Table 1

Statistical tests used to analyze data

FeatureComparisonData structure (D’Agostino normality test)Type of testSample size
(# of NMJs, # of animals)
MeanStatisticp ValueOutlier test
Structure
Bouton numberw1118 vs cowGDP/DfNormalUnpaired two-tailed t testw1118 (15,8); cow null (16,8)23.53 vs 41.13t = 8.296 df = 29p < 0.0001
Bouton numbervglut-GAL4 vs UAS-cow-RNAiNot normalKruskal–Wallis with Dunn's multiple-comparisons testvglut-GAL4 (16,8); UAS-Cow-RNAi (16,8)26.69 vs 28.8Mean rank diff = −2.938p > 0.9999
vglut-GAL4 vs vglut>cow-RNAivglut-GAL4 (16,8); vglut>cow-RNAi (15,8)26.69 vs 37.38Mean rank diff = −19.09p = 0.0002
UAS-cow-RNAi vs vglut>cow-RNAiUAS-cow-RNAi (16,8); vglut>cow-RNAi (15,8)28.8 vs 37.38Mean rank diff = −16.16p = 0.0031
Bouton number24B-GAL4 vs UAS-cow-RNAiNot normalKruskal–Wallis with Dunn's multiple-comparisons test24B-GAL4 (16,8); UAS-cow-RNAi (16,8)30.63 vs 31.5Mean rank diff = −6.188p = 0.6307
24B-GAL4 vs 24B>cow-RNAi24B-GAL4 (16,8); 24B>cow-RNAi (16,8)30.63 vs 28.06Mean rank diff = 3.563p > 0.9999
UAS-cow-RNAi vs 24B>cow-RNAiUAS-cow-RNAi (16,8); 24B>cow-RNAi (16,8)31.5 vs 28.06Mean rank diff = 9.75p = 0.1451
Bouton numbervglut/+ vs vglut>CowNormalUnpaired two-tailed t testvglut/+ (16,8); vglut>Cow (16,8)25.25 vs 27.06t = 1.122 df = 30p = 0.2706
Bouton number24B/+ vs 24B>CowNormalUnpaired two-tailed t test24B/+ (16,8); 24B>Cow (16,8)30.38 vs 29.81t = 0.2317 df = 30p = 0.8183
Bouton numberFRT-Wg vs FRT-Wg;CowGDPNot normalKruskal–Wallis with Dunn's multiple-comparisons testFRT-Wg (24,12); FRT-Wg;CowGDP (24,12)26.71 vs 31.71Mean rank diff = −22.29p = 0.0300
FRT-Wg vs NRT-WgFRT-Wg (24,12); NRT-Wg (24,12)26.71 vs 27.04Mean rank diff = −3.521p > 0.9999
FRT-Wg vs NRT-Wg;CowGDPFRT-Wg (24,12); NRT-Wg;CowGDP (23,12)26.71 vs 26.78Mean rank diff = 0.4312p > 0.9999
FRT-Wg;CowGDP vs NRT-WgFRT-Wg;CowGDP (24,12); NRT-Wg (24,12)31.71 vs 27.04Mean rank diff = 18.77p = 0.1085
FRT-Wg;CowGDP vs NRT-Wg;CowGDPFRT-Wg;CowGDP (24,12); NRT-Wg;CowGDP (23,12)31.71 vs 26.78Mean rank diff = 22.72p = 0.0278
NRT-Wg vs NRT-Wg;CowGDPNRT-Wg (24,12); NRT-Wg;CowGDP (23,12)27.04 vs 26.78Mean rank diff = 3.952p > 0.9999
Bouton numberw1118 vs cowGDP/+Not normalKruskal–Wallis with Dunn's multiple-comparisons testw1118 (15,8); cowGDP/+ (15,8)28.33 vs 35.73Mean rank diff = −15.93p = 0.0929
