为了避免各位错过最新的推文教程，强烈建议大家将“科研后花园”设置为“星标”！
###安装LorMe包install.packages("LorMe")##加载MicrobiomeStat包library(LorMe) # Lightening One-Code Resolving Microbial Ecology Solutionlibrary(ggplot2) # Create Elegant Data Visualisations Using the Grammar of Graphics
##加载示例数据集data(testotu) # Load the standard Qiime output feature tablehead(testotu) # First column -ID, last column -taxonomic annotation, others - the feature table.feature_table<- testotu[, -c(1,22)]tax_anno<- testotu[, c(1,22)]#创建分组数据groupinformation <- data.frame(group = c(rep("a", 10), rep("b", 10)),factor1 = rnorm(10),factor2 = rnorm(mean = 100, 10),subject = factor(c(1:10, 1:10)),group2 = c(rep("e", 5), rep("f", 5), rep("e", 5), rep("f", 5)))###对数据进行封装test_object <- tax_summary(groupfile = groupinformation,inputtable = feature_table,reads = TRUE,taxonomytable = tax_anno)###对一些默认设置进行配置my_col=color_scheme("Plan1")my_order=c("b","a")my_facet_order=c("e","f")test_object_plan2 <- object_config(taxobj = test_object,treat_location = 1,rep_location = 4,facet_location = 5,subject_location = NULL,treat_col = my_col,treat_order = my_order,facet_order = my_facet_order)
Taxonomy tidying...Genarating tables...DoneContained elements:[1] "Groupfile" "Base" "Base_percent"[4] "Base_taxonomy" "Phylum" "Phylum_percent"[7] "Phylum_taxonomy" "Genus" "Genus_percent"[10] "Genus_taxonomy" "parameters"Warning message:Expected 7 pieces. Missing pieces filled with `NA` in 261 rows [4,6, 9, 12, 18, 20, 24, 32, 37, 43, 44, 45, 46, 58, 59, 68, 70, 71,72, 76, ...].
1）默认基础分析：
Alpha_results<- Alpha_diversity_calculator(taxobj = test_object_plan2,taxlevel = "Base" #analysis level)
###Distribution hypothesis####Normality Test (Shapiro-Wilk): Failed (P = 0.005623099 )Equal Variance Test (Brown-Forsythe): Passed (P = 0.404 )Treatment_Name N Median Q1 Q31 a 10 5.432989 4.492731 5.1242262 b 10 5.395290 4.973662 5.331129###Dependent Variable: Indexvalue #######Mann-Whitney Rank Sum Test#######Statistics####Mann-Whitney U Statistic= 42n(small)= 10 , n(big)= 10P_estimate = 0.5707504 ,P_exact = 0.5453497###Conclusion####The difference in the median values between the two groups is not great enough to exclude the possibility that the difference is due to random sampling variability; there is not a statistically significant difference (P = 0.5453497 ).Analysis finished###Distribution hypothesis####Normality Test (Shapiro-Wilk): Failed (P = 0.006954524 )Equal Variance Test (Brown-Forsythe): Passed (P = 0.264 )Treatment_Name N Median Q1 Q31 a 10 626.5 336.25 522.42 b 10 608.0 516.00 586.9###Dependent Variable: Indexvalue #######Mann-Whitney Rank Sum Test#######Statistics####Mann-Whitney U Statistic= 44n(small)= 10 , n(big)= 10P_estimate = 0.6774705 ,P_exact = 0.6500246###Conclusion####The difference in the median values between the two groups is not great enough to exclude the possibility that the difference is due to random sampling variability; there is not a statistically significant difference (P = 0.6500246 ).Analysis finished###Distribution hypothesis####Normality Test (Shapiro-Wilk): Failed (P = 0.02277682 )Equal Variance Test (Brown-Forsythe): Passed (P = 0.906 )Treatment_Name N Median Q1 Q31 a 10 0.8415442 0.7893959 0.82665272 b 10 0.8431299 0.8036199 0.8368023###Dependent Variable: Indexvalue #######Mann-Whitney Rank Sum Test#######Statistics####Mann-Whitney U Statistic= 42n(small)= 10 , n(big)= 10P_estimate = 0.5707504 ,P_exact = 0.5453497###Conclusion####The difference in the median values between the two groups is not great enough to exclude the possibility that the difference is due to random sampling variability; there is not a statistically significant difference (P = 0.5453497 ).Analysis finished###Distribution hypothesis####Normality Test (Shapiro-Wilk): Failed (P = 0.0004472301 )Equal Variance Test (Brown-Forsythe): Passed (P = 0.921 )Treatment_Name N Median Q1 Q31 a 10 0.9909291 0.9793478 0.98653302 b 10 0.9903503 0.9799472 0.9865132###Dependent Variable: Indexvalue #######Mann-Whitney Rank Sum Test#######Statistics####Mann-Whitney U Statistic= 50n(small)= 10 , n(big)= 10P_estimate = 1 ,P_exact = 1###Conclusion####The difference in the median values between the two groups is not great enough to exclude the possibility that the difference is due to random sampling variability; there is not a statistically significant difference (P = 1 ).Analysis finished###Distribution hypothesis####Normality Test (Shapiro-Wilk): Failed (P = 0.01048326 )Equal Variance Test (Brown-Forsythe): Passed (P = 0.215 )Treatment_Name N Median Q1 Q31 a 10 718.085 414.0291 607.20042 b 10 693.228 652.6971 679.5795###Dependent Variable: Indexvalue #######Mann-Whitney Rank Sum Test#######Statistics####Mann-Whitney U Statistic= 47n(small)= 10 , n(big)= 10P_estimate = 0.8501067 ,P_exact = 0.8205958###Conclusion####The difference in the median values between the two groups is not great enough to exclude the possibility that the difference is due to random sampling variability; there is not a statistically significant difference (P = 0.8205958 ).Analysis finished###Distribution hypothesis####Normality Test (Shapiro-Wilk): Failed (P = 0.0108276 )Equal Variance Test (Brown-Forsythe): Passed (P = 0.237 )Treatment_Name N Median Q1 Q31 a 10 712.4917 423.9344 600.29882 b 10 671.8403 616.9682 658.7892###Dependent Variable: Indexvalue #######Mann-Whitney Rank Sum Test#######Statistics####Mann-Whitney U Statistic= 53n(small)= 10 , n(big)= 10P_estimate = 0.8501067 ,P_exact = 0.8205958###Conclusion####The difference in the median values between the two groups is not great enough to exclude the possibility that the difference is due to random sampling variability; there is not a statistically significant difference (P = 0.8205958 ).Analysis finished
2）在不同分类水平进行Alpha分析（以属水平为例）：
Alpha_results2<- Alpha_diversity_calculator(taxobj = test_object_plan2,taxlevel = "Genus",prefix = "Genus")
###Distribution hypothesis####Normality Test (Shapiro-Wilk): Failed (P = 0.002079162 )Equal Variance Test (Brown-Forsythe): Passed (P = 0.356 )Treatment_Name N Median Q1 Q31 a 10 4.774252 4.130925 4.5414992 b 10 4.754462 4.511624 4.690952###Dependent Variable: Indexvalue #######Mann-Whitney Rank Sum Test#######Statistics####Mann-Whitney U Statistic= 43n(small)= 10 , n(big)= 10P_estimate = 0.6231762 ,P_exact = 0.5967012###Conclusion####The difference in the median values between the two groups is not great enough to exclude the possibility that the difference is due to random sampling variability; there is not a statistically significant difference (P = 0.5967012 ).Analysis finished###Distribution hypothesis####Normality Test (Shapiro-Wilk): Failed (P = 0.0127267 )Equal Variance Test (Brown-Forsythe): Passed (P = 0.12 )Treatment_Name N Median Q1 Q31 a 10 285.5 196.75 253.72 b 10 281.0 257.50 275.5###Dependent Variable: Indexvalue #######Mann-Whitney Rank Sum Test#######Statistics####Mann-Whitney U Statistic= 52n(small)= 10 , n(big)= 10P_estimate = 0.9095864 ,P_exact = 0.8796494###Conclusion####The difference in the median values between the two groups is not great enough to exclude the possibility that the difference is due to random sampling variability; there is not a statistically significant difference (P = 0.8796494 ).Analysis finished###Distribution hypothesis####Normality Test (Shapiro-Wilk): Failed (P = 0.002801331 )Equal Variance Test (Brown-Forsythe): Passed (P = 0.845 )Treatment_Name N Median Q1 Q31 a 10 0.8443819 0.7964615 0.82386312 b 10 0.8451148 0.8118400 0.8349486###Dependent Variable: Indexvalue #######Mann-Whitney Rank Sum Test#######Statistics####Mann-Whitney U Statistic= 40n(small)= 10 , n(big)= 10P_estimate = 0.4726756 ,P_exact = 0.4496918###Conclusion####The difference in the median values between the two groups is not great enough to exclude the possibility that the difference is due to random sampling variability; there is not a statistically significant difference (P = 0.4496918 ).Analysis finished###Distribution hypothesis####Normality Test (Shapiro-Wilk): Failed (P = 0.0003992957 )Equal Variance Test (Brown-Forsythe): Passed (P = 0.955 )Treatment_Name N Median Q1 Q31 a 10 0.9852937 0.9742226 0.98104972 b 10 0.9853026 0.9751303 0.9807535###Dependent Variable: Indexvalue #######Mann-Whitney Rank Sum Test#######Statistics####Mann-Whitney U Statistic= 49n(small)= 10 , n(big)= 10P_estimate = 0.96985 ,P_exact = 0.939743###Conclusion####The difference in the median values between the two groups is not great enough to exclude the possibility that the difference is due to random sampling variability; there is not a statistically significant difference (P = 0.939743 ).Analysis finished###Distribution hypothesis####Normality Test (Shapiro-Wilk): Failed (P = 0.02471859 )Equal Variance Test (Brown-Forsythe): Passed (P = 0.161 )Treatment_Name N Median Q1 Q31 a 10 310.6667 245.1957 283.15032 b 10 300.8500 294.2031 297.7674###Dependent Variable: Indexvalue #######Mann-Whitney Rank Sum Test#######Statistics####Mann-Whitney U Statistic= 54n(small)= 10 , n(big)= 10P_estimate = 0.7913368 ,P_exact = 0.7623688###Conclusion####The difference in the median values between the two groups is not great enough to exclude the possibility that the difference is due to random sampling variability; there is not a statistically significant difference (P = 0.7623688 ).Analysis finished###Distribution hypothesis####Normality Test (Shapiro-Wilk): Failed (P = 0.02658585 )Equal Variance Test (Brown-Forsythe): Passed (P = 0.163 )Treatment_Name N Median Q1 Q31 a 10 303.4108 250.0425 279.37952 b 10 294.1081 279.7710 291.9993###Dependent Variable: Indexvalue #######Mann-Whitney Rank Sum Test#######Statistics####Mann-Whitney U Statistic= 56n(small)= 10 , n(big)= 10P_estimate = 0.677585 ,P_exact = 0.6501474###Conclusion####The difference in the median values between the two groups is not great enough to exclude the possibility that the difference is due to random sampling variability; there is not a statistically significant difference (P = 0.6501474 ).Analysis finished
