--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/NMF/NMF-working-2-5-20.R	Thu Feb 06 14:20:36 2020 -0500
@@ -0,0 +1,190 @@
+NAMEOFOUTPUTFILE<-"output1.csv"
+
+SuperAwesometrial <- read.delim2("input1.tabular", header=FALSE)
+#once you've used the other script to turn the FASFA into a CSV, copypaste the filepath and name 
+#of the csv into this line between the quote marks.  
+
+SBF<-read.csv("input3.csv", stringsAsFactors = FALSE, header = FALSE)
+SBF<-t(SBF)
+
+PositiveMotifs <- read.csv("input2.csv", stringsAsFactors=FALSE)
+#because of R reasons, it is required that the motifs in this file have blank cells instead of spaces where there is no letter in 
+#the motif
+
+YsToim<-rep("xY",times=nrow(PositiveMotifs))
+PositiveMotifs[,11]<-YsToim
+
+
+
+################################################################################################################################
+#I have to paste them, then split and unlist them, then find the x and paste again
+Positive9Letters<-PositiveMotifs[,4:18]
+#head(Positive9Letters)
+PositiveTrueMotifs<-c()
+
+AccessionNumbers<-as.character(SBF[2:nrow(SBF),1])
+AccessionNumbers<-AccessionNumbers[!is.na(AccessionNumbers)]
+ALLPOSSIBLE<-SuperAwesometrial[,1]
+ALLPOSSIBLE<-as.character(ALLPOSSIBLE)
+################################################################################################################################
+
+for (q in 1:nrow(Positive9Letters)) {
+  LeftJust<-0
+  RightJust<-0
+  
+  motifmotif<-Positive9Letters[q,]
+  motifmotif<-paste(motifmotif, collapse = "",sep = "")
+  
+  motifmotif<-unlist(strsplit(motifmotif, split = ""))
+  
+  position <- match(x = "x", table = motifmotif)
+  LeftJust<-position-1
+  RightJust<-length(motifmotif)-position-1
+  
+  LeftSpaces<-rep(x=" ", times=(7-LeftJust))
+  RightSpaces<-rep(x=" ", times=(7-RightJust))
+  
+  motifmotif<-motifmotif[!motifmotif %in% c("x")]
+  
+  motifmotif<-c(LeftSpaces,motifmotif,RightSpaces)
+  motifmotif<-paste(motifmotif, collapse = "",sep = "")
+  PositiveTrueMotifs<-c(PositiveTrueMotifs,motifmotif)
+}
+
+
+
+################################################################################################################################
+allmotifs<-matrix(data=rep("Motifs", times= 1000000),ncol = 1)
+thenames<-matrix(data=rep("AccessionNumbers", times= 1000000),ncol = 1)
+################################################################################################################################
+
+################################################################################################################################
+
+#I need to preallocate these vectors.  I will find out how many y's there are total and then make the vector that many long
+#Or what I need is two separate loops.  First loop finds all the accession number positions that Grep to the FASTA (which is called ALLPOSSIBLE)
+#then take only those AAs from the fasta and count their y's, preallocate the vector for part 2 to that many y's
+#those accessions and such as saved in a vector... this seems like it would be no faster actually
+
+#then_that_are <- which(AccessionNumbers %in% ALLPOSSIBLE)
+
+MotifNumber<-2
+
+#TrueMotifNums<-which(ALLPOSSIBLE %in% AccessionNumbers)
+#fihlodeANs<-c()
+
+locations<-unique(grep(paste(AccessionNumbers,collapse="|"), ALLPOSSIBLE))
+
+if (sum(locations)>0){
+  whereisit<-locations
+  for (u in 1:length(whereisit)) {
+    i<-whereisit[u]
+    name<-c()
+    data<-c()
+    name<-as.character(SuperAwesometrial[i,1])
+    #the name of each protein is the first column 
+    name<-sub(x=name, pattern=",", replacement="")
+    #the names may contain commas, remove them
+    data<-as.character(SuperAwesometrial[i,3])
+    #the amino acids are stored in the third column
