Just committing a few additions to the interval mapping code

1 files changed, 161 insertions, 209 deletions

diff --git a/wqflask/wqflask/interval_mapping/interval_mapping.py b/wqflask/wqflask/interval_mapping/interval_mapping.py
index 3ec08f6b..48e8018e 100644
--- a/wqflask/wqflask/interval_mapping/interval_mapping.py
+++ b/wqflask/wqflask/interval_mapping/interval_mapping.py
@@ -52,7 +52,7 @@ class IntervalMapping(object):
  
         self.set_options(start_vars)
  
-        self.gen_data(tempdata)
+        self.gen_qtl_results(tempdata)
 
         #Get chromosome lengths for drawing the interval map plot
         chromosome_mb_lengths = {}
@@ -60,217 +60,11 @@ class IntervalMapping(object):
             chromosome_mb_lengths[key] = self.species.chromosomes.chromosomes[key].mb_length
         
         self.js_data = dict(
+            lrs_lod = self.lrs_lod,
             chromosomes = chromosome_mb_lengths,
             qtl_results = self.qtl_results,
         )
 
-    def get_qtl_results(self):
-        """Gets the LOD (or LRS) score at each marker in order do the qtl mapping"""
-        
-        
-        #INTERCROSS = (self.genotype.type=="intercross")
-
-        #THESE ARE OLD COMMENTS
-        #draw the LRS scale
-        #We first determine whether or not we are using a sliding scale.
-        #If so, we need to compute the maximum LRS value to determine where the max y-value should be, and call this LRSMax.
-        #LRSTop is then defined to be above the LRSMax by enough to add one additional LRSScale increment.
-        #if we are using a set-scale, then we set LRSTop to be the user's value, and LRSMax doesn't matter.
-    
-        #if self.lrs_lod == 'LOD':
-        #    lodm = self.LODFACTOR
-        #else:
-        #    lodm = 1.0
-                
-        if self.lrsMax <= 0:  #sliding scale
-            LRSMax = max(map(max, self.qtlresults)).lrs
-            #genotype trait will give infinite LRS
-            LRSMax = min(LRSMax, webqtlConfig.MAXLRS)
-            if self.permChecked and not self.multipleInterval:
-                self.significance = min(self.significance, webqtlConfig.MAXLRS)
-                self.suggestive = min(self.suggestive, webqtlConfig.MAXLRS)
-                LRSMax = max(self.significance, LRSMax)
-        else:
-            LRSMax = self.lrsMax*lodm
-            
-        if LRSMax/lodm > 100:
-            LRSScale = 20.0
-        elif LRSMax/lodm > 20:
-            LRSScale = 5.0
-        elif LRSMax/lodm > 7.5:
-            LRSScale = 2.5
-        else:
-            LRSScale = 1.0
-    
-        LRSAxisList = Plot.frange(LRSScale, LRSMax/lodm, LRSScale)
-        #make sure the user's value appears on the y-axis
-        #update by NL 6-21-2011: round the LOD value to 100 when LRSMax is equal to 460
-        LRSAxisList.append(round(LRSMax/lodm)) 
-    
-        #draw the "LRS" or "LOD" string to the left of the axis
-        LRSScaleFont=pid.Font(ttf="verdana", size=14*fontZoom, bold=0)
-        LRSLODFont=pid.Font(ttf="verdana", size=14*zoom*1.5, bold=0)
-        yZero = yTopOffset + plotHeight
-        
-    
-        canvas.drawString(self.LRS_LOD, xLeftOffset - canvas.stringWidth("999.99", font=LRSScaleFont) - 10*zoom, \
-                          yZero - 150, font=LRSLODFont, color=pid.black, angle=90)
-                        
-        for item in LRSAxisList:
-            yLRS = yZero - (item*lodm/LRSMax) * LRSHeightThresh
-            canvas.drawLine(xLeftOffset, yLRS, xLeftOffset - 4, yLRS, color=self.LRS_COLOR, width=1*zoom)
-            scaleStr = "%2.1f" % item
-            canvas.drawString(scaleStr, xLeftOffset-4-canvas.stringWidth(scaleStr, font=LRSScaleFont)-5, yLRS+3, font=LRSScaleFont, color=self.LRS_COLOR)
-    
-    
-        #"Significant" and "Suggestive" Drawing Routine
-        # ======= Draw the thick lines for "Significant" and "Suggestive" =====  (crowell: I tried to make the SNPs draw over these lines, but piddle wouldn't have it...)
