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/programming/Rcode/Rexamples/R/SNPAssortedMating.R

https://github.com/DannyArends/Other
R | 364 lines | 321 code | 20 blank | 23 comment | 48 complexity | 2d1d7c099e48ee8ef852cb2cfd65f88d MD5 | raw file
    

  1. #####################################################################
    2. 

  2. #
    3. 

  3. # AssortedMating.R
    4. 

  4. #
    5. 

  5. # copyright parent_check (c) 2009, Danny Arends
    6. 

  6. # last modified Apr, 2009
    7. 

  7. # first written Apr, 2009
    8. 

  8. # 
    9. 

  9. # Contains: assortedmating
    10. 

  10. #
    11. 

  11. ######################################################################
    12. 

  12. 

  13. plotDIR <- function(dir = "D:\\GBIC\\Lude\\Resultsgood", which = 2){
    14. 

  14. 	setwd(dir)
    15. 

  15. 	cnt <- 0
    16. 

  16. 	genome <- NULL
    17. 

  17. 	m_markers <- 1
    18. 

  18. 	m_done <- 0
    19. 

  19. 	for(x in dir()){
    20. 

  20. 		if(!is.na(grep("res",x)==1&&1)){
    21. 

  21. 		chr <- read.table(x,row.names=1,header=FALSE,sep="\t")
    22. 

  22. 		markers <- nrow(chr)
    23. 

  23. 		m_done <- m_done+markers
    24. 

  24. 		score <- max(abs(chr))
    25. 

  25. 		cnt <- cnt+1
    26. 

  26. 		m_markers <- c(m_markers,m_done)
    27. 

  27. 		}
    28. 

  28. 	}
    29. 

  29. 	c <- c("black","gray")
    30. 

  30. 	cnt <- 0
    31. 

  31. 	names <- NULL
    32. 

  32. 	if(which==1){
    33. 

  33. 		plot(x=c(1,m_done),y=c(0,2000),main="Population Score",xlab="Markers",ylab="Chi^2",type="n")
    34. 

  34. 	}else{
    35. 

  35. 		if(which==2){
    36. 

  36. 			plot(x=c(1,m_done),y=c(-150,150),main="InbreadingScores",xlab="Markers",ylab="Chi^2", type="n")
    37. 

  37. 		}else{
    38. 

  38. 			plot(x=c(1,m_done),y=c(-150,150),main="AMScores",xlab="Markers",ylab="Chi^2", type="n")
    39. 

  39. 		}
    40. 

  40. 	}
    41. 

  41. 	for(x in dir()){
    42. 

  42. 		if(!is.na(grep("res",x)==1&&1)){
    43. 

  43. 		cnt <- cnt+1
    44. 

  44. 		names <- c(names,x)
    45. 

  45. 		chr <- read.table(x,row.names=1,header=FALSE,sep="\t")
    46. 

  46. 		colo <- (cnt%%length(c))
    47. 

  47. 		if(colo==0){colo<- length(c)}
    48. 

  48. 		points(x=m_markers[cnt]+1:length(chr[,which]),chr[,which],type="h",col=c[colo], main=x)
    49. 

  49. 		}
    50. 

  50. 	}
    51. 

  51. 	names <- gsub("res","",names)
    52. 

  52. 	names <- gsub(".txt","",names)
    53. 

  53. 	legend("topright",names,lty=1,col=c,cex=.6,ncol=2)
    54. 

  54. }
    55. 

  55. 

  56. plotLength<- function(x,LengthMatrix,name=TRUE,which = 2){
    57. 

  57. 	if(which==1){
    58. 

  58. 		text <- "Inbreading (Chi^2)"
    59. 

  59. 	}else{
    60. 

  60. 		text <- "Deviation from random mating(Chi^2)"
    61. 

  61. 	}
    62. 

  62. 	if(name){
    63. 

  63. 		lbls <- paste("Chr ",LengthMatrix[,1],"_",LengthMatrix[,2],sep="")
    64. 

  64. 		size=0.5
    65. 

  65. 	}else{
    66. 

  66. 		lbls <- rownames(LengthMatrix)
    67. 

  67. 		size=0.7
    68. 

  68. 	}
    69. 

  69. 	plot(x[[2]],type="b",axes=0,xlab="",ylab=text)
    70. 

