#Directorio: C:/Laura Cano/Maestría/Tesis/Fotos/Cultivo MSFs/01-03-22 Electroporación, daño e inmuno pag.8 bitácora2/B-gal"
setwd("C:/Laura Cano/Maestría/Tesis/Fotos/Cultivo MSFs/Daño 3N")
#ANOVA
Datos<-read.csv("Danopcdna_palt_3N.csv", header=TRUE)
#Bgal
#Prueba de normalidad
#Bgal
shapiro.test(lm(Bgal~Muestra, Datos)$residuals)
##
## Shapiro-Wilk normality test
##
## data: lm(Bgal ~ Muestra, Datos)$residuals
## W = 0.92678, p-value = 0.3472
#Apoptóticos
shapiro.test(lm(Apoptoticos~Muestra, Datos)$residuals)
##
## Shapiro-Wilk normality test
##
## data: lm(Apoptoticos ~ Muestra, Datos)$residuals
## W = 0.88045, p-value = 0.08882
#Deformes
shapiro.test(lm(Deformes~Muestra, Datos)$residuals)
##
## Shapiro-Wilk normality test
##
## data: lm(Deformes ~ Muestra, Datos)$residuals
## W = 0.96721, p-value = 0.8795
#Núcleoscm
shapiro.test(lm(Nucleoscm~Muestra, Datos)$residuals)
##
## Shapiro-Wilk normality test
##
## data: lm(Nucleoscm ~ Muestra, Datos)$residuals
## W = 0.91571, p-value = 0.2524
#Homoscedasticidad
#Bgal
bartlett.test(Bgal~Muestra, Datos)
##
## Bartlett test of homogeneity of variances
##
## data: Bgal by Muestra
## Bartlett's K-squared = 0.31168, df = 3, p-value = 0.9578
#Apoptóticos
bartlett.test(Apoptoticos~Muestra, Datos)
##
## Bartlett test of homogeneity of variances
##
## data: Apoptoticos by Muestra
## Bartlett's K-squared = 8.6134, df = 3, p-value = 0.0349
#Deformes
bartlett.test(Deformes~Muestra, Datos)
##
## Bartlett test of homogeneity of variances
##
## data: Deformes by Muestra
## Bartlett's K-squared = 4.4157, df = 3, p-value = 0.2199
#Nucleoscm
bartlett.test(Nucleoscm~Muestra, Datos)
##
## Bartlett test of homogeneity of variances
##
## data: Nucleoscm by Muestra
## Bartlett's K-squared = 8.1123, df = 3, p-value = 0.04375
#Dos vías con interacción
Datos2vias<-read.csv("2vias3N.csv", header=TRUE)
anova2Bgal<-aov(Bgal ~ Plasmido * Tratamiento, Datos2vias)
summary(anova2Bgal)
## Df Sum Sq Mean Sq F value Pr(>F)
## Plasmido 1 395.3 395.3 6.116 0.038526 *
## Tratamiento 1 2131.5 2131.5 32.981 0.000432 ***
## Plasmido:Tratamiento 1 236.8 236.8 3.665 0.091917 .
## Residuals 8 517.0 64.6
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
#plot(anova2Bgal)
#Post hoc
TukeyHSD(anova2Bgal)
## Tukey multiple comparisons of means
## 95% family-wise confidence level
##
## Fit: aov(formula = Bgal ~ Plasmido * Tratamiento, data = Datos2vias)
##
## $Plasmido
## diff lwr upr p adj
## pcDNA-pALT 11.47833 0.7753795 22.18129 0.038526
##
## $Tratamiento
## diff lwr upr p adj
## Etop-Ctrl 26.655 15.95205 37.35795 0.0004325
##
## $`Plasmido:Tratamiento`
## diff lwr upr p adj
## pcDNA:Ctrl-pALT:Ctrl 2.593333 -18.426421 23.61309 0.9776815
## pALT:Etop-pALT:Ctrl 17.770000 -3.249754 38.78975 0.1005511
## pcDNA:Etop-pALT:Ctrl 38.133333 17.113579 59.15309 0.0017957
## pALT:Etop-pcDNA:Ctrl 15.176667 -5.843088 36.19642 0.1741819
## pcDNA:Etop-pcDNA:Ctrl 35.540000 14.520246 56.55975 0.0028204
## pcDNA:Etop-pALT:Etop 20.363333 -0.656421 41.38309 0.0575654
#Kruskal nucleoscm
kruskal.test(Nucleoscm~Muestra, data=Datos)
##
## Kruskal-Wallis rank sum test
##
## data: Nucleoscm by Muestra
## Kruskal-Wallis chi-squared = 9.6667, df = 3, p-value = 0.02162
#Post hoc