w1118 vs NotumKO/+w1118 (15,8); NotumKO/+ (16,8)28.33 vs30.75Mean rank diff = −5.565p > 0.9999
w1118 vs. cowGDP/NotumKOw1118 (15,8); cowGDP/NotumKO (16,8)28.33 vs 46.13Mean rank diff = −35.81p < 0.0001
cowGDP/+ vs NotumKO/+cowGDP/+ (15,8); NotumKO/+ (16,8)35.73 vs 30.75Mean rank diff = 10.37p = 0.6569
cowGDP/+ vs cowGDP/NotumKOcowGDP/+ (15,8); cowGDP/NotumKO (16,8)35.75 vs 46.13Mean rank diff = −19.88p = 0.0129
NotumKO/+ vs cowGDP/NotumKONotumKO/+ (16,8); cowGDP/NotumKO (16,8)30.75 vs 46.13Mean rank diff = −30.25p < 0.0001
Bouton numberw1118 vs cowGDP/cowGDPNormalOrdinary one-way ANOVA with Tukey's multiple-comparisons testw1118 (18,10); cowGDP/cowGDP (19,10)22.94 vs 33.74q = 9.731 df = 76p < 0.0001
w1118 vs NotumKO/NotumKOw1118 (18,10); NotumKO/NotumKO (20,10)22.94 vs 30.5q = 6.897 df = 76p < 0.0001
w1118 vs cowGDP,NotumKO/cowGDP,NotumKOw1118 (18,10); cowGDP,NotumKO/cowGDP,NotumKO (23,12)22.94 vs 29.13q = 5.83 df = 76p = 0.0005
cowGDP/cowGDP vs NotumKO/NotumKOcowGDP/cowGDP (19,10); NotumKO/NotumKO (20,10)33.74 vs 30.5q = 2.996 df = 76p = 0.1564
cowGDP/cowGDP vs cowGDP,NotumKO/cowGDP,NotumKOcowGDP/cowGDP (19,10); cowGDP,NotumKO/cowGDP,NotumKO (23,12)33.74 vs 29.13q = 4.407 df = 76p = 0.0135
NotumKO/NotumKO vs cowGDP,NotumKO/cowGDP,NotumKONotumKO/NotumKO (20,10); cowGDP,NotumKO/cowGDP,NotumKO (23,12)30.5 vs 29.13q = 1.328 df = 76p = 0.7838
% Satellite Boutonsw1118 vs cowGDP/DfNormalUnpaired two-tailed t testw1118 (15,8); cow null (15,8)3.301 vs 3.336%t = 0.03021 df = 28p = 0.9761ROUT, Q = 1%, removed 1 cowGDP/Df value
% Satellite boutonsvglut-GAL4/+ vs UAS-Cow-RNAi/+NormalOrdinary one-way ANOVA with Tukey's multiple-comparisons testvglut-GAL4/+ (16,8); UAS-Cow-RNAi/+ (15,8)2.895 vs 2.908%q = 0.016 df = 42p > 0.9999ROUT, iQ = 1%, removed 2 vglut>Cow-RNAi values
vglut-GAL4/+ vs vglut>Cow-RNAivglut-GAL4/+ (16,8); vglut>Cow-RNAi (14,8)2.895 vs 5.772%q = 3.309 df = 42p = 0.0612
UAS-Cow-RNAi/+ vs vglut>Cow-RNAiUAS-Cow-RNAi/+ (15,8); vglut>Cow-RNAi (14,8)2.908 vs 5.772%q = 3.244 df = 42p = 0.0677
% Satellite boutons24B-GAL4/+ vs UAS-Cow-RNAi/+Not normalKruskal–Wallis with Dunn's multiple-comparisons test24B-GAL4/+ (16,8); UAS-Cow-RNAi/+ (16,8)0.88 vs 2.381%Mean rank diff = −8.656p = 0.1328
24B-GAL4/+ vs 24B>cow-RNAi24B-GAL4/+ (16,8); 24B>cow-RNAi (16,8)0.88 vs 2.806%Mean rank diff = −8.969p = 0.1114
UAS-Cow-RNAi/+ vs 24B>cow-RNAiUAS-Cow-RNAi/+ (16,8): 24B>cow-RNAi (16,8)2.381 vs 2.806%Mean rank diff = −0.3125p > 0.9999
% Satellite boutonsvglut/+ vs vglut>CowNot normalMann–Whitney testvglut/+ (16,8); vglut>Cow (16,8)2.326 vs 7.121%U = 38p = 0.0003
% Satellite boutons24B/+ vs 24B>CowNormalUnpaired two-tailed t test24B/+ (16,8); 24B>Cow (16,8)3.164 vs 5.476%t = 1.177 df = 30p = 0.2486
% Satellite boutonsFRT-Wg vs FRT-Wg;CowGDPNot normalKruskal–Wallis with Dunn's multiple-comparisons testFRT-Wg (16,8); FRT-Wg;CowGDP (16,8)2.038 vs 1.002%Mean rank diff = 5.167p > 0.9999
FRT-Wg vs NRT-WgFRT-Wg (16,8); NRT-Wg (16,8)2.038 vs 8.304%Mean rank diff = −26.08p = 0.0021
FRT-Wg vs NRT-Wg;CowGDPFRT-Wg (16,8); NRT-Wg;CowGDP (16,8)2.038 vs 3.595%Mean rank diff = −5.452p > 0.9999
FRT-Wg;CowGDP vs NRT-WgFRT-Wg;CowGDP (16,8); NRT-Wg (16,8)1.002 vs 8.304%Mean rank diff = −31.25p = 0.0001
FRT-Wg;CowGDP vs NRT-Wg;CowGDPFRT-Wg;CowGDP (16,8); NRT-Wg;CowGDP (16,8)1.002 vs3.595%Mean rank diff = −10.62p > 0.9999
NRT-Wg vs NRT-Wg;CowGDPNRT-Wg (16,8); NRT-Wg;CowGDP (16,8)8.304 vs 3.595%Mean rank diff = 20.63p = 0.0038
% Satellite boutonsw1118 vs cowGDP/+Not normalKruskal–Wallis with Dunn's multiple-comparisons testw1118 (15,8); cowGDP/+ (15,8)1.89 vs 3.079%Mean rank diff = −7.867p > 0.9999
w1118 vs NotumKO/+w1118 (15,8); NotumKO/+ (16,8)1.89 vs 3.379%Mean rank diff = −10.95p = 0.4586
w1118 vs cowGDP/NotumKOw1118 (15,8); cowGDP/NotumKO (16,8)1.89 vs 3.337%Mean rank diff = −13.2p = 0.1961
cowGDP/+ vs NotumKO/+cowGDP/+ (15,8); NotumKO/+ (16,8)3.079 vs 3.379%Mean rank diff = −3.079p > 0.9999
cowGDP/+ vs cowGDP/NotumKOcowGDP/+ (15,8); cowGDP/NotumKO (16,8)3.079 vs 3.337%Mean rank diff = −5.329p > 0.9999
NotumKO/+ vs cowGDP/NotumKONotumKO/+ (16,8); cowGDP/NotumKO (16,8)3.379 vs 3.337%Mean rank diff = −2.25p > 0.9999
% Satellite boutonsw1118 vs cowGDP/cowGDPNot normalKruskal–Wallis with Dunn's multiple-comparisons testw1118 (18,10); cowGDP/cowGDP (19,10)1.904 vs 1.623%Mean rank diff = 2.006p > 0.9999
w1118 vs NotumKO/NotumKOw1118 (18,10); NotumKO/NotumKO (20,10)1.904 vs 2.443%Mean rank diff = −1.989p > 0.9999
w1118 vs cowGDP,NotumKO/cowGDP,NotumKOw1118 (18,10); cowGDP,NotumKO/cowGDP,NotumKO (23,12)1.904 vs 0.5223%Mean rank diff = 9.155p = 0.7029
cowGDP/cowGDP vs NotumKO/NotumKOcowGDP/cowGDP (19,10); NotumKO/NotumKO (20,10)1.623 vs 2.443%Mean rank diff = −3.995p > 0.9999