  70. 	box()
    71. 

  71. 	Axis(side=1,at=1:37,labels=lbls,cex.axis=size,las=0.5,las=2)
    72. 

  72. 	Axis(side=2)
    73. 

  73. }
    74. 

  74. 

  75. assortedmating.init <- function(){
    76. 

  76. 	workD="D:\\GBIC\\Lude\\DataDanny"
    77. 

  77. 	setwd(workD)	
    78. 

  78. 	snps <- as.matrix(read.table("length.txt"))
    79. 

  79. 	LengthMatrix <- NULL
    80. 

  80. 	for(x in dir()[grep("Chr",dir())]){
    81. 

  81. 		if(is.na(grep("res",x)==1&&1)){
    82. 

  82. 			cat("Reading",x,"\n")
    83. 

  83. 			data <- read.table(x,row.names=1)
    84. 

  84. 			for(searching in 1:nrow(snps)){
    85. 

  85. 				chr <- as.numeric(snps[searching,2])
    86. 

  86. 				if(chr %in% data[,1]){
    87. 

  87. 					bp <- as.numeric(snps[searching,3])
    88. 

  88. 					cat("SNPs in length.txt on this chromosome:",snps[searching,1:3],"\n")
    89. 

  89. 					smaller <- which(data[,2]<(bp+1000))
    90. 

  90. 					larger <- which(data[,2]>(bp-1000))
    91. 

  91. 					intersect(smaller,larger)
    92. 

  92. 					if(!is.na(intersect(smaller,larger)&&1)){
    93. 

  93. 						for( y in intersect(smaller,larger)){
    94. 

  94. 							cat("->",rownames(data)[y],data[y,1],data[y,2],"\n")
    95. 

  95. 							LengthMatrix <- rbind(LengthMatrix,data[y,])
    96. 

  96. 						}
    97. 

  97. 					}
    98. 

  98. 				}
    99. 

  99. 			}
    100. 

  100. 		}
    101. 

  101. 	}
    102. 

  102. 	LengthMatrix
    103. 

  103. }
    104. 

  104. 

  105. 

  106. doDir <- function(){
    107. 

  107. setwd("D:\\GBIC\\Lude\\DataDanny")
    108. 

  108. order <- as.vector(read.csv("ChipIDOrderInGenotypeFiles.txt",header=FALSE,sep="\n"))
    109. 

  109. info <- read.csv("ChipIDToSampleInformation.txt",row.names=1,header=TRUE,sep="\t")
    110. 

  110. coln <- c("Chr","Pos",as.vector(order[,1]))
    111. 

  111. for(x in dir()){
    112. 

  112. 	if(!is.na(grep("Chr",x)==1&&1)){
    113. 

  113. 	if(is.na(grep("res",x)==1&&1)){
    114. 

  114. 		data <- read.csv(x,row.names=1,header=TRUE,sep="\t")
    115. 

  115. 		colnames(data) <- coln
    116. 

  116. 		assortedmating(data,info,1,nrow(data)-1,paste("res",x,sep=""),plot=FALSE)
    117. 

  117. 	}
    118. 

  118. 	}
    119. 

  119. }
    120. 

  120. }
    121. 

  121. 

  122. init <- function(){
    123. 

  123. setwd("D:\\GBIC\\Lude\\RAW")
    124. 

  124. data <- read.csv("Chr2.txt",row.names=1,sep="\t")
    125. 

  125. order <- as.vector(read.csv("ChipIDOrderInGenotypeFiles.txt",header=FALSE,sep="\n"))
    126. 

  126. info <- read.csv("ChipIDToSampleInformation.txt",row.names=1,header=TRUE,sep="\t")
    127. 

  127. coln <- c("Chr","Pos",as.vector(order[,1]))
    128. 

  128. colnames(data) <- coln
    129. 

  129. }
    130. 

  130. 

  131. initplottingqq <- function(name="Chromosome 1",resF="resChr1.txt"){
    132. 

  132. 	setwd("D:\\GBIC\\Lude\\Resultsgood")
    133. 

  133. 	r <- read.csv(resF,row.names=1,header=FALSE,sep="\t")
    134. 

  134. 	plottingqq(name,r[,3],3)
    135. 

  135. }
    136. 

  136. 

  137. readallres <- function(){
    138. 