+    data<-strsplit(data,"")
+    #split them into their component letters
+    data<-unlist(data)
+    #turn them into a vector
+    motif<-c()
+    
+    #this part below is where I can speed things up
+    The_Ys<-data=="Y"
+    #find any Y in the protein
+    if (sum(The_Ys>0)){ #if there is at least one Y
+      Where_are_they<-which(The_Ys %in% TRUE)
+      for (z in 1:length(Where_are_they)) { #then for every Y, make a motif
+        
+        j<-Where_are_they[z]
+        #for (j in 1:length(data)){
+        #if ("Y" %in% data[j]){
+        #if there is a Y aka Tyrosine in the data
+        #allmotifs=rbind(allmotifs,data[(i-4):(i+4)])
+        a <- j-7
+        a<-ifelse(a<1, a <- 1, a <- a)
+        # if (a<1){
+        #   a <- 1
+        # }
+        b<-j+7
+        b<-ifelse(b>length(data), b <- length(data), b <- 
+                    b)
+        # if (b>length(data)){
+        #   b<-length(data)
+        # }
+        #take the motif that is +/- 4 from that Y, sanity checks so that values are never off the grid from the protein
+        
+        LeftSide<-7-(j-a)
+        RightSide<-7-(b-j)
+        #how is the motif justified?  Does it have exactly 4 letters to the left/right, or does it not?
+        
+        leftspaces<-rep(" ",times=LeftSide)
+        rightspaces<-rep(" ",times=RightSide)
+        #add blank spaces if the motif has less than 4 letters to the left/right
+        
+        
+        motif<-(data[(a):(b)])
+        motif<-c(leftspaces,motif,rightspaces)
+        #save that motif, which is the Y and +/- 4 amino acids, including truncation
+        
+        # lens<-c(lens,length(motif))
+        # leni<-c(leni,i)
+        # lenj<-c(lenj,j)
+        
+        motif<-paste(motif, sep="", collapse="")
+        #the 4 amino acids, put them back together into a single string
+        motif<-matrix(data=c(motif),nrow = 1)
+        namesss<-matrix(data=c(name),nrow = 1)
+        #keep this motif and separately keep the name of the protein it came from
+        
+        # allmotifs<-rbind(allmotifs,motif)
+        # thenames<-rbind(thenames,namesss)
+        allmotifs[MotifNumber,1]<-motif
+        thenames[MotifNumber,1]<-namesss
+        MotifNumber<-MotifNumber+1
+        
+        #add names and motifs to a growing list
+        
+        # write.table(motif, file="TRIALTIALRIAALSKFDJSD.csv", quote=FALSE, sep=",",
+        #             row.names=FALSE,col.names = FALSE, na="", append=TRUE)
+        #and then write it into a csv, the sep is needed so that the two pieces of the data frame are separated
+        #append has 1to equal true because this thing will loop around many times adding more and more data points
+        #you must create a new filename/filepath with each new data you run
+      }
+      
+    }
+  }
+}
+
+
+
+
+################################################################################################################################
+################################################################################################################################
+################################################################################################################################
+
+
+# for (i in 1:nrow(SuperAwesometrial)){
+# 
+# }
+
+names(allmotifs)<-thenames
+
+truemotifs<-allmotifs[!duplicated(allmotifs)]
+#truenames<-thenames[!duplicated(thenames)]
+#remove duplicates from the motifs and names
+
+#make the motifs and names into matrices
+
+
+truemotifs<-truemotifs[!truemotifs %in% PositiveTrueMotifs]
+
+outputfile<-cbind(names(truemotifs),truemotifs)
+
+outputfile <- gsub(",","",outputfile)
+
+write.table(outputfile, file=NAMEOFOUTPUTFILE, quote=FALSE, sep=",",
+             row.names=FALSE,col.names = FALSE, na="", append=TRUE)