cowGDP/cowGDP vs cowGDP,NotumKO/cowGDP,NotumKOcowGDP/cowGDP (19,10); cowGDP,NotumKO/cowGDP,NotumKO (23,12)1.623 vs 0.5223%Mean rank diff = 7.149p > 0.9999
NotumKO/NotumKO vs cowGDP,NotumKO/cowGDP,NotumKONotumKO/NotumKO (20,10); cowGDP,NotumKO/cowGDP,NotumKO (23,12)2.443 vs 0.5223%Mean rank diff = 11.14p = 0.2978
Expression
Cow intensityvglut/+ vs vglut>CowNot normalMann–Whitney testvglut/+ (16,8); vglut>Cow (16,8)1 vs 3.035U = 0p < 0.0001
Cow intensity24B/+ vs 24B>CowNot normalMann–Whitney test24B/+ (16,8); 24B>Cow (16,8)1 vs 3.907U = 0p < 0.0001
Wg intensityvglut/+ vs vglut>CowNot normalMann–Whitney testvglut/+ (16,8); vglut>Cow (16,8)1 vs 0.6731U = 46p = 0.0014
Wg intensity24B/+ vs 24B>CowNormalUnpaired two-tailed t test24B/+ (16,8); 24B>Cow (16,8)1 vs 1.518t = 3.266 df = 30p = 0.0027
Wg intensityw1118 vs cowGDP/+NormalOrdinary one-way ANOVA with Tukey's multiple-comparisons testw1118 (15,8); cowGDP/+ (15,8)1 vs 0.885q = 1.328 df = 56p = 0.7840
w1118 vs NotumKO/+w1118 (15,8); NotumKO/+ (15,8)1 vs 1.095q = 1.094 df = 56p = 0.8660
w1118 vs cowGDP/NotumKOw1118 (15,8); cowGDP/NotumKO (15,8)1 vs 0.9014q = 1.139 df = 56p = 0.8515
cowGDP/+ vs NotumKO/+cowGDP/+ (15,8); NotumKO/+ (15,8)0.885 vs 1.095q = 2.422 df = 56p = 0.3268
cowGDP/+ vs cowGDP/NotumKOcowGDP/+ (15,8); cowGDP/NotumKO (15,8)0.885 vs 0.9014q = 0.1886 df = 56p = 0.9991
NotumKO/+ vs cowGDP/NotumKONotumKO/+ (15,8); cowGDP/NotumKO (15,8)1.095 vs 0.9014q = 2.234 df = 56p = 0.3985
Brp punctae numberw1118 vs cowGDPNormalUnpaired two-tailed t testw1118 (15,8); cowGDP (15,8)193.1 vs 284.8t = 6.152 df = 28p < 0.0001
Brp punctae Volumew1118 vs cowGDPNormalUnpaired two-tailed t testw1118 (15,8); cowGDP (15,8)0.8576 vs 0.7164 μm3 t = 3.429 df = 28p = 0.0019ROUT, Q = 1%, removed 1 cowGDP value
Brp punctae numberw1118 vs cowGDPNormalUnpaired two-tailed t testw1118 (11,8); cowGDP (10,8)298.6 vs 387.9t = 3.598 df = 19p = 0.0019
GluR cluster numberw1118 vs cowGDPNormalUnpaired two-tailed t testw1118 (11,8); cowGDP (9,6)382 vs 542.8t = 4.353 df = 18p = 0.0004
Function
EJC amplitudew1118 vs cowGDPNormalOrdinary one-way ANOVA with Tukey's multiple-comparisons testw1118 (26,20); cowGDP (20,18)171.6 vs 212.1 nAq = 3.868 df = 53p = 0.0227ROUT, Q = 1%, removed 1 cowGDP value
w1118 vs cowGDP/Dfw1118 (26,20); cowGDP/Df (10,9)171.6 vs 254.2 nAq = 4.197 df = 53p = 0.0123