  138. 	setwd("D:\\GBIC\\Lude\\Resultsgood")
    139. 

  139. 	reslist <- NULL
    140. 

  140. 	for(x in dir()){
    141. 

  141. 		if(!is.na(grep("Chr",x)==1&&1)){
    142. 

  142. 			if(!is.na(grep("res",x)==1&&1)){
    143. 

  143. 				cat(x,"\n")
    144. 

  144. 				data <- read.csv(x,row.names=1,header=FALSE,sep="\t")
    145. 

  145. 				reslist <- rbind(reslist,data)
    146. 

  146. 			}
    147. 

  147. 		}
    148. 

  148. 	}
    149. 

  149. 	reslist
    150. 

  150. }
    151. 

  151. 

  152. ScaledownusingHW <- function(result,cutoff){
    153. 

  153. 	result[result[,1]<cutoff,]
    154. 

  154. }
    155. 

  155. 

  156. AboveAM <- function(result,cutoff_hw,cutoff_am){
    157. 

  157. 	adhereHW <- ScaledownusingHW(result,cutoff_hw);
    158. 

  158. 	uber <-  adhereHW[adhereHW[,3]>cutoff_am,]
    159. 

  159. 	write.table(file=paste("HW<"+cutoff_hw+"AM<"+cutoff_am+".txt",sep=""),uber,sep="\t",quote=F,row.names=F,col.names=F)
    160. 

  160. }
    161. 

  161. addLoc <- function(name){
    162. 

  162. 

  163. }
    164. 

  164. 

  165. plottingqq <- function(name,scores,df){
    166. 

  166. 	pos <- scores[scores>=0]
    167. 

  167. 	neg <- scores[scores<0]
    168. 

  168. 	exp_pos <- rchisq(length(pos),df=df)
    169. 

  169. 	exp_neg <- -rchisq(length(neg),df=df)
    170. 

  170. 	colors = rep("blue",length(neg))
    171. 

  171. 	colors = c(colors,rep("green",length(pos)))
    172. 

  172. 	
    173. 

  173. 	plot(-75:150,-75:150,main=paste(name,"DegFree:",df),xlab="Observed Chi^2",ylab="Expected Chi^2",type="n")
    174. 

  174. 	points(sort(c(pos,neg)),sort(c(exp_pos,exp_neg)),pch=19,lwd=0.1,col=colors)
    175. 

  175. 	lines(-max(abs(scores)):max(abs(scores)),-max(abs(scores)):max(abs(scores)),col="black")
    176. 

  176. 	legend("bottomright", legend = c("Homozygote", "Hetrozygote"),col=c("blue","green"),pch=19,title="Chi^2 Scores")
    177. 

  177. }
    178. 

  178. 

  179. assortedmating <- function(data,info,start=1,number=0,name="Test.txt",plot=TRUE,verbose=TRUE,logger=FALSE){
    180. 

  180. 	PopulationScores <- NULL		#Teststatistic results holder
    181. 

  181. 	DirScores <- NULL
    182. 

  182. 	SPopulationScores <- NULL				#Scaled Teststatistic result holder
    183. 

  183. 	InbreadingScores <- NULL				#Inbreading coeficient result holder
    184. 

  184. 	ReturnMatrix <- c("",0,0,0,0)			#Final scoring matrix
    185. 

  185. 	pDir <- NULL				#ParentalMatingSchema LikelyhoodScores
    186. 

  186. 	PopScores <- NULL
    187. 

  187. 	ParScores <- NULL
    188. 

  188. 	ourcat(logger,"AM","INFO: Analyzing",number,"SNPMarkers\n",verbose=verbose)
    189. 

  189. 	
    190. 

  190. 	plist <- NULL
    191. 

  191. 	for(locus in start:(start+number)){
    192. 

  192. 		ourcat(logger,"AM","-----------------------------------------------------------------------\n",verbose=verbose)
    193. 

  193. 		ourcat(logger,"AM","Starting with locus:",locus,"\n",verbose=verbose)
    194. 

  194. 		ourcat(logger,"AM","-----------------------------------------------------------------------\n",verbose=verbose)
    195. 

  195. 		ind_num <- 1
    196. 

  196. 		nparents <- 0
    197. 