pairwise.wilcox.test(x=Datos$Nucleoscm, g= Datos$Muestra, p.adjust.method = "fdr")
##
## Pairwise comparisons using Wilcoxon rank sum exact test
##
## data: Datos$Nucleoscm and Datos$Muestra
##
## pALT-Ctrl pALT-Etop pcDNA-Ctrl
## pALT-Etop 0.12 - -
## pcDNA-Ctrl 0.40 0.12 -
## pcDNA-Etop 0.12 0.12 0.12
##
## P value adjustment method: fdr
#Kruskal Apoptóticos
kruskal.test(Apoptoticos~Muestra, data=Datos)
##
## Kruskal-Wallis rank sum test
##
## data: Apoptoticos by Muestra
## Kruskal-Wallis chi-squared = 10.385, df = 3, p-value = 0.01556
pairwise.wilcox.test(x=Datos$Apoptoticos, g= Datos$Muestra, p.adjust.method = "hommel")
##
## Pairwise comparisons using Wilcoxon rank sum exact test
##
## data: Datos$Apoptoticos and Datos$Muestra
##
## pALT-Ctrl pALT-Etop pcDNA-Ctrl
## pALT-Etop 0.1 - -
## pcDNA-Ctrl 0.1 0.1 -
## pcDNA-Etop 0.1 0.1 0.1
##
## P value adjustment method: hommel
#ANOVA Apoptóticos
anova2apop<-aov(Apoptoticos ~ Plasmido * Tratamiento, Datos2vias)
summary(anova2apop)
## Df Sum Sq Mean Sq F value Pr(>F)
## Plasmido 1 24.40 24.40 18.845 0.00247 **
## Tratamiento 1 99.25 99.25 76.665 2.27e-05 ***
## Plasmido:Tratamiento 1 12.26 12.26 9.472 0.01517 *
## Residuals 8 10.36 1.29
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
#plot(anova2apop)
#Post hoc
TukeyHSD(anova2apop)
## Tukey multiple comparisons of means
## 95% family-wise confidence level
##
## Fit: aov(formula = Apoptoticos ~ Plasmido * Tratamiento, data = Datos2vias)
##
## $Plasmido
## diff lwr upr p adj
## pcDNA-pALT -2.851667 -4.366469 -1.336864 0.0024746
##
## $Tratamiento
## diff lwr upr p adj
## Etop-Ctrl 5.751667 4.236864 7.266469 2.27e-05
##
## $`Plasmido:Tratamiento`
## diff lwr upr p adj
## pcDNA:Ctrl-pALT:Ctrl -0.830000 -3.80495265 2.144953 0.8086324
## pALT:Etop-pALT:Ctrl 7.773333 4.79838068 10.748286 0.0001458
## pcDNA:Etop-pALT:Ctrl 2.900000 -0.07495265 5.874953 0.0560178
## pALT:Etop-pcDNA:Ctrl 8.603333 5.62838068 11.578286 0.0000697
## pcDNA:Etop-pcDNA:Ctrl 3.730000 0.75504735 6.704953 0.0163196
## pcDNA:Etop-pALT:Etop -4.873333 -7.84828598 -1.898381 0.0034401
#ANOVA Deformes
anova2def<-aov(Deformes ~ Plasmido * Tratamiento, Datos2vias)
summary(anova2def)
## Df Sum Sq Mean Sq F value Pr(>F)
## Plasmido 1 0.963 0.963 1.119 0.3209
## Tratamiento 1 18.402 18.402 21.384 0.0017 **
## Plasmido:Tratamiento 1 1.178 1.178 1.369 0.2756
## Residuals 8 6.884 0.861
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
#plot(anova2def)
#Post hoc
TukeyHSD(anova2def)
## Tukey multiple comparisons of means
## 95% family-wise confidence level
##
## Fit: aov(formula = Deformes ~ Plasmido * Tratamiento, data = Datos2vias)
##
## $Plasmido
## diff lwr upr p adj
## pcDNA-pALT 0.5666667 -0.6683798 1.801713 0.3209334
##
## $Tratamiento
## diff lwr upr p adj
## Etop-Ctrl 2.476667 1.24162 3.711713 0.0017007
##
## $`Plasmido:Tratamiento`
## diff lwr upr p adj
## pcDNA:Ctrl-pALT:Ctrl -0.060000 -2.4855336 2.365534 0.9998059
## pALT:Etop-pALT:Ctrl 1.850000 -0.5755336 4.275534 0.1455880
## pcDNA:Etop-pALT:Ctrl 3.043333 0.6177998 5.468867 0.0162564
## pALT:Etop-pcDNA:Ctrl 1.910000 -0.5155336 4.335534 0.1304129
## pcDNA:Etop-pcDNA:Ctrl 3.103333 0.6777998 5.528867 0.0146257
## pcDNA:Etop-pALT:Etop 1.193333 -1.2322002 3.618867 0.4419206