Installing and loading our package.
Create table based on the assessed species of the study.
try_table <- data.frame(Species=marchantiales$metadata$id_species[seq(1, nrow(marchantiales$metadata), 3)])
try_table$`Sample ID` <- marchantiales$metadata$id_samples[seq(1, nrow(marchantiales$metadata), 3)]Add columns containing geographical coordinates, exposition, specimen and type of plant material used in the study.
try_table$Latitude <- marchantiales$metadata$latitude[seq(1, nrow(marchantiales$metadata), 3)]
try_table$Longitude <- marchantiales$metadata$longitude[seq(1, nrow(marchantiales$metadata), 3)]
try_table$Altitude <- ""
try_table$Exposition <- "natural environment"
try_table$`Voucher specimen` <- marchantiales$metadata$voucher_specimen[seq(1, nrow(marchantiales$metadata), 3)]
try_table$`Plant maturity` <- "mature gametophyte"Fix some inconsistent naming.
try_table$`Sample ID` <- unique(gsub(x=try_table$`Sample ID`, pattern="\\.\\d.*", replacement=""))
try_table$`Sample ID` <- gsub(x=try_table$`Sample ID`, pattern="GOT|OEL", replacement="SWE")
try_table$`Sample ID` <- gsub(x=try_table$`Sample ID`, pattern="OE", replacement="SWE")
try_table$`Sample ID` <- gsub(x=try_table$`Sample ID`, pattern="HAL", replacement="GER")Now, create primary and secondary column names.
Create table containing the morphometric measurements performed in this study.
try_table_char_list <- marchantiales$char_list
try_table_char_list <- try_table_char_list[, -grep("(\\.mean)", colnames(try_table_char_list))]
colnames(try_table_char_list) <- gsub(x=colnames(try_table_char_list), pattern="\\.", replacement=" ")
colnames(try_table_char_list) <- paste(toupper(substr(colnames(try_table_char_list), 1, 1)), substr(colnames(try_table_char_list), 2, nchar(colnames(try_table_char_list))), sep="")
colnames(try_table_char_list) <- gsub(x=colnames(try_table_char_list), pattern=" cross", replacement=" cross-section")Fix some naming issues.
rownames(try_table_char_list) <- gsub(x=rownames(try_table_char_list), pattern="Asterella.gracilis", replacement="A.gracilis.SWE")
rownames(try_table_char_list) <- gsub(x=rownames(try_table_char_list), pattern="Athalamia.hyalina.var..suecica", replacement="A.hyalina.SWE")
rownames(try_table_char_list) <- gsub(x=rownames(try_table_char_list), pattern="Mannia.fragrans", replacement="M.fragrans.SWE")
rownames(try_table_char_list) <- gsub(x=rownames(try_table_char_list), pattern="Reboulia.hemisphaerica.subsp..hemisphaerica", replacement="R.hemisphaerica.SWE")
rownames(try_table_char_list) <- gsub(x=rownames(try_table_char_list), pattern="Riccia.beyrichiana", replacement="R.beyrichiana.SWE")
rownames(try_table_char_list) <- gsub(x=rownames(try_table_char_list), pattern="Riccia.bifurca", replacement="R.bifurca.SWE")
rownames(try_table_char_list) <- gsub(x=rownames(try_table_char_list), pattern="Riccia.canaliculata", replacement="R.canaliculata.SWE")
rownames(try_table_char_list) <- gsub(x=rownames(try_table_char_list), pattern="Riccia.cavernosa", replacement="R.cavernosa.SWE")
rownames(try_table_char_list) <- gsub(x=rownames(try_table_char_list), pattern="Riccia.ciliifera.HAL", replacement="R.ciliifera.GER")
rownames(try_table_char_list) <- gsub(x=rownames(try_table_char_list), pattern="Riccia.ciliifera.SWE", replacement="R.ciliifera.SWE")
rownames(try_table_char_list) <- gsub(x=rownames(try_table_char_list), pattern="Riccia.gothica", replacement="R.gothica.SWE")
rownames(try_table_char_list) <- gsub(x=rownames(try_table_char_list), pattern="Riccia.gougetiana.var..armatissima", replacement="R.gougetiana.GER")
rownames(try_table_char_list) <- gsub(x=rownames(try_table_char_list), pattern="Riccia.huebeneriana", replacement="R.huebeneriana.SWE")
rownames(try_table_char_list) <- gsub(x=rownames(try_table_char_list), pattern="Riccia.sorocarpa", replacement="R.sorocarpa.SWE")
rownames(try_table_char_list) <- gsub(x=rownames(try_table_char_list), pattern="Riccia.subbifurca.SWE1", replacement="R.subbifurca.SWE1")
rownames(try_table_char_list) <- gsub(x=rownames(try_table_char_list), pattern="Riccia.subbifurca.SWE2", replacement="R.subbifurca.SWE2")Add table with morphometric measurements to main trait table.