cowGDP vs cowGDP/DfcowGDP (20,18); cowGDP/Df (10,9)212.1 vs 254.2 nAq = 1.063 df = 53p = 0.7341
EJC amplitudew1118 vs cowGDP/+NormalOrdinary one-way ANOVA with Tukey's multiple-comparisons testw1118 (10,6); cowGDP/+ (11,6)217.2 vs 234.9 nAq = 0.9383 df = 40p = 0.9101
w1118 vs notumKO/+w1118 (10,6); notumKO/+ (11,9)217.2 vs 214.1 nAq = 0.1649 df = 40p = 0.9994
w1118 vs cowGDP/notumKOw1118 (10,6); cowGDP/notumKO (12,7)217.2 vs 235.9 nAq = 1.009 df = 40p = 0.8911
cowGDP/+ vs notumKO/+cowGDP/+ (11,6); notumKO/+ (11,9)234.9 vs 214.1 nAq = 1.13 df = 40p = 0.8543
cowGDP/+ vs cowGDP/notumKOcowGDP/+ (11,6); cowGDP/notumKO (12,7)234.9 vs 235.9 nAq = 0.05304 df = 40p > 0.9999
notumKO/+ vs cowGDP/notumKOnotumKO/+ (11,9); cowGDP/notumKO (12,7)214.1 vs 235.9 nAq = 1.208 df = 40p = 0.8282
mEJC Frequencyw1118 vs cowGDPNormalOrdinary one-way ANOVA with Tukey's multiple-comparisons testw1118 (22,17); cowGDP (21,15)1.396 vs 1.765 Hzq = 1.419 df = 53p = 0.5780
w1118 vs cowGDP/Dfw1118 (22,17); cowGDP/Df (13,11)1.396 vs 2.41 Hzq = 3.406 q = 53p = 0.0503
cowGDP vs cowGDP/DfcowGDP (21,15); cowGDP/Df (13,11)1.764 vs 2.41 Hzq = 2.15 df = 53p = 0.2897
mEJC Frequencyvglut-GAL4/+ vs vglut>Cow-RNAiNormalUnpaired two-tailed t testvglut-GAL4/+ (10,7); vglut>Cow-RNAi (11,7)1.497 vs 2.449 Hzt = 2.142 df = 19p = 0.0454ROUT, Q = 1%, removed 1 vglut-GAL4/+ value
mEJC amplitudew1118 vs cowGDPNormalOrdinary one-way ANOVA with Tukey's multiple-comparisons testw1118 (21,16); cowGDP (21,15)0.7518 vs 0.8682 nAq = 2.506 df = 52p = 0.1889ROUT, Q = 1%, removed 1 w1118 value
w1118 vs cowGDP/Dfw1118 (21,16); cowGDP/Df (13,11)0.7518 vs 0.7165 nAq = 0.6647 df = 52p = 0.8856
cowGDP vs cowGDP/DfcowGDP (21,15); cowGDP/Df (13,11)0.8682 vs 0.7165 nAq = 2.857 df = 52p = 0.1175
mEJC amplitudevglut-GAL4/+ vs vglut>Cow-RNAiNormalUnpaired two-tailed t testvglut-GAL4/+ (11,7); vglut>Cow-RNAi (11,7)0.8015 vs 0.8446 nAt = 0.8011 df = 20p = 0.4325
Frequencyvglut/+ vs vglut>RNAiNot normal (Shapiro–Wilk normality test performed because N too small)Mann–Whitney testvglut/+ (7,4); vglut>RNAi (6,3)1.617 vs 2.977 Hz/μm2 U = 7p = 0.0513
Mean ΔF/F0 vglut/+ vs vglut>RNAiNormal (Shapiro–Wilk normality test performed because N too small)Unpaired two-tailed t testvglut/+ (8,4); vglut>RNAi (5,3)0.7912 vs 1.058 ΔF/F0 t = 3.013 df = 11p = 0.0118