-        if self.permChecked and not self.multipleInterval:
-            significantY = yZero - self.significance*LRSHeightThresh/LRSMax
-            suggestiveY = yZero - self.suggestive*LRSHeightThresh/LRSMax
-            startPosX = xLeftOffset
-            for i, _chr in enumerate(self.genotype):
-                rightEdge = int(startPosX + self.ChrLengthDistList[i]*plotXScale - self.SUGGESTIVE_WIDTH/1.5)
-                canvas.drawLine(startPosX+self.SUGGESTIVE_WIDTH/1.5, suggestiveY, rightEdge, suggestiveY, color=self.SUGGESTIVE_COLOR,
-                    width=self.SUGGESTIVE_WIDTH*zoom, clipX=(xLeftOffset, xLeftOffset + plotWidth-2))
-                canvas.drawLine(startPosX+self.SUGGESTIVE_WIDTH/1.5, significantY, rightEdge, significantY, color=self.SIGNIFICANT_COLOR, 
-                    width=self.SIGNIFICANT_WIDTH*zoom, clipX=(xLeftOffset, xLeftOffset + plotWidth-2))
-                sugg_coords = "%d, %d, %d, %d" % (startPosX, suggestiveY-2, rightEdge + 2*zoom, suggestiveY+2)
-                sig_coords = "%d, %d, %d, %d" % (startPosX, significantY-2, rightEdge + 2*zoom, significantY+2)
-                if self.LRS_LOD == 'LRS':
-                    sugg_title = "Suggestive LRS = %0.2f" % self.suggestive
-                    sig_title = "Significant LRS = %0.2f" % self.significance
-                else:
-                    sugg_title = "Suggestive LOD = %0.2f" % (self.suggestive/4.61)
-                    sig_title = "Significant LOD = %0.2f" % (self.significance/4.61)
-                Areas1 = HT.Area(shape='rect',coords=sugg_coords,title=sugg_title)
-                Areas2 = HT.Area(shape='rect',coords=sig_coords,title=sig_title)
-                gifmap.areas.append(Areas1)
-                gifmap.areas.append(Areas2)
-    
-                startPosX +=  (self.ChrLengthDistList[i]+self.GraphInterval)*plotXScale
-    
-    
-        if self.multipleInterval:
-            lrsEdgeWidth = 1
-        else:
-            additiveMax = max(map(lambda X : abs(X.additive), self.qtlresults[0]))
-            if INTERCROSS:
-                dominanceMax = max(map(lambda X : abs(X.dominance), self.qtlresults[0]))
-            else:
-                dominanceMax = -1
-            lrsEdgeWidth = 2
-        for i, qtlresult in enumerate(self.qtlresults):
-            m = 0
-            startPosX = xLeftOffset
-            thisLRSColor = self.colorCollection[i]
-            for j, _chr in enumerate(self.genotype):
-                LRSCoordXY = []
-                AdditiveCoordXY = []
-                DominanceCoordXY = []
-                for k, _locus in enumerate(_chr):
-                    if self.plotScale == 'physic':
-                        Xc = startPosX + (_locus.Mb-startMb)*plotXScale
-                    else:
-                        Xc = startPosX + (_locus.cM-_chr[0].cM)*plotXScale
-                    # updated by NL 06-18-2011: 
-                    # fix the over limit LRS graph issue since genotype trait may give infinite LRS;
-                    # for any lrs is over than 460(LRS max in this system), it will be reset to 460
-                    if 	qtlresult[m].lrs> 460 or qtlresult[m].lrs=='inf':
-                        Yc = yZero - webqtlConfig.MAXLRS*LRSHeightThresh/LRSMax
-                    else:	
-                        Yc = yZero - qtlresult[m].lrs*LRSHeightThresh/LRSMax						
-    
-                    LRSCoordXY.append((Xc, Yc))
-                    if not self.multipleInterval and self.additiveChecked:
-                        Yc = yZero - qtlresult[m].additive*AdditiveHeightThresh/additiveMax