  197. 		ObservedAllel <- c(0,0,0,0)
    198. 

  198. 		Observed <- rep(0,10)
    199. 

  199. 		Expected <- rep(0,10)
    200. 

  200. 		ExpectedAllel <- c(0,0,0,0)
    201. 

  201. 		Observedtable <- cbind(rep(0,10),rep(0,10),rep(0,10),rep(0,10),rep(0,10),rep(0,10),rep(0,10),rep(0,10),rep(0,10),rep(0,10))
    202. 

  202. 		Expectedtable <- cbind(rep(0,10),rep(0,10),rep(0,10),rep(0,10),rep(0,10),rep(0,10),rep(0,10),rep(0,10),rep(0,10),rep(0,10))
    203. 

  203. 		names(ObservedAllel) <- c("A","C","G","T")
    204. 

  204. 		names(ExpectedAllel) <- c("A","C","G","T")
    205. 

  205. 		rownames(Observedtable) <- c("AA","AC","AG","AT","CC","CG","CT","GG","GT","TT")
    206. 

  206. 		names(Observed) <- c("AA","AC","AG","AT","CC","CG","CT","GG","GT","TT")
    207. 

  207. 		names(Expected) <- c("AA","AC","AG","AT","CC","CG","CT","GG","GT","TT")
    208. 

  208. 		rownames(Expectedtable) <- c("AA","AC","AG","AT","CC","CG","CT","GG","GT","TT")
    209. 

  209. 		colnames(Observedtable) <- c("AA","AC","AG","AT","CC","CG","CT","GG","GT","TT")
    210. 

  210. 		colnames(Expectedtable) <- c("AA","AC","AG","AT","CC","CG","CT","GG","GT","TT")
    211. 

  211. 		#cat("here",ind_num)
    212. 

  212. 		for(ind in rownames(info)){
    213. 

  213. 			#cat("starting with:",ind,"\n")
    214. 

  214. 			colnum <- which(colnames(data)==ind)
    215. 

  215. 			#cat(ind,"colnum in data:",colnum,"\n")
    216. 

  216. 			#cat(ind,"rownum in info:",ind_num,"\n")
    217. 

  217. 			ind.status <- info[ind_num,1]
    218. 

  218. 			ind.sex <- info[ind_num,2]
    219. 

  219. 			ind.MFC <- info[ind_num,3]
    220. 

  220. 			ind.Fam <- info[ind_num,4]
    221. 

  221. 			#cat("Data:",ind.status,ind.sex,ind.MFC,ind.Fam,sep="\t","\n")
    222. 

  222. 			if(info[ind_num,3]=="M" || info[ind_num,3]=="F"){
    223. 

  223. 				#parentfound
    224. 

  224. 				nparents <- nparents+1
    225. 

  225. 				geno_1 <- as.character(data[locus,colnum])
    226. 

  226. 				geno_1 <- paste(sort(c(substr(geno_1,1,1),substr(geno_1,2,2)))[1],sort(c(substr(geno_1,1,1),substr(geno_1,2,2)))[2],sep="")
    227. 

  227. 				ObservedAllel[substr(geno_1,1,1)] <- ObservedAllel[substr(geno_1,1,1)]+1
    228. 

  228. 				ObservedAllel[substr(geno_1,2,2)] <- ObservedAllel[substr(geno_1,2,2)]+1
    229. 

  229. 				Observed[geno_1] <- Observed[geno_1] +1
    230. 

  230. 				for(ind2_num in which(info[,4]==ind.Fam)){
    231. 

  231. 					if(info[ind2_num,3] != info[ind_num,3] && info[ind2_num,3] != "C"){
    232. 

  232. 						#cat(rownames(info)[ind2_num]," !!!\n")
    233. 

  233. 						colnum_2 <- which(colnames(data)==rownames(info)[ind2_num])
    234. 

  234. 						#cat("Colnum2:",colnum_2,"\n")
    235. 

  235. 						geno_2 <- as.character(data[locus,colnum_2])
    236. 

  236. 						#cat("Geno's:",geno_1,geno_2,"\n")
    237. 

  237. 						geno_2 <- paste(sort(c(substr(geno_2,1,1),substr(geno_2,2,2)))[1],sort(c(substr(geno_2,1,1),substr(geno_2,2,2)))[2],sep="")
    238. 