try_table <- cbind(try_table, try_table_char_list[match(try_table$`Sample ID`, rownames(try_table_char_list)), ])
try_table_colnames_1st <- c(try_table_colnames_1st, colnames(try_table_char_list))
try_table_colnames_2nd <- c(try_table_colnames_2nd, rep("", times=length(colnames(try_table_char_list))))Create table containing chemodiversity measures.
try_table_chemodiv_full <- cbind(marchantiales$model_div$richness, marchantiales$model_div$shannon, marchantiales$model_div$pielou, marchantiales$model_div$hillfunc)
colnames(try_table_chemodiv_full) <- c("Chemical richness", "Chemical Shannon diversity", "Chemical Pielou\\'s evenness index", "Chemical functional Hill diversity")
rownames(try_table_chemodiv_full) <- rownames(marchantiales$comp_list)Fix naming issues.
try_table_chemodiv <- NULL
for (i in unique(gsub(x=rownames(try_table_chemodiv_full), pattern="\\.\\d.*", replacement=""))) try_table_chemodiv <- rbind(try_table_chemodiv, apply(X=try_table_chemodiv_full[gsub(x=rownames(try_table_chemodiv_full), pattern="\\.\\d.*", replacement="")==i, ], MARGIN=2, FUN=function(x) { median(x) } ))
rownames(try_table_chemodiv) <- unique(gsub(x=rownames(try_table_chemodiv_full), pattern="\\.\\d.*", replacement=""))
rownames(try_table_chemodiv) <- gsub(x=rownames(try_table_chemodiv), pattern="GOT|OEL", replacement="SWE")
rownames(try_table_chemodiv) <- gsub(x=rownames(try_table_chemodiv), pattern="OE", replacement="SWE")
rownames(try_table_chemodiv) <- gsub(x=rownames(try_table_chemodiv), pattern="HAL", replacement="GER")Add table with chemodiversity measures to main trait table.
Create table containing the molecular classification from the Natural Product Classifier.
First, take the pathway information acquired in positive ion mode.
try_table_nppathway_list_pos_full <- make_classes_at_level(level=1, div_samples=marchantiales$div_npclasses_samples_pos)Fix naming.
try_table_nppathway_list_pos <- NULL
for (i in unique(gsub(x=rownames(try_table_nppathway_list_pos_full), pattern="\\.\\d.*", replacement=""))) try_table_nppathway_list_pos <- rbind(try_table_nppathway_list_pos, apply(X=try_table_nppathway_list_pos_full[gsub(x=rownames(try_table_nppathway_list_pos_full), pattern="\\.\\d.*", replacement="")==i, ], MARGIN=2, FUN=function(x) { median(x) } ))
rownames(try_table_nppathway_list_pos) <- unique(gsub(x=rownames(try_table_nppathway_list_pos_full), pattern="\\.\\d.*", replacement=""))
rownames(try_table_nppathway_list_pos) <- gsub(x=rownames(try_table_nppathway_list_pos), pattern="GOT|OEL", replacement="SWE")
rownames(try_table_nppathway_list_pos) <- gsub(x=rownames(try_table_nppathway_list_pos), pattern="OE", replacement="SWE")
rownames(try_table_nppathway_list_pos) <- gsub(x=rownames(try_table_nppathway_list_pos), pattern="HAL", replacement="GER")Take the pathway information acquired in negative ion mode.