-                        AdditiveCoordXY.append((Xc, Yc))
-                    if not self.multipleInterval and INTERCROSS and self.additiveChecked:
-                        Yc = yZero - qtlresult[m].dominance*DominanceHeightThresh/dominanceMax
-                        DominanceCoordXY.append((Xc, Yc))
-                    m += 1
-                canvas.drawPolygon(LRSCoordXY,edgeColor=thisLRSColor,closed=0, edgeWidth=lrsEdgeWidth, clipX=(xLeftOffset, xLeftOffset + plotWidth))
-                if not self.multipleInterval and self.additiveChecked:
-                    plusColor = self.ADDITIVE_COLOR_POSITIVE
-                    minusColor = self.ADDITIVE_COLOR_NEGATIVE
-                    for k, aPoint in enumerate(AdditiveCoordXY):
-                        if k > 0:
-                            Xc0, Yc0 = AdditiveCoordXY[k-1]
-                            Xc, Yc = aPoint
-                            if (Yc0-yZero)*(Yc-yZero) < 0:
-                                if Xc == Xc0: #genotype , locus distance is 0
-                                    Xcm = Xc
-                                else:	
-                                    Xcm = (yZero-Yc0)/((Yc-Yc0)/(Xc-Xc0)) +Xc0
-                                if Yc0 < yZero:
-                                    canvas.drawLine(Xc0, Yc0, Xcm, yZero, color=plusColor, width=1, clipX=(xLeftOffset, xLeftOffset + plotWidth))
-                                    canvas.drawLine(Xcm, yZero, Xc, yZero-(Yc-yZero), color=minusColor, width=1, clipX=(xLeftOffset, xLeftOffset + plotWidth))
-                                else:
-                                    canvas.drawLine(Xc0, yZero - (Yc0-yZero), Xcm, yZero, color=minusColor, width=1, clipX=(xLeftOffset, xLeftOffset + plotWidth))
-                                    canvas.drawLine(Xcm, yZero, Xc, Yc, color=plusColor, width=1, clipX=(xLeftOffset, xLeftOffset + plotWidth))
-                            elif (Yc0-yZero)*(Yc-yZero) > 0:
-                                if Yc < yZero:
-                                    canvas.drawLine(Xc0, Yc0, Xc, Yc, color=plusColor, width=1, clipX=(xLeftOffset, xLeftOffset + plotWidth))
-                                else:
-                                    canvas.drawLine(Xc0, yZero - (Yc0-yZero), Xc, yZero - (Yc-yZero), color=minusColor, width=1, clipX=(xLeftOffset, xLeftOffset + plotWidth))
-                            else:
-                                minYc = min(Yc-yZero, Yc0-yZero)
-                                if minYc < 0:
-                                    canvas.drawLine(Xc0, Yc0, Xc, Yc, color=plusColor, width=1, clipX=(xLeftOffset, xLeftOffset + plotWidth))
-                                else:
-                                    canvas.drawLine(Xc0, yZero - (Yc0-yZero), Xc, yZero - (Yc-yZero), color=minusColor, width=1, clipX=(xLeftOffset, xLeftOffset + plotWidth))
-                if not self.multipleInterval and INTERCROSS and self.dominanceChecked:
-                    plusColor = self.DOMINANCE_COLOR_POSITIVE
-                    minusColor = self.DOMINANCE_COLOR_NEGATIVE
-                    for k, aPoint in enumerate(DominanceCoordXY):
-                        if k > 0:
-                            Xc0, Yc0 = DominanceCoordXY[k-1]
-                            Xc, Yc = aPoint
-                            if (Yc0-yZero)*(Yc-yZero) < 0:
-                                if Xc == Xc0: #genotype , locus distance is 0
-                                    Xcm = Xc
-                                else:	
-                                    Xcm = (yZero-Yc0)/((Yc-Yc0)/(Xc-Xc0)) +Xc0
-                                if Yc0 < yZero:
