## ----biocstyle, echo = FALSE, results = "asis"-------------------------------- BiocStyle::markdown() ## ---- echo = FALSE------------------------------------------------------------ knitr::opts_chunk$set( collapse = TRUE, comment = "#>" ) ## ----init, message = FALSE, echo = FALSE, results = "hide"-------------------- ## Silently loading all packages library(BiocStyle) library(peakPantheR) library(faahKO) library(pander) ## ---- eval = FALSE------------------------------------------------------------ # if (!requireNamespace("BiocManager", quietly = TRUE)) # install.packages("BiocManager") # # BiocManager::install("peakPantheR") ## ---- eval = FALSE------------------------------------------------------------ # # Install devtools # if(!require("devtools")) install.packages("devtools") # devtools::install_github("phenomecentre/peakPantheR") ## ---- eval = FALSE------------------------------------------------------------ # library(peakPantheR) # # peakPantheR_start_GUI(browser = TRUE) # # To exit press ESC in the command line ## ---- fig.align="center", out.width = "700px", echo = FALSE------------------- knitr::include_graphics("../man/figures/example-UI.png") ## ---- eval = FALSE------------------------------------------------------------ # if (!requireNamespace("BiocManager", quietly = TRUE)) # install.packages("BiocManager") # # BiocManager::install("faahKO") ## ----------------------------------------------------------------------------- library(faahKO) ## file paths input_spectraPaths <- c(system.file('cdf/KO/ko15.CDF', package = "faahKO"), system.file('cdf/KO/ko16.CDF', package = "faahKO"), system.file('cdf/KO/ko18.CDF', package = "faahKO")) input_spectraPaths ## ---- eval=FALSE-------------------------------------------------------------- # # targetFeatTable # input_targetFeatTable <- data.frame(matrix(vector(), 2, 8, dimnames=list(c(), # c("cpdID", "cpdName", "rtMin", "rt", "rtMax", "mzMin", # "mz", "mzMax"))), stringsAsFactors=FALSE) # input_targetFeatTable[1,] <- c(1, "Cpd 1", 3310., 3344.888, 3390., 522.194778, # 522.2, 522.205222) # input_targetFeatTable[2,] <- c(2, "Cpd 2", 3280., 3385.577, 3440., 496.195038, # 496.2, 496.204962) # input_targetFeatTable[,c(1,3:8)] <- sapply(input_targetFeatTable[,c(1,3:8)], # as.numeric) ## ---- results = "asis", echo = FALSE------------------------------------------ # use pandoc for improved readability input_targetFeatTable <- data.frame(matrix(vector(), 2, 8, dimnames=list(c(), c("cpdID", "cpdName", "rtMin", "rt", "rtMax", "mzMin", "mz", "mzMax"))), stringsAsFactors=FALSE) input_targetFeatTable[1,] <- c(1, "Cpd 1", 3310., 3344.888, 3390., 522.194778, 522.2, 522.205222) input_targetFeatTable[2,] <- c(2, "Cpd 2", 3280., 3385.577, 3440., 496.195038, 496.2, 496.204962) input_targetFeatTable[,c(1,3:8)] <- sapply(input_targetFeatTable[,c(1,3:8)], as.numeric) rownames(input_targetFeatTable) <- NULL pander::pandoc.table(input_targetFeatTable, digits = 9) ## ---- eval=FALSE-------------------------------------------------------------- # library(faahKO) # # # Define the file paths (3 samples) # input_spectraPaths <- c(system.file('cdf/KO/ko15.CDF', package = "faahKO"), # system.file('cdf/KO/ko16.CDF', package = "faahKO"), # system.file('cdf/KO/ko18.CDF', package = "faahKO")) # # # Define the targeted features (2 features) # input_targetFeatTable <- data.frame(matrix(vector(), 2, 8, dimnames=list(c(), # c("cpdID", "cpdName", "rtMin", "rt", "rtMax", "mzMin", # "mz", "mzMax"))), stringsAsFactors=FALSE) # input_targetFeatTable[1,] <- c("ID-1", "Cpd 1", 3310., 3344.888, 3390., # 522.194778, 522.2, 522.205222) # input_targetFeatTable[2,] <- c("ID-1", "Cpd 2", 3280., 3385.577, 3440., # 496.195038, 496.2, 496.204962) # input_targetFeatTable[,3:8] <- sapply(input_targetFeatTable[,3:8], as.numeric) # # # Define some random compound and spectra metadata # # cpdMetadata # input_cpdMetadata <- data.frame(matrix(data=c('a','b',1,2), nrow=2, ncol=2, # dimnames=list(c(), c('testcol1','testcol2')), # byrow=FALSE), stringsAsFactors=FALSE) # # spectraMetadata # input_spectraMetadata <- data.frame(matrix(data=c('c','d','e',3,4,5), nrow=3, # ncol=2, # dimnames=list(c(),c('testcol1','testcol2')), # byrow=FALSE), stringsAsFactors=FALSE) # # # Initialise a simple peakPantheRAnnotation object # # [3 files, 2 features, no uROI, no FIR] # initAnnotation <- peakPantheRAnnotation(spectraPaths=input_spectraPaths, # targetFeatTable=input_targetFeatTable, # cpdMetadata=input_cpdMetadata, # spectraMetadata=input_spectraMetadata) # # # Rename and save the annotation to disk # annotationObject <- initAnnotation # save(annotationObject, # file = './example_annotation_ppR_UI.RData', # compress=TRUE) # ## ---- eval=FALSE-------------------------------------------------------------- # # Define targeted features without uROI and FIR (2 features) # input_targetFeatTable <- data.frame(matrix(vector(), 2, 8, dimnames=list(c(), # c("cpdID", "cpdName", "rtMin", "rt", "rtMax", "mzMin", # "mz", "mzMax"))), stringsAsFactors=FALSE) # input_targetFeatTable[1,] <- c("ID-1", "Cpd 1", 3310., 3344.888, 3390., # 522.194778, 522.2, 522.205222) # input_targetFeatTable[2,] <- c("ID-1", "Cpd 2", 3280., 3385.577, 3440., # 496.195038, 496.2, 496.204962) # input_targetFeatTable[,3:8] <- sapply(input_targetFeatTable[,3:8], as.numeric) # # # save to disk # write.csv(input_targetFeatTable, # file = './1-fitParams_example_UI.csv', # row.names = FALSE) ## ---- results = "asis", echo = FALSE------------------------------------------ # use pandoc for improved readability input_targetFeatTable <- data.frame(matrix(vector(), 2, 8, dimnames=list(c(), c("cpdID", "cpdName", "rtMin", "rt", "rtMax", "mzMin", "mz", "mzMax"))), stringsAsFactors=FALSE) input_targetFeatTable[1,] <- c("ID-1", "Cpd 1", 3310., 3344.888, 3390., 522.194778, 522.2, 522.205222) input_targetFeatTable[2,] <- c("ID-1", "Cpd 2", 3280., 3385.577, 3440., 496.195038, 496.2, 496.204962) input_targetFeatTable[,3:8] <- sapply(input_targetFeatTable[,3:8], as.numeric) rownames(input_targetFeatTable) <- NULL pander::pandoc.table(input_targetFeatTable, digits = 9) ## ---- eval=FALSE-------------------------------------------------------------- # # Define the spectra paths and metada # input_spectraMeta <- data.frame(matrix(vector(), 3, 3, # dimnames=list(c(),c("filepath","testcol1","testcol2"))), # stringsAsFactors=FALSE) # input_spectraMeta[1,] <- c(system.file('cdf/KO/ko15.CDF', package = "faahKO"), # "c", 3) # input_spectraMeta[2,] <- c(system.file('cdf/KO/ko16.CDF', package = "faahKO"), # "d", 4) # input_spectraMeta[3,] <- c(system.file('cdf/KO/ko18.CDF', package = "faahKO"), # "e", 5) # # # save to disk # write.csv(input_spectraMeta, # file = './2-spectraMetaWPath_example_UI.csv', # row.names = FALSE) ## ---- results = "asis", echo = FALSE------------------------------------------ # use pandoc for improved readability input_spectraMeta <- data.frame(matrix(vector(), 3, 3, dimnames=list(c(),c("filepath","testcol1","testcol2"))), stringsAsFactors=FALSE) input_spectraMeta[1,] <- c(system.file('cdf/KO/ko15.CDF', package = "faahKO"), "c", 3) input_spectraMeta[2,] <- c(system.file('cdf/KO/ko16.CDF', package = "faahKO"), "d", 4) input_spectraMeta[3,] <- c(system.file('cdf/KO/ko18.CDF', package = "faahKO"), "e", 5) rownames(input_spectraMeta) <- NULL pander::pandoc.table(input_spectraMeta, digits = 0) ## ---- eval=FALSE-------------------------------------------------------------- # # Define the feature metada # input_featMeta <- data.frame(matrix(vector(), 2, 2, # dimnames=list(c(),c("testcol1","testcol2"))), # stringsAsFactors=FALSE) # input_featMeta[1,] <- c("a", 1) # input_featMeta[2,] <- c("b", 2) # # # save to disk # write.csv(input_featMeta, # file = './3-featMeta_example_UI.csv', # row.names = FALSE) ## ---- results = "asis", echo = FALSE------------------------------------------ # use pandoc for improved readability input_featMeta <- data.frame(matrix(vector(), 2, 2, dimnames=list(c(),c("testcol1","testcol2"))), stringsAsFactors=FALSE) input_featMeta[1,] <- c("a", 1) input_featMeta[2,] <- c("b", 2) rownames(input_featMeta) <- NULL pander::pandoc.table(input_featMeta, digits = 0) ## ---- echo = FALSE------------------------------------------------------------ devtools::session_info()