saveName=None, yMax=yMax, figSize=figSize, median=median, legendLoc='upper left', legendCols=2, normProtein='BSubL24') num = ['AMP_L', 'AMP_U'] den = ['AMP_U', 'AMP_L', 'AMP_S'] filtPlots_45SPulse = plotDataSets(files45SPulse, names45SPulse, num, den, AllSubunits, '45S pulse', '[U+L]/[U+L+S]', reds, saveName=None, yMax=yMax, figSize=figSize, median=median, legendLoc='upper left', legendCols=2, normProtein='BSubL01') filtPlots_50SIF2Pulse = plotDataSets(files50SIF2Pulse, names50SIF2Pulse, num, den, AllSubunits, '50S IF2 pulse', '[U+L/[U+L+S]', blues, saveName=None, yMax=yMax, figSize=figSize, median=median, legendLoc='upper left', legendCols=2, normProtein='BSubL01') ##################Merge data########################### num = ['AMP_U'] den = ['AMP_U', 'AMP_S'] normProtein='BSubL24' merged45 = qMS.mergeFiles(files45S, num, den, normProtein) merged50 = qMS.mergeFiles(files50SIF2, num, den, normProtein) verifiedZero = ['BSubL16', 'BSubL28', 'BSubL36', 'BSubL31a'] for i in verifiedZero: merged45[i] = numpy.array([0.0]) ##################Plot protein inventory data########################### myPlot = vizLib.plotStatsDict(merged45, name='45SMerged', proteins=LargeSubunit, offset=0.4, markerSize=12, color='#e31a1c', yMax = 1.5, median=False) myPlot = vizLib.addStatsDictToPlot(merged50, myPlot, name='50SMerged', offset=0.6, markerSize=12, color='#377db8', median=False) myPlot.set_ylabel('protein occupancy\nnormalized to L24', multialignment='center') myPlot.set_title('protein occupancy 45S vs. 50S') pylab.legend(loc='lower left', prop={'size':12}) pylab.tight_layout() pylab.show('all')
proteinToNormalizeTo = "BSubL24" LargeSubunit = ['BSubL01', 'BSubL02', 'BSubL03', 'BSubL04', 'BSubL05', 'BSubL06', 'BSubL10', 'BSubL11', 'BSubL12', 'BSubL13', 'BSubL14', 'BSubL15', 'BSubL16', 'BSubL17', 'BSubL18', 'BSubL19', 'BSubL20', 'BSubL21', 'BSubL22', 'BSubL23', 'BSubL24', 'BSubL27', 'BSubL28', 'BSubL29', 'BSubL30', 'BSubL32', 'BSubL33a', 'BSubL35', 'BSubL36'] McMaster45S = [path+i for i in ["McMaster45S_esi-run1_filt.csv", "McMaster45S_esi-run2.1_filt.csv", "McMaster45S_esi-run2_filt.csv", "McMaster45S_qtof_filt_filtppm.csv"]] McMaster50S = [path+i for i in ["McMaster50S_esi-run1_filt.csv", "McMaster50S_esi-run2.1_filt.csv", "McMaster50S_esi-run2_filt.csv", "McMaster50S_qtof_filt_filtppm.csv"]] fileLists = [McMaster45S, McMaster50S] merged = [] for listOfFiles in fileLists: merged.append(qMS.mergeFiles(listOfFiles, pulse, numerator, denominator, proteinToNormalizeTo, LargeSubunit)) myPlot = qMS.makePlotWithDataSets(merged, LargeSubunit, ["McMaster45S_merged", 'McMaster50S_merged']) for i in LargeSubunit: pVal = stats.ttest_ind(merged[0][i]['vals'], merged[1][i]['vals'], equal_var=False) print merged[0]['BSubL02']['vals'] print merged[1]['BSubL20']['vals'] L30ttest = stats.ttest_ind(merged[0]['BSubL02']['vals'], merged[1]['BSubL02']['vals']) L12ttest = stats.ttest_ind(merged[0]['BSubL34']['vals'], merged[1]['BSubL34']['vals']) print L30ttest print L12ttest ##################Plot pool data vs. protein inventory data########################### ''' verifiedZero = ['BSubL16', 'BSubL28', 'BSubL36'] for z in verifiedZero: