## ----setup, include = FALSE--------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>", warning = FALSE ) ## ----eval = FALSE------------------------------------------------------------- # # Check if BiocManager is installed # if (!requireNamespace("BiocManager", quietly = TRUE)) # install.packages("BiocManager") # # Install HMP2Data package using BiocManager # BiocManager::install("HMP2Data") ## ----eval = FALSE------------------------------------------------------------- # BiocManager::install("jstansfield0/HMP2Data") ## ----message=FALSE, warning=FALSE--------------------------------------------- library(HMP2Data) library(phyloseq) library(SummarizedExperiment) library(MultiAssayExperiment) library(dplyr) library(ggplot2) library(UpSetR) ## ----------------------------------------------------------------------------- data("momspi16S_mtx") momspi16S_mtx[1:5, 1:3] ## ----------------------------------------------------------------------------- data("momspi16S_tax") colnames(momspi16S_tax) momspi16S_tax[1:5, 1:3] ## ----eval=FALSE, echo=FALSE--------------------------------------------------- # # Check if Greengene IDs match between the 16S and taxonomy data # # all.equal(rownames(momspi16S_mtx), rownames(momspi16S_tax)) # Should be TRUE ## ----------------------------------------------------------------------------- data("momspi16S_samp") colnames(momspi16S_samp) momspi16S_samp[1:5, 1:3] # Check if sample names match between the 16S and sample data # all.equal(colnames(momspi16S_mtx), rownames(momspi16S_samp)) # Should be TRUE ## ----message=FALSE------------------------------------------------------------ momspi16S_phyloseq <- momspi16S() momspi16S_phyloseq ## ----------------------------------------------------------------------------- data("momspiCyto_mtx") momspiCyto_mtx[1:5, 1:5] ## ----------------------------------------------------------------------------- data("momspiCyto_samp") colnames(momspiCyto_samp) momspiCyto_samp[1:5, 1:5] ## ----eval=FALSE, echo=FALSE--------------------------------------------------- # # Check if sample names match between the 16S and sample data # # all.equal(colnames(momspiCyto_mtx), rownames(momspiCyto_samp)) # Should be TRUE ## ----------------------------------------------------------------------------- momspiCyto <- momspiCytokines() momspiCyto ## ----------------------------------------------------------------------------- momspiMA <- momspiMultiAssay() momspiMA ## ----------------------------------------------------------------------------- rRNA <- momspiMA[[1L]] ## ----------------------------------------------------------------------------- cyto <- momspiMA[[2L]] ## ----------------------------------------------------------------------------- colData(momspiMA) %>% head() ## ----------------------------------------------------------------------------- completeMA <- intersectColumns(momspiMA) completeMA ## ----------------------------------------------------------------------------- data("IBD16S_mtx") IBD16S_mtx[1:5, 1:5] ## ----------------------------------------------------------------------------- data("IBD16S_tax") colnames(IBD16S_tax) IBD16S_tax[1:5, 1:5] ## ----------------------------------------------------------------------------- data("IBD16S_samp") colnames(IBD16S_samp) %>% head() IBD16S_samp[1:5, 1:5] ## ----------------------------------------------------------------------------- IBD <- IBD16S() IBD ## ----------------------------------------------------------------------------- data("T2D16S_mtx") T2D16S_mtx[1:5, 1:5] ## ----------------------------------------------------------------------------- data("T2D16S_tax") colnames(T2D16S_tax) T2D16S_tax[1:5, 1:5] ## ----------------------------------------------------------------------------- data("T2D16S_samp") colnames(T2D16S_samp) T2D16S_samp[1:5, 1:5] ## ----------------------------------------------------------------------------- T2D <- T2D16S() T2D ## ----------------------------------------------------------------------------- list("MOMS-PI 16S" = momspi16S_phyloseq, "MOMS-PI Cytokines" = momspiCyto, "IBD 16S" = IBD, "T2D 16S" = T2D) %>% table_two() ## ----------------------------------------------------------------------------- list("MOMS-PI 16S" = momspi16S_phyloseq, "MOMS-PI Cytokines" = momspiCyto, "IBD 16S" = IBD, "T2D 16S" = T2D) %>% visit_table() ## ----------------------------------------------------------------------------- list("MOMS-PI 16S" = momspi16S_phyloseq, "MOMS-PI Cytokines" = momspiCyto, "IBD 16S" = IBD, "T2D 16S" = T2D) %>% patient_table() ## ----fig.height=4, fig.width=4------------------------------------------------ # set up ggplots p1 <- ggplot(momspi16S_samp, aes(x = visit_number)) + geom_histogram(bins = 20, color = "#00BFC4", fill = "lightblue") + xlim(c(0,20)) + xlab("Visit number") + ylab("Count") # theme(panel.background = element_blank(), panel.grid = element_blank()) p1 ## ----fig.height=4, fig.width=7------------------------------------------------ # make data.frame for plotting plot_visits <- data.frame(study = c(rep("MOMS-PI Cytokines", nrow(momspiCyto_samp)), rep("IBD 16S", nrow(IBD16S_samp)), rep("T2D 16S", nrow(T2D16S_samp))), visits = c(momspiCyto_samp$visit_number, IBD16S_samp$visit_number, T2D16S_samp$visit_number)) p2 <- ggplot(plot_visits, aes(x = visits, fill = study)) + geom_histogram(position = "dodge", alpha = 0.7, bins = 30, color = "#00BFC4") + xlim(c(0, 40)) + theme(legend.position = c(0.8, 0.8)) + xlab("Visit number") + ylab("Count") p2 ## ----fig.height=6, fig.width=10----------------------------------------------- # set up data.frame for UpSetR tmp_data <- split(momspi16S_samp, momspi16S_samp$subject_id) momspi_upset <- lapply(tmp_data, function(x) { table(x$sample_body_site) }) momspi_upset <- bind_rows(momspi_upset) tmp <- as.matrix(momspi_upset[, -1]) tmp <- (tmp > 0) *1 tmp[is.na(tmp)] <- 0 momspi_upset <- data.frame(patient = names(tmp_data), tmp) # plot upset(momspi_upset, order.by = 'freq', matrix.color = "blue", text.scale = 2) ## ----------------------------------------------------------------------------- # set up data.frame for UpSetR tmp_data <- split(momspiCyto_samp, momspiCyto_samp$subject_id) momspiCyto_upset <- lapply(tmp_data, function(x) { table(x$sample_body_site) }) momspiCyto_upset <- bind_rows(momspiCyto_upset) tmp <- as.matrix(momspiCyto_upset[, -1]) tmp <- (tmp > 0) *1 tmp[is.na(tmp)] <- 0 momspiCyto_upset <- data.frame(patient = names(tmp_data), tmp) # plot upset(momspiCyto_upset, order.by = 'freq', matrix.color = "blue", text.scale = 2) ## ----------------------------------------------------------------------------- # set up data.frame for UpSetR tmp_data <- split(IBD16S_samp, IBD16S_samp$subject_id) IBD_upset <- lapply(tmp_data, function(x) { table(x$biopsy_location) }) IBD_upset <- bind_rows(IBD_upset) tmp <- as.matrix(IBD_upset[, -1]) tmp <- (tmp > 0) *1 tmp[is.na(tmp)] <- 0 IBD_upset <- data.frame(patient = names(tmp_data), tmp) # plot upset(IBD_upset, order.by = 'freq', matrix.color = "blue", text.scale = 2) ## ----------------------------------------------------------------------------- # set up data.frame for UpSetR tmp_data <- split(T2D16S_samp,T2D16S_samp$subject_id) T2D_upset <- lapply(tmp_data, function(x) { table(x$sample_body_site) }) T2D_upset <- bind_rows(T2D_upset) tmp <- as.matrix(T2D_upset) tmp <- (tmp > 0) *1 tmp[is.na(tmp)] <- 0 T2D_upset <- data.frame(patient = names(tmp_data), tmp) # plot upset(T2D_upset, order.by = 'freq', matrix.color = "blue", text.scale = 2) ## ----------------------------------------------------------------------------- momspi_cytokines_participants <- colData(momspiCyto) momspi_cytokines_participants[1:5, ] ## ----------------------------------------------------------------------------- momspi_cytokines <- assay(momspiCyto) momspi_cytokines[1:5, 1:5] ## ----------------------------------------------------------------------------- momspi_16S_participants <- sample_data(momspi16S_phyloseq) ## ----------------------------------------------------------------------------- momspi16s_data <- as.matrix(otu_table(momspi16S_phyloseq)) ## ----------------------------------------------------------------------------- momspi16s_taxa <- tax_table(momspi16S_phyloseq) %>% as.data.frame() ## ----eval = FALSE------------------------------------------------------------- # library(readr) # write_csv(data.frame(file_id = rownames(momspi_cytokines_participants), momspi_cytokines_participants), "momspi_cytokines_participants.csv") # write_csv(data.frame(momspi_cytokines), "momspi_cytokines.csv") ## ----message=FALSE------------------------------------------------------------ sessionInfo()