  238. 						Observedtable[geno_1,geno_2] <- Observedtable[geno_1,geno_2] +1
    239. 

  239. 					}				
    240. 

  240. 				}
    241. 

  241. 			}
    242. 

  242. 			ind_num = ind_num+1
    243. 

  243. 		}
    244. 

  244. 		n.allells=sum(ObservedAllel)
    245. 

  245. 		for(x in 1:length(ObservedAllel)){
    246. 

  246. 			ExpectedAllel[x]=(ObservedAllel[x]) / n.allells
    247. 

  247. 			#here there is a bug: expected != observed / n.allees (this is exected freq)
    248. 

  248. 			ourcat(logger,"AM",names(ObservedAllel)[x],"\t",ObservedAllel[x],"\t",ExpectedAllel[x],"\n",verbose=verbose)
    249. 

  249. 		}
    250. 

  250. 		ourcat(logger,"AM","-----------------------------------------------------------------------\n",verbose=verbose)
    251. 

  251. 		for(x in 1:length(Observed)){
    252. 

  252. 			#cat(x)
    253. 

  253. 			geno_1 <- names(Observed)[x]
    254. 

  254. 			geno_1 <- paste(sort(c(substr(geno_1,1,1),substr(geno_1,2,2)))[1],sort(c(substr(geno_1,1,1),substr(geno_1,2,2)))[2],sep="")
    255. 

  255. 			if(substr(geno_1,1,1) != substr(geno_1,2,2)){
    256. 

  256. 				Expected[x] <- (ExpectedAllel[substr(geno_1,1,1)] * ExpectedAllel[substr(geno_1,2,2)]) * n.allells
    257. 

  257. 			}else{
    258. 

  258. 				Expected[x] <- (ExpectedAllel[substr(geno_1,1,1)] * ExpectedAllel[substr(geno_1,2,2)]) * n.allells /2
    259. 

  259. 			}
    260. 

  260. 			ourcat(logger,"AM","Tests",names(Observed)[x],"\t",Observed[x],"\t",Expected[x],"\n",verbose=verbose)
    261. 

  261. 		}
    262. 

  262. 		cat(" ",colnames(Observedtable),"\n",sep="\t")
    263. 

  263. 		for(x in 1:dim(Observedtable)[1]){
    264. 

  264. 			cat(rownames(Observedtable)[x],rep("\t",x))
    265. 

  265. 			for(y in x:dim(Observedtable)[2]){
    266. 

  266. 				Expectedtable[x,y] <- as.integer((Observed[x]/nparents)*(Observed[y]/nparents)*(nparents/2))
    267. 

  267. 				if(x==y){
    268. 

  268. 					Observedtable[x,y] <- Observedtable[x,y]/2
    269. 

  269. 				}else{
    270. 

  270. 					Expectedtable[x,y] <- Expectedtable[x,y]*2
    271. 

  271. 				}
    272. 

  272. 				cat(Observedtable[x,y],"/",Expectedtable[x,y],"\t",sep="")
    273. 

  273. 			}
    274. 

  274. 			cat("\n")
    275. 

  275. 		}
    276. 

  276. 		#Statistics
    277. 

  277. 		teststat = 0
    278. 

  278. 		dir = 0
    279. 

  279. 		teststat1 = 0
    280. 

  280. 		for(x in 1:length(Expected)){
    281. 

  281. 			geno_1 <- names(Expected)[x]
    282. 

  282. 			a <- substr(geno_1,1,1)
    283. 

  283. 			b <- substr(geno_1,2,2)
    284. 

  284. 			value=0
    285. 

  285. 			if(Expected[x] !=0){
    286. 

  286. 				value = ((Observed[x]-Expected[x])^2/Expected[x])
    287. 

  287. 				teststat <- teststat+value
    288. 

  288. 				if(a==b){
    289. 

  289. 					dir <- 1-(Observed[x]/Expected[x])
    290. 

  290. 				}
    291. 

  291. 			}else{
    292. 

  292. 				teststat <- teststat+0
    293. 

  293. 			}
    294. 

  294. 		}
    295. 

  295. 		ourcat(logger,"AM","Pop TestStat:",teststat,dir,dir*teststat,"\n",verbose=verbose)
    296. 

  296. 		dirHO = 0
    297. 

  297. 		dirHE = 0
    298. 

