Various comparisons used in the text

growthAnalysis/comps.py

+import common.lin as lin
+import grates as grs
+import patternTransitions as p
+import growth_control as gc
+import numpy as np
+from scipy.stats import ttest_ind
+
+
+def gratio(xs, xs1):
+     if not xs or not xs1:
+         return 0.0
+
+     m1 = np.median(xs)
+     m2 = np.median(xs1)
+
+     return (m1 - m2) / (m1 + m2)
+
+ 
+#load FM1 at specified timepoints
+tss, linss = lin.mkSeries1(d="../data/FM1/tv/",
+                           dExprs="../data/geneExpression/",
+                           linDataLoc="../data/FM1/tracking_data/",
+                           ft=lambda t: t in {10, 40, 96, 120, 132})
+lin.filterL1_st(tss)
+grates = grs.grates_avg_cons(tss, linss)
+grates_gene = p.getGAnisosPerGene(tss, grates)
+grates_st = gc.get_grs_state()
+
+
+rgd_g = {}
+for g in set(grates_gene.keys()).difference(set(['AHP6'])):
+    grs1 = grates_gene['AHP6']
+    grs2 = grates_gene[g]
+    _, pval = ttest_ind(grs1, grs2)
+    rgd_g[g] = (gratio(grs1, grs2),
+                pval)
+
+rgd_g_ = {}
+for g in set(grates_gene.keys()).difference(set(['CUC1_2_3'])):
+    grs1 = grates_gene['CUC1_2_3']
+    grs2 = grates_gene[g]
+    _, pval = ttest_ind(grs1, grs2)
+    rgd_g_[g] = (gratio(grs1, grs2),
+                 pval)
+
+rgd_st26 = {}
+for g in set(grates_st.keys()).difference(set([26, 27])):
+    grs1 = grates_st[26] + grates_st[27]
+    grs2 = grates_st[g]
+    _, pval = ttest_ind(grs1, grs2)
+    rgd_st26[g] = (gratio(grs1, grs2),
+                   pval)
+
+rgd_st16 = {}
+for g in set(grates_st.keys()).difference(set([16, 17])):
+    grs1 = grates_st[16] + grates_st[17]
+    grs2 = grates_st[g]
+    _, pval = ttest_ind(grs1, grs2)
+    rgd_st16[g] = (gratio(grs1, grs2),
+                   pval)
+
+
+t=132
+ts = tss[t]
+g = gc.GPairRegions(t, ts, 'ETTIN', 'STM')
+g1 = gc.GPairRegions(t, ts, 'AP1', 'LFY')
+
+g.plot_distr()
+g1.plot_distr()