-                                    canvas.drawLine(Xc0, Yc0, Xcm, yZero, color=plusColor, width=1, clipX=(xLeftOffset, xLeftOffset + plotWidth))
-                                    canvas.drawLine(Xcm, yZero, Xc, yZero-(Yc-yZero), color=minusColor, width=1, clipX=(xLeftOffset, xLeftOffset + plotWidth))
-                                else:
-                                    canvas.drawLine(Xc0, yZero - (Yc0-yZero), Xcm, yZero, color=minusColor, width=1, clipX=(xLeftOffset, xLeftOffset + plotWidth))
-                                    canvas.drawLine(Xcm, yZero, Xc, Yc, color=plusColor, width=1, clipX=(xLeftOffset, xLeftOffset + plotWidth))
-                            elif (Yc0-yZero)*(Yc-yZero) > 0:
-                                if Yc < yZero:
-                                    canvas.drawLine(Xc0, Yc0, Xc, Yc, color=plusColor, width=1, clipX=(xLeftOffset, xLeftOffset + plotWidth))
-                                else:
-                                    canvas.drawLine(Xc0, yZero - (Yc0-yZero), Xc, yZero - (Yc-yZero), color=minusColor, width=1, clipX=(xLeftOffset, xLeftOffset + plotWidth))
-                            else:
-                                minYc = min(Yc-yZero, Yc0-yZero)
-                                if minYc < 0:
-                                    canvas.drawLine(Xc0, Yc0, Xc, Yc, color=plusColor, width=1, clipX=(xLeftOffset, xLeftOffset + plotWidth))
-                                else:
-                                    canvas.drawLine(Xc0, yZero - (Yc0-yZero), Xc, yZero - (Yc-yZero), color=minusColor, width=1, clipX=(xLeftOffset, xLeftOffset + plotWidth))
-                startPosX +=  (self.ChrLengthDistList[j]+self.GraphInterval)*plotXScale
-        
-        ###draw additive scale
-        if not self.multipleInterval and self.additiveChecked:
-            additiveScaleFont=pid.Font(ttf="verdana",size=12*fontZoom,bold=0)
-            additiveScale = Plot.detScaleOld(0,additiveMax)
-            additiveStep = (additiveScale[1]-additiveScale[0])/additiveScale[2]
-            additiveAxisList = Plot.frange(0, additiveScale[1], additiveStep)
-            maxAdd =  additiveScale[1]
-            addPlotScale = AdditiveHeightThresh/additiveMax
-            
-            additiveAxisList.append(additiveScale[1])
-            for item in additiveAxisList:
-                additiveY = yZero - item*addPlotScale
-                canvas.drawLine(xLeftOffset + plotWidth,additiveY,xLeftOffset+4+ plotWidth,additiveY,color=self.ADDITIVE_COLOR_POSITIVE, width=1*zoom)
-                scaleStr = "%2.3f" % item
-                canvas.drawString(scaleStr,xLeftOffset + plotWidth +6,additiveY+5,font=additiveScaleFont,color=self.ADDITIVE_COLOR_POSITIVE)
-            
-            canvas.drawLine(xLeftOffset+plotWidth,additiveY,xLeftOffset+plotWidth,yZero,color=self.ADDITIVE_COLOR_POSITIVE, width=1*zoom)
-        
-        canvas.drawLine(xLeftOffset, yZero, xLeftOffset, yTopOffset, color=self.LRS_COLOR, width=1*zoom)  #the blue line running up the y axis
-
-
     def set_options(self, start_vars):
         """Sets various options (physical/genetic mapping, # permutations, which chromosome"""
         
@@ -281,6 +75,38 @@ class IntervalMapping(object):
         self.do_bootstrap = start_vars['do_bootstrap']
         self.control_locus = start_vars['control_locus']
         self.selected_chr = start_vars['selected_chr']
+        self.weighted_regression = start_vars['weighted']
+        self.lrs_lod = start_vars['lrs_lod']
+
+
+    def gen_qtl_results(self, tempdata):
+        """Generates qtl results for plotting interval map"""
+
+        self.dataset.group.get_markers()
+
+        pheno_vector = np.array([val == "x" and np.nan or float(val) for val in self.vals])
+
+        #if self.dataset.group.species == "human":
+        #    p_values, t_stats = self.gen_human_results(pheno_vector, tempdata)
+        #else:
+        genotype_data = [marker['genotypes'] for marker in self.dataset.group.markers.markers]
+        
+        no_val_samples = self.identify_empty_samples()
+        trimmed_genotype_data = self.trim_genotypes(genotype_data, no_val_samples)
+        
+        genotype_matrix = np.array(trimmed_genotype_data).T
+        
+        t_stats, p_values = lmm.run(
+            pheno_vector,
+            genotype_matrix,
+            restricted_max_likelihood=True,
+            refit=False,
+            temp_data=tempdata
+        )
+        
+        self.dataset.group.markers.add_pvalues(p_values)
+        
+        self.qtl_results = self.dataset.group.markers.markers
 
 
     def identify_empty_samples(self):
@@ -290,6 +116,7 @@ class IntervalMapping(object):
                 no_val_samples.append(sample_count)
         return no_val_samples
         
+        
     def trim_genotypes(self, genotype_data, no_value_samples):
         trimmed_genotype_data = []
         for marker in genotype_data:
@@ -304,4 +131,129 @@ class IntervalMapping(object):
                     pass
                 new_genotypes.append(genotype)
             trimmed_genotype_data.append(new_genotypes)
-        return trimmed_genotype_data
\ No newline at end of file
+        return trimmed_genotype_data
+
+    #def get_qtl_results(self):
+    #    """Gets the LOD (or LRS) score at each marker in order do the qtl mapping"""
+    #
+    #    
+    #    
+    #    #self.genotype = self.genotype.addinterval()
+    #    #resultSlice = []
+    #    #controlGeno = []
+    #    
+    #    #if self.multipleInterval:
+    #    #    self.suggestive = 0
+    #    #    self.significance = 0
+    #    #    if self.selectedChr > -1:
+    #    #        self.genotype.chromosome = [self.genotype[self.selectedChr]]
+    #    #else:
+    #    #single interval mapping
+    #    #try:
+    #    #    self.suggestive = float(fd.formdata.getvalue('permSuggestive'))
+    #    #    self.significance = float(fd.formdata.getvalue('permSignificance'))
+    #    #except:
+    #    #    self.suggestive = None
+    #    #    self.significance = None
+    #    
+    #    #NOT DOING MULTIPLE TRAITS YET, BUT WILL NEED TO LATER
+    #    #_strains, _vals, _vars = self.traitList[0].exportInformative(weightedRegression)
+    #    
+    #    #if webqtlUtil.ListNotNull(_vars):
+    #    #    pass
+    #    #else:
+    #    #    weightedRegression = 0
+    #    #    _strains, _vals, _vars = self.traitList[0].exportInformative()
+    #        
+    #    ##locate genotype of control Locus
+    #    #if self.controlLocus:
+    #    #    controlGeno2 = []
+    #    #    _FIND = 0
+    #    #    for _chr in self.genotype:
+    #    #        for _locus in _chr:
+    #    #            if _locus.name == self.controlLocus:
+    #    #                controlGeno2 = _locus.genotype
+    #    #                _FIND = 1
+    #    #                break
+    #    #        if _FIND:
+    #    #            break
+    #    #    if controlGeno2:
+    #    #        _prgy = list(self.genotype.prgy)
+    #    #        for _strain in _strains:
+    #    #            _idx = _prgy.index(_strain)
+    #    #            controlGeno.append(controlGeno2[_idx])
+    #    #    else:
+    #    #        return "The control marker you selected is not in the genofile."