  298. 		ParentDirection <- NULL
    299. 

  299. 		Pnames <- NULL
    300. 

  300. 		for(x in 1:dim(Expectedtable)[1]){
    301. 

  301. 			for(y in 1:dim(Expectedtable)[2]){
    302. 

  302. 				value <- 0
    303. 

  303. 				if(Expectedtable[x,y] !=0){
    304. 

  304. 					value <- ((Observedtable[x,y]-Expectedtable[x,y])^2/Expectedtable[x,y])	
    305. 

  305. 				}
    306. 

  306. 				if(x==y){
    307. 

  307. 					dirHO = dirHO+value
    308. 

  308. 				}else{
    309. 

  309. 					dirHE = dirHE+value
    310. 

  310. 				}
    311. 

  311. 				ParentDirection <- c(ParentDirection,value)
    312. 

  312. 				Pnames <- c(Pnames,paste(names(Expectedtable)[x],names(Expectedtable)[y]))
    313. 

  313. 				teststat1 <- teststat1+value
    314. 

  314. 			}
    315. 

  315. 		}
    316. 

  316. 		cat(dirHO,dirHE,"\n")
    317. 

  317. 		if((dirHO-dirHE) < 0){
    318. 

  318. 			teststat1 = -teststat1
    319. 

  319. 		}
    320. 

  320. 		ourcat(logger,"AM","Pop TestStat_1:",teststat1,"\n",verbose=verbose)
    321. 

  321. 		pDir <- cbind(pDir,ParentDirection)
    322. 

  322. 		rownames(pDir) <- Pnames
    323. 

  323. 		if(plot){
    324. 

  324. 			op <- par(mfrow = c(2,1))
    325. 

  325. 			DirScores <- c(DirScores,dir)
    326. 

  326. 			PopScores <- c(PopScores,teststat)
    327. 

  327. 			max <- max(as.numeric(PopScores))
    328. 

  328. 			min <- min(as.numeric(PopScores))
    329. 

  329. 			plot(c(1,length(PopScores)),c(min,max),xlab="markers",ylab="Chi^2",type='n')
    330. 

  330. 			lines(PopScores,lwd=2,col=rgb(0.3,0.3,1.0,1.0),type="o")
    331. 

  331. 

  332. 			ParScores <- c(ParScores,teststat1)		
    333. 

  333. 			max <- max(as.numeric(ParScores))
    334. 

  334. 			min <- min(as.numeric(ParScores))
    335. 

  335. 			plot(c(1,length(ParScores)),c(min,max),xlab="markers",ylab="Chi^2",type='n')
    336. 

  336. 			lines(ParScores,lwd=2,col=rgb(0.3,0.3,1.0,1.0),type="o")
    337. 

  337. 		}
    338. 

  338. 		cat(file=name,paste(rownames(data)[locus],teststat,dir,teststat1,sep="\t"),"\n",append=T)
    339. 

  339. 	}
    340. 

  340. 	list(PopScores,DirScores,ParScores,pDir)
    341. 

  341. }
    342. 

  342. 

  343. 

  344. init.QQplot <- function(){
    345. 

  345. 	full <- NULL
    346. 

  346. 	for(x in dir()[grep("Chr",dir())]){
    347. 

  347. 		if(!is.na(grep("res",x)==1&&1)){
    348. 

  348. 			cat("Reading",x,"\n")
    349. 

  349. 			data <- read.table(x)
    350. 

  350. 			full <- c(full,data[,2])
    351. 

  351. 		}
    352. 

  352. 	}
    353. 

  353. 

  354. }
    355. 

  355. 

  356. init.length <- function(){
    357. 

  357. 	setwd("D:\\GBIC\\Lude\\DataDanny")
    358. 

  358. 	order <- as.vector(read.csv("ChipIDOrderInGenotypeFiles.txt",header=FALSE,sep="\n"))
    359. 

  359. 	info <- read.csv("ChipIDToSampleInformation.txt",row.names=1,header=TRUE,sep="\t")
    360. 

  360. 	coln <- c("Chr","Pos",as.vector(order[,1]))
    361. 

  361. 	load("LM.Rdata")
    362. 

  362. 	colnames(LengthMatrix) <- coln
    363. 

  363. 	aaa <- assortedmating(LengthMatrix,info,1,5)
    364. 

  364. }
    365.