--- tags: GeneLab title: GLDS-249, RR6, V4 amplicon data --- # GLDS-249, RR6, V4 amplicon data [toc] # Beta diversity views ## Live-animal return (LAR) Flight vs Ground <a href="https://i.imgur.com/Smc9lFm.png"><img src="https://i.imgur.com/Smc9lFm.png"></a> <center><a href="https://i.imgur.com/syeS8Ed.png"><img src="https://i.imgur.com/syeS8Ed.png"></a></center> --- ## ISS-terminated (ISS-T) Flight vs Ground <a href="https://i.imgur.com/gWqJFEr.png"><img src="https://i.imgur.com/gWqJFEr.png"></a> <a href="https://i.imgur.com/BA9Ki6s.png"><img src="https://i.imgur.com/BA9Ki6s.png"></a> <a href=""><img src=""></a> <a href=""><img src=""></a> --- # R code ```r= library("phyloseq") library("vegan") library("DESeq2") library("ggplot2") library("dendextend") library("tidyr") library("viridis") library("reshape") library("tidyverse") ## reading in data files count_tab <- read.table("Final_Outputs/FluidAA_counts.tsv", header=TRUE, row.names=1, check.names=FALSE, sep="\t") tax_tab <- read.table("Final_Outputs/FluidAA_taxonomy.tsv", header=TRUE, row.names=1, check.names=FALSE, sep="\t", na.strings="NA") # samples table downloaded from the GLDS page: https://genelab-data.ndc.nasa.gov/genelab/accession/GLDS-249/ sample_info_tab <- read.table("GLDS-249_samples_export.csv", header = TRUE, check.names = FALSE, sep = ",", comment.char = "") colnames(sample_info_tab) sample_info_tab <- sample_info_tab %>% select(`Sample Name`, `Factor Value: Spaceflight`, `Factor Value: Euthanasia`) colnames(sample_info_tab) <- c("Sample", "Treatment", "Experiment") # renaming factors sample_info_tab$Treatment <- sample_info_tab$Treatment %>% str_replace("Basal Control ", "Basal") %>% str_replace("Space Flight ", "Flight") %>% str_replace("Ground Control ", "Ground") sample_info_tab$Experiment <- sample_info_tab$Experiment %>% str_replace("On Earth ", "LAR") %>% str_replace("On ISS ", "ISS-T") sample_info_tab <- sample_info_tab %>% column_to_rownames(var = "Sample") ### problem with metadata # some are marked as LAR, but they have ISS-T in their sample name, I'm using what's in the sample name for now sample_info_tab sample_info_tab$Experiment <- row.names(sample_info_tab) %>% str_replace("Mmus_C57-6T_FCS_[A-Z]*_", "") %>% str_replace("_Rep?_", "") %>% str_replace("_.*", "") # adding colors for treatment basal_col <- "lightsalmon" flight_col <- "grey12" ground_col <- "blue3" sample_info_tab$treatment_color <- sample_info_tab$Treatment %>% str_replace("Basal", basal_col) %>% str_replace("Ground", ground_col) %>% str_replace("Flight", flight_col) ## shortening sample names to remove any redundant info and so they match names(count_tab) <- names(count_tab) %>% str_replace("Mmus_C57-6T_FCS_", "") %>% str_replace("_Rep.?", "") %>% str_replace("_FluidAA", "") row.names(sample_info_tab) <- row.names(sample_info_tab) %>% str_replace("Mmus_C57-6T_FCS_", "") %>% str_replace("_Rep.?", "") ## LAR Flight/Ground only LAR_Flight_Ground_samples <- sample_info_tab %>% filter(Experiment == "LAR", Treatment %in% c("Flight", "Ground")) %>% row.names() LAR_Flight_Ground_count_tab <- count_tab %>% select(all_of(LAR_Flight_Ground_samples)) LAR_Flight_Ground_sample_info_tab <- sample_info_tab[row.names(sample_info_tab) %in% LAR_Flight_Ground_samples, ] # vst transforming LAR_Flight_Ground_deseq_counts <- DESeqDataSetFromMatrix(LAR_Flight_Ground_count_tab, colData = LAR_Flight_Ground_sample_info_tab, design = ~Treatment) LAR_Flight_Ground_deseq_counts_vst <- varianceStabilizingTransformation(LAR_Flight_Ground_deseq_counts) LAR_Flight_Ground_vst_trans_count_tab <- assay(LAR_Flight_Ground_deseq_counts_vst) LAR_Flight_Ground_euc_dist <- dist(t(LAR_Flight_Ground_vst_trans_count_tab)) # hclust LAR_Flight_Ground_euc_clust <- hclust(LAR_Flight_Ground_euc_dist, method="ward.D2") LAR_Flight_Ground_euc_dend <- as.dendrogram(LAR_Flight_Ground_euc_clust, hang=0.1) # color by treatment LAR_Flight_Ground_dend_cols <- as.character(LAR_Flight_Ground_sample_info_tab$treatment_color[order.dendrogram(LAR_Flight_Ground_euc_dend)]) labels_colors(LAR_Flight_Ground_euc_dend) <- LAR_Flight_Ground_dend_cols plot(LAR_Flight_Ground_euc_dend, ylab="VST Euc. dist.", main="V4 amplicons (LAR F/G only; N=16)") legend("topright", legend=c("Flight", "Ground"), fill=c(flight_col, ground_col), title="Treatment", inset=0.05) # ordination ## making physeq object of vs-transformed tab LAR_Flight_Ground_vst_count_phy <- otu_table(LAR_Flight_Ground_vst_trans_count_tab, taxa_are_rows=T) LAR_Flight_Ground_sample_info_tab_phy <- sample_data(LAR_Flight_Ground_sample_info_tab) LAR_Flight_Ground_vst_physeq <- phyloseq(LAR_Flight_Ground_vst_count_phy, LAR_Flight_Ground_sample_info_tab_phy) # generating and visualizing the PCoA with phyloseq LAR_Flight_Ground_vst_pcoa <- ordinate(LAR_Flight_Ground_vst_physeq, method="MDS", distance="euclidean") LAR_Flight_Ground_eigen_vals <- LAR_Flight_Ground_vst_pcoa$values$Eigenvalues # allows us to scale the axes according to their magnitude of separating apart the samples # colored by treatment, shape by experiment plot_ordination(LAR_Flight_Ground_vst_physeq, LAR_Flight_Ground_vst_pcoa) + geom_point(size=3, aes(color = Treatment), shape=17) + scale_color_manual(values = rev(unique(as.vector(LAR_Flight_Ground_sample_info_tab$treatment_color)))) + coord_fixed(sqrt(LAR_Flight_Ground_eigen_vals[2]/LAR_Flight_Ground_eigen_vals[1])) + ggtitle("PCoA (VST Euc. dist.; LAR only; N=16)") + theme_bw() + theme(legend.position="bottom") + labs(color = "Treatment") ## whole-community diff test (anova) anova(betadisper(LAR_Flight_Ground_euc_dist, LAR_Flight_Ground_sample_info_tab$Treatment)) # 0.66, ok for permanova adonis(LAR_Flight_Ground_euc_dist~LAR_Flight_Ground_sample_info_tab$Treatment) # 0.001, at least one group is diff from the others at 0.001 plot_ordination(LAR_Flight_Ground_vst_physeq, LAR_Flight_Ground_vst_pcoa) + geom_point(size=3, aes(color = Treatment), shape=17) + scale_color_manual(values = rev(unique(as.vector(LAR_Flight_Ground_sample_info_tab$treatment_color)))) + coord_fixed(sqrt(LAR_Flight_Ground_eigen_vals[2]/LAR_Flight_Ground_eigen_vals[1])) + ggtitle("PCoA (VST Euc. dist.; LAR only; N=16)", subtitle = "Perm. ANOVA = 0.001") + theme_bw() + theme(legend.position="bottom", plot.title = element_text(face = "bold")) + labs(color = "Treatment") ## ISS_T Flight/Ground only ISS_T_Flight_Ground_samples <- sample_info_tab %>% filter(Experiment == "ISS-T", Treatment %in% c("Flight", "Ground")) %>% row.names() ISS_T_Flight_Ground_count_tab <- count_tab %>% select(all_of(ISS_T_Flight_Ground_samples)) ISS_T_Flight_Ground_sample_info_tab <- sample_info_tab[row.names(sample_info_tab) %in% ISS_T_Flight_Ground_samples, ] # vst transforming ISS_T_Flight_Ground_deseq_counts <- DESeqDataSetFromMatrix(ISS_T_Flight_Ground_count_tab, colData = ISS_T_Flight_Ground_sample_info_tab, design = ~Treatment) ISS_T_Flight_Ground_deseq_counts_vst <- varianceStabilizingTransformation(ISS_T_Flight_Ground_deseq_counts) ISS_T_Flight_Ground_vst_trans_count_tab <- assay(ISS_T_Flight_Ground_deseq_counts_vst) ISS_T_Flight_Ground_euc_dist <- dist(t(ISS_T_Flight_Ground_vst_trans_count_tab)) # hclust ISS_T_Flight_Ground_euc_clust <- hclust(ISS_T_Flight_Ground_euc_dist, method="ward.D2") ISS_T_Flight_Ground_euc_dend <- as.dendrogram(ISS_T_Flight_Ground_euc_clust, hang=0.1) # color by treatment ISS_T_Flight_Ground_dend_cols <- as.character(ISS_T_Flight_Ground_sample_info_tab$treatment_color[order.dendrogram(ISS_T_Flight_Ground_euc_dend)]) labels_colors(ISS_T_Flight_Ground_euc_dend) <- ISS_T_Flight_Ground_dend_cols plot(ISS_T_Flight_Ground_euc_dend, ylab="VST Euc. dist.", main="V4 amplicons (ISS-T F/G only; N=16)") legend("topright", legend=c("Flight", "Ground"), fill=c(flight_col, ground_col), title="Treatment", inset=0.05) # ordination ## making physeq object of vs-transformed tab ISS_T_Flight_Ground_vst_count_phy <- otu_table(ISS_T_Flight_Ground_vst_trans_count_tab, taxa_are_rows=T) ISS_T_Flight_Ground_sample_info_tab_phy <- sample_data(ISS_T_Flight_Ground_sample_info_tab) ISS_T_Flight_Ground_vst_physeq <- phyloseq(ISS_T_Flight_Ground_vst_count_phy, ISS_T_Flight_Ground_sample_info_tab_phy) # generating and visualizing the PCoA with phyloseq ISS_T_Flight_Ground_vst_pcoa <- ordinate(ISS_T_Flight_Ground_vst_physeq, method="MDS", distance="euclidean") ISS_T_Flight_Ground_eigen_vals <- ISS_T_Flight_Ground_vst_pcoa$values$Eigenvalues # allows us to scale the axes according to their magnitude of separating apart the samples # colored by treatment, shape by experiment plot_ordination(ISS_T_Flight_Ground_vst_physeq, ISS_T_Flight_Ground_vst_pcoa) + geom_point(size=3, aes(color = Treatment), shape=17) + scale_color_manual(values=rev(unique(as.vector(ISS_T_Flight_Ground_sample_info_tab$treatment_color)))) + coord_fixed(sqrt(ISS_T_Flight_Ground_eigen_vals[2]/ISS_T_Flight_Ground_eigen_vals[1])) + ggtitle("PCoA (VST Euc. dist.; ISS_T only; N=16)") + theme_bw() + theme(legend.position="bottom") + labs(color = "Treatment") ## whole-community diff test (anova) anova(betadisper(ISS_T_Flight_Ground_euc_dist, ISS_T_Flight_Ground_sample_info_tab$Treatment)) # 0.65, ok for permanova adonis(ISS_T_Flight_Ground_euc_dist~ISS_T_Flight_Ground_sample_info_tab$Treatment) # 0.001, at least one group is diff from the others at 0.001 plot_ordination(ISS_T_Flight_Ground_vst_physeq, ISS_T_Flight_Ground_vst_pcoa) + geom_point(size=3, aes(color = Treatment), shape=17) + scale_color_manual(values=rev(unique(as.vector(ISS_T_Flight_Ground_sample_info_tab$treatment_color)))) + coord_fixed(sqrt(ISS_T_Flight_Ground_eigen_vals[2]/ISS_T_Flight_Ground_eigen_vals[1])) + ggtitle("PCoA (VST Euc. dist.; ISS-T only; N=16)", subtitle = "Perm. ANOVA = 0.001") + theme_bw() + theme(legend.position="bottom", plot.title = element_text(face = "bold")) + labs(color = "Treatment") ``` <a href=""><img src=""></a> <a href=""><img src=""></a> <a href=""><img src=""></a> <a href=""><img src=""></a> <a href=""><img src=""></a> <a href=""><img src=""></a> <a href=""><img src=""></a> <a href=""><img src=""></a> <a href=""><img src=""></a>