+    #    #
+    #    #    
+    #    #    if self.significance and self.suggestive:
+    #    #        pass
+    #    #    else:
+    #    #        if self.permChecked:
+    #    #            if weightedRegression:
+    #    #                self.LRSArray = self.genotype.permutation(strains = _strains, trait = _vals, 
+    #    #                    variance = _vars, nperm=fd.nperm)
+    #    #            else:
+    #    #                self.LRSArray = self.genotype.permutation(strains = _strains, trait = _vals, 
+    #    #                    nperm=fd.nperm)
+    #    #            self.suggestive = self.LRSArray[int(fd.nperm*0.37-1)]
+    #    #            self.significance = self.LRSArray[int(fd.nperm*0.95-1)]
+    #    #
+    #    #        else:
+    #    #            self.suggestive = 9.2
+    #    #            self.significance = 16.1
+    #    #
+    #    #    #calculating bootstrap
+    #    #    #from now on, genotype could only contain a single chromosome 
+    #    #    #permutation need to be performed genome wide, this is not the case for bootstrap
+    #    #    
+    #    #    #due to the design of qtlreaper, composite regression need to be performed genome wide
+    #    #    if not self.controlLocus and self.selectedChr > -1:
+    #    #        self.genotype.chromosome = [self.genotype[self.selectedChr]]
+    #    #    elif self.selectedChr > -1: #self.controlLocus and self.selectedChr > -1
+    #    #        lociPerChr = map(len, self.genotype)
+    #    #        resultSlice = reduce(lambda X, Y: X+Y, lociPerChr[:self.selectedChr], 0)
+    #    #        resultSlice = [resultSlice,resultSlice+lociPerChr[self.selectedChr]]
+    #    #    else:
+    #    #        pass
+    #        
+    #    #calculate QTL for each trait
+    #    self.qtl_results = []
+    #
+    #    #for thisTrait in self.traitList:
+    #    _strains, _vals, _vars = thisTrait.exportInformative(weightedRegression)
+    #    if self.controlLocus:
+    #        if weightedRegression:
+    #            qtlresult = self.genotype.regression(strains = _strains, trait = _vals, 
+    #                    variance = _vars, control = self.controlLocus)
+    #        else:
+    #            qtlresult = self.genotype.regression(strains = _strains, trait = _vals,
+    #                control = self.controlLocus)
+    #        if resultSlice:
+    #            qtlresult = qtlresult[resultSlice[0]:resultSlice[1]]
+    #    else:
+    #        if weightedRegression:
+    #            qtlresult = self.genotype.regression(strains = _strains, trait = _vals, 
+    #                    variance = _vars)
+    #        else:
+    #            qtlresult = self.genotype.regression(strains = _strains, trait = _vals)
+    #
+    #    self.qtlresults.append(qtlresult)
+    #    
+    #    if not self.multipleInterval:
+    #        if self.controlLocus and self.selectedChr > -1:
+    #            self.genotype.chromosome = [self.genotype[self.selectedChr]]
+    #            
+    #        if self.bootChecked:
+    #            if controlGeno:
+    #                self.bootResult = self.genotype.bootstrap(strains = _strains, trait = _vals,
+    #                    control = controlGeno, nboot=fd.nboot)
+    #            elif weightedRegression:
+    #                self.bootResult = self.genotype.bootstrap(strains = _strains, trait = _vals, 
+    #                    variance = _vars, nboot=fd.nboot)
+    #            else:
+    #                self.bootResult = self.genotype.bootstrap(strains = _strains, trait = _vals, 
+    #                    nboot=fd.nboot)
+    #        else:
+    #            self.bootResult = []
+