
+        #r_load(precompfilelocation)                 # Load the pre-computed EMMA results into R
+        #allpvalues = ro.r['pval_small']               # Get a pointer to the pre-computed results
 
+        self.results = {}
+        self.results['imgurl1'] = webqtlUtil.genRandStr("phewas_") + ".png"
+        self.results['imgloc1'] = GENERATED_IMAGE_DIR + self.results['imgurl1']
+        print("IMAGE AT:", self.results['imgurl1'] )
+        print("IMAGE AT:", self.results['imgloc1'] )
         # Create the PheWAS plot (The gene/probe name, chromosome and gene/probe positions should come from the user input)
         # TODO: generate the PDF in the temp folder, with a unique name
-        self.r_PheWASManhattan("1:25", allpvalues, phenoaligner, snpaligner, "1:25", 1, 25, 25 )
+        self.r_PheWASManhattan("Test", precompfilelocation, phenoaligner, snpaligner, "None", 1, 25, 25, self.results['imgloc1'] )
+        #self.r_PheWASManhattan(allpvalues)
+        #self.r_Stop()
+
         print("Initialization of PheWAS done !")
 
+    def loadImage(self, path, name):
+        print("pre-loading imgage results:", self.results[path])
+        imgfile = open(self.results[path], 'rb')
+        imgdata = imgfile.read()
+        imgB64 = imgdata.encode("base64")
+        bytesarray = array.array('B', imgB64)
+        self.results[name] = bytesarray
+
+    def render_image(self, results):
+        self.loadImage("imgloc1", "imgdata1")
+
     def process_results(self, results):
         print("Processing PheWAS output")
         # TODO: get the PDF in the temp folder, and display it to the user
         template_vars = {}
+        template_vars["results"] = self.results
+        self.render_image(self.results)
         return(dict(template_vars))
 
diff --git a/wqflask/wqflask/templates/phewas_analysis.html b/wqflask/wqflask/templates/phewas_analysis.html
index 2b04d85b..f72564ae 100644
--- a/wqflask/wqflask/templates/phewas_analysis.html
+++ b/wqflask/wqflask/templates/phewas_analysis.html
@@ -4,6 +4,12 @@
 {% block content %} <!-- Start of body -->
 <div class="container">
   <h1>PheWAS analysis results</h1>
-  YAY ! We have our own route
+  YAY ! We have our own route<br>
+  <a href="/tmp/{{ results['imgurl1'] }}">
+      <img alt="Embedded Image" src="data:image/png;base64,
+      {% for elem in results['imgdata1'] -%}
+      {% print("%c"|format(elem)) %}
+      {%- endfor %}
+      " /></a>
 </div>
 {% endblock %}