try_table_nppathway_list_neg_full <- make_classes_at_level(level=1, div_samples=marchantiales$div_npclasses_samples_neg)Fix naming.
try_table_nppathway_list_neg <- NULL
for (i in unique(gsub(x=rownames(try_table_nppathway_list_neg_full), pattern="\\.\\d.*", replacement=""))) try_table_nppathway_list_neg <- rbind(try_table_nppathway_list_neg, apply(X=try_table_nppathway_list_neg_full[gsub(x=rownames(try_table_nppathway_list_neg_full), pattern="\\.\\d.*", replacement="")==i, ], MARGIN=2, FUN=function(x) { median(x) } ))
rownames(try_table_nppathway_list_neg) <- unique(gsub(x=rownames(try_table_nppathway_list_neg_full), pattern="\\.\\d.*", replacement=""))
rownames(try_table_nppathway_list_neg) <- gsub(x=rownames(try_table_nppathway_list_neg), pattern="GOT|OEL", replacement="SWE")
rownames(try_table_nppathway_list_neg) <- gsub(x=rownames(try_table_nppathway_list_neg), pattern="OE", replacement="SWE")
rownames(try_table_nppathway_list_neg) <- gsub(x=rownames(try_table_nppathway_list_neg), pattern="HAL", replacement="GER")Join pos and neg tables.
try_table_nppathway_list <- cbind(try_table_nppathway_list_pos, try_table_nppathway_list_neg)
try_table_nppathway_list <- cbind(sapply(unique(colnames(try_table_nppathway_list)[duplicated(colnames(try_table_nppathway_list))]), function(x) rowSums(try_table_nppathway_list[,grepl(paste(x, "$", sep=""), colnames(try_table_nppathway_list))])), try_table_nppathway_list[,!duplicated(colnames(try_table_nppathway_list)) & ! duplicated(colnames(try_table_nppathway_list), fromLast=TRUE)])Now, take the class information as second level in positive mode.
try_table_npsuperclass_list_pos_full <- make_classes_at_level(level=2, div_samples=marchantiales$div_npclasses_samples_pos)Fix naming.
try_table_npsuperclass_list_pos <- NULL
for (i in unique(gsub(x=rownames(try_table_npsuperclass_list_pos_full), pattern="\\.\\d.*", replacement=""))) try_table_npsuperclass_list_pos <- rbind(try_table_npsuperclass_list_pos, apply(X=try_table_npsuperclass_list_pos_full[gsub(x=rownames(try_table_npsuperclass_list_pos_full), pattern="\\.\\d.*", replacement="")==i, ], MARGIN=2, FUN=function(x) { median(x) } ))
rownames(try_table_npsuperclass_list_pos) <- unique(gsub(x=rownames(try_table_npsuperclass_list_pos_full), pattern="\\.\\d.*", replacement=""))
rownames(try_table_npsuperclass_list_pos) <- gsub(x=rownames(try_table_npsuperclass_list_pos), pattern="GOT|OEL", replacement="SWE")
rownames(try_table_npsuperclass_list_pos) <- gsub(x=rownames(try_table_npsuperclass_list_pos), pattern="OE", replacement="SWE")
rownames(try_table_npsuperclass_list_pos) <- gsub(x=rownames(try_table_npsuperclass_list_pos), pattern="HAL", replacement="GER")Take the class information in negative mode.
try_table_npsuperclass_list_neg_full <- make_classes_at_level(level=2, div_samples=marchantiales$div_npclasses_samples_neg)Fix naming.
try_table_npsuperclass_list_neg <- NULL
for (i in unique(gsub(x=rownames(try_table_npsuperclass_list_neg_full), pattern="\\.\\d.*", replacement=""))) try_table_npsuperclass_list_neg <- rbind(try_table_npsuperclass_list_neg, apply(X=try_table_npsuperclass_list_neg_full[gsub(x=rownames(try_table_npsuperclass_list_neg_full), pattern="\\.\\d.*", replacement="")==i, ], MARGIN=2, FUN=function(x) { median(x) } ))
rownames(try_table_npsuperclass_list_neg) <- unique(gsub(x=rownames(try_table_npsuperclass_list_neg_full), pattern="\\.\\d.*", replacement=""))
rownames(try_table_npsuperclass_list_neg) <- gsub(x=rownames(try_table_npsuperclass_list_neg), pattern="GOT|OEL", replacement="SWE")
rownames(try_table_npsuperclass_list_neg) <- gsub(x=rownames(try_table_npsuperclass_list_neg), pattern="OE", replacement="SWE")
rownames(try_table_npsuperclass_list_neg) <- gsub(x=rownames(try_table_npsuperclass_list_neg), pattern="HAL", replacement="GER")Join pos and neg tables.
