e4d6a8484d
Former-commit-id: 0579e878a69b7c285ca71870e9ca5730649a2fda Former-commit-id: 7cced5b488441d87bf070a9a444317db0e048880
225 lines
5.2 KiB
R
Executable File
225 lines
5.2 KiB
R
Executable File
#!/usr/bin/env Rscript
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#
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# compute start, stop, splice-junctions models for core DB
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#
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# source("make.models.r")
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#
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LIB_DIR <- Sys.getenv("LIB_DIR")
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if (LIB_DIR == "") LIB_DIR = "."
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source(paste0(LIB_DIR, "/util.base.r"))
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source(paste0(LIB_DIR, "/util.cons.r"))
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source(paste0(LIB_DIR, "/util.modelio.r"))
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# -------------------------------
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# parameters
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# -------------------------------
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# core cutoffs
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source("db.models.params.txt")
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# -------------------------------
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# genome infos
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# -------------------------------
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notify("loading info table")
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chromo <- read.table("db.info.txt", com="", head=T, stringsAsFactors=F)
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# -------------------------------
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# CDS
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# -------------------------------
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notify("loading cds table")
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cds <- read.table("db.cds.txt", com="", header=T, stringsAsFactors=F)
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cds$start <- as.factor(cds$start)
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cds$stop <- as.factor(cds$stop)
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cds <- cds[cds$status=="Ok",]
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cds <- cds[cds$genefam!="none",]
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cds$categ <- "dust"
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x <- sort(table(cds$genefam), dec=T)
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ok <- names(x[x >= CORE_NCDS_CUTOFF])
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cds$categ[cds$genefam %in% ok] <- "core"
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x <- x[! names(x) %in% ok]
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ok <- names(x[x >= SHEL_NCDS_CUTOFF])
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cds$categ[cds$genefam %in% ok] <- "shell"
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#
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cds.ori <- cds
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cds.lst <- split(cds.ori, cds.ori$categ)
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#
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# write out families
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#
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# patterns & names
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invisible(lapply(cds.lst, function(cds) {
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x <- sort(table(cds$genefam), decreasing=T)
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tab <- paste0("^", names(x), "$")
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names(tab) <- names(x)
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y <- sapply(split(cds$gene, cds$genefam), function(g) {
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head(names(sort(table(g), decreasing=T)), 1)
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})
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tab <- cbind(tab, y[names(x)])
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categ <- unique(cds$categ)
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f <- paste0("db.", categ, ".pat.txt")
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notify("writing patterns for", categ, ":", f)
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write.table(tab, file=f, quote=F, col.names=F, row.names=T)
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}))
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# -------------------------------
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# Start models (core only)
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# -------------------------------
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if (! "core" %in% names(cds.lst)) {
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notify("*** no gene found in core")
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notify("*** please change parameters")
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quit(save='no', status=1)
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}
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cds <- cds.lst[["core"]]
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#
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# start by genes
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#
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tab <- split(cds$start, cds$genefam)
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fatg <- sapply(tab, function(x) table(x)["atg"]/length(x)*100)
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names(fatg) <- names(tab)
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start.dft <- names(which(fatg >= CORE_START_ATG_CUTOFF))
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start.spc <- names(which(fatg < CORE_START_ATG_CUTOFF))
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tab <- cds[cds$genefam %in% start.dft,]
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tab <- table(tab$start)
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# default model
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x <- sort(tab[tab>=CORE_START_DFT_CUTOFF], decreasing=T)
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write.model.start(x, "default")
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# gene specific models
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invisible(sapply(start.spc, function(g) {
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x <- cds[cds$genefam == g,]
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tx <- table(x$start)
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tx <- sort(tx[tx>=CORE_START_OTH_CUTOFF], decreasing=T)
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write.model.start(tx, g)
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}))
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# -------------------------------
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# Stop models (core only)
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# -------------------------------
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# write default stop model
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tab <- table(cds$stop)
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x <- sort(tab[tab>=CORE_STOP_CUTOFF], decreasing=T)
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write.model.stop(x, "default")
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# -------------------------------
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# splice junctions
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# -------------------------------
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notify("loading intron table")
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intron <- read.table("db.intron.txt", com="", header=T, stringsAsFactors=F)
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# remove invalid sequences
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intron$seq <- gsub("\\.|-", "", intron$acceptor.donor)
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lseq <- nchar(gsub("[^acgt]", "", intron$seq))
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intron <- intron[lseq == 20,]
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# remove genes out of core
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intron <- intron[intron$genefam %in% cds$genefam,]
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# acceptors / donors
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intron$acc <- substr(intron$seq, 5, 6)
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intron$don <- substr(intron$seq, 15, 16)
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# consensus
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cons.px <- cons.build(intron$acceptor.donor)
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cons.px <- cons.px[,! is.nan(colSums(cons.px))]
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seq.px <- sapply(intron$acceptor.donor, function(s) gsub("[^acgt]", "", s))
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conf.px <- cons.confusion(cons.px, seq.px)
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sfam <- split(conf.px$l2scor, intron$genefam)
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sfam <- sfam[order(sapply(sfam, median))]
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# extract splice exceptions
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name.bad <- names(which(sapply(sfam, median) < 0))
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name.spc <- names(which(sapply(sfam[name.bad], length) >= CORE_SPLICE_CUTOFF))
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name.ok <- setdiff(unique(intron$genefam), name.bad)
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name.bad <- setdiff(name.bad, name.spc)
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name.list <- c(sapply(name.spc, function(x) x), list(default=name.ok))
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cons <- lapply(name.list, function(x) cons.build(intron[intron$genefam %in% x, "acceptor.donor"]))
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# write junction models
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invisible(sapply(names(cons), function(n) write.model.splice3(cons[[n]], n)))
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invisible(sapply(names(cons), function(n) write.model.splice5(cons[[n]], n)))
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# use uniform model for bad guys
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invisible(sapply(name.bad, function(n) write.unif.splice(3, n)))
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invisible(sapply(name.bad, function(n) write.unif.splice(5, n)))
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invisible(write.unif.splice('', "none"))
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# -------------------------------
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# keep data for plotting
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# -------------------------------
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DB <- list()
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params <- list()
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params$CORE_NCDS_CUTOFF <- CORE_NCDS_CUTOFF
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params$CORE_START_ATG_CUTOFF <- CORE_START_ATG_CUTOFF
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params$CORE_START_DFT_CUTOFF <- CORE_START_DFT_CUTOFF
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params$CORE_START_OTH_CUTOFF <- CORE_START_OTH_CUTOFF
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params$CORE_STOP_CUTOFF <- CORE_STOP_CUTOFF
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params$CORE_SPLICE_CUTOFF <- CORE_SPLICE_CUTOFF
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params$SHEL_NCDS_CUTOFF <- SHEL_NCDS_CUTOFF
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DB$params <- params
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DB$chromo <- chromo
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DB$cds.lst <- cds.lst
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DB$intron <- intron
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DB$cons <- cons
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notify("saving db.data.Rdata")
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save(DB, file="db.data.Rdata")
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# -------------------------------
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# end
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# -------------------------------
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quit(save='no')
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