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PERMANOVA
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161 lines (119 loc) · 5.84 KB
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#This Script is used specifically for
#PERMANOVA Calculations for the Lake Michigan Microbiome Project
#######################################
#Sample Type
set.seed(1)
# Calculate bray curtis distance matrix
final_bray <- phyloseq::distance(scale_Final, method = "bray")
# make a data frame from the sample_data
sampledf <- data.frame(sample_data(Final))
# Adonis test
adonis(final_bray ~ Type, data = sampledf)
#Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
#Type 3 16.521 5.5071 23.261 0.23278 0.001 ***
#Residuals 230 54.453 0.2368 0.76722
#Total 233 70.975 1.00000
beta <- betadisper(final_bray, sampledf$Type)
permutest(beta)
#Df Sum Sq Mean Sq F N.Perm Pr(>F)
#Groups 3 0.27773 0.092576 12.111 999 0.001 ***
#Residuals 230 1.75810 0.007644
##########################################
#Permanova by Lake
adonis(final_bray ~ Lake, data = sampledf)
# Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
#Lake 1 8.168 8.1675 30.17 0.11508 0.001 ***
#Residuals 232 62.807 0.2707 0.88492
#Total 233 70.975 1.00000
beta <- betadisper(final_bray, sampledf$Lake)
permutest(beta)
#Df Sum Sq Mean Sq F N.Perm Pr(>F)
#Groups 1 0.41828 0.41828 64.264 999 0.001 ***
#Residuals 232 1.51004 0.00651
########################################################
#By Month Collected
adonis(final_bray ~ Month_Collected, data = sampledf)
#Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
#Month_Collected 6 6.763 1.12714 3.9846 0.09529 0.001 ***
#Residuals 227 64.212 0.28287 0.90471
#Total 233 70.975 1.00000
beta <- betadisper(final_bray, sampledf$Month_Collected)
permutest(beta)
#Df Sum Sq Mean Sq F N.Perm Pr(>F)
#Groups 6 0.05374 0.0089564 1.5159 999 0.184
#Residuals 227 1.34119 0.0059083
#########################################################
#Depth_in_Meters
adonis(final_bray ~ Depth_in_Meters, data = sampledf)
#Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
#Depth_in_Meters 7 15.613 2.23050 9.1055 0.21999 0.001 ***
#Residuals 226 55.361 0.24496 0.78001
#Total 233 70.975 1.00000
beta <- betadisper(final_bray, sampledf$Depth_in_Meters)
permutest(beta)
#Df Sum Sq Mean Sq F N.Perm Pr(>F)
#Groups 7 1.6165 0.230924 27.506 999 0.001 ***
#Residuals 226 1.8974 0.008395
##########################################################
#Cruise
adonis(final_bray ~ Cruise, data = sampledf)
#Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
#Cruise 2 7.111 3.5554 12.86 0.10019 0.001 ***
#Residuals 231 63.864 0.2765 0.89981
#Total 233 70.975 1.00000
beta <- betadisper(final_bray, sampledf$Cruise)
permutest(beta)
#Df Sum Sq Mean Sq F N.Perm Pr(>F)
#Groups 2 0.50003 0.250016 36.837 999 0.001 ***
#Residuals 231 1.56780 0.006787
##########################################################
#Sediment vs. Mussel
adonis(final_bray ~ Sed_or_Mus, data = sampledf)
#Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
#Sed_or_Mus 1 14.700 14.7002 60.604 0.20712 0.001 ***
#Residuals 232 56.274 0.2426 0.79288
#Total 233 70.975 1.00000
beta <- betadisper(final_bray, sampledf$Sed_or_Mus)
permutest(beta)
#Df Sum Sq Mean Sq F N.Perm Pr(>F)
#Groups 1 0.06145 0.061453 7.5802 999 0.008 **
#Residuals 232 1.88084 0.008107
###########################################################
#Cruise + Lake
adonis(final_bray ~ Lake + Cruise, data = sampledf)
#Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
#Lake 1 8.168 8.1675 31.2065 0.11508 0.001 ***
#Cruise 2 2.610 1.3051 4.9866 0.03678 0.001 ***
#Residuals 230 60.197 0.2617 0.84815
#Total 233 70.975 1.00000
#Sed/Mus + Type
adonis(final_bray ~ Sed_or_Mus + Type, data = sampledf)
#Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
#Sed_or_Mus 1 14.700 14.7002 62.091 0.20712 0.001 ***
#Type 2 1.821 0.9106 3.846 0.02566 0.001 ***
#Residuals 230 54.453 0.2368 0.76722
#Total 233 70.975 1.00000
#Sed/Mus + Lake
adonis(final_bray ~ Sed_or_Mus + Lake, data = sampledf)
#Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
#Sed_or_Mus 1 14.700 14.700 68.060 0.20712 0.001 ***
#Lake 1 6.381 6.381 29.543 0.08991 0.001 ***
#Residuals 231 49.893 0.216 0.70297
#Total 233 70.975 1.00000
#Sed/Mus + Month Collected
adonis(final_bray ~ Sed_or_Mus + Month_Collected, data = sampledf)
#Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
#Sed_or_Mus 1 14.700 14.7002 63.493 0.20712 0.001 ***
#Month_Collected 6 3.950 0.6583 2.843 0.05565 0.001 ***
#Residuals 226 52.325 0.2315 0.73723
#Total 233 70.975 1.00000
#Sed/Mus + Cruise + Depth + Month
adonis(final_bray ~ Sed_or_Mus + Cruise + Depth_in_Meters
+ Month_Collected, data = sampledf)
#Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
#Sed_or_Mus 1 14.700 14.7002 80.141 0.20712 0.001 ***
#Cruise 2 5.812 2.9061 15.843 0.08189 0.001 ***
#Depth_in_Meters 6 8.879 1.4798 8.068 0.12510 0.001 ***
#Month_Collected 6 1.595 0.2659 1.450 0.02248 0.007 **
#Residuals 218 39.988 0.1834 0.56341
#Total 233 70.975 1.00000