try_table_npsuperclass_list <- cbind(try_table_npsuperclass_list_pos, try_table_npsuperclass_list_neg)
try_table_npsuperclass_list <- cbind(sapply(unique(colnames(try_table_npsuperclass_list)[duplicated(colnames(try_table_npsuperclass_list))]), function(x) rowSums(try_table_npsuperclass_list[,grepl(paste(x, "$", sep=""), colnames(try_table_npsuperclass_list))])), try_table_npsuperclass_list[,!duplicated(colnames(try_table_npsuperclass_list)) & ! duplicated(colnames(try_table_npsuperclass_list), fromLast=TRUE)])Add the total number of molecules belonging to biosynthetic pathways to the main trait table.
try_table$`Molecules in Biosynthetic pathways` <- rowSums(try_table_npsuperclass_list)
try_table_colnames_1st <- c(try_table_colnames_1st, "Molecules in Biosynthetic pathways")
try_table_colnames_2nd <- c(try_table_colnames_2nd, "")Add table with molecular pathway information to main trait table.
try_table_selected_nppathway <- try_table_nppathway_list
try_table <- cbind(try_table, try_table_selected_nppathway)
try_table_colnames_1st <- c(try_table_colnames_1st, colnames(try_table_selected_nppathway))
try_table_colnames_2nd <- c(try_table_colnames_2nd, rep("", times=length(colnames(try_table_selected_nppathway))))Add table with molecular class information to main trait table.
try_table_selected_npsuperclass <- try_table_npsuperclass_list[, grep(x=colnames(try_table_npsuperclass_list), pattern=".*; ", perl=TRUE)]
try_table <- cbind(try_table, try_table_selected_npsuperclass)
try_table_colnames_1st <- c(try_table_colnames_1st, gsub(x=colnames(try_table_selected_npsuperclass), pattern="; .*", replacement=""))
try_table_colnames_2nd <- c(try_table_colnames_2nd, gsub(x=colnames(try_table_selected_npsuperclass), pattern=".*; ", replacement=""))Create table containing the molecular descriptors.
Fix naming.
try_table_mdes_list <- NULL
for (i in unique(gsub(x=rownames(try_table_mdes_list_full), pattern="\\.\\d.*", replacement=""))) try_table_mdes_list <- rbind(try_table_mdes_list, apply(X=try_table_mdes_list_full[gsub(x=rownames(try_table_mdes_list_full), pattern="\\.\\d.*", replacement="")==i, ], MARGIN=2, FUN=function(x) { median(x) } ))
rownames(try_table_mdes_list) <- unique(gsub(x=rownames(try_table_mdes_list_full), pattern="\\.\\d.*", replacement=""))
rownames(try_table_mdes_list) <- gsub(x=rownames(try_table_mdes_list), pattern="GOT|OEL", replacement="SWE")
rownames(try_table_mdes_list) <- gsub(x=rownames(try_table_mdes_list), pattern="OE", replacement="SWE")
rownames(try_table_mdes_list) <- gsub(x=rownames(try_table_mdes_list), pattern="HAL", replacement="GER")Take high-level descriptors as primary (abstracted) category in TRY.
Take low-level molecular descriptors as second category in TRY. They are represented by the CDK abbreviations.
Add table with molecular descriptors to main trait table.
try_table <- cbind(try_table, try_table_mdes_list)
try_table_colnames_1st <- c(try_table_colnames_1st, try_table_mdes_high_level)
try_table_colnames_2nd <- c(try_table_colnames_2nd, try_table_mdes_low_level)Finally, export the table as TSV file. This file can be directly shared with TRY.