## ----vali,echo=FALSE,fig.cap="Figure 1: List of implemented features in PSSMCOOL package",out.width = '70%'---- knitr::include_graphics("figures/feature_table.jpg") ## ----------------------------------------------------------------------------- library(PSSMCOOL) ## ----pssm-ac,echo=FALSE,fig.cap="Figure 2: process of extracting PSSM-AC feature vector from PSSM",out.width = '70%'---- knitr::include_graphics("figures/pssm_ac.jpg") ## ----------------------------------------------------------------------------- X<-pssm_ac(system.file("extdata", "C7GQS7.txt.pssm", package="PSSMCOOL")) head(X, n = 50) ## ----dpc-pssm,echo=FALSE,fig.cap="Figure 3: process of extracting DPC-PSSM feature vector from PSSM",out.width = '70%'---- knitr::include_graphics("figures/dpc-pssm.jpg") ## ----------------------------------------------------------------------------- X<-aac_pssm(system.file("extdata", "C7GQS7.txt.pssm", package="PSSMCOOL")) head(X, n = 50) ss<-dpc_pssm(system.file("extdata", "C7GQS7.txt.pssm", package="PSSMCOOL")) head(X, n = 50) ss<-aadp_pssm(system.file("extdata", "C7GQS7.txt.pssm", package="PSSMCOOL")) head(X, n = 50) ## ----trigram,echo=FALSE,fig.cap="Figure 4: process of extracting trigram-PSSM feature vector from PSSM",out.width = '70%'---- knitr::include_graphics("figures/trigram.jpg") ## ----------------------------------------------------------------------------- X<-trigrame_pssm(paste0(system.file("extdata",package="PSSMCOOL"),"/C7GSI6.txt.pssm")) head(X, n = 50) ## ----pse-pssm,echo=FALSE,fig.cap="Figure 5: process of extracting Pse-PSSM feature vector from PSSM",out.width = '70%'---- knitr::include_graphics("figures/pse-pssm.jpg") ## ----------------------------------------------------------------------------- X<-pse_pssm(system.file("extdata", "C7GQS7.txt.pssm", package="PSSMCOOL")) head(X, n = 50) ## ----k-separated,echo=FALSE,fig.cap="Figure 6: process of extracting K-separated-bigam-PSSM feature vector from PSSM",out.width = '70%'---- knitr::include_graphics("figures/k-separated.jpg") ## ----------------------------------------------------------------------------- X<-k_separated_bigrams_pssm(system.file("extdata", "C7GQS7.txt.pssm", package="PSSMCOOL"),5) head(X, n = 50) ## ----eedp,echo=FALSE,fig.cap="Figure 7: process of extracting EDP-EEDP-MEDP feature vectors from PSSM",out.width = '70%'---- knitr::include_graphics("figures/EEDP.jpg") ## ----------------------------------------------------------------------------- X<-EDP_EEDP_MEDP(paste0(system.file("extdata",package="PSSMCOOL"),"/C7GS61.txt.pssm")) head(X[[3]], n = 50) # in here X[[3]] indicates MEDP feature vector ## ----ab-pssm,echo=FALSE,fig.cap="Figure 8: process of extracting AB-PSSM feature vectors from PSSM",out.width = '70%'---- knitr::include_graphics("figures/AB-PSSM.jpg") ## ----------------------------------------------------------------------------- X<- AB_PSSM(system.file("extdata","C7GRQ3.txt.pssm",package="PSSMCOOL")) head(X[1], n = 50) ## ----------------------------------------------------------------------------- X<-AATP_TPC(paste0(system.file("extdata",package="PSSMCOOL"),"/C7GQS7.txt.pssm")) head(X[[2]], n = 50) #in here X[[2]] indicates AATP feature vector ## ----------------------------------------------------------------------------- X<-CS_PSe_PSSM(system.file("extdata", "C7GSI6.txt.pssm", package="PSSMCOOL"),"total") head(X, n = 50) ## ----fpssm,echo=FALSE,fig.cap="Figure 9: process of making FPSSM and extracting corresponding feature vectors",out.width = '70%'---- knitr::include_graphics("figures/s-fpssm.jpg") ## ----------------------------------------------------------------------------- X<-FPSSM(system.file("extdata","C7GQS7.txt.pssm",package="PSSMCOOL"),20) head(X, n = 50) ## ----scsh2,echo=FALSE,fig.cap="Figure 10: process of extracting scsh2 feature vector",out.width = '70%'---- knitr::include_graphics("figures/SCSH2.jpg") ## ----scshtable,echo=FALSE,fig.cap="Figure 11: tables of all 2-mers and all 3-mers",out.width = '70%'---- knitr::include_graphics("figures/scshtable.jpg") ## ----------------------------------------------------------------------------- X<- scsh2(system.file("extdata","C7GRQ3.txt.pssm",package="PSSMCOOL"),2) head(X, n = 200) ## ----------------------------------------------------------------------------- X<-rpssm(system.file("extdata", "C7GQS7.txt.pssm", package="PSSMCOOL")) head(X, n = 50) ## ----ccpssm,echo=FALSE,fig.cap="Figure 12: process of extracting PSSM-CC feature vector",out.width = '70%'---- knitr::include_graphics("figures/cc-pssm.jpg") ## ----------------------------------------------------------------------------- X<-pssm_cc(system.file("extdata","C7GQS7.txt.pssm",package="PSSMCOOL")) head(X, n = 50) ## ----------------------------------------------------------------------------- X<-Discrete_Cosine_Transform(system.file("extdata", "C7GQS7.txt.pssm", package="PSSMCOOL")) head(X, n = 50) ## ----dwt,echo=FALSE,fig.cap="Figure 13: Schematic diagram of a DWT with 4 levels",out.width = '70%'---- knitr::include_graphics("figures/dwt.jpg") ## ----------------------------------------------------------------------------- X<-dwt_PSSM(system.file("extdata", "C7GQS7.txt.pssm", package="PSSMCOOL")) head(X, n = 50) ## ----disulfid,echo=FALSE,fig.cap="Figure 14: The process of extracting disulfide-PSSM feature from the PSSM",out.width = '70%'---- knitr::include_graphics("figures/disulfid.jpg") ## ----------------------------------------------------------------------------- X<-disulfid(system.file("extdata", "C7GQS7.txt.pssm", package="PSSMCOOL")) head(X[,1:50]) ## ----------------------------------------------------------------------------- X<-DP_PSSM(system.file("extdata", "C7GQS7.txt.pssm", package="PSSMCOOL")) head(X, n = 50) ## ----------------------------------------------------------------------------- X<-DFMCA_PSSM(system.file("extdata", "C7GQS7.txt.pssm", package="PSSMCOOL"),7) head(X, n = 50) ## ----------------------------------------------------------------------------- X<-grey_pssm_pseAAC(system.file("extdata", "C7GQS7.txt.pssm", package="PSSMCOOL")) head(X, n = 50) ## ----smooth,echo=FALSE,fig.cap="Figure 15: process of smoothed-PSSM generation, (A) represents the PSSM and (B) represents the smoothed-PSSM",out.width = '70%'---- knitr::include_graphics("figures/smoothed.jpg") ## ----------------------------------------------------------------------------- X<-smoothed_PSSM(system.file("extdata", "C7GQS7.txt.pssm", package="PSSMCOOL"),7,11,c(2,3,8,9)) head(X[,1:50], n = 50) ## ----------------------------------------------------------------------------- X<-kiderafactor(system.file("extdata", "C7GQS7.txt.pssm", package="PSSMCOOL"),c(2,3,8,9)) head(X[,1:50], n = 50) ## ----------------------------------------------------------------------------- X<-MBMGACPSSM(system.file("extdata", "C7GQS7.txt.pssm", package="PSSMCOOL")) head(X, n = 50) ## ----------------------------------------------------------------------------- X<-LPC_PSSM(system.file("extdata", "C7GQS7.txt.pssm", package="PSSMCOOL")) head(X, n = 50) ## ----pssm400,echo=FALSE,fig.cap="Figure 16: process of extracting PSSM400 feature vector, which for amino acid S, represents the corresponding rows in PSSM",out.width = '70%'---- knitr::include_graphics("figures/pssm400.jpg") ## ----------------------------------------------------------------------------- X<-pssm400(system.file("extdata","C7GQS7.txt.pssm",package="PSSMCOOL")) head(X, n = 50) ## ----------------------------------------------------------------------------- X<- RPM_PSSM(system.file("extdata","C7GRQ3.txt.pssm",package="PSSMCOOL")) X ## ----------------------------------------------------------------------------- X<-PSSMBLOCK(system.file("extdata", "C7GQS7.txt.pssm", package="PSSMCOOL"),5) head(X, n = 50) ## ----pssmsd,echo=FALSE,fig.cap="Figure 17: process of extracting PSSM-SD feature vector values for column j",out.width = '70%'---- knitr::include_graphics("figures/pssmsd.jpg") ## ----------------------------------------------------------------------------- X<-PSSM_SD(system.file("extdata", "C7GQS7.txt.pssm", package="PSSMCOOL")) head(X, n = 50) ## ----------------------------------------------------------------------------- X<-pssm_seg(system.file("extdata", "C7GQS7.txt.pssm", package="PSSMCOOL"),3) head(X, n = 50) ## ----------------------------------------------------------------------------- X<-SOMA_PSSM(system.file("extdata", "C7GQS7.txt.pssm", package="PSSMCOOL")) head(X, n = 50) ## ----------------------------------------------------------------------------- X<-SVD_PSSM(system.file("extdata", "C7GQS7.txt.pssm", package="PSSMCOOL")) head(X, n = 20) ## ----eval=FALSE--------------------------------------------------------------- # # install.packages("PSSMCOOL") # # library(PSSMCOOL) ## ----eval=FALSE--------------------------------------------------------------- # current_directory <- "/home/PSSMCOOL/" # Please provide your desired directory. # setwd(current_directory) ## ----eval=FALSE--------------------------------------------------------------- # pssm_url <- 'https://github.com/BioCool-Lab/PSSMCOOL/raw/main/classification-code-data/all_needed_pssms90.zip' # download.file(pssm_url, './all_needed_pssm90.zip', method = 'auto', quiet = FALSE) # unzip('all_needed_pssm90.zip', exdir = 'all_needed_pssm90') # PSSM_directory <- 'all_needed_pssm90/all_needed_pssms90/' ## ----eval=FALSE--------------------------------------------------------------- # url <- "https://raw.githubusercontent.com/BioCool-Lab/PSSMCOOL/main/classification-code-data/positive.csv" # download.file(url, './PositiveData.csv') # positive_data <- read.csv("./PositiveData.csv", header = TRUE) ## ----eval=FALSE--------------------------------------------------------------- # url <- "https://raw.githubusercontent.com/BioCool-Lab/PSSMCOOL/main/classification-code-data/negative.csv" # download.file(url, './NegativeData.csv') # negative_data <- read.csv("./NegativeData.csv", header = TRUE) ## ----eval=FALSE--------------------------------------------------------------- # positiveFeatures<- c() # for(i in 1:dim(positive_data)[1]) { # ff<-FPSSM2(paste0(PSSM_directory, positive_data[i,1],'.fasta.pssm'), # paste0(PSSM_directory, positive_data[i,2],'.fasta.pssm'), 20) # positiveFeatures<-rbind(positiveFeatures, ff) # } ## ----eval=FALSE--------------------------------------------------------------- # positiveFirstColumn <- c() # for(i in 1:dim(positive_data)[1]) { # dd <- paste(positive_data[i,1], '-' ,positive_data[i,2]) # positiveFirstColumn <- rbind(positiveFirstColumn, dd) # } ## ----eval=FALSE--------------------------------------------------------------- # pos_class <- rep("Interaction", dim(positiveFeatures)[1]) # positiveFeatures2 <- cbind(positiveFirstColumn, positiveFeatures, pos_class) ## ----eval=FALSE--------------------------------------------------------------- # negativeFeatures <- c() # for(i in 1:dim(negative_data)[1]) { # ff2<-FPSSM2(paste0(PSSM_directory, negative_data[i,1],'.fasta.pssm'), # paste0(PSSM_directory, negative_data[i,2],'.fasta.pssm'), 20) # negativeFeatures<-rbind(negativeFeatures, ff2) # } ## ----eval=FALSE--------------------------------------------------------------- # negativeFirstColumn <- c() # for(i in 1:dim(negative_data)[1]) { # dd2 <- paste(negative_data[i,1], '-' ,negative_data[i,2]) # negativeFirstColumn <- rbind(negativeFirstColumn, dd2) # } ## ----eval=FALSE--------------------------------------------------------------- # neg_class <- rep("Non.Interaction", dim(negativeFeatures)[1]) # negativeFeatures2 <- cbind(negativeFirstColumn, negativeFeatures, neg_class) ## ----eval=FALSE--------------------------------------------------------------- # mainDataSet <- rbind(positiveFeatures2, negativeFeatures2) ## ----eval=FALSE--------------------------------------------------------------- # install.packages('caret', dependencies = TRUE) # library(caret) # bmp.R2.submission.data.df <- as.data.frame(mainDataSet) # colnames(bmp.R2.submission.data.df)[1] <- "interactions" # dim(bmp.R2.submission.data.df)#1730 102 ## ----eval=FALSE--------------------------------------------------------------- # rownames(bmp.R2.submission.data.df) <- bmp.R2.submission.data.df$interactions ## ----eval=FALSE--------------------------------------------------------------- # bmp.R2.submission.data.df <-bmp.R2.submission.data.df[,-1] # View(bmp.R2.submission.data.df) # colnames(bmp.R2.submission.data.df) <- c(paste0('Frt', 1: dim(positiveFeatures)[2]), 'Class') # dim(bmp.R2.submission.data.df)#1730 101 # table(bmp.R2.submission.data.df$Class) ## ----eval=FALSE--------------------------------------------------------------- # bmp.R2.submission.data.df$Class <- # as.factor(bmp.R2.submission.data.df$Class) # write.csv(bmp.R2.submission.data.df, 'DataSet.csv') ## ----eval=FALSE--------------------------------------------------------------- # bmp.R2.submission.data.df <- read.csv("DataSet.csv") # setting.the.trainControl.3 <- function() # { # #setting the trainControl function parameter: repeated CV; downsampling; # set.seed(100) # fitControl <- trainControl(## 10-fold CV # method = "cv", # returnData = TRUE, # classProbs = TRUE, # ) # return(fitControl) # } ## ----eval=FALSE--------------------------------------------------------------- # trainControl.for.PSSM <- setting.the.trainControl.3() ## ----eval=FALSE--------------------------------------------------------------- # cross.validation.bulit.model.treebag <- # train(Class ~ ., data = bmp.R2.submission.data.df, # method = "treebag", # trControl = trainControl.for.PSSM, # verbose = FALSE) # print(cross.validation.bulit.model.treebag$results) ## ----eval=FALSE--------------------------------------------------------------- # cross.validation.bulit.model.C5.0Tree <- # train(Class ~ ., data = bmp.R2.submission.data.df, # method = "C5.0Tree", # trControl = trainControl.for.PSSM, # verbose = FALSE) # print(cross.validation.bulit.model.C5.0Tree$results) ## ----sessionInfo,echo=FALSE,out.width = '70%'--------------------------------- knitr::include_graphics("figures/sessionInfo.PNG")