3）可视化：
#柱状图Alpha_results$plotlist$Plotobj_Shannon$Barplot#箱线图Alpha_results$plotlist$Plotobj_Shannon$Boxplot#小提琴图Alpha_results$plotlist$Plotobj_Shannon$Violinplot
4）差异检验：
Alpha_results$plotlist$Plotobj_Shannon$Statistics5）提取计算结果并自定义可视化：
####提取计算结果并基于ggplot2包自定义绘图library(ggsignif) # Significance Brackets for 'ggplot2'data_Alpha <- Alpha_results$alphaframe#Shannonp1 <- ggplot(data_Alpha[data_Alpha$Indexname=="Shannon",],aes(group2, Indexvalue, fill = group2))+geom_boxplot(width=0.8,outlier.color =NA)+geom_jitter(aes(fill = group2), shape = 21, color = "black",size = 2.5,width = 0.2)+theme_bw() +theme(axis.title = element_text(size = 18),panel.grid = element_blank(),axis.text = element_text( size = 13),legend.position = "none")+scale_y_continuous(expand = c(0,0),limits = c(4,6.5))+labs(x=NULL,y="Shannon")+geom_signif(comparisons = list(c("e","f")),map_signif_level = T, #使用*号显示显著性test = "t.test",#检验方法textsize = 4,#字号大小y_position = c(6.2),#横线位置tip_length = c(0),#横线下方线条的长度size=0.8,color="black")#线条颜色及粗细#Simpsonp2 <- ggplot(data_Alpha[data_Alpha$Indexname=="Simpson",],aes(group2, Indexvalue, fill = group2))+geom_boxplot(width=0.8,outlier.color =NA)+geom_jitter(aes(fill = group2), shape = 21, color = "black",size = 2.5,width = 0.2)+theme_bw() +theme(axis.title = element_text(size = 18),panel.grid = element_blank(),axis.text = element_text( size = 13),legend.position = "none")+scale_y_continuous(expand = c(0,0),limits = c(0.72,0.95))+labs(x=NULL,y="Simpson")+geom_signif(comparisons = list(c("e","f")),map_signif_level = T, #使用*号显示显著性test = "t.test",#检验方法textsize = 4,#字号大小y_position = c(0.92),#横线位置tip_length = c(0),#横线下方线条的长度size=0.8,color="black")#线条颜色及粗细#ACEp3 <- ggplot(data_Alpha[data_Alpha$Indexname=="ACE",],aes(group2, Indexvalue, fill = group2))+geom_boxplot(width=0.8,outlier.color =NA)+geom_jitter(aes(fill = group2), shape = 21, color = "black",size = 2.5,width = 0.2)+theme_bw() +theme(axis.title = element_text(size = 18),panel.grid = element_blank(),axis.text = element_text( size = 13),legend.position = "none")+scale_y_continuous(expand = c(0,0),limits = c(290,880))+labs(x=NULL,y="ACE")+geom_signif(comparisons = list(c("e","f")),map_signif_level = T, #使用*号显示显著性test = "t.test",#检验方法textsize = 4,#字号大小y_position = c(800),#横线位置tip_length = c(0),#横线下方线条的长度size=0.8,color="black")#线条颜色及粗细#Chaop4 <- ggplot(data_Alpha[data_Alpha$Indexname=="Chao",],aes(group2, Indexvalue, fill = group2))+geom_boxplot(width=0.8,outlier.color =NA)+geom_jitter(aes(fill = group2), shape = 21, color = "black",size = 2.5,width = 0.2)+theme_bw() +theme(axis.title = element_text(size = 18),panel.grid = element_blank(),axis.text = element_text( size = 13),legend.position = "none")+scale_y_continuous(expand = c(0,0),limits = c(290,880))+labs(x=NULL,y="Chao")+geom_signif(comparisons = list(c("e","f")),map_signif_level = T, #使用*号显示显著性test = "t.test",#检验方法textsize = 4,#字号大小y_position = c(800),#横线位置tip_length = c(0),#横线下方线条的长度size=0.8,color="black")#线条颜色及粗细library(patchwork)p1+p2+p3+p4
更多内容大家请阅读LorMe包的帮助文档！
参考：LorMe